RBI Bulletin - Dec 22, 2025

DECEMBER 2025 VOLUME LXXIX NUMBER 12Editorial Committee Sanjay Kumar Hansda Anujit Mitra Rekha Misra Anupam Prakash Sunil Kumar Rajeev Jain Snehal Herwadkar V. Dhanya Shweta Kumari Anirban Sanyal Sujata Kundu Editor Asish Thomas George The Reserve Bank of India Bulletin is issued monthly by the Department of Economic and Policy Research, Reserve Bank of India, under the direction of the Editorial Committee. The Central Board of the Bank is not responsible for interpretation and opinions expressed. In the case of signed articles, the responsibility is that of the author. © Reserve Bank of India 2025 All rights reserved. Reproduction is permitted provided an acknowledgement of the source is made. For subscription to Bulletin, please refer to Section ‘Recent Publications’ The Reserve Bank of India Bulletin can be accessed at https://bulletin.rbi.org.inCONTENTS Bi-monthly Monetary Policy Statement (December 3-5, 2025) Governor’s Statement: December 5, 2025 1 Resolution of the Monetary Policy Committee (MPC) December 3 to 5, 2025 7 Speeches Stablecoins – Do They Have a Role in the Financial System 11 Shri T Rabi Sankar Reading the Pitch: Banking Strategies for a Long Innings 17 Shri Swaminathan J. Micro Matters, Macro Momentum: Microfinance for Viksit Bharat 21 Shri Swaminathan J. Timely and Topical Statistics for Agile Policy Making 25 Dr. Poonam Gupta Articles State of the Economy 31 Government Finances 2025-26: A Half-Yearly Review 61 Composite Leading Indicator for GVA - Manufacturing for India 81 Decoding Safe Asset Volatility Amid Geopolitical Risks 101 Using Neural Networks Current Statistics 115 Recent Publications 171BI-MONTHLY MONETARY POLICY STATEMENT (DECEMBER 3-5, 2025) Governor’s StatementGovernor’s Statement MONETARY POLICY STATEMENT 2025-26 (DECEMBER 3-5) Governor’s Statement* and pressures from AI-fuelled optimism and concerns over high valuations are playing out in global equity Sanjay Malhotra markets, while divergence in the monetary policy trajectory of central banks is adding to the uncertainty Good morning and Namaskar. We are in the last on capital flows and yield spreads. month of an eventful and a challenging 2025. We look Major Decisions of the Monetary Policy Committee back at the year so far with satisfaction. The economy (MPC) and the RBI witnessed robust growth and benign inflation; The Monetary Policy Committee (MPC) met on the the banking system further consolidated and the 3rd, 4th and 5th of December to deliberate and decide regulatory framework was refined to strengthen the on the policy repo rate. After a detailed assessment financial system, enhance ease of doing business, of the evolving macroeconomic conditions and the and improve consumer protection. At the same time, outlook, the MPC voted unanimously to reduce we approach the new year with hope, vigour and the policy repo rate by 25 basis points (bps) to 5.25 determination to further support the economy and per cent with immediate effect. Consequently, the accelerate progress. standing deposit facility (SDF) rate under the liquidity Since the October policy, the Indian economy has adjustment facility (LAF) shall stand adjusted to 5.00 witnessed rapid disinflation, with inflation coming per cent and the marginal standing facility (MSF) rate down to an unprecedentedly low level. For the first and the Bank Rate to 5.50 per cent. The MPC also time since the adoption of flexible inflation targeting decided to continue with the neutral stance. (FIT), average headline inflation for a quarter at 1.7 per cent in Q2:2025-26, breached the lower tolerance Moreover, in view of the evolving liquidity threshold (2 per cent) of the inflation target (4 per conditions and the outlook, the Reserve Bank has cent). It dipped further to a mere 0.3 per cent in decided to conduct OMO purchases of government October 2025. On the other hand, real GDP growth securities of ₹1,00,000 crore and a 3-year USD/INR Buy accelerated to 8.2 per cent in Q2, buoyed by strong Sell swap of USD 5 billion this month to inject durable spending during the festive season which was further liquidity into the system. facilitated by the rationalisation of the goods and I shall now briefly set out the rationale for the services tax (GST) rates. Inflation at a benign 2.2 per decisions of the MPC. cent and growth at 8.0 per cent in H1:2025-26 present The MPC noted that headline inflation has eased a rare goldilocks period. significantly and is likely to be softer than the earlier Contrary to earlier expectations, global growth projections, primarily on account of the exceptionally has been relatively strong. Evolving geopolitical and benign food prices. Reflecting these favourable trade environments, however, continue to weigh conditions, the projections for average headline on the outlook. Inflation paths remain divergent inflation in 2025-26 and Q1:2026-27 have been further with headline inflation remaining above target in revised downwards. Core inflation, which had been most advanced economies, while pressures in most rising steadily since Q1:2024-25, eased at the margin emerging markets are contained, providing room for in Q2:2025-26 and is expected to remain anchored in accommodative monetary policy. Conflicting pulls the period ahead. Both headline and core inflation are * Governor’s Statement - December 5, 2025. expected to be at or below the 4 per cent target during RBI Bulletin December 2025 1MONETARY POLICY STATEMENT 2025-26 (DECEMBER 3-5) Governor’s Statement the first half of 2026-27. The underlying inflation during October-November. Rural demand3 continues pressures are even lower as the impact of increase to be robust while urban demand is recovering in price of precious metals is about 50 basis points steadily.4 Investment activity remains healthy5 with (bps). Growth, while remaining resilient, is expected private investment gaining steam6 on the back to soften somewhat. of expansion in non-food bank credit,7 and high capacity utilisation8. Merchandise exports declined Thus, the growth-inflation balance, especially sharply in October amid subdued external demand, the benign inflation outlook on both headline and accompanied by softer services exports.9 On the core, continues to provide the policy space to support supply side, agricultural growth is supported by the growth momentum. Accordingly, the MPC healthy kharif crop production,10 higher reservoir unanimously voted to reduce the policy repo rate levels11 and better rabi crop sowing.12 Manufacturing by 25 bps to 5.25 per cent. The MPC also decided to activity continues to improve, while the services continue with the neutral stance. sector is maintaining a steady pace.13 Assessment of Growth and Inflation Looking ahead, domestic factors such as healthy Growth agricultural prospects, continued impact of GST rationalisation, benign inflation, healthy balance Real gross domestic product (GDP) registered a six-quarter high growth of 8.2 per cent in Q2:2025-26, 3 Retail two-wheeler sales expanded by 51.8 per cent in October 2025. The underpinned by resilient domestic demand amidst demand under Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) declined by 33.4 per cent in October-November, reflecting global trade and policy uncertainties.1 On the supply improvement in farm sector employment. side, real gross value added (GVA) expanded by 8.1 4 Retail passenger vehicle sales increased by 11.3 per cent (y-o-y) in October on the back of festive demand and GST cuts. Domestic air per cent, aided by buoyant industrial and services passenger traffic witnessed a growth of 5.2 per cent in October-November. 5 Imports of capital goods expanded by 8.7 per cent during October. sectors. Economic activity during the first half of 6 Growth in fixed assets of private manufacturing companies has the financial year benefited from income tax and accelerated to 9.0 per cent during H1:2025-26 based on half-yearly balance sheet of listed companies. goods and services tax (GST) rationalisation, softer 7 Bank credit to food processing, textiles, chemicals, base metals, and crude oil prices, front-loading of government capital engineering goods increased y-o-y by 10.2 per cent, 9.1 per cent, 12.2 per cent, 13.1 per cent, and 25.1 per cent, respectively, in October 2025. expenditure, and facilitative monetary and financial 8 As per the early results, seasonally adjusted capacity utilisation (CU) conditions supported by benign inflation. of manufacturing sector at 74.8 per cent in Q2:2025-26 is well above the long-term average. High-frequency indicators suggest that domestic 9 India's merchandise exports contracted by 11.9 per cent (y-o-y) to US$ 34.4 billion, while imports rose sharply by 16.6 per cent to US$ 76.0 billion economic activity is holding up in Q3, although in October 2025. Services exports grew by 12.5 per cent and services imports expanded by 7.8 per cent in September but moderated sharply to there are some emerging signs of weakness in few 2.2 per cent and 2.9 per cent, respectively, in October. leading indicators.2 GST rationalisation and festival- 10 The production of kharif food grains in 2025-26, as per the first advance estimates (FAE), is estimated at 2.3 per cent higher than the final estimates related spending supported domestic demand of 2024-25. 11 All-India water storage in 155 major reservoirs stands at 87.8 per cent of 1 Private final consumption expenditure (PFCE) expanded by 7.9 per cent the total capacity as of November 27, 2025, as against 81.9 per cent a year during Q2:2025-26 as against 7.0 per cent in Q1:2025-26. Gross fixed capital ago and decadal average of 72.3 per cent. formation (GFCF) also remained resilient at 7.3 per cent in Q2:2025-26. 12 As on 28th November, rabi crop sowing is higher by 9.9 per cent when 2 PMI Manufacturing has moderated to a 9-month low of 56.6 in compared to the same period last year. November 2025. Growth in index of industrial production (IIP) moderated 13 GST revenues rose by 4.6 per cent and 0.7 per cent, respectively, in to 0.4 per cent in October 2025 from 4.6 per cent in September 2025. October and November 2025 despite rate rationalisation. Port cargo traffic Construction indicators viz., steel consumption and cement production increased by 12.0 per cent in October while toll collections registered an recorded modest growth of 2.4 per cent and 5.3 per cent, respectively, expansion of 2.9 per cent in November. Aggregate bank credit and deposits during October. Electricity demand remained in contractionary zone in registered robust growth of 11.4 per cent and 10.2 per cent, respectively, November 2025. as on November 14, 2025. 2 RBI Bulletin December 2025Governor’s Statement MONETARY POLICY STATEMENT 2025-26 (DECEMBER 3-5) sheets of corporates and financial institutions and adequate reservoir levels and conducive soil moisture. congenial monetary and financial conditions should Barring some metals, international commodity prices continue to support economic activity. Continuing are likely to moderate going forward.18 Overall, reform initiatives would further facilitate growth. inflation is likely to be softer than what was projected On the external front, services exports are likely in October, mainly on account of the fall in food to remain strong, while merchandise exports face prices. Considering all these factors, CPI inflation for some headwinds. External uncertainties continue 2025-26 is now projected at 2.0 per cent with Q3 at to pose downside risks to the outlook, while speedy 0.6 per cent; and Q4 at 2.9 per cent. CPI inflation for conclusion of various ongoing trade and investment Q1:2026-27 and Q2 are projected at 3.9 per cent and negotiations present upside potential. Taking all these 4.0 per cent, respectively. The underlying inflation factors into consideration, real GDP growth for 2025- pressures are even lower as the impact of increase in 26 is projected at 7.3 per cent, with Q3 at 7.0 per cent; price of precious metals is about 50 bps. The risks are and Q4 at 6.5 per cent. Real GDP growth for Q1:2026- evenly balanced. 27 is projected at 6.7 per cent and Q2 at 6.8 per cent. External Sector The risks are evenly balanced. India’s current account deficit moderated Inflation from 2.2 per cent of GDP in Q2:2024-25 to 1.3 per Headline CPI inflation declined to an all time cent in Q2:2025-26 on account of robust services low in October 2025.14 The faster than anticipated exports19 and strong remittances.20 In October 2025, decline in inflation was led by correction in food merchandise exports contracted year-on-year, whereas prices15, contrary to the usual trend witnessed during merchandise imports continued to increase for the the months of September-October. Core inflation (CPI second consecutive month, resulting in a widening of headline excluding food and fuel) remained largely the trade deficit.21 Healthy services exports coupled contained in September-October, despite continued with strong remittance receipts are expected to keep price pressures exerted by precious metals.16 Excluding CAD modest during 2025-26. gold, core inflation moderated to 2.6 per cent in On the external financing side, gross foreign October. Overall, the decline in inflation has become direct investment (FDI) to India increased at a robust more generalised.17 pace during the first half of the year. Net FDI also Turning to the inflation outlook, food increased significantly due to a decline in repatriation supply prospects have improved on the back of 18 As per the World Bank Commodity Price Forecasts (October 2025), higher kharif production, healthy rabi sowing, energy, food, raw materials and fertiliser prices are projected to decline in 2026 from the 2025 levels. 14 Based on the current CPI series (Base: 2012 = 100). 19 India's services exports grew by 8.8 per cent (y-o-y) during Q2:2025- 15 Food group registered a deflation of (-) 3.7 per cent on a y-o-y basis 26, while services imports rose by 3.7 per cent with net services exports after registering (-)1.4 per cent deflation in September. Within food group, growing by 14.5 per cent during the same period. In October 2025, services vegetables, cereals and spices recorded a deflation of (-) 27.6 per cent, (-) exports at US$ 35.2 billion grew at 2.2 per cent, while services imports at 16.2 per cent and (-) 3.3 per cent, respectively. US$ 17.7 billion increased by 2.9 per cent. Net services exports grew by 1.5 16 Core inflation moved within a narrow range of 4.3-4.4 per cent during per cent and stood at US$ 17.4 billion. September-October. 20 India's inward remittances increased by 10.7 per cent (y-o-y) to US$ 39.0 17 Nearly 80 per cent of the CPI basket recorded less than 4 per cent billion in Q2:2025-26. inflation in October 2025, as compared with 63 per cent in April and about 21 In October 2025, India's merchandise exports contracted by 11.9 per 60 per cent a year ago. The CPI-Combined diffusion index, a measure of cent on a y-o-y basis, whereas merchandise imports rose by 16.9 per cent dispersion of price changes, declined to 55.8, its lowest value since July to reach an all-time high of US$ 76.1 billion, resulting in a widening of the 2020. merchandise trade deficit to US$ 41.7 billion in October 2025. RBI Bulletin December 2025 3MONETARY POLICY STATEMENT 2025-26 (DECEMBER 3-5) Governor’s Statement despite a rise in outward FDI.22 Foreign portfolio Commercial Banks has declined by 69 bps for fresh investment (FPI) to India recorded net outflows of rupee loans during February-October 2025 (the US$ 0.7 billion in 2025-26 so far (April-December interest rate effect27 is 78 bps). The moderation in the 03), due to outflows in the equity segment. Flows weighted average lending rate (WALR) of outstanding under external commercial borrowings and non- rupee loans has been to the extent of 63 bps. resident deposit accounts moderated as compared Transmission has been broad-based across sectors. to last year.23 As on November 28, 2025, India’s On the deposit side, the weighted average domestic foreign exchange reserves stood at US$ 686.2 billion, term deposit rate (WADTDR) on fresh deposits has providing a robust import cover of more than 11 declined by 105 bps, while that on outstanding months. Overall, India’s external sector remains deposits has softened by 32 bps over the same period. resilient.24 We are confident of meeting our external I would like to reiterate that we are committed financing requirements comfortably. to provide sufficient durable liquidity to the banking system. We continuously assess the durable liquidity Liquidity and Financial Market Conditions requirements of the banking system due to changes in System liquidity, as measured by the net position currency in circulation, forex operations, and reserve under the LAF, stood at an average surplus of ₹1.5 maintenance. Going forward too, we shall continue lakh crore for the period since the MPC last met in to do so. After reviewing the liquidity situation and October 2025.25 the outlook, we have decided to conduct open market Money market rates have remained largely operation (OMO) purchases of government securities aligned to the policy repo rate amidst comfortable amounting to ₹1,00,000 crore and 3-year USD/INR Buy liquidity conditions.26 G-sec yields have remained Sell swaps of USD 5 billion this month. The details range-bound since the last policy. In response to the will be notified separately later today. These measures cumulative 100 bps cut in the policy repo rate, the will ensure adequate durable liquidity in the system weighted average lending rate (WALR) of Scheduled and further facilitate monetary transmission. I would also like to take this opportunity to 22 Gross foreign direct investment (FDI) flows to India grew by 19.4 per cent to US$ 51.8 billion in April-September 2025-26 from US$ 43.4 billion clarify that injection (absorption) of liquidity through during the same period a year ago. Net FDI inflows increased by 127.6 per cent to US$ 7.7 billion in April-September 2025-26 from US$ 3.4 billion purchase (sale) of government securities under OMOs during the same period a year ago. and that through operations under the LAF (VRR or 23 Net inflows under external commercial borrowings to India moderated to US$ 6.2 billion during April-October 2025-26 from US$ 8.1 billion a year VRRR) of short term duration serve very different ago. Non-resident deposits recorded net inflows of US$ 6.1 billion in April- purposes. While the objective of purchase (sale) September 2025-26, lower than US$ 10.2 billion in the same period last year. under OMO is to provide (absorb) durable liquidity, 24 India's external debt to GDP ratio declined to 18.9 per cent at end-June 2025 from 19.1 per cent at end-March 2025, while the net international the purpose of repo operations is to manage transient investment position (IIP) moderated to (-) 8.0 per cent of GDP at end-June liquidity so as to align the operating target – the 2025 from (-) 8.6 per cent of GDP at end-March 2025. 25 The average daily net absorption under the LAF stood at ₹2.9 lakh crore Weighted Average Call Rate (WACR) – to the policy and ₹1.6 lakh crore in August and September, respectively. The average repo rate. So, it is quite possible that we inject durable daily net absorption under the LAF declined to ₹0.9 lakh crore in October 2025 but improved to ₹1.9 lakh crore in November 2025. As on December liquidity through purchase of government securities 03, net absorption under the LAF stood at ₹2.6 lakh crore. 26 In response to the cumulative policy repo rate cut of 100 bps in the under OMO on the one hand while simultaneously current easing cycle (up to December 03), the WACR, the 3-month T-bill rate, the rate on 3-month CPs issued by NBFCs, and the 3-month CD rate 27 Interest rate effect on transmission to weighted average lending rate declined by 110 bps, 113 bps, 124 bps, and 140 bps, respectively. (WALR) is calculated by keeping the weight constant (as of January 2025). 4 RBI Bulletin December 2025Governor’s Statement MONETARY POLICY STATEMENT 2025-26 (DECEMBER 3-5) withdrawing transient liquidity through a VRRR Bank credit growth too has seen an uptick in operation on the other hand. recent months.31 Sector-wise32 data reveals that the growth was supported by sustained lending to retail I would further like to reiterate that the primary and service sector segments. Industrial credit growth instrument of monetary policy is the policy repo firmed up, aided by buoyant credit flow to micro, small rate.28 It is expected that changes in the short term and medium enterprises (MSMEs). Large industries interest rates will transmit to various long-term rates. At the same time, the primary purpose of open also recorded improvement in credit growth. market operations is to provide sufficient liquidity Additional Measures and not to directly influence G-sec yields. Before I conclude, I have one additional measure Financial Stability to announce. The system-level financial parameters related We have been focusing on improving customer to capital adequacy, liquidity, asset quality and services. We have taken a large number of measures profitability of Scheduled Commercial Banks (SCBs) in this regard. Re-KYC, financial inclusion and continue to remain robust.29 Similarly, the system- “Aapki Poonji, Aapka Adhikar” campaigns are some level parameters of NBFCs too are sound, with of the initiatives taken in association with other adequate capital position and improved gross non- stakeholders. Earlier in the year, we reviewed our performing asset (GNPA) ratios30. Citizens Charter too. We made applications for all The total flow of resources to the commercial our services online. We are publishing the summary sector has strengthened, bolstered by greater non- of our monthly disposal and pendency of various bank intermediation. In the current financial year applications on the first of every month. I am happy to so far, the total flow of resources was ₹20.1 lakh note that more than 99.8 per cent of the applications crore vis-à-vis ₹16.5 lakh crore in the corresponding are disposed of within stipulated timelines. period of the previous year. Outstanding credit from However, in the recent past, as a result of, inter bank and non-bank sources increased by 13 per cent alia, receipt of a large number of grievances, (y-o-y). pendency with the RBI Ombudsman has increased. I 28 We moved away from targeting money supply in 1998. exhort all regulated entities to keep customers central 29 SCB Parameters: The outstanding credit and deposit increased by 11.31per cent and 9.74per cent on a y-o-y basis, respectively, between in their policies and operations, improve customer October-24 and October-25. The system-level Capital to Risk Weighted service and reduce grievances. Further, we propose Assets Ratio (CRAR) of 17.24 per cent in September 2025 was well above the regulatory minimum level. Ratio of non-performing loans improved to hold a two-month campaign from 1st January further (GNPA ratio at 2.05 per cent in September 2025 vis-à-vis 2.54 per cent in September 2024, NNPA Ratio at 0.48 per cent in September 2025 next year with an aim to resolve all grievances pending vis-à-vis 0.57 per cent in September 2024). Liquidity buffers were robust, with an LCR of 131.69 per cent as of end September 2025. The annualised for more than a month with the RBI Ombudsman. return on assets (RoA) and return on equity (RoE) stood at 1.32 per cent I elicit the support of all regulated entities in this and 13.06 per cent, respectively, in September 2025. Net Interest Margin was 3.26 per cent for September 2025 (3.52 per cent in September 2024). endeavour. 30 NBFC Parameters: Total CRAR of NBFCs was 25.11 per cent and Tier I CRAR was 23.27 per cent in September 2025, well above the minimum regulatory requirements. GNPA ratio has improved from 2.57 per cent in 31 On a year-on-year basis, bank credit registered a growth of 11.4 per cent September 2024 to 2.21 per cent in September 2025, while NNPA ratio as on November 14, 2025, compared to 11.2 per cent a year ago. also improved from 1.04 per cent in September 2024 to 0.99 per cent 32 Sectoral non-food credit data are based on sector-wise and industry- in September 2025. RoA for the sector decreased from 3.25 per cent in wise bank credit (SIBC) return, which covers select banks accounting for September 2024 to 2.83 per cent in September 2025. NIM has decreased about 95 per cent of total non-food credit extended by all SCBs, pertaining from 5.51 per cent in September 2024 to 4.24 per cent in September 2025. to the last reporting Friday of the month. Data available till October 2025. RBI Bulletin December 2025 5MONETARY POLICY STATEMENT 2025-26 (DECEMBER 3-5) Governor’s Statement Concluding Remarks remain growth supportive. We will continue to meet the productive requirements of the economy in a Let me now conclude. Despite an unfavourable proactive manner while ensuring macroeconomic and challenging external environment, the Indian stability. economy has shown remarkable resilience and is poised to register high growth. The headroom Thank you. Namaskar and Jai Hind. provided by the inflation outlook has allowed us to 6 RBI Bulletin December 2025BI-MONTHLY MONETARY POLICY STATEMENT (DECEMBER 3-5, 2025) Resolution of the Monetary Policy Committee (MPC) December 3 to 5, 2025Monetary Policy Statement, 2025-26 MONETARY POLICY STATEMENT 2025-26 (DECEMBER 3-5) Monetary Policy Statement, In India, real gross domestic product (GDP) registered a six-quarter high growth of 8.2 per cent 2025-26 Resolution of the in Q2:2025-26, underpinned by resilient domestic Monetary Policy Committee demand amidst global trade and policy uncertainties. On the supply side, real gross value added (GVA) (MPC)* expanded by 8.1 per cent, aided by buoyant industrial and services sectors. Economic activity during the Monetary Policy Decisions first half of the financial year benefited from income The Monetary Policy Committee (MPC) held its tax and goods and services tax (GST) rationalisation, 58th meeting from December 3 to 5, 2025, under softer crude oil prices, front-loading of government the chairmanship of Shri Sanjay Malhotra, Governor, capital expenditure, and facilitative monetary and Reserve Bank of India. The MPC members Dr. Nagesh financial conditions supported by benign inflation. Kumar, Shri Saugata Bhattacharya, Prof. Ram Singh, High-frequency indicators suggest that domestic Dr. Poonam Gupta and Shri Indranil Bhattacharyya economic activity is holding up in Q3, although attended the meeting. there are some emerging signs of weakness in a few After a detailed assessment of the evolving leading indicators. GST rationalisation and festival- macroeconomic and financial developments and the related spending supported domestic demand during outlook, the MPC voted unanimously to reduce the October-November. Rural demand continues to be policy repo rate under the liquidity adjustment facility robust while urban demand is recovering steadily. (LAF) to 5.25 per cent. Consequently, the standing Investment activity remains healthy with private deposit facility (SDF) rate shall stand adjusted to 5.00 investment gaining steam on the back of expansion per cent and the marginal standing facility (MSF) rate in non-food bank credit and high capacity utilisation. and the Bank Rate to 5.50 per cent. The MPC also Merchandise exports declined sharply in October amid decided to continue with the neutral stance. subdued external demand, accompanied by softer services exports. On the supply side, agricultural Growth and Inflation Outlook growth is supported by healthy kharif crop production, The global economy is holding up better than higher reservoir levels and better rabi crop sowing. expected, though the earlier frontloading of trade is Manufacturing activity continues to improve, and the showing signs of normalising. Uncertainty has eased services sector is maintaining a steady pace. somewhat following the end of the US government Looking ahead, domestic factors such as healthy shutdown and progress on trade agreements, yet it agricultural prospects, continued impact of GST remains elevated. Global inflation dynamics remain rationalisation, benign inflation, healthy balance uneven, with inflation trending above target in sheets of corporates and financial institutions and most major advanced economies. The US dollar congenial monetary and financial conditions should strengthened primarily on safe haven demand while continue to support economic activity. Continuing treasury yields remained range bound. Equity markets reform initiatives would further facilitate growth. remain volatile, driven by shifting views on the On the external front, services exports are likely monetary policy outlook and concerns surrounding to remain strong, while merchandise exports face stretched valuations in tech stocks. some headwinds. External uncertainties continue * Released on December 5, 2025. to pose downside risks to the outlook, while RBI Bulletin December 2025 7MONETARY POLICY STATEMENT 2025-26 (DECEMBER 3-5) Monetary Policy Statement, 2025-26 speedy conclusion of ongoing trade and investment are likely to moderate going forward. Overall, inflation negotiations present upside potential. Taking all these is likely to be softer than what was projected in factors into consideration, real GDP growth for 2025- October, mainly on account of the fall in food prices. 26 is projected at 7.3 per cent, with Q3 at 7.0 per cent; Considering all these factors, CPI inflation for 2025-26 and Q4 at 6.5 per cent. Real GDP growth for Q1:2026- is now projected at 2.0 per cent with Q3 at 0.6 per cent; 27 is projected at 6.7 per cent and Q2 at 6.8 per cent and Q4 at 2.9 per cent. CPI inflation for Q1:2026-27 (Chart 1). The risks are evenly balanced. and Q2 are projected at 3.9 per cent and 4.0 per cent, respectively (Chart 2). In fact, the underlying inflation Headline CPI inflation declined to an all time pressures are even lower as the impact of increase in low in October 2025. The faster than anticipated price of precious metals is about 50 basis points (bps). decline in inflation was led by correction in food The risks are evenly balanced. prices, contrary to the usual trend witnessed during the months of September-October. Core inflation (CPI Rationale for Monetary Policy Decisions headline excluding food and fuel) remained largely The MPC noted that headline inflation has eased contained in September-October, despite continued significantly and is likely to be softer than the earlier price pressures exerted by precious metals. Excluding projections, primarily on account of the exceptionally gold, core inflation moderated to 2.6 per cent in benign food prices. Reflecting these favourable October. Overall, the decline in inflation has become conditions, the projections for average headline more generalised. inflation in 2025-26 and Q1:2026-27 have been further Turning to the inflation outlook, food revised downwards. Core inflation, which had been supply prospects remain bright on the back of rising steadily since Q1:2024-25, eased at the margin higher kharif production, healthy rabi sowing, in Q2:2025-26 and is expected to remain anchored in adequate reservoir levels and conducive soil moisture. the period ahead. Both headline and core inflation Barring some metals, international commodity prices are expected to be around the 4 per cent target during 8 RBI Bulletin December 2025 tnec reP Chart 1: Quarterly Projection of Real GDP Growth (y-o-y) 14 12 10 8 6 4 2 0 50 per cent CI 70 per cent CI 90 per cent CI CI - Confidence Interval 32-2202:2Q 32-2202:3Q 32-2202:4Q 42-3202:1Q 42-3202:2Q 42-3202:3Q 42-3202:4Q 52-4202:1Q 52-4202:2Q 52-4202:3Q 52-4202:4Q 62-5202:1Q 62-5202:2Q 62-5202:3Q 62-5202:4Q 72-6202:1Q 72-6202:2Q Chart 2: Quarterly Projection of CPI Inflation (y-o-y) 50 per cent CI 70 per cent CI 90 per cent CI CI - Confidence Interval tnec reP 10 8 6 4 2 0 -2 32-2202:2Q 32-2202:3Q 32-2202:4Q 42-3202:1Q 42-3202:2Q 42-3202:3Q 42-3202:4Q 52-4202:1Q 52-4202:2Q 52-4202:3Q 52-4202:4Q 62-5202:1Q 62-5202:2Q 62-5202:3Q 62-5202:4Q 72-6202:1Q 72-6202:2QMonetary Policy Statement, 2025-26 MONETARY POLICY STATEMENT 2025-26 (DECEMBER 3-5) the first half of 2026-27. The underlying inflation by 25 bps to 5.25 per cent. The MPC also decided to pressures are even lower as the impact of increase in continue with the neutral stance. However, Prof. Ram price of precious metals is about 50 bps. Growth, while Singh was of the view that the stance be changed from remaining resilient, is expected to soften somewhat. neutral to accommodative. Thus, the growth-inflation balance, especially The minutes of the MPC’s meeting will be the benign inflation outlook on both headline and published on December 19, 2025. core, continues to provide the policy space to support The next meeting of the MPC is scheduled during the growth momentum. Accordingly, the MPC February 4 to 6, 2026. unanimously voted to reduce the policy repo rate RBI Bulletin December 2025 9SPEECHES Stablecoins – Do They Have a Role in the Financial System Shri T Rabi Sankar Reading the Pitch: Banking Strategies for a Long Innings Shri Swaminathan J. Micro Matters, Macro Momentum: Microfinance for Viksit Bharat Shri Swaminathan J. Timely and Topical Statistics for Agile Policy Making Dr. Poonam GuptaStablecoins – Do They Have a Role in the Financial System SPEECH Stablecoins – Do They Have a But the fundamental challenge of cryptocurrencies is that they claim to change the very nature of money Role in the Financial System* – because cryptocurrencies do not represent value either in terms of intrinsic worth or in terms of Shri T. Rabi Sankar promise to pay. In my talk today, I propose to explore what the nature of such challenge is, and what are I. Introduction the implications of cryptocurrencies for the financial Distinguished industry leaders, colleagues and system as we know it. guests. To be able to understand the nature or character It is a privilege to be able to stand here and talk of money, we need to look a little deeper. to such a learned gathering and I am thankful to Mint II. Attributes of Money for inviting me. In a modern economy, there are two types of Money, as we know it, has been a central pillar of money viz., currency and bank deposits – currency human society for centuries, enabling trade, facilitating (physical) is issued directly by the State (through economic activity, and underpinning the very notion its central bank) while deposits (digital) are issued of trust in social and financial interactions. Over under license by commercial banks. All money is time, the form of money has evolved with technology issued either directly by the central bank or indirectly - from commodities to metal to paper to balances in through banks authorised by it. Thus, all money in deposit accounts to now, digital tokens. While the modern economies is effectively FIAT in nature. It is forms of money have evolved with technology, the this fiat or sovereign aspect of modern money which fundamental character of money - what it represents, creates ‘trust’ in money and provides it stability. or what gives it credibility – has always been that it represents value that has users’ trust. That value A second defining feature of modern money is either intrinsic (metal money) or derived from a is “Singleness”, the property that different forms promise to pay (paper money or deposit money) by of money in an economy viz., cash, deposits, are a trusted person. Theoretically, money can be issued denominated in a single unit and interchangeable at by any person as long as he has the trust of the users. par. This ‘Singleness’ also arises from the fact that The more stable forms of money in history have, settlement of all transactions take place in central however, always been issued by sovereigns, not by bank money. ‘Singleness’ of money ensures that trade private issuers. Examples of private money (money and commerce are smooth without any concern for issued by non-sovereigns) can be found in history but the value of different types of money. Ultimately, in they have not been stable arrangements. In practice, modern economies, the fact that all “money” is fiat therefore, money has credibility because its value is also ensures that money is SINGLE. promised by the sovereign. Let us now sum up our understanding of what This fundamental character of money is under money has evolved into – that money represents challenge from cryptocurrencies. Not in terms of VALUE trusted by users, that money is FIAT and, that technology, as money in the form of digital tokens money is SINGLE. can exist without changing the nature of money itself. Let us now see how a cryptocurrency measures * Keynote address delivered by Deputy Governor Shri T. Rabi Sankar at the Mint Annual BFSI Conclave 2025 on December 12, 2025 in Mumbai. up to these attributes of money. RBI Bulletin December 2025 11SPEECH Stablecoins – Do They Have a Role in the Financial System III. Attributes of Cryptocurrency b. Assuming such a liability is legally established, the next point to keep in mind The historical evolution of Cryptocurrency is the is that stablecoin is private money. Thus, outcome of decades of search for a cyber solution stablecoins fail to satisfy the two defining for total anonymity of transactions outside of state features of modern money, viz., (i) money control. The creation of Bitcoin in 2008 was the result as fiat and (ii) singleness of money. It is of that search. Bitcoin, or rather, the Blockchain, the possible that in a stablecoin system, there technology underpinning the Bitcoin, demonstrated would be hundreds, or more, of currencies that a digital token can be transferred between in an economy making any such system unknown counterparts without the need for an inherently unstable. intermediary. The technology was revolutionary. But the Bitcoin itself was just a tool to demonstrate the Since we can reasonably establish that unbacked technology, it had no value, either intrinsic or as a cryptocurrencies are not assets and merely speculative promise to pay. It was not money. The price of Bitcoin bets, akin to betting on a gambling event, we would today does not represent value in the sense money has focus, in the rest of this talk, on Stablecoins, which are value. This value is purely speculative like the price close enough to money to pose a significant challenge of a tulip during the tulip mania of the seventeenth to the financial system. First, let us look at the benefits century. of stablecoins that their proponents claim they have. To summarise, cryptocurrencies have no intrinsic IV. Benefits of Stablecoins value. They are not backed by a promise to pay, that Proponents of stablecoins present a range of is, they have no issuer. Since they do not meet the claims, the more important of which are, improved basic attributes of money, they are not money. In fact, cross-border payment efficiency, greater financial since they do not have any underlying cash flow, they inclusion, and the ability to drive digital financial are not financial assets as well, or, for that matter, any innovation. asset at all. How about Stablecoins, which are cryptocurrencies Efficient cross-border payments against which the “issuer” holds reserves to maintain An oft cited benefit is that stablecoins can make a stable value. Since they are pegged to a fiat currency, payments, particularly cross-border payments faster, they can perform the functions of a currency. Also, cheaper and more efficient. In the domestic space, real- as they are backed by financial or other assets, they time fast payment systems such as UPI already enable do represent value. Therefore, they have some of the fast, low-cost, and reliable payments, and there is no basic attributes of a money. However, we need to keep reason to believe that stablecoins would be superior in mind two factors. from the point of view of cost or speed or reliability. a. Is there a promise to pay? For stablecoins In the cross-border space, stablecoins can potentially to be money the issuer needs to promise to enable faster and perhaps cheaper payments than pay par value to the holder. It is not clear what the current corresponding banking system whether Stablecoins are the liability of their provides, mainly because stablecoins do not face issuers. It would appear that neither of the settlement risks. On the other hand, it is not certain two major cryptocurrencies in use today that stablecoin issuers would have the same degree make such unconditional promise. of acceptability as international banks that are closely 12 RBI Bulletin December 2025Stablecoins – Do They Have a Role in the Financial System SPEECH regulated and backstopped by central banks. Also, V. Risks of Stablecoins the purported efficiency is doubtful when there are a Beyond the facilitation of illicit payments and large number of stablecoins in the ecosystem. circumvention of control measures, stablecoins Improve financial inclusion raise significant concerns for monetary stability, fiscal policy, banking intermediation, and systemic Another claim often made is that stablecoins resilience. enhance financial inclusion by providing access to digital money for those outside of traditional banking Risk of Currency Substitution systems. Financial inclusion requires solutions that A core risk of stablecoins is currency substitution. are accessible, affordable and safe. Many countries Their design as currency-like instruments introduces have made substantial progress in financial inclusion the potential for currency substitution, particularly through digital public infrastructure and simplified in emerging markets, where they could compete account opening frameworks without the need to with domestic fiat money. Stablecoins, whether create parallel private forms of money. The inherent denominated in domestic currency or foreign instability of stablecoins means they are clearly currency, would reduce demand for the local currency inferior alternative to fiat money as tools of financial and raise the risk of dollarisation. inclusion. As stablecoins remain dependent on Risk to Monetary Policy smartphones and digital wallets, internet connectivity Widespread adoption of stablecoins would and technical know-how, they may not be available to undermine central banks’ ability to control money those segments of the population that are most in supply and interest rates. ‘If both an official currency need of financial services. and a crypto asset are used for pricing goods and Bridge to the real economy services, domestic prices could become highly Finally, supporters of stablecoins often argue that unstable due to the inherent volatility of the crypto they can act as a bridge for the crypto ecosystem to the asset’ (IMF-FSB 2023). If residents increasingly hold or real economy. Yet the evidence today indicates that transact stablecoins, changes in domestic policy rates stablecoins remain primarily used as instruments to may have limited influence on economic decisions, facilitate trading and leverage within the crypto market weakening the effectiveness of monetary policy. itself. Their role as meaningful transactional currency Weakening Capital Account Management in everyday economic activity remains limited. Stablecoins pose challenges for capital flow To sum up, many of these benefits are neither management (CFM) as domestic households diversify unique to stablecoins nor have stablecoins yet their balance sheets by including foreign-currency established any of the benefits their proponents denominated stablecoins. This trend would make it claim. By their very nature, they are in many ways difficult for authorities to implement capital controls, inferior to available forms of money in achieving those which are a critical instrument for financial stability benefits. On the other hand the risks they introduce in many emerging markets, including India. The to financial stability, and broader macro-financial pseudonymous nature of blockchain transactions stability are extremely serious. We will now take a compounds these risks as it creates channels for closer look at these risks in detail before considering unmonitored inflows and outflows, diluting the how India should approach stablecoins. effectiveness of CFMs and complicating both RBI Bulletin December 2025 13SPEECH Stablecoins – Do They Have a Role in the Financial System macroeconomic management and external sector issuance of fiat money by the central bank, is thus oversight. diverted to private operators, often located outside the home jurisdiction, if stablecoins are dominated in Bank and Credit Intermediation a foreign currency. It is likely that most countries will Banks are the primary entities that intermediate see a leakage of seigniorage income to private issuers between savers and investors in an economy. This of Dollar linked stablecoins. This loss of Government ability derives from banks’ role in credit creation. To revenue does not receive the serious focus it deserves, the extent stablecoins replace bank deposits, banks not even from central bankers. would lose their role in financial intermediation. This Domestic-Currency Stablecoins Are Not Risk-Free would result either in a rise in cost of credit as banks lose access to low-cost deposits, or banks having to Some argue that permitting domestic currency depend on the central bank to provide the liquidity denominated stablecoins would not involve these required to fund credit. A financial system that has to risks. While such instruments may reduce risks increasingly depend on central bank liquidity to fund to capital account concerns, the fundamental commercial credit would not sustain. vulnerabilities such as currency substitution, bank disintermediation, reduced monetary-policy control, Systemic Risks singleness and loss of seigniorage income remain. The combination of weakened banks, reduced This is the reason why advanced economies are not monetary policy effectiveness, and limited immune to the risks posed by stablecoins. capital account management amplifies systemic Stablecoins introduce real and severe risks vulnerabilities. Large-scale stablecoin adoption could ranging from monetary and fiscal disruption to expose domestic economies to external shocks and banking disintermediation, to systemic instability. cross-border volatility, leaving traditional policy The risks are significantly higher for EMDEs, but they instruments less effective in managing financial are also major risks for AEs. Understanding these stress. vulnerabilities is critical before considering regulatory Loss of Seigniorage frameworks or policy adoption. It is not surprising then that global policy bodies and standard-setting When a central bank issues currency, it receives organisations continue to highlight the risks of equal value that is invested in assets like Government stablecoins. securities which are used to back the currency issued. These assets earn a return, which is significantly VI. Global Policy Responses higher, than the cost of printing and issuing money. Financial Stability Board (FSB) attempted This difference – higher returns against lower cost of to create a baseline for the regulation of global issue – is seigniorage income, which is transferred stablecoin arrangements through its High-level to the Government. Since currency issue is a social Recommendations1 issued in 2023. But even these function, seigniorage income rightfully belongs to recommendations explicitly admit that they do not the Government, as the representative of the people. address virtually any of the major risks associated There is no case for seigniorage to accrue to private 1 High-level Recommendations for the Regulation, Supervision and profit-making entities. Yet, this is exactly what Oversight of Global Stablecoin Arrangements, July 17, 2023 https://www. fsb.org/uploads/P170723-3.pdf Stablecoin issuers earn as income. Seigniorage, which 2 https://www.fsb.org/2023/09/imf-fsb-synthesis-paper-policies-for- is inherently a sovereign revenue arising from the crypto-assets/ 14 RBI Bulletin December 2025Stablecoins – Do They Have a Role in the Financial System SPEECH with Stablecoins – risks that particularly matter most At the same time, India must acknowledge the to jurisdictions like ours. The IMF and FSB joint promise of innovation that technologies such as Synthesis Paper of 20232 also recognised that EMDEs blockchain and tokenisation bring. A central pillar face a distinct and amplified set of vulnerabilities. of this strategy is the adoption and cross-border In its 2025 Annual Economic Report, the BIS points readiness of Central Bank Digital Currencies (CBDCs). out that stablecoins fail the basic tests of singleness, CBDCs are digital tokens like stablecoins yet they elasticity, and integrity that any form of money must are inherently superior since they satisfy all the meet and are hence structurally unsuitable to anchor attributes that money should have – fiat, single, a monetary system. trusted and representing value - and do not pose many of the risks associated with stablecoins. They can The asymmetrical risks to EMDEs often does not receive the importance it merits. Stablecoins perform all the functions stablecoins claim to offer are borderless instruments operating in a world such as programmability, atomic settlement, lower of borders. If one jurisdiction with a liberal capital cross-border frictions, while being fully anchored account allows unrestricted use of stablecoins, and within the existing financial system. Encouraging they circulate widely in a neighbouring country with CBDC use domestically is essential and can be done capital controls, the financial stability of the latter can by making CBDC functionally similar to physical be fundamentally undermined. Issues critical to the cash, especially with respect to tiered anonymity. stability of EMDEs are often acknowledged but not For example, ensuring anonymity for small-value prioritised. CBDC transactions, much like cash, would provide users comfort and trust while preserving safeguards So, what does all this mean for a country like India? for high-value flows. Such an approach also avoids How should we deal with stablecoins and safeguard disintermediation risks for the banking system. financial stability and monetary sovereignty? These questions naturally lead us to consider the domestic The cross-border dimension is even more critical. policy imperatives that must guide India’s approach Much of the appeal of stablecoins lies in their promise in this evolving global environment. of cheaper, faster international transfers. But the same efficiency can be achieved through bilateral or VII. Policy Approach for India – Promote CBDCs - multilateral CBDC corridors. This is an area where Harness Innovation and Protect Stability India can play a shaping role, by helping build the For India, the approach to stablecoins must be case for interoperable CBDC arrangements among guided by caution and an appreciation of domestic emerging markets and beyond. imperatives. Stablecoins can undermine trust in the currency and finance system. India already benefits A third pillar of India’s approach should be from a payments landscape that is highly efficient, the interlinking of fast payment systems (FPS). reliable, and robust. Systems such as UPI, RTGS, and Interlinking domestic FPS directly contributes to the NEFT provide fast, low-cost, and secure payment G20 objectives of faster, cheaper, more accessible capabilities to millions of users. This leaves little and transparent cross-border payments. The recent justification for their integration into the financial linkages between UPI and several partner jurisdictions system, even before considering the broader risks they are important steps forward, increasingly reducing pose. India’s policy on stablecoins must be driven by the need for any private digital alternatives for domestic priorities. remittances. RBI Bulletin December 2025 15SPEECH Stablecoins – Do They Have a Role in the Financial System Finally, as we weigh policy choices, we must also In fact, the bigger threat is a stablecoin that works address a central argument often made by proponents well. India stands at a decisive policy crossroads. of stablecoins who claim that the associated risks can Despite India having good macroeconomic conditions be managed through regulation. Regulation can indeed and sound policies, the domestic factors and mitigate some risks, but the larger question remains: compulsions must be considered when evaluating Can we afford to experiment with the foundations of policy options for stablecoins. The choices made today will impact the future of our monetary system global monetary and financial stability that have been and financial sector integrity. India’s strategy must be carefully built over the years for instruments that lack clear and coherent, anchored in four key principles: the safety features of money, that are inherently risky and that remain untested at scale? As highlighted a. Preserve trust in the national currency, in the BIS Annual Economic Report 20253, society monetary and payment system faces a clear choice which is either to strengthen the b. Safeguard monetary sovereignty and macro- monetary system using proven foundations of trust financial stability and advanced, programmable technologies, or to risk c. Encourage responsible innovation through repeating the hard lessons of history by relying on CBDCs and interoperable payment systems, unsound private digital currencies with real societal and costs. d. Ensure that innovation strengthens, rather VIII. Conclusion than bypasses, the regulated financial system. We have seen that stablecoins lack the basic attributes of money, their advantages are neither I will end with my response to the question posed in the title of this speech. Do stablecoins serve a unique nor unambiguous and their risks are all too purpose? It seems to me that they do not; at any rate, real. It may be noted we have not referred to the risks they do not serve a purpose that cannot be served associated with the assets that back a stablecoin. That better by fiat money. is because it does not matter, for either the benefits or the risks of stablecoins to materialise. Thank you. 3 (BIS 2025). https://www.bis.org/publ/arpdf/ar2025e3.htm 16 RBI Bulletin December 2025Reading the Pitch: Banking Strategies for a Long Innings SPEECH Reading the Pitch: Banking Since there is a cricketer waiting in the room, let me borrow something from the game. Think of the Strategies for a Long Innings* next part of my speech as an over, with six deliveries. Each ball is one key idea that I believe will shape the Shri Swaminathan J. future of banking in India. I promise there will be no googlies. The legendary cricketer, the Very Very Special Laxman ji; Shri P D Singh, CEO of Standard Chartered Ball 1: New challenges in banking today Bank, India & South Asia, distinguished leaders from The first is about the nature of risk. The traditional across the banking, financial and capital markets risks we grew up with, such as credit, market and ecosystem, colleagues, ladies and gentlemen. liquidity risk, have not gone away. In some ways, It is a pleasure to be with you this evening they have become more complex. Lending is more at “Success Through Synergy”. This annual event is granular, markets are deeper, and interconnectedness an invaluable platform for thoughtful conversations has increased. At the same time, new categories of on where our industry is headed. I am grateful for the risk have come to the fore. opportunity to share a few reflections. Technology has blurred the boundaries between I am also aware that I stand between you and a banks, non-banks and big tech firms. Competition is celebrity cricketer. So, I will keep my innings brief and no longer only from the bank across the street. It may brisk, rotate the strike between a few key themes, and be from an app that lives on your customer’s phone. then retire gracefully to the dugout quickly so that all Reputation risk has become sharper in a world where of us can get to witness the legendary Laxman play information, and misinformation, travel instantly. A his strokes! single customer complaint, if not handled well, can We are meeting at a time when banking is being become a public issue in a few hours. reshaped by powerful forces. Technology is changing Climate-related risks, physical as well as how customers interact with financial services. transition-related, are starting to make impact. Cyber Markets are more integrated, and shocks travel risk is now a permanent feature of bank risk registers. faster. Geopolitical developments, climate risks and The cost of one major incident can far exceed the loss cyber threats are adding new layers of complexity. from a traditional fraud. At the same time, India’s economic prospects, digital In this setting, risk management and governance public infrastructure and entrepreneurial energy are creating huge opportunities. cannot be a back-office function. They are central to strategy. Senior management and Boards have to ask In such an environment, success for any one themselves not only “What is our return on capital” institution cannot come in isolation. It depends on the but also “What risk culture are we building”. strength of the entire ecosystem, and on the quality of collaboration among banks, non-banks, market Ball 2: Drivers of customer service in a digital era participants, fintechs, regulators and customers. That The second one is on customer service. Technology is why the theme “Success Through Synergy” is so apt. has given us powerful tools to reach customers, to * Speech by Shri Swaminathan J, Deputy Governor at “Success Through simplify processes and to make payments and credit Synergy” an annual banking event organised by Standard Chartered Bank on November 28, 2025. more convenient. RBI Bulletin December 2025 17SPEECH Reading the Pitch: Banking Strategies for a Long Innings But the basic expectations of customers remain show up most clearly when something has gone very human. They want to be treated fairly. They wrong. This is where robust internal grievance want products that are suitable for their needs, redress mechanisms are critical. explained in simple terms. They want transparency Cyber fraud and digital scams have increased, and in pricing and conditions. And when something goes they can cause real hardship to ordinary customers. wrong, they want someone to listen and resolve their Banks have invested in systems to detect suspicious problem promptly. transactions, to send alerts and to strengthen In a digital, high-speed world, the test of customer authentication. These efforts are welcome and must service is not only “Did we respond?” but “Did we continue. But technology alone is not enough. Sharing actually solve the issue fairly and quickly?” of fraud typologies, coordinated efforts to take down mule accounts, and working with law enforcement Customer service is also about inclusion. The agencies are all important. design of products and interfaces must be easy to access, not only to the tech-savvy, but also to those From the customer’s perspective, what matters who may be less comfortable with digital interfaces. is not who is legally liable under the fine print. What matters is whether they feel their bank stood by them Ball 3: Innovation and collaboration with fintechs in a moment of stress. In the long run, that perception The third point is about innovation and affects trust more than any advertisement campaign. partnership. Fintechs have entered almost every This is where financial literacy and awareness segment of financial services, from payments and also become part of our agenda. When banks invest small ticket credit to wealth management and cross- in helping users navigate digital channels safely, they border remittances. Many of them have brought fresh are building a more resilient customer base. ideas, agility and a new way of looking at customer Ball 5: Data, analytics and responsible use of “the pain points. new oil” Banks bring something equally important. They The fifth idea is about data. It has often been bring trust, balance sheet strength, experience in said that data is the new oil. I would add that data is managing risk over cycles, and deep knowledge of also like water. It can sustain life if used properly, but regulation and compliance. if it is polluted or misused, it can cause damage. The question is not whether banks will “win” Banks sit on large volumes of customer data. With against fintechs or vice versa. The question is how appropriate analytics, this data can generate insights we can structure partnerships where the strengths of into behavioural patterns. It can help improve each are combined in a safe and sustainable way. underwriting, detect early signs of stress, and tailor In cricketing terms, it is like a good batting products to suit different customer segments. It can partnership where both players complement each help reduce costs and improve efficiency. other, respect the match conditions and run between At the same time, responsible use of data is the wickets with mutual understanding. essential. Customers must have confidence that their Ball 4: Customer centricity, grievance redress and data is being used with care, that privacy is respected, cyber frauds and that there is no misuse or unauthorised sharing. The fourth point brings us to a very important Models and algorithms must be explainable to issue. Customer centricity is not a slogan. It must management and boards, and their outcomes need to 18 RBI Bulletin December 2025Reading the Pitch: Banking Strategies for a Long Innings SPEECH be monitored for fairness and unintended exclusion. important. But at the end of the day, decisions are Both banks and supervisors may increasingly use made by people, and culture is shaped by the tone at advanced analytics, but these tools should support the top. human judgment, not replace it. Strong governance, an ethical culture, and a Ball 6: IT resilience and third-party dependencies clear sense of purpose are what allow institutions to navigate cycles, absorb shocks and serve their The sixth and last point is about resilience. As customers and the economy over the long term. banks digitise more and more of their operations and move to cloud and outsourced solutions, their As regulators, we see banks as partners. Our role dependence on IT systems and third-party providers is like that of the umpire: we set and interpret the has increased significantly. Outages that earlier rules, monitor the game and call out the occasional affected only a branch can now affect millions of no-ball or wide when needed, so that the play customers. Even planned downtimes need to be remains fair and safe. The task of scoring runs, by communicated and managed carefully. serving customers well, managing risks prudently and supporting growth, rests with you. Banks cannot simply rely on the assurance of service providers. They must understand the Let me conclude with one final cricketing technology, the control environment and the thought. In T20 cricket, it is tempting to go for big concentration risk arising from many institutions shots every ball. In Test cricket, patience, discipline, and respect for match conditions matter more. Our relying on the same provider. financial system must combine both mindsets. We The question is not whether an incident will need the innovation and energy of T20, but we must ever happen. The question is how quickly and anchor it in the prudence and resilience of Test effectively the institution can detect, contain and cricket. Only then can we build institutions that not recover from it. only post quick scores, but also stay at the crease for Bringing it all together decades. If you look back at these six balls in that over, a I wish all of you continued success in your common thread runs through them. It is the central journey. May your partnerships be strong, your importance of governance, culture and people. defences solid, your shots well timed, and your Technology, data, regulation and processes are all innings long. Jai Hind. RBI Bulletin December 2025 19Micro Matters, Macro Momentum: Microfinance for Viksit Bharat SPEECH Micro Matters, Macro microfinance can travel far beyond traditional branch footprints. Momentum: Microfinance for This progress shows up in the numbers. The Viksit Bharat* Financial Inclusion Index has moved from 43.4 on March 31, 2017, to 67.0 on March 31, 2025. That Shri Swaminathan J. is a meaningful shift in access and availability. However, the task now is depth and quality of use. Shri Harsh Bhanwala and other distinguished In that context, let me share four reasons as to why members on the Board of MFIN; CEO, MFIN, Dr. microfinance matters. Alok Misra; Director, Bankers Institute of Rural First, it bridges asymmetry. Many low- Development, Dr. Nirupam Mehrotra; esteemed income households have irregular incomes, thin industry leaders, distinguished guests, awardees documentation, and no collateral. Microfinance of the ASCEND programme, ladies, and gentlemen. enables them to obtain small loans, where instalments Good evening. are aligned to real cash cycles rather than to a salaried It is a pleasure to join you today at the launch calendar. of Micro Matters: Macro View - India Microfinance Second, it creates productive capacity. Credit Review FY 2024-25 and the special session on is deployed into inventory, livestock, tools, and “Microfinance for Viksit Bharat.” My compliments to working capital. Small assets start generating cash Dr. Alok Misra and the MFIN team for producing a that can service the next, slightly larger loan which timely mirror of the sector and a compass for the road can eventually transform a person into a micro- ahead. entrepreneur. The theme of this year’s review captures a Third, it serves as a platform for innovation. powerful idea: when microfinance is delivered Assisted digital journeys, Aadhaar-based KYC, responsibly, it does not remain “micro.” It becomes alternative credit scoring, etc. were first proven at macro progress. It turns access into livelihoods, the frontiers of microfinance. The sector often pilots borrowers into business owners, and informal activity what the rest of the system later scales. into measurable economic output. As we work toward Lastly and most importantly, it brings the Viksit Bharat 2047, the question is how microfinance benefits of formal finance to those otherwise can contribute most - how we scale its impact soundly, excluded and help them create a transaction record. transparently and with accountability. That record opens doors to larger formal credit over Why Microfinance matters now? time and connects households to savings, insurance, and pensions. Over the last decade, India has laid strong rails for inclusion. Jan Dhan has given households a basic In sum, microfinance can turn access into use, and use into progress on rails the country has already account, Aadhaar has simplified verification, UPI built. The agenda now should be to convert reach has made small payments instant, and the Account into inclusive growth through better underwriting, Aggregator framework has the potential to unlock reasonable pricing and consistent customer consented cash-flow data. On these public rails, protection. With that in view, let me outline five key * Speech by Shri Swaminathan J, Deputy Governor at the MFIN event at Mumbai on November 14, 2025. ideas that can shape the next phase. RBI Bulletin December 2025 21SPEECH Micro Matters, Macro Momentum: Microfinance for Viksit Bharat Five ideas to shape the next phase Regulatory initiatives and supervisory expectations Serve the household, not just the applicant: Credit In 2022, the Reserve Bank undertook a careful decisions work best when they read the full cash life reset of the microfinance framework. After extensive cycle of the family. It is better to promote a savings stakeholder feedback, a revised framework was issued habit, a basic insurance cover, and a short emergency with the overarching intent to expand inclusion, line, as all these together can make credit quality place borrower welfare at the centre, and align rules predictable. across all regulated lenders offering microfinance. Along with clarifying what qualifies as microfinance, Tech-enabled underwriting with human the framework also removed pricing caps, a long- judgment: Technology can help overcome thin files, standing demand of the industry. but human expert judgment must stay. AI models must be explainable, so review exceptions by a Greater flexibility brings a higher bar for conduct. The Reserve Bank expects lenders to use the human, and back-test results regularly. The aim is room provided by the 2022 framework in a way that less friction, not less prudence. strengthens borrower welfare and long-term portfolio From mono-product to micro-enterprise finance: quality. Let me therefore enumerate some of our Product design needs to match how small businesses expectations. actually grow. A single working-capital loan is often Pricing and transparency: Pricing should be the first step; but it should progressively graduate reasonable, reflecting cost, risk, and efficiency into inventory finance, capital asset financing, and improvements, and not taking undue advantage of basic payments support. the borrower’s situation. Customers deserve a clear Build climate resilience at the base of the view, which means plain-language loan agreements/ pyramid: Climate is now a credit variable. Districts contracts that set out instalments, fees, and total cost; face heat spikes, floods, or erratic rainfall that strain and staff who can explain these in local language. household income and collections. Lenders have to Where technology or funding reduces cost-to-serve, respond with products that can keep customers and borrowers should also reap the benefit. Boards of portfolios steady through weather shocks. entities are expected to review spreads against cost Responsible use of data: the rails and the data of funds and operating efficiency, and to question must work for the borrower. Customer data and outliers. its privacy is a responsibility. Consent should Lending should not result in over-indebtedness: be clear and in local language, data used for the A proper assessment should consider all sources of purpose stated, and storage kept secure. Used income, recognise seasonal variability, and verify all well, these rails prevent over-indebtedness and current obligations to ensure that additional lending enable responsible personalisation rather than does not lead to unsustainable indebtedness. indiscriminate up-selling. Collections conduct and grievance redress: Taken together, the aim is to convert first access Outsourcing collections does not dilute into regular use, regular use into stable income, and accountability. Lenders remain responsible for how stable income into a clear route to formal credit. This customers are treated, including by BCs and recovery is the quality of growth the sector should now aim agents. Grievances must be easy to file, acknowledged for. promptly, and resolved within published timeframes. 22 RBI Bulletin December 2025Micro Matters, Macro Momentum: Microfinance for Viksit Bharat SPEECH Further, the quality of resolution matters as much as Governance, incentives, and culture: Incentives speed. should reward responsible growth, accurate underwriting, and good conduct, not just volumes. Model risk, analytics, and fairness: Digital Complaint analysis, collections exceptions, and adoption is welcome when it improves suitability pricing outliers deserve board time. and reduces friction. Analytics and models require Eventually if industry standards remain high, strong governance. Inputs should be documented, regulatory or supervisory intervention can stay light. and outcomes should be tested for accuracy and Flexibility and accountability travel together; the unwanted bias. sector’s longevity and health depends on that balance. Accurate reporting: Bureau reporting needs to be Let me end with a line1 from Smt. Ela R. Bhatt, timely and complete so good repayment behaviour who founded SEWA and pioneered the concept of travels with the borrower and lenders can see total microfinance through women led SHGs in the 1970s. obligations of a borrower. Inaccurate or late reporting hurts both households and institutions. “When we put the human being at the centre, we begin to get a more holistic and integrated view Operational resilience and partner hygiene: of development. We begin to co-relate our activities Resilience must reach the last mile. Cyber hygiene with its impact on our own self, on the society we live at branch, partner, and device level protects both in, and on the universe we live in. And in this way we customers and institutions. Partner due diligence restore balance and harmony in the world.” for Business Correspondents and Direct Selling If we stay true to these basics, more first time Agents should follow a common baseline that covers loan customers will graduate to larger formal credit, training, data handling, and conduct standards, with and the quality of growth will rise across states and periodic spot checks. segments. That is how micro becomes macro progress, Concentration risk and early warning: and how we advance the larger journey to Viksit Concentration, whether geographic or segmental can Bharat 2047. My compliments and thanks to MFIN magnify shocks. Early warning frameworks that track for this opportunity, to lenders and partners across skip patterns, roll-rates, repeat top-ups, etc. allow the ecosystem, and to the field teams who carry this timely course correction. work to the last mile. Jai Hind. 1 Women’s World Banking, Speech by Smt. Ela R. Bhatt at the Gandhi Lecture on Non-violence at McMaster University on October 18, 2013. https://www.womensworldbanking.org/insights/women-poverty- ela-bhatt-ghandi-lecture-nonviolence-mcmaster-university. RBI Bulletin December 2025 23Timely and Topical Statistics for Agile Policy Making SPEECH Timely and Topical Statistics for production baskets are changing rapidly. But that is not all. Agile Policy Making* Alongside, the ways in which we produce, Dr. Poonam Gupta market, distribute, and finance consumption and investment are evolving too. Global and domestic supply chains are realigning. Savings and investment Good morning, Dr. Mahendra Dev, Chairman, habits of households are changing, as are the modes EAC-PM, Dr. Saurabh Garg, Secretary, Ministry of of financial intermediation. All of these have a bearing Statistics and Programme Implementation (MoSPI), on what we construct and how we construct our key officers from MoSPI, fellow economists, and fellow macro data series. policymakers. It is my privilege to be a part of this pre- In my remarks, I will briefly outline some of the release consultative workshop. initiatives we are taking at the Reserve Bank of India I would like to recognise the leadership of Dr. (RBI) in order to enhance our own data and statistical Saurabh Garg in bringing credibility, ownership, and, offerings, in view of these underlying shifts. may I say, excitement, to the process of base revision RBI’s data offerings can be grouped into three of the key macroeconomic data series of India. I would categories. also like to acknowledge the invaluable contributions of the experts, academics, and officials, many of First, as you know, the RBI curates, compiles and whom are present here today, in this exercise. The disseminates a vast amount of economic and financial data and statistics are public goods. In helping create data, at frequencies ranging from daily to annual. It the revised series, you all are performing an important is not just an important source, but at times the only source for comprehensive data on banking, the balance public service. of payments, non-banking financial companies, state Our statistical system has a long tradition of finances, municipal finances, and the finances of the professionalism, transparency, and methodological Panchayati Raj institutions. rigour. Gross Domestic Product (GDP), Consumer RBI disseminates these data promptly through Price Index (CPI), and Index of Industrial Production press releases, its flagship publications, as well as (IIP) are among the most widely used indicators through timely updates on its data portal, the Database for decision-making by governments, businesses, on Indian Economy (DBIE). financial institutions, and households. Therefore, the base revision of these series is not merely a Second, in addition to such ‘hard data’, the RBI conducts eight forward-looking surveys (four technical exercise, it is of foundational importance for at quarterly and four at bi-monthly frequency) of the wider community. With the economy becoming households, corporates, banks, and professional more diversified and digital, with rising prosperity, forecasters, covering areas such as inflation demographic shifts, evolving consumer preferences, expectations, consumer confidence, and sectoral and deeper financial inclusion, our consumption and outlooks.1 These surveys provide early signals of shifts * Speech delivered at the Pre-release Consultative Workshop on Base Revision of Consumer Price Index (CPI), Gross Domestic Product (GDP) 1 These include i. Bank Lending Survey; ii. Industrial Outlook Survey and Index of Industrial Production (IIP), Mumbai, on November 26, 2025. of the Manufacturing Sector; iii. Inflation Expectations Survey of Assistance received from Anand Shankar, Somnath Sharma, Dhirendra Households; iv. OBICUS on Manufacturing Sector; v. Rural Consumer Gajbhiye, GV Nadhanael, John V Guria, Pallavi Chavan and Tushar B Das, Confidence Survey; vi. Services and Infrastructure Outlook Survey; vii. and comments received from AR Joshi, Indranil Bhattacharya and Sangita Survey of Professional Forecasters on Macroeconomic Indicators; and viii. Misra, are gratefully acknowledged. Urban Consumer Confidence Survey. RBI Bulletin December 2025 25SPEECH Timely and Topical Statistics for Agile Policy Making in economic activity and sentiments. They serve as surveys, and corporate performance. Since 2009, it inputs in the policy deliberations as well as meet the has provided near-real-time updates of the Handbook needs of the wider community, even before the ‘hard’ of Statistics on the Indian Economy through the statistics become available. DBIE, ensuring that users receive the most current information.3 Finally, as a part of its mandate to conduct monetary policy, which under the flexible inflation The efforts to make it savvier, user friendly and targeting regime (FIT), is forward-looking, RBI extensive are continuing on an ongoing basis. Planned prepares and releases inflation and growth forecasts enhancements include a redesign of the underlying in its bi-monthly monetary policy announcements.2 data architecture, development of Application Programming Interfaces (APIs) for automatic Let me briefly describe some of our recent retrieval, improved search and visualisation tools, initiatives in each one of these offerings. and harmonised user experience across the portal, Recent Initiatives Pertaining to the ‘Hard’ Data mobile app and future digital channels. published by the RBI (ii) Data on Flow of Financial Resources and (i) The RBI compiles a large body of Outstanding Credit to Commercial Sector in India administrative and regulatory-reporting data that it - The Indian financial system has traditionally been receives directly from regulated and other entities. largely bank-dominated. Therefore, quite reasonably, These include information ranging from Basic bank credit growth has thus far been viewed as a key Statistical Returns, supervisory returns, liquidity parameter to assess the flow of financial resources and capital adequacy metrics, non-performing to the commercial sector and its implications for the assets (NPAs), to high-frequency payments data growth outlook of the economy. such as UPI, NEFT, and RTGS transactions. In recent However, given the increasing role of non- years, as the demand for timely, granular, and user- bank sources of finance, an assessment of the friendly data has increased, the RBI has intensified its broader spectrum of flow of financial resources to efforts to modernise its data dissemination systems, the commercial sector from banks and non-bank expand coverage, and enhance the user experience sources (including domestic and foreign) has become through the adoption of advanced technologies. essential. The Database on Indian Economy, was launched Against this backdrop, we have started to compile in 2004 as the RBI’s unified data dissemination data on the total flow of financial resources to the platform. Over time, the DBIE has undergone commercial sector. The non-bank sources include continuous enhancements in coverage, functionality, issuances of equity, commercial paper, and corporate and accessibility. It now hosts more than 2,000 bonds by non-financial entities directly in the statistical tables, which contain over 20,000 individual money and capital markets as well as credit to these data series spanning the real sector, financial markets, entities from non-banking financial institutions. public finance, the external sector, banking statistics, External commercial borrowings and foreign direct 2 The Reserve Bank also conducts a bi-monthly Survey of Professional investments are additional sources of resources to Forecasters to capture the assessments and expectations of economists and industry experts on major economic parameters such as GDP growth, inflation, and external-sector developments including exports and 3 The interface has been progressively refined. In addition, RBIDATA, a imports. mobile application, was launched in February 2025. 26 RBI Bulletin December 2025Timely and Topical Statistics for Agile Policy Making SPEECH the commercial sector. In fact, during 2024-25, just a Recent Initiatives in the RBI’s Surveys little less than half (48.7 per cent) of total resources Furthermore, the RBI is upgrading its enterprise to the commercial sector were mobilised from non- and household surveys. Enterprise surveys, such as bank sources. Order Books, Inventories and Capacity Utilisation Given the primacy of this information in Survey (OBICUS), and the Industrial and Services assessing overall resource flow to economic activity, Outlook surveys are being comprehensively reviewed, starting this month, we have started disseminating as their methodologies have remained largely unchanged for nearly a decade. We are planning for two tables, namely, ‘Flow of Financial Resources periodic updates to expand coverage, incorporate to Commercial Sector in India’, and ‘Outstanding emerging sectors, refine methodologies, and enhance Credit to Commercial Sector in India’ in the RBI data quality. Bulletin.4 These data will be updated and released in the RBI Bulletin on a monthly frequency from now Household surveys on inflation expectations on. and consumer confidence have been expanded progressively to more cities and rural areas over the (iii) More timely and frequent Balance of last two years. However, their broad methodology Payments Data - Further, to facilitate the timely has remained unchanged since 2018. These surveys and more frequent availability of India’s balance of are undergoing a fresh evaluation to address the gap payments (BoP) statistics, the time lag in the release between perceived and realised inflation, improve of the quarterly BoP statistics has been brought questionnaire design, and explore the inclusion of down from 90 days to around 60 days beginning household panels.6 from Q1:2025-26.5 This was achieved by optimising Recent Initiatives in our Inflation and Growth the data reporting timelines and streamlining the Forecasts internal processes. Under the FIT framework, our mandate is to Going ahead, we will endeavour to prepare and maintain price stability while keeping in mind the release the monthly BoP statistics (albeit at a slightly objective of growth. Because monetary policy operates more aggregate-level and at a lag of approximately 40 with well-recognised lags in transmission, decisions days). To achieve this, the data processing timelines taken today affect output and inflation over several of various reporting entities are being expedited and quarters. streamlined, and further internal cohesion is being established. For the Monetary Policy Committee (MPC) to fulfil its mandate effectively, it must therefore form a view 4 An article titled ‘Flow of Financial Resources to Commercial Sector in not just of current conditions, but also of where the India during 2024-25’, including outstanding credit to the commercial sector in India for three financial years, viz., 2022-23, 2023-24 and 2024- economy is likely to be in the near-term. Therefore, 25, was published in the September 2025 issue of the RBI Bulletin. Annual data on ‘Flow of Financial Resources to Commercial Sector in India’ for 6 The expected outcomes of enterprise surveys include (i) enhancing the period 2019-20 to 2024-25 (as per revised format) was published in the coverage of surveys (ii) inclusion of emerging industry-groups like the Handbook of Statistics on the Indian Economy 2024-25. semiconductors, electric vehicles, Production Linked Incentive industry- 5 This has been done without compromising the data coverage. The groups in the sampling frame (iii) revising the methodology for aggregation data are released at a disaggregated level as per the IMF’s guidelines. of survey indicators (iv) modifying the survey questionnaires, (v) adopting Additionally, the IMF has revised the BoP compilation manual with more rigorous data quality checks among others. The expected outcomes the release of its 7th edition of the Integrated Balance of Payments for Household surveys include augmenting, rewording, and refining the and International Investment Position Manual (BPM7) [from its earlier semantics of the survey questionnaire, and possibility of inclusion of BPM6] in March 2025. With these updates/developments, countries are panel of households as part of survey design (based on several rounds encouraged to publish their BoP and national account statistics in line of pilot survey) to better capture inflation expectations and economic with the BPM7 framework. sentiments of the households. RBI Bulletin December 2025 27SPEECH Timely and Topical Statistics for Agile Policy Making the bi-monthly MPC resolution provides forecasts of have also extended the scope of our stakeholder inflation and growth up to four quarters ahead.7 consultations, wherein besides, a detailed schedule of existing consultations, we have added a day- Any forecasting exercise, by its very nature, has long workshop with a rotating set of professional the risk of incurring forecast errors. forecasters so that we can learn from each other. Such errors are a common feature around the Besides minimising the forecast errors, what world. These are generally larger when there are is equally important is to ensure that there is no unpredictable shocks or events and are larger when systematic bias in the forecasts. As far as the inflation one is predicting far ahead into the future.8 Research forecasts used in the MPC resolution are concerned, has shown that variance across forecasters tends to they are unbiased. The recently released Discussion increase during periods of uncertainty.9 Inflation Paper on Review of the Monetary Policy Framework forecasting is equally challenging in India, if not more shows that, the deviation of inflation and growth so, given the high and outdated weight of food in the forecasts of the Monetary Policy Committee in India CPI basket and the volatile nature of food prices. during the inflation-targeting regime does not have Therefore, we take a multifaceted approach in any systematic directional bias from the realised forecasting inflation. This includes (i) using a suite of inflation and growth.10 structural and time-series models, each providing a Just as the inflation forecasts, the RBI uses a varied different lens on the economy; (ii) examining historical set of approaches to generate its growth projections. RBI patterns in data to identify the underlying momentum in prices, and assess the base effects, which often relies on a balanced synthesis of robust econometric shape near-term inflation dynamics; (iii) drawing analysis, contemporary economic conditions, and upon a wide range of high-frequency indicators and forward-looking sectoral perspectives in preparing its surveys to capture real-time movements in demand, projections. Among the technical models, projections supply, and their implications on prices; (iv) seeking are derived from a suite of approaches, rather than any expert views to interpret turning points, structural single model. These include the benchmark indicator breaks, and emerging risks that models alone may not approach, a dynamic factor model, and various time be able to fully capture. series models for short-term growth projections.11 We are committed to using the state-of-the- Before each Monetary Policy meeting, we hold art models and approaches to improve our forecast nearly a dozen discussions with stakeholders from the accuracy continuously. Thus, we have been assessing real sector, financial markets, banks, NBFCs, analysts, the appropriate time length that we should consider and economists. These interactions provide us with in our models, ensuring that we use more recent valuable insights into their perspectives, outlooks, and relevant information than the distant past. We 10 Annex 4: Inflation and Growth Projection Analysis. Review of Monetary Policy Framework - A Discussion Paper, RBI, August 2025. 7 Except in February MPC resolution where 5 quarter ahead projection 11 The use of multiple methods imparts robustness to RBI’s projections. for inflation is provided along with the annual inflation projection for The Benchmark Indicator Approach, which relates to deriving sectoral the next financial year. Additionally, the Reserve Bank of India Act and contributions to GDP as recommended by the NSO, is used to nowcast Monetary Policy Committee and Monetary Policy Process Regulations GDP growth. The dynamic factor model relating to deriving condensed (2016) requires the RBI to present the projections of inflation and growth factors from a wide range of high frequency indicators is also used for and the balance of risks, and an assessment of our projection performance nowcasting GDP growth. The time series models include ARIMAX in the Monetary Policy Report, released bi-annually in April and October. model (ARIMA model including exogenous variables), and VARX model 8 Inflation Forecast Accuracy Under High Volatility: Cross-Country (vector autoregressive model including both endogenous and exogenous Evidence. Box I.1 in the Monetary Policy Report, April 2023, RBI. variables). ARIMAX and VARX models complement each other as the 9 Uncertainty and Disagreement among Professional Macroeconomic former focuses on a single target variable (GDP growth), while the latter Forecasters, RBI Bulletin, November 2021. jointly models multiple variables with mutual interactions. 28 RBI Bulletin December 2025Timely and Topical Statistics for Agile Policy Making SPEECH and forecasts, which inform our assessments. Our must keep pace with an economy that is growing and periodic interactions with the NSO are noteworthy, as evolving rapidly. Regularly updating and revising the they help in improving the RBI’s methods. existing data series, as well as constructing new ones, is essential to capture ongoing transformations. We Closing Remarks all are looking forward to the revised series being The Indian economy has been a high growth prepared by MoSPI. I once again congratulate MoSPI economy that has exhibited both resilience and for launching this consultative process and wish the agility. Our statistical offerings, data and techniques workshop every success. RBI Bulletin December 2025 29ARTICLES State of the Economy Government Finances 2025-26: A Half-Yearly Review Composite Leading Indicator for GVA - Manufacturing for India Decoding Safe Asset Volatility Amid Geopolitical Risks Using Neural NetworksState of the Economy ARTICLE State of the Economy* Portfolio flows to emerging markets turned negative for the first time after six consecutive months of positive inflows, driven by outflows from equity Global uncertainty retreated further from its markets. US Treasury yields exhibited bi-directional highly elevated levels. Major equity markets experienced movements, reflecting uncertainty about the Fed rate volatile movements due to concerns about stretched outlook for 2026, and strengthening of sentiments market valuations. The Indian economy, supported by for a rate hike by the Bank of Japan in December. resilient domestic demand in Q2:2025-26, grew at its fastest pace in the last six quarters. High-frequency Global commodity prices barring precious indicators for November suggest that overall economic metals remained largely stable. Inflation in Advanced activity has held up with demand conditions remaining Economies (AEs) continued to exhibit downward robust. Headline CPI inflation edged up but continued stickiness due to persistent services inflation. to remain below the lower tolerance level. Financial Inflation in Emerging Market and Developing conditions remained benign, and the flow of financial Economies (EMDEs), in contrast, remained more resources to the commercial sector remained robust. aligned with the target. India’s current account deficit moderated in Q2:2025- Monetary policy actions by major central banks 26 over the same period last year, supported by a lower during November gravitated towards maintaining merchandise trade deficit, robust services exports, and a status quo. The month of December saw a clear strong remittance receipts. divergence in the monetary policy of some systemic Introduction central banks. There are indications that central banks are nearing the end of their rate-cutting cycle, In November, global uncertainty, including trade with a greater focus on data dependency going and policy uncertainties, retreated further from forward. its highly elevated levels. Global economic activity expanded at a steady rate in November, aided by The Indian economy, with a larger-than- new export orders and the strengthening of trade in anticipated six-quarter high GDP growth during manufacturing and services. The month of November Q2:2025-26, has demonstrated remarkable resilience also saw China’s trade surplus reach a record of more amidst persistent global trade uncertainties. Domestic than USD 1 trillion for the year so far. drivers, particularly private consumption demand, underpinned the pick-up in growth momentum. Major equity markets experienced volatile High-frequency indicators for November suggest that movements, particularly during mid-November, overall economic activity held up. Demand conditions due to concerns about stretched market valuations. remained robust, with indicators of urban demand * This article has been prepared by Rekha Misra, Asish Thomas George, strengthening further. While services sector activity Shashi Kant, Biswajeet Mohanty, Shreya Kansal, Durga G, Amin Ashraf, Vikas Anand, Sanjana Sejwal, Bhagyashree Chattopadhyay, Aayushi continued to register strong expansion in activity, Khandelwal, Ettem Abhignu Yadav, Sakshi Chauhan, Ragini, Siddharth manufacturing showed some signs of deceleration. Arya, Sarthak Gulati, Shivam, Nilava Das, Dibyarka Chaule, Manu Swarnkar, Navya Singh, Pulastya Bandhopadhyay, Avnish Kumar, Kartikey Bhargav, Samridhi, Athira C A, Pallak Goyal, and Khushi Sinha. In November, the merchandise trade deficit The guidance and comments provided by Dr. Poonam Gupta, Deputy narrowed on account of a surge in merchandise Governor, are gratefully acknowledged. Peer review by Monika Sethi and Shromona Ganguly is also acknowledged. Views expressed in this article exports and a contraction in merchandise imports. are those of the authors and do not represent the views of the Reserve Bank of India.t represent the views of the Reserve Bank of India. Net services exports growth moderated in October, RBI Bulletin December 2025 31ARTICLE State of the Economy with both services exports and imports growth November from a month ago and remained relatively witnessing a slowdown in pace. lower than that for most major currencies. Headline CPI inflation edged up in November India’s external sector exhibited resilience but continued to remain below the lower tolerance despite a challenging global environment. Current level for the third consecutive month. Moderation account deficit narrowed in Q2:2025-26 compared to in food deflation and the setting-in of unfavourable that for the same period last year with a moderation in merchandise trade deficit, robust services trade base effects contributed to the uptick in headline surplus, and resilient remittances. Capital flows, inflation. Core (i.e., CPI excluding food and fuel) however, were tempered by persistent global inflation remained steady; however, after abstracting uncertainties. Foreign exchange reserves remain the impact of gold and silver prices, it fell to a new sufficient to comfortably meet India’s external all-time low. financing requirements. The Monetary Policy Committee (MPC), in its Set against this backdrop, the remainder of bi-monthly review of December 2025, unanimously the article is structured into four sections. Section decided to reduce the policy repo rate by 25 bps to II covers the rapidly evolving developments 5.25 per cent. The MPC also decided to maintain its in the global economy. Section III provides an neutral stance. The decisions were guided by the assessment of domestic macroeconomic conditions. benign inflation outlook for both headline and core, Section IV encapsulates financial conditions in which provided space for monetary policy to further India, while Section V presents the concluding support the growth momentum. observations. Financial conditions remained benign with II. Global Setting system liquidity in surplus during the second half of Global uncertainty continued to moderate in November and early December. The weighted average November, extending the mild retreat observed call rate – the operating target of monetary policy – in October, even though the level of uncertainty remained broadly aligned with the policy repo rate. indices remained elevated. World trade and policy Growth in bank deposits registered an uptick in uncertainties eased, supported by renewed traction November. The total flow of financial resources to in US trade negotiations and the resolution of the US the commercial sector remained strong, bolstered by government shutdown. Financial market volatility, robust non-bank intermediation. which surged during the third week of November Indian equity markets witnessed a rebound due to concerns about stretched AI valuations, in the first half of November and exhibited bi- moderated thereafter on strong corporate earnings. directional movements thereafter. While healthy Volatility resurfaced during mid-December with corporate results for Q2:2025-26 and policy rate renewed scepticism around AI investments (Charts II.1a and II.1b). cuts by the Reserve Bank and the US Fed improved market sentiments, muted foreign portfolio flows The global composite PMI for November and uncertainty surrounding the India-US trade deal continued to indicate an expansion in economic weighed them down. Foreign portfolio outflows from activity, albeit at a slower rate than in the previous the equity markets exerted downward pressure on month. New export orders stabilised after contracting the rupee; nonetheless, rupee volatility moderated in for seven consecutive months, supported by 32 RBI Bulletin December 2025State of the Economy ARTICLE Chart II.1: Global Uncertainty Eased Further, Markets Experienced Volatile Movements a. Uncertainty Indices b. Volatility Indices Index (Jan 2024 = 100) Index (Jan 2025 = 100) 800 12000 700 10000 600 8000 500 400 6000 300 4000 200 2000 100 0 0 World Uncertainty Index World Policy Uncertainty Index US VIX Emerging Markets VIX World Trade Uncertainty Index (RHS) EURO STOXX VIX Sources: World Uncertainty Index (WUI) database; and Bloomberg. improved trade for manufactured goods and services witnessed a fresh rise in contrast with a sustained from China following the dissipation of trade contraction for most AEs (Charts II.2a and II.2b). tensions between the US and China (Table II.1). Global commodity prices remained largely stable. Business activity, as reflected by PMI indices Divergent movements were also observed across expanded across major AEs except Canada. Among commodity markets, with a continued uptick in gold major EMDEs, business activity expanded in India prices and a softening bias in crude oil prices. World and China but contracted in Brazil. As regards Bank Commodity Price Index for November remained new export orders, EMDEs led by India and China steady as lower energy prices were offset by modest Table II.1: Global PMI Composite Eased Modestly, Export Orders Come out of Contraction Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 Jun-25 Jul-25 Aug-25 Sep-25 Oct-25 Nov-25 PMI composite 52.4 52.6 51.8 51.5 52.1 50.8 51.2 51.7 52.5 52.9 52.5 52.9 52.7 PMI manufacturing 50.1 49.6 50.1 50.6 50.3 49.8 49.5 50.4 49.7 50.9 50.7 50.8 50.5 PMI services 53.1 53.8 52.2 51.5 52.7 50.8 52 51.8 53.5 53.3 52.9 53.4 53.3 PMI export orders 49.3 48.7 49.6 49.7 50.1 47.5 48.0 49.1 48.5 48.9 49.7 48.5 50.0 PMI export orders: 48.6 48.2 49.4 49.6 50.1 47.3 48.0 49.2 48.2 48.7 49.5 48.3 49.9 manufacturing PMI export orders: 51.3 50.3 50.2 50.2 50.1 48.2 47.9 48.7 49.4 49.3 50.1 49.3 50.3 services 50 <<<<<<Contraction---------------------------------------------------------------Expansion>>>>>> Notes: 1. The Purchasing Managers’ Index (PMI), a diffusion index, captures the change in each variable compared to the prior month, noting whether each has risen/improved, fallen/deteriorated or remained unchanged. A PMI value >50 denote expansion; <50 denote contraction; and =50 denote ‘no change’. 2. Heat map is applied on data from April 2023 till November 2025. The map is colour coded–red denotes the lowest value, yellow denotes 50 (or the no change value), and green denotes the highest value in each of the PMI series. Source: S&P Global. RBI Bulletin December 2025 33 42-naJ 42-raM 42-yaM 42-luJ 42-peS 42-voN 52-naJ 52-raM 52-yaM 52-luJ 52-peS 52-voN 310 280 250 220 190 160 130 100 70 52-naJ-10 52-naJ-32 52-beF-41 52-raM-80 52-raM-03 52-rpA-12 52-yaM-31 52-nuJ-40 52-nuJ-62 52-luJ-81 52-guA-90 52-guA-13 52-peS-22 52-tcO-41 52-voN-50 52-voN-72 52-ceD-91ARTICLE State of the Economy increases in non-energy items. Food and Agriculture the back of supply disruptions and price distortions Organization’s Food Price Index declined for the third due to tariff risks. Brent crude oil prices traded with a consecutive month, dragged by dairy products, meat, downside bias due to concerns about oversupply and sugar and vegetable oils (Chart II.3a). Bloomberg growing optimism over a possible Russia-Ukraine Commodity price index increased further, driven by peace deal (Chart II.3b). precious metals. Gold prices rose in November on Fed rate cut expectations and continued to increase Headline inflation presented contrasting further in December. Copper prices inched higher on pictures across economies. Inflation eased but Chart II.3: Commodity and Food Prices a. Commodity and Food Indices b. Gold - Copper - Brent Crude Oil Index (Jan 2024 = 100) Index (Jan 2025 = 100) 110 105 100 95 90 Food and Agriculture Organization Food Price Index Bloomberg commodity index World Bank Commodity Price Index Gold Copper Brent Crude oil Sources: Food and Agriculture Organization; Bloomberg; and World Bank. 34 RBI Bulletin December 2025 42-naJ 42-raM 42-yaM 42-luJ 42-peS 42-voN 52-naJ 52-raM 52-yaM 52-luJ 52-peS 52-voN 160 150 140 130 120 110 100 90 80 70 52-naJ-10 52-naJ-32 52-beF-41 52-raM-80 52-raM-03 52-rpA-12 52-yaM-31 52-nuJ-40 52-nuJ-62 52-luJ-81 52-guA-90 52-guA-13 52-peS-22 52-tcO-41 52-voN-50 52-voN-72 52-ceD-91 Chart II.2: Purchasing Managers’ Index: Comparison across Jurisdictions a. S&P Global Composite PMI b. PMI Export Orders (Index) (Index) 62 58 54 50 46 42 Oct-25 Nov-25 Oct-25 Nov-25 Note: A level of 50 of the PMI indicates no change in activity, while a reading above 50 signals expansion and below 50 suggests contraction. Source: S&P Global. aidnI eropagniS niapS setatS detinU ylatI enozoruE labolG ailartsuA ynamreG napaJ modgniK detinU anihC ecnarF aissuR lizarB adanaC 54 50 46 42 aidnI anihC ylatI ailartsuA ecnarF dlroW enozoruE setatS detinU niapS aissuR modgniK detinU napaJ ynamreG adanaCState of the Economy ARTICLE Chart II.4: Headline Inflation a. Select AEs b. Select EMDEs (Per cent) (Per cent) 4.0 3.5 3.2 3.0 2.9 2.7 2.5 2.1 2.0 1.5 1.0 Brazil Russia China US UK Euro area Japan South Africa India Source: Bloomberg. remained at elevated levels in AEs amidst persistent December on strong earnings from the financial services inflation. In the Euro area, headline inflation and IT sectors, before falling as tech valuation increased further in November driven by services fears resurfaced. Japan’s stock market witnessed costs, while inflation in the US eased. Inflation net gains since the end of November propelled by in the UK fell to a six-month low led by food and fiscal stimulus before falling again on increasing beverages. Japan’s inflation also edged lower on low expectations of monetary tightening. Chinese food inflation (Chart II.4a). Among major EMDEs, equity markets edged lower as technology stocks inflation picked up in China to a 21-month high retreated, even as stronger than expected exports driven by a rebound in food prices even as core and regulatory easing for high-performing securities inflation remained steady. In contrast, a lower food firms provided support (Chart II.5a). inflation led to easing of inflationary pressures In November, US Treasury yields declined amidst in Brazil and in Russia, where headline inflation increasing rate cut expectations. Yields, thereafter, moderated to its lowest level since September 2023. firmed up to a 16-year high in early December Inflation in South Africa eased due to moderation in following hawkish comments from the Bank of transport costs (Chart II.4b). Japan. Though yields moderated post the Fed policy Equity markets in the US fell until the third in December, the fall was capped by uncertainty on week of November on concerns about stretched Fed rate outlook for 2026. The JP Morgan emerging valuations of tech companies. Subsequently, markets market bond yield spread, on an average, narrowed recovered with strong corporate results and edged sequentially in November-December so far (Chart up in December following the Fed rate cut. However, II.5b). After moving sideways in November, the US it pared gains with the re-emergence of valuation dollar weakened in December on soft economic data concerns. European stocks gained during November- and concerns about a shrinking yield advantage over RBI Bulletin December 2025 35 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voN 9 6.6 7 5 4.5 3 3.5 1 0.7 0.7 -1 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voNARTICLE State of the Economy Chart II.5: Global Financial Markets a. Equity Indices: Select Economies b. Government Bond Yields Index (April 07, 2025=100) (Per cent, left scale; Index, right scale) 350 4.7 330 4.5 310 4.3 290 4.2 270 4.1 250 232.1 3.9 230 S&P 500 SSE Composite Index Nikkei 225 STOXX 600 Note: Equity markets are represented by S&P 500 for US, SSE Composite Index for US Govt Bonds J.P. Morgan EMBI Global Spread (RHS) China, Nikkei 225 for Japan, and STOXX 600 for Europe. Source: Bloomberg. Source: Bloomberg. c. Currency Indices d. Portfolio Flows to Emerging Markets (Index, left scale; Index, right scale) (US$ billion) MSCI EME currency index Dollar index (RHS) Debt Equity Total Source: Bloomberg. Source: Institute of International Finance. other economies as Fed cut its policy rate (Chart II.5c). The month of December saw a clear divergence Portfolio flows to emerging markets turned negative in the monetary policy of some systemic central in November after a six-month streak of inflows. banks. While the US and the UK delivered a rate Equity markets registered significant outflows on cut emphasising the soft labour market conditions, weak global risk appetite while debt flows remained Japan increased its policy rate to a 30-year high as steady and positive (Chart II.5d). inflation remained above target. Seven out of 15 central banks that held their meetings in December In November 2025, most major central banks kept their key policy rates unchanged. Among the kept policy rates unchanged. Among the AEs, while AEs, Australia, Canada, Switzerland, Euro area, and South Korea maintained status quo on financial Sweden held their key rates unchanged. Amongst stability risks, New Zealand cut the rate to an over EMDEs, Indonesia and Brazil kept their interest three-year low on growth considerations. In the case rates unchanged for the third and fourth consecutive of EMDEs, China, Malaysia, and Indonesia kept their meeting, respectively. Russia, Philippines, Thailand interest rates unchanged in November, whereas and Mexico cut their policy rates (Chart II.6). South Africa reduced the policy rate due to concerns about growth. 36 RBI Bulletin December 2025 52-naJ-10 52-naJ-32 52-beF-41 52-raM-80 52-raM-03 52-rpA-12 52-yaM-31 52-nuJ-40 52-nuJ-62 52-luJ-81 52-guA-90 52-guA-13 52-peS-22 52-tcO-41 52-voN-50 52-voN-72 52-ceD-91 1,860 110 1839.2 1,840 108 1,820 106 1,800 104 1,780 102 11 ,, 77 46 00 98.6 100 1,720 98 1,700 96 52-naJ-10 52-naJ-32 52-beF-41 52-raM-80 52-raM-03 52-rpA-12 52-yaM-31 52-nuJ-40 52-nuJ-62 52-luJ-81 52-guA-90 52-guA-13 52-peS-22 52-tcO-41 52-voN-50 52-voN-72 52-ceD-91 50 30 10 -10 -30 -50 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voN 165 155 145 135 125 115 105 95 52-rpA-3 52-rpA-61 52-rpA-92 52-yaM-21 52-yaM-52 52-nuJ-7 52-nuJ-02 52-luJ-3 52-luJ-61 52-luJ-92 52-guA-11 52-guA-42 52-peS-6 52-peS-91 52-tcO-2 52-tcO-51 52-tcO-82 52-voN-01 52-voN-32 52-ceD-6 52-ceD-91State of the Economy ARTICLE Chart II.6: Central Banks Pursued Divergent Policy Rate Paths in December Type Countries III. Domestic Developments Aggregate Demand The Indian economy, supported by resilient In Q2:2025-26, real gross domestic product domestic demand, grew at its fastest pace in the (GDP) registered a growth of 8.2 per cent, the highest last six quarters in Q2:2025-26. On the supply side, since Q4:2023-24, on the back of robust private services and industrial sectors exhibited robust consumption and fixed investment. The growth growth despite the ongoing global trade and policy in private consumption was sustained by a robust uncertainties. Available high-frequency indicators rural demand and easing inflationary pressures. Net suggest that overall economic activity held up in the exports continued to be a drag on growth (Chart III.1 post-festival month of November. While services and Annex Table A1). activity continued to register strong expansion, Notwithstanding a sharp uptick in real GDP manufacturing showed some signs of deceleration. growth in Q2, the nominal GDP registered a four- quarter low growth of 8.7 per cent. The narrowing The Monetary Policy Committee (MPC), in its of the gap between nominal and real GDP growth bi-monthly review of December 2025, unanimously reflected the moderation in the GDP deflator to a low decided to reduce the policy repo rate by 25 bps to of 0.5 per cent (Chart III.2). 5.25 per cent. The MPC also decided to continue with the neutral stance. The decisions were guided by the The high-frequency indicators suggest that overall benign inflation outlook for both headline and core, economic activity held up in the post-festival month which provided space for monetary policy to further of November. While the low GST revenue collections support the growth momentum. were largely influenced by GST rate rationalisation, RBI Bulletin December 2025 37 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voN 5202.21.91 Australia 0 0 0 0 0 0 0 0 0 0 0 0 Canada 0 0 0 0 0 0 0 0 0 0 0 0 Euro area 0 0 0 0 0 0 0 0 0 0 0 0 Japan 0 0 0 0 0 0 0 0 0 0 0 0 New Zealand 0 -1 0 0 0 0 0 0 0 -1 0 0 Advanced Economies South Korea 0 0 0 0 0 0 0 0 0 0 0 0 Sweden 0 0 0 0 0 0 0 0 0 0 0 0 Switzerland 0 0 0 0 0 0 0 0 0 0 0 0 United Kingdom 0 0 0 0 0 0 0 0 0 0 0 0 United States 0 0 0 0 0 0 0 0 0 0 0 0 Brazil 1 0 1 0 1 0 0 0 0 0 0 0 China 0 0 0 0 0 0 0 0 0 0 0 0 India 0 0 0 0 0 -1 0 0 0 0 0 0 Indonesia 0 0 0 0 0 0 0 0 0 0 0 0 Malaysia 0 0 0 0 0 0 0 0 0 0 0 0 Emerging Market and Mexico 0 -1 -1 0 -1 -1 0 0 0 0 0 0 Developiong Economies Philippines 0 0 0 0 0 0 0 0 0 0 0 0 Russia 0 0 0 0 0 -1 -2 0 -1 -1 0 0 Saudi Arabia 0 0 0 0 0 0 0 0 0 0 0 0 South Africa 0 0 0 0 0 0 0 0 0 0 0 0 Thailand 0 0 0 0 0 0 0 0 0 0 0 0 Rate change < -0.75 -0.75 to -0.50 -0.50 to -0.25 -0.25 to <0 0 (No change) >0 to 0.25 0.25 to 0.50 0.50 to 0.75 > 0.75 Colour Note: White-coloured blocks indicate an off-policy month. Source: Bloomberg.ARTICLE State of the Economy Chart III.1: Weighted Contribution to GDP Growth Chart III.2: Moderation in GDP Deflator Inflation (Percentage points) (Per cent) 15 4 10 8.2 3 5 0 2 -5 Q1 Q2 Q3 Q4 Q1 Q2 1 2024-25 2025-26 0.5 Private final consumption expenditure Gross fixed capital formation Government final consumption expenditure 0 Net exports Others Q1 Q2 Q3 Q4 Q1 Q2 GDP (Y-o-y growth, per cent) 2024-25 2025-26 Note: Others include change in stocks, valuables, and statistical discrepancies. Source: National Statistics Office (NSO). Sources: NSO; and RBI staff calculations. other available high-frequency indicators of increase in petroleum consumption was driven by a economic activity such as e-way bills, petroleum pick-up in construction and agricultural operations. consumption and digital payments, registered a Digital payments registered robust growth in both pick-up in growth. The sharp increase in e-way bill transaction value and volume. Electricity demand generation indicates a rise in goods movement and declined for the second consecutive month due to freight activity supported by the GST reforms. The the early onset of winter season (Table III.1). Table III.1: High Frequency Indicators of Overall Economic Activity Indicator Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 Jun-25 Jul-25 Aug-25 Sep-25 Oct-25 Nov-25 GST E-way bills 16.3 17.6 23.1 14.7 20.2 23.4 18.9 19.3 25.8 22.4 21.0 8.2 27.6 GST revenue 0.6 7.3 12.3 9.1 9.9 12.6 16.4 6.2 7.5 6.5 9.1 4.6 0.7 Toll collection 11.9 9.8 14.8 18.7 11.9 16.6 16.4 15.5 14.8 12.7 4.5 4.6 2.9 Electricity demand 3.7 5.1 1.3 2.4 5.7 2.8 -4.8 -2.3 2.6 3.8 3.5 -5.8 -0.6 Petroleum consumption 10.6 2.0 3.0 -5.2 -3.1 0.2 1.1 0.5 -4.4 4.8 7.6 -0.4 3.0 Of which 9.6 11.1 6.7 5.0 5.7 5.0 9.2 6.8 5.9 5.5 8.0 7.4 2.6 Petrol Diesel 8.5 5.9 4.2 -1.3 0.9 4.2 2.1 1.5 2.4 1.2 6.6 -0.3 4.7 Aviation turbine fuel 8.5 8.7 9.4 4.2 5.7 3.9 4.4 3.3 -2.3 -2.9 -0.8 2.1 5.4 Digital payments - Volume 30.1 33.1 33.0 26.7 30.8 30.0 29.2 28.3 30.9 31.1 28.1 21.5 27.2 Digital payments - Value 9.5 19.6 18.6 9.5 17.3 18.4 12.6 17.4 16.6 5.3 13.4 8.8 14.9 <<Contraction --------------------------------------------------------------------------------------- Expansion>> Notes: 1. The y-o-y growth (in per cent) has been calculated for all indicators. 2. The heatmap is applied on data from April 2023 to the latest month for which data is available. Digital Payments data for November 2025 are provisional. 3. The heatmap translates the data range for each indicator into a colour gradient scheme with red denoting the lowest values and green corresponding to the highest values of the respective data series. 4. The data on toll collections for November 2025 growth rate is calculated by aggregating daily data. Sources: Goods and Services Tax Network (GSTN); RBI; Central Electricity Authority (CEA); National Payments Corporation of India (NPCI); and Ministry of Petroleum and Natural Gas, GoI. 38 RBI Bulletin December 2025State of the Economy ARTICLE Table III.2: High Frequency Indicators- Robust Demand Conditions Indicator Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 Jun-25 Jul-25 Aug-25 Sep-25 Oct-25 Nov-25 Urban Domestic air passenger traffic 13.8 10.8 14.1 12.1 9.9 9.7 2.6 3.7 -2.5 -0.5 -2.5 3.5 6.7 demand Retail passenger vehicle sales -11.8 -2.0 15.5 -10.3 6.3 1.6 -3.1 2.5 -0.8 0.9 5.8 10.7 19.7 Retail automobile Sales 12.0 -12.5 6.6 -7.2 -0.7 2.9 5.4 4.8 -4.3 2.8 5.2 40.5 2.1 Rural Retail tractor sales 29.9 25.8 5.2 -14.5 -5.7 7.6 2.8 8.7 11.0 30.1 3.6 14.2 56.5 demand Retail two-wheeler sales 16.3 -17.6 4.2 -6.3 -1.8 2.3 7.3 4.7 -6.5 2.2 6.5 51.8 -3.1 <<Contraction ----------------------------------------------------------------------------------------- Expansion>> Notes: 1. The y-o-y growth (in per cent) has been calculated for all indicators. 2. The heatmap is applied on data from April 2023 to the latest month for which data is available. 3. The heatmap translates the data range for each indicator into a colour gradient scheme with red denoting the lowest values and green corre- sponding to the highest values of the respective data series. 4. The data on domestic air passenger traffic for November 2025 growth rate is calculated by aggregating daily data. Sources: Airports Authority of India; Federation of Automobile Dealers Associations (FADA); and Ministry of Rural Development, GoI. During November, overall demand conditions expansionary zone. PMI employment for services remained robust. Indicators of urban demand remained steady. The Naukri JobSpeak Index surged strengthened further, building up on the festival in November led by fresh hiring especially in non- season pick-up. Retail passenger vehicle sales grew IT sectors like education, hospitality, and real estate. at their highest pace in over a year, aided by GST Work demand under the Mahatma Gandhi National benefits, marriage season demand, and improved Rural Employment Guarantee Scheme (MGNREGS) supply. Domestic air passenger traffic registered its continued to contract, suggesting improvement in fastest growth since May 2025. Retail tractor sales rural labour market conditions (Table III.3). growth, buoyed by positive rabi season prospects, During April-October, 2025, the Centre’s gross reduction in GST rates and hike in minimum fiscal deficit as per cent of budget estimate (BE) support prices of rabi crops, registered a significant was higher than the same period last financial year, pick-up. Other high frequency indicators of while the revenue deficit as per cent of BE was lower rural demand, namely, retail automobiles sales, (Chart III.3a).2 The higher fiscal deficit was driven by however, witnessed a sharp deceleration in the post higher capital expenditure and contraction in net festive season coupled with adverse base effects tax revenue.3 The revenue expenditure of the Centre (Table III.2).1 remained flat, with interest payments registering As per the Periodic Labour Force Survey (released higher growth and major subsidies recording a on December 15), the all-India unemployment rate contraction.4 A slower growth of tax revenue was declined to 4.7 per cent in November, with a fall in observed in both direct and indirect tax collections.5 both rural and urban areas. Labour force participation rate rose to a seven-month high accompanied by 2 As per the latest data released by the Controller General of Accounts (CGA). an improvement in the worker population ratio. 3 During April-October 2025-26, the y-o-y growth in capital expenditure and net tax revenue were 32.4 per cent and -2.4 per cent, respectively. The PMI employment for manufacturing witnessed net tax collections of the Centre recorded a contraction since the increase deceleration in November but remained in the in gross tax revenue during the period was more than offset by a rise in the devolution of tax from Centre to the States. 4 During April-October 2025-26, the y-o-y growth in Centre’s spending on 1 Adverse base effects stem from the festive season being in November interest payment and major subsidies were 13.0 per cent and (-) 0.8 per in 2024. cent, respectively. RBI Bulletin December 2025 39ARTICLE State of the Economy Table III.3: Robustness in High Frequency Indicators for Employment Indicator Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 Jun-25 Jul-25 Aug-25 Sep-25 Oct-25 Nov-25 Unemployment rate (PLFS: All-India) 5.1 5.6 5.6 5.2 5.1 5.2 5.2 4.7 Unemployment rate (PLFS: Rural) 4.5 5.1 4.9 4.4 4.3 4.6 4.4 3.9 Unemployment rate (PLFS: Urban) 6.5 6.9 7.1 7.2 6.7 6.8 7.0 6.5 Naukri JobSpeak Index 2.0 8.7 3.9 4.0 -1.5 8.9 0.3 10.5 6.8 3.4 10.1 -9.3 23.5 PMI employment: manufacturing 52.9 53.4 54.8 54.5 53.4 54.2 54.9 55.1 53.3 53.1 52.1 52.4 50.9 PMI employment: services 56.6 55.5 56.3 56.2 52.5 53.9 57.1 55.1 51.4 52.2 51.9 51.4 51.6 MGNREGA: work demand 3.9 8.2 14.4 2.8 2.2 -6.5 4.4 4.4 -12.3 -26.2 -27.1 -35.1 -31.9 <<Contraction --------------------------------------------------------------------------------------------- Expansion>> Notes: 1. All PLFS indicators are in the current weekly status and for people aged 15 years and above. 2. The y-o-y growth (in per cent) has been calculated for the Naukri JobSpeak Index and MGNREGA Work Demand. 3. The heatmap is applied on data from April 2023 to the latest month for which data is available. 4. The heatmap translates the data range for each indicator into a colour gradient scheme with red denoting the lowest values and green corresponding to the highest values of the respective data series. 5. All PMI values are reported in index form. A PMI value >50 denotes expansion, <50 denotes contraction and =50 denotes ‘no change’. In the PMI heatmaps, red denotes the lowest value, yellow denotes 50 (or the no change value), and green denotes the highest value in each of the PMI series. Sources: Ministry of Statistics and Program Implementation (MoSPI), GoI; Info Edge; and S&P Global. The robust performance of non-tax revenue and The deficit indicators of states during April- non-debt capital receipts had offset the contraction October 2025, as a proportion of BE for the financial in net tax revenue and supported the growth in total year, were lower than the same period last year (Chart receipts.6 III.3b). This improvement was driven by a sharp Chart III.3: Deficit Indicators (April-October) a. Union Government b. State Governments (Actuals as per cent of budget estimates) (Actuals as per cent of budget estimates) 60 140 133.8 52.2 52.6 51.8 50 120 46.7 46.5 100 40 34.3 80 30 68.1 60 20 47.1 44.6 40 38.0 25.0 10 20 0 0 Revenue Gross fiscal Primary Revenue Gross fiscal Primary deficit deficit deficit deficit deficit deficit 2024-25 2025-26 2024-25 2025-26 Note: Data pertain to 23 States/UTs. Sources: Controller General of Accounts; Comptroller and Auditor General of India; and Union Budget Documents. 5 The direct and indirect tax growth decelerated from 12.3 per cent and 8.9 per cent in April-October 2024-25 to 6.0 per cent and 1.5 per cent, respectively, in April-October 2025-26. Within major direct and indirect taxes, only corporation tax and union excise duty registered an acceleration in growth in comparison to the previous year. 6 The total receipts of the Centre comprises of revenue receipts (consists of tax revenue as well as non-tax revenue) and non-debt capital receipts (i.e., capital receipts other than borrowings). 40 RBI Bulletin December 2025State of the Economy ARTICLE moderation in revenue expenditure growth. Within October was mainly driven by gold as the post-festive revenue receipts, state excise growth remained season demand declined. As a result, gold accounted strong, while SGST growth decelerated. for 11 per cent of merchandise trade deficit in November, down from 33 per cent in October (Chart During the year so far (April-November), the III.4). Exports to the US increased in the month merchandise trade deficit was higher than that of of November after declining consecutively in the last year, primarily driven by petroleum products, previous two months.10 electronic goods and gold.7 India’s merchandise On December 11, Mexico imposed higher exports and imports during this period witnessed a import duties ranging from 5 to 50 per cent on 1400 broad-based expansion.8 products imported from countries without a free In November, the merchandise trade deficit trade agreement. Mexico is India’s major export narrowed on account of a surge in merchandise destination for three sub-segments of engineering exports and a contraction in merchandise imports.9 goods, namely, two and three-wheelers, motor The contraction in imports in November vis-à-vis vehicles / cars and auto components and parts.11 Chart III.4: India’s Merchandise Trade a. Exports Surged While Imports Declined b. Merchandise Trade Deficit Narrowed (Y-o-y, per cent) (US$ billion) 25 20 19.4 15 10 5 0 -1.9 -5 -10 -15 -20 Exports Imports Sources: PIB; DGCI&S. 7 The merchandise trade deficit during April-November 2025 was at US$ 223.1 billion as against US$ 203.3 billion during April-November 2024. 8 17 out of 30 major commodities (accounting for 58.2 per cent of exports basket) and 19 out of 30 major commodities (accounting for 51.9 per cent of imports basket) registered expansion in 2025-26 (April-November). 9 The merchandise trade deficit narrowed to US$ 24.5 billion in November 2025 from US$ 31.9 billion in November 2024. Merchandise exports stood at US$ 38.1 billion in November 2025 [increase of 19.4 per cent (y-o-y)]. Key segments such as engineering goods, electronic goods, gems and jewelery; drugs and pharmaceuticals; and petroleum products drove the exports while rice, plastic and linoleum, carpet, oil seeds, and jute manufacturing including floor covering dragged the exports down. Exports to 14 out of top 20 major destinations expanded, with exports to destinations such as the US, the UAE and China growing, while contracting to the Netherlands and Singapore. Merchandise imports stood at US$ 62.7 billion in November 2025 [contraction of 1.9 per cent (y-o-y)]. Gold, petroleum products, vegetable oil, coal, coke and briquettes; and artificial resins and plastic materials dragged down the imports, while electronic goods, fertilisers, crude and manufactured; pearls, precious and semi-precious stones; machinery, electrical and non-electrical, and silver contributed positively to the imports during the month. 10 Merchandise exports to the US increased by 22.6 per cent (y-o-y) in November 2025. 11 Mexico accounted for 1.3 per cent of India’s total exports in 2024-25. India exported US$ 3.5 billion worth of engineering goods to Mexico in 2024-25 accounting for 61.5 per cent of total exports to Mexico and 3.0 per cent of total engineering goods exports. US$ 1.8 billion worth of two-three wheelers, motor vehicles/ cars, and auto components and parts were exported to Mexico in 2024-25. RBI Bulletin December 2025 41 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voN 100 80 62.7 60 38.1 40 20 0 -20 -40 -31.9 -24.5 -60 Exports Imports Trade balance 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voNARTICLE State of the Economy Mexico accounted for 5 -12 per cent of the total Chart III.5: Services Exports Continue to exports of India in these sectors during 2024-25. As Grow albeit at Moderate Pace (Per cent, y-o-y) India does not have a trade agreement with Mexico, 35 tariffs on Indian exports of these goods are set to 30 increase from 20 per cent to 50 per cent from January 25 1, 2026. 20 15 Net services exports growth moderated in October, 10 with both services exports and imports witnessing a 2.9 5 2.2 slowdown in pace.12 Growth in services exports and 0 imports softened on account of weak performance in -5 software and transport services (Chart III.5). -10 -15 Aggregate Supply On the supply side, growth in real gross value Exports Imports Source: RBI. added (GVA) increased to 8.1 per cent in Q2:2025- other crops under foodgrains has declined, partially 26 from 7.6 per cent in the previous quarter. The reflecting the crop damage caused by excessive increase in GVA growth was driven by a strong rainfall (Chart III.7).13 pickup in industrial activity and sustained buoyancy For kharif marketing season 2025-26 so far, the in services sector (Chart III.6 and Annex Table A2). procurement of rice is higher than the last year.14 Industrial sector growth picked up on the back of strong performance in manufacturing. The services sector continued to sustain its growth momentum with financial, real estate and professional services being the key sub-component driving its growth. Agriculture and allied activities saw some moderation in growth on account of lower-than-expected kharif production resulting from localised crop damages due to excessive rainfall. Agriculture The first advance estimates for agricultural production of 2025-26 indicate an increase in kharif foodgrains production over the last year, driven primarily by a pick-up in cereals production– particularly rice and maize. The production of all 13 The production of kharif foodgrains in 2025-26, as per the 1st AE, 12 Net services exports grew by 1.5 per cent (y-o-y) to US$ 17.4 billion in is estimated at 173.3 million tonnes, 2.3 per cent higher than the final October 2025 from US$ 17.2 billion in October 2024. During April-October estimates of 2024-25. 2025, net services exports increased to US$ 116.2 billion from US$ 101.5 14 As on December 19, 2025, rice procurement reached 281 lakh tonnes billion during April-October 2024. which is 8.8 per cent higher than corresponding period of last year. 42 RBI Bulletin December 2025 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO Chart III.6: Weighted Contribution to GVA Growth (Percentage points) 10 8.1 8 6 4 2 0 Q1 Q2 Q3 Q4 Q1 Q2 2024-25 2025-26 Agriculture and allied activities Industry Services GVA (Y-o-y growth, per cent) Sources: NSO; and RBI staff calculations.State of the Economy ARTICLE Chart III.7: Agriculture Kharif Crop Production Chart III.8: Higher Rabi Sown Area 2025-26: First Advance Estimates (Lakh hectares, left scale; per cent, right scale) (Million tonnes, left scale; per cent, right scale) 600 120 140 8 537 513 103 120 6.3 6 500 100 4.6 88 100 4 400 83 84 80 75 80 2 300 60 1.4 276 258 60 0 -1.6 -1.7 200 40 40 -2 -4.1 29 115117 20 -4 90 100 87 20 42 41 0 -6 12 Rice Coarse Pulses Oilseeds Cotton# Sugarcane* 11 0 0 Cereals Wheat Rice Pulses Coarse Oilseeds Total Cereals 2024-25 (FE) 2025-26 (1st AE) 2025-26 over 2024-25 (RHS) 2024-25 2025-26 Per cent of full season normal area (RHS) #: Million bales of 170 kgs each, *: Sugarcane is in 10 million tonnes. Note: FE: Final Estimates, AE: Advance Estimates. Note: Data is as on December 12. Source: Ministry of Agriculture and Farmers’ Welfare. Source: Ministry of Agriculture and Farmers’ Welfare. Consequently, the combined stock of rice and wheat driven by a slowdown in manufacturing output, with the government remains comfortable, with a brought about primarily by the fewer working days. record high stock of rice.15 Mining and electricity sectors registered contraction in October. The combined index of eight core High reservoir levels, because of good post- industries remained unchanged, as growth in steel, monsoon rainfall, have supported the ongoing rabi cement, fertilisers and refinery products was offset sowing.16 Sown area under all major crops stands by contractions in coal, electricity, natural gas and higher than the last year indicating better prospects crude oil. for the rabi crop (Chart III.8).17 The high-frequency indicators for November Monthly Indicators of Industrial Activity point to robust industrial activity. Steel output Growth in industrial activity, as measured by grew strongly, reflecting continued momentum in the year-on-year change in the Index of Industrial infrastructure and construction activity. Automobile Production (IIP), fell to a 14-month low in October, production in November registered its highest growth since February 2024 with all the segments 15 As on December 01, 2025, the total stock stood at 867 lakh tonnes with recording double-digit growth. Two-wheeler the rice stock at 575.7 lakh tonnes (5.6 times the buffer norms) and wheat stock at 291.4 lakh tonnes (1.4 times the buffer requirement). production also rebounded after the decline in 16 As on December 18, 2025, the average storage level in 166 major reservoirs in the country has reached 83 per cent of its full capacity. The October. Stable domestic demand, coupled with same is 6.8 per cent and 21.9 per cent higher than the last year and normal GST reforms, sustained the sector’s strong growth. storage, respectively. 17 The area sown under rabi crops (as on December 12) has covered 84 per PMI manufacturing, though continuing to witness cent of the full season normal acreage and it is 4.7 per cent higher than the area sown during corresponding period of last year. strong expansion, registered some deceleration due RBI Bulletin December 2025 43ARTICLE State of the Economy Table III.4: High Frequency Indicators for Industry showed Robust Growth Indicator Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 Jun-25 Jul-25 Aug-25 Sep-25 Oct-25 Nov-25 IIP-headline 5.0 3.7 5.2 2.7 3.9 2.6 1.9 1.5 4.3 4.1 4.6 0.4 IIP manufacturing 5.5 3.7 5.8 2.8 4.0 3.1 3.2 3.7 6.0 3.8 5.6 1.8 IIP capital goods 8.9 10.5 10.2 8.2 3.6 14.0 13.3 3.0 6.8 4.5 5.4 2.4 PMI manufacturing 56.5 56.4 57.7 56.3 58.1 58.2 57.6 58.4 59.1 59.3 57.7 59.2 56.6 PMI export order 54.6 54.7 58.6 56.3 54.9 57.6 56.9 60.6 57.3 56.1 56.5 54.7 54.1 PMI manufacturing: future output 65.5 62.5 65.1 64.9 64.4 64.6 63.1 62.2 57.6 60.5 64.8 62.3 57.1 Eight core index 5.8 5.1 5.1 3.4 4.5 1.0 1.2 2.2 3.7 6.5 3.3 0.0 Electricity generation: conventional 2.6 4.5 -1.3 2.4 4.8 -1.8 -8.2 -6.1 -0.8 1.0 0.8 -10.6 -5.1 Electricity generation: renewable 19.0 17.9 31.9 12.2 25.2 28.0 18.2 28.7 26.4 22.7 16.4 21.4 Automobile production 8.0 1.3 9.4 2.3 6.5 -1.7 5.2 1.2 10.7 8.1 10.8 -2.8 22.3 Passenger vehicle production 6.5 9.2 3.7 4.5 11.2 10.8 5.4 -1.8 0.1 -4.1 16.1 9.8 22.8 Tractor production 24.7 20.9 23.7 -7.8 18.5 20.5 9.1 9.8 11.5 9.4 23.0 13.0 37.5 Two-wheelers production 8.8 -0.6 10.3 1.6 5.6 -4.1 4.7 1.4 12.3 10.0 9.8 -5.6 20.9 Three-wheelers production -5.5 7.6 16.2 6.5 6.0 4.1 16.9 8.6 24.0 15.8 15.9 15.9 55.4 Crude steel production 4.5 8.3 7.4 6.0 8.5 9.3 11.0 12.6 13.8 12.8 13.2 9.4 11.8 Finished steel production 2.8 5.3 6.7 6.7 10.0 6.6 7.0 10.9 13.8 13.8 13.8 10.0 13.5 Import of capital goods 4.4 6.1 15.5 -0.5 8.6 24.5 15.7 3.4 13.3 0.2 12.8 8.7 13.1 <<Contraction ----------------------------------------------------------------------------------------- Expansion>> Notes: 1. The y-o-y growth (in per cent) has been calculated for all indicators (except for PMI). 2. The heatmap translates the data range for each indicator into a colour gradient scheme with red denoting the lowest values and green corresponding to the highest values of the respective data series. 3. The heatmap is applied on data from April 2023 to the latest month for which data is available. 4. All PMI values are reported in index form. A PMI value >50 denotes expansion, <50 denotes contraction and =50 denotes ‘no change’. In the PMI heatmaps, red denotes the lowest value, yellow denotes 50 (or the no change value), and green denotes the highest value in each of the PMI series. Sources: Ministry of Statistics and Programme Implementation (MoSPI); S&P Global; Central Electricity Authority (CEA), Ministry of Power; Society of Indian Automobile Manufacturers (SIAM); Office of Economic Adviser, GoI; Joint Plant Committee; Directorate General of Commercial Intelligence & Statistics; and Tractor and Mechanisation Association. to slowdown in growth of new orders and future The Climate Change Performance Index (CCPI) output prospects (Table III.4). Report 202618 has ranked India as the 5th best country among G20 countries (23rd rank globally), Monthly Indicators of Services Activity acknowledging India’s strong progress in renewable India’s services sector in November continued energy. Notably, India’s adaptation-relevant expenditure as a per cent of GDP has increased to demonstrate a strong expansion in activity. Retail significantly by 150 per cent from 2016-17 to 2022- commercial vehicles sales and international air 23.19 In line with its commitment to deal with the passenger traffic remained robust. Port cargo traffic issue of climate change, India advocated for greater registered a pick-up in growth (Table III.5). adaptation finance at the 30th Conference of the Parties (COP30) held in November 2025.20 18 The Climate Change Performance Index Report 2026 published by Germanwatch on November 18, 2025 evaluates and compares the climate protection performance of 63 countries and the European Union (EU). 20 According to the United Nations Environment Programme (UNEP) 19 https://www.pib.gov.in/PressReleasePage.aspx?PRID=2192347& Adaptation Gap Report 2025, there is a wide adaptation finance gap with developing countries requiring US$ 310-365 billion annually by 2035, reg=3&lang=2. while the current flows stand at only US$ 26 billion. 44 RBI Bulletin December 2025State of the Economy ARTICLE Table III.5: High Frequency Indicators for Services Remained Strong Indicator Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 Jun-25 Jul-25 Aug-25 Sep-25 Oct-25 Nov-25 PMI services 58.4 59.3 56.5 59.0 58.5 58.7 58.8 60.4 60.5 62.9 60.9 58.9 59.8 International air passenger traffic 10.7 9.0 11.1 7.7 6.8 13.0 5.0 3.4 5.5 7.7 7.3 9.7 9.2 Domestic air cargo 0.3 4.3 6.9 -2.5 4.9 16.6 2.3 2.6 4.8 7.1 2.8 -2.3 International air cargo 16.1 10.5 7.1 -6.3 3.3 8.6 6.8 -1.2 4.2 4.5 2.3 -2.3 Port cargo traffic -5.0 3.4 7.6 3.6 13.3 7.0 4.3 5.6 4.0 2.5 11.5 11.9 14.6 Retail commercial vehicle sales -9.3 -5.2 8.2 -8.6 2.7 -1.0 -3.7 6.6 0.2 8.6 2.7 21.1 19.9 Hotel occupancy 11.1 -0.2 1.2 0.6 1.9 7.2 -2.8 -0.3 -2.4 -3.2 -0.6 0.0 Steel consumption 9.5 5.2 10.9 10.9 13.6 6.0 8.1 9.3 7.3 10.0 8.9 4.7 7.1 Cement production 13.1 10.3 14.3 10.7 12.2 6.3 9.7 8.2 11.6 5.4 5.0 5.3 <<Contraction --------------------------------------------------------------------------------------------- Expansion>> Notes: 1. The y-o-y growth (in per cent) has been calculated for all indicators (except for PMI). 2. The heatmap translates the data range for each indicator into a colour gradient scheme with red denoting the lowest values and green corresponding to the highest values of the respective data series. 3. The heatmap is applied to data from April 2023 to the latest month for which data is available. 4. The data on international air passenger traffic for November 2025 growth rate is calculated by aggregating daily data. 5. All PMI values are reported in index form. A PMI value >50 denotes expansion, <50 denotes contraction and =50 denotes ‘no change’. In the PMI heatmaps, red denotes the lowest value, yellow denotes 50 (or the no change value), and green denotes the highest value in each of the PMI series. Sources: Federation of Automobile Dealers Associations (FADA); Indian Ports Association; Airports Authority of India; HVS Anarock; Joint Plant Committee; Office of Economic Adviser; and S&P Global. Inflation Headline inflation21 edged up in November to food prices, after reaching an all-time low of 0.3 per 0.7 per cent, driven by a lower rate of deflation in cent in October (Chart III.9).22 Chart III.9: Food and Fuel Propelled the Rise in Headline Inflation a. CPI Inflation b. Contributions (Y-o-y, per cent) (Percentage points) 12 10 8 6 4 4.3 2 2.3 0.7 0 -2 -2.8 -4 -6 Food and beverages Fuel and light CPI excluding food and fuel CPI Headline (y-o-y, per cent) Sources: National Statistical Office (NSO); and RBI staff calculations. 21 As per the provisional data released by the National Statistical Office (NSO) on December 12, 2025. 22 The increase in inflation by about 45 bps was on account of a momentum effect of around 30 bps and unfavourable base effect of around 15 bps. The positive momentum was primarily driven by food and fuel prices. RBI Bulletin December 2025 45 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voN 8 6 4 2 0.7 0 -2 CPI excluding food and fuel Fuel and light Food and beverages CPI Headline (y-o-y, per cent) 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voNARTICLE State of the Economy Chart III.10: Key Driver of Increase in Inflation: Easing Deflation in Vegetables Sources: NSO; and RBI staff estimates. Food prices remained in deflation for the third and intoxicants, and personal care and effects consecutive month, although the pace of deflation subgroups increased. Excluding precious metals, moderated.23 Within food group, prices declined for core inflation was at 2.4 per cent. vegetables, pulses and spices on a year-on-year basis. Inflation in both urban and rural areas edged up Inflation in sub-groups such as cereals, oils and in November with the latter moving out of deflation.24 fats, prepared meals and non-alcoholic beverages Across states/UTs, inflation varied between (-) 4.2 moderated, while that in meat and fish, eggs, milk per cent to 8.3 per cent, with the majority of states and products, and fruits edged up (Chart III.10). continuing to record inflation below 2 per cent. Fuel and light inflation picked up to 2.3 per cent Overall, inflationary pressures were subdued across in November from 2.0 per cent in October. This was states/UTs. However, 25 out of 37 states/UTs recorded driven by kerosene PDS prices which came out of an uptick in inflation (Chart III.11). deflation after seven months. Inflation continued to High-frequency food price data for December so remain elevated for LPG. far (up to 19th) point to a pick-up in cereal prices. Core (i.e., CPI excluding food and fuel) inflation Among pulses, gram prices moderated, while tur/ remained stable at 4.3 per cent in November, the arhar dal prices increased. Prices of moong remained same as in October. Inflation moderated within steady. Within edible oils, the prices of sunflower oil clothing and footwear, health, recreation and and groundnut oil increased. Mustard oil prices were amusement, education and household goods and flat. Tomato and onion prices picked up while potato services subgroups while inflation in pan, tobacco prices eased (Chart III.12). 23 Food deflation moderated to 2.8 per cent in November from 3.7 per cent 24 Inflation in urban and rural areas was at 1.4 per cent and 0.1 per cent, in the previous month. respectively. 46 RBI Bulletin December 2025State of the Economy ARTICLE Chart III.11: Generalised Increase in Inflation across Table III.6: Petroleum Products Prices States in November Item Unit Domestic Prices Month-over- (Y-o-y, per cent) month (Per cent) Dec-24 Nov-25 Dec-25^ Nov-25 Dec-25^ Inflation Number of Petrol ₹/litre 101.02 101.12 101.13 0.00 0.01 Range States/UTs <2 27 Diesel ₹/litre 90.48 90.53 90.53 0.00 0.00 2-4 8 Kerosene ₹/litre 44.75 45.91 48.64 1.24 5.95 4-6 0 (subsidised) 6-8 0 8-10 2 LPG (non- ₹/cylinder 813.3 863.3 863.3 0.0 0.0 subsidised) Inflation Number of ^: For the period December 1-19, 2025. Trend States/UTs Note: Other than kerosene, prices represent the average Indian Oil Decline or 12 Corporation Limited (IOCL) prices in four major metros (Delhi, Kolkata, Stable Mumbai and Chennai). For kerosene, prices denote the average of the Increase 25 subsidised prices in Kolkata, Mumbai and Chennai. Sources: IOCL; Petroleum Planning and Analysis Cell (PPAC); and RBI staff calculations. <2 2-4 8-10 Notes: 1. Map is for illustrative purposes only. subsidised kerosene prices increased (up to 19th) 2. Kerala and Lakshadweep experienced inflation above 8 per cent. Sources: NSO; and RBI Staff estimates. [Table III.6]. Retail selling prices of petrol, diesel and In November, manufacturing PMI recorded a LPG remained unchanged in December while moderation in the rate of expansion of both input and Chart III.12: Food Prices Registered Marginal Uptick in December a. Cereals b. Pulses Index (Jan 2024 = 100) Index (Jan 2024 = 100) 120 110 104.8 100 95.2 90 80 77.2 70 Rice Wheat Gram dal Tur/ Arhar dal Moong dal c. Vegetables d. Edible Oils Index (Jan 2024 = 100) Index (Jan 2024 = 100) Potato Onion Tomato Groundnut oil Sunflower oil Mustard oil Note: Data pertain to weekly averages. Sources: Department of Consumer Affairs, GoI; and RBI staff estimates. RBI Bulletin December 2025 47 52-naJ-2 52-naJ-92 52-beF-52 52-raM-42 52-rpA-02 52-yaM-71 52-nuJ-31 52-luJ-01 52-guA-6 52-peS-2 52-peS-92 52-tcO-62 52-voN-22 52-ceD-91 250 200 150 154.9 100 115.1 74.0 50 0 52-naJ-2 52-naJ-92 52-beF-52 52-raM-42 52-rpA-02 52-yaM-71 52-nuJ-31 52-luJ-01 52-guA-6 52-peS-2 52-peS-92 52-tcO-62 52-voN-22 52-ceD-91 140 130 129.4 120 121.5 110 100 100.9 90 52-naJ-2 52-naJ-92 52-beF-52 52-raM-42 52-rpA-02 52-yaM-71 52-nuJ-31 52-luJ-01 52-guA-6 52-peS-2 52-peS-92 52-tcO-62 52-voN-22 52-ceD-91 110 107 104.5 104 101 99.8 98 95 52-naJ-2 52-naJ-92 52-beF-52 52-raM-42 52-rpA-02 52-yaM-71 52-nuJ-31 52-luJ-01 52-guA-6 52-peS-2 52-peS-92 52-tcO-62 52-voN-22 52-ceD-91ARTICLE State of the Economy Chart III.13: Pace of Input and Output Price Expansion Eased for both Manufacturing and Services Firms a. Manufacturing b. Services Index (50=No Change) Index (50=No Change) 60 55 52.9 51.1 50 45 Input Prices Output Prices Input Prices Prices Charged Note: A level of 50 corresponds to no change in activity, and a reading above 50 denotes expansion and vice versa. Source: S&P. output prices. Benign inflation during the month kept IV. Financial Conditions input cost pressures low for firms, also limiting hikes to Overall financial conditions continued to selling prices to maintain competitive pricing by firms remain benign albeit with tightening across market in global markets. For services PMI also, deceleration segments except G-sec market since the second half continued in both input prices and selling prices as a of November (Chart IV.1). result of the receding cost pressures and firms’ efforts Banking system liquidity remained largely to secure new business (Chart III.13). in surplus during the second half of November 25 For detailed methodology see https://rbi.org.in/Scripts/BS_ViewBulletin.aspx?Id=23451 48 RBI Bulletin December 2025 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voN 60 55 51.3 50.7 50 45 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voN Chart IV.1: Benign Daily Financial Conditions Index (Standard deviation from average since 2012) 1.0 0.8 0.6 0.4 -0.4 -0.6 -0.8 -1.0 Money Government securities Corporate bond Equity Foreign exchange Financial conditions index (standardised) Note: The financial conditions index provides a metric based on its historical average; in this context, a zero value corresponds to a financial system operating at the historical average level of all the financial indicators included in the index. To present the results, standardised index is used. 25 Source: RBI staff estimates. 52-naJ-13 52-beF-7 52-beF-41 52-beF-12 52-beF-82 52-raM-7 52-raM-41 52-raM-12 52-raM-82 52-rpA-4 52-rpA-11 52-rpA-81 52-rpA-52 52-yaM-2 52-yaM-9 52-yaM-61 52-yaM-32 52-yaM-03 52-nuJ-6 52-nuJ-31 52-nuJ-02 52-nuJ-72 52-luJ-4 52-luJ-11 52-luJ-81 52-luJ-52 52-guA-1 52-guA-8 52-guA-51 52-guA-22 52-guA-92 52-peS-5 52-peS-21 52-peS-91 52-peS-62 52-tcO-3 52-tcO-01 52-tcO-71 52-tcO-42 52-tcO-13 52-voN-7 52-voN-41 52-voN-12 52-voN-82 52-ceD-5 52-ceD-21 52-ceD-91 Tighter conditions 0.2 0.0 -0.2 Easier conditionsState of the Economy ARTICLE and December (up to 19th). Temporary increases ₹1.2 lakh crore in the preceding one-month period in government cash balances due to GST related (Chart IV.2). With an improvement in the overall payments and an increase in currency-in-circulation liquidity conditions in the first half of December, led to some decline in system liquidity during the 3-day VRRRs of varying maturities were conducted second half of November. The last tranche of CRR to absorb surplus liquidity from the banking system. reduction, effective November 29, 2025 improved Average balances under the standing deposit facility liquidity conditions till mid-December. System remained marginally higher, and banks’ recourse to liquidity turned into deficit in the second half the marginal standing facility remained unchanged.27 of December (up to 19th) on account of buildup Money Market in government cash balances due to advance tax payments. To offset the transient liquidity tightness, The weighted average call rate (WACR) remained the Reserve Bank conducted variable rate repo broadly aligned with the policy repo rate in November, auctions. With the aim of injecting durable liquidity despite some temporary liquidity squeezes during the into the system, the Reserve Bank conducted open latter half of November. The WACR hovered within market operation (OMO) purchases of government the policy corridor as liquidity conditions improved securities amounting to ₹1 lakh crore and 3-year USD/ since the beginning of December with some hardening INR Buy/Sell swaps of USD 5 billion in December.26 witnessed in second half of December due to liquidity Overall, average net absorption under the tightness. The spread of WACR over the policy liquidity adjustment facility increased to ₹1.63 lakh repo rate, on average, remained unchanged during crore during November 16 − December 19 from November 16 − December 19, compared with the Chart IV.2: Comfortable Liquidity Conditions (₹ lakh crore) 4.5 3.5 2.5 1.5 0.5 -0.5 -1.5 -2.5 -3.5 -4.5 Daily standing deposit facility Variable rate reverse repo Marginal standing facility Variable rate repo Net liquidity adjustment facility Total absorption Source: RBI. 26 OMO purchase auctions were conducted on December 11 and December 18 in two equal tranches for an amount of ₹50,000 crore each. Three-year USD/ INR Buy Sell swap auction was conducted on December 16, 2025. 27 Average balances under the standing deposit facility increased modestly to ₹1.64 lakh crore during November 16 to December 19, 2025 from ₹1.56 lakh crore in the preceding one-month period. Borrowings from the marginal standing facility averaged ₹0.02 lakh crore during this period. RBI Bulletin December 2025 49 52-beF-7 52-beF-61 52-beF-52 52-raM-6 52-raM-51 52-raM-42 52-rpA-2 52-rpA-11 52-rpA-02 52-rpA-92 52-yaM-8 52-yaM-71 52-yaM-62 52-nuJ-4 52-nuJ-31 52-nuJ-22 52-luJ-1 52-luJ-01 52-luJ-91 52-luJ-82 52-guA-6 52-guA-51 52-guA-42 52-peS-2 52-peS-11 52-peS-02 52-peS-92 52-tcO-8 52-tcO-71 52-tcO-62 52-voN-4 52-voN-31 52-voN-22 52-ceD-1 52-ceD-01 52-ceD-91ARTICLE State of the Economy preceding one-month period (Chart IV.3a). Overnight market perceptions of end of current easing cycle. rates in the collateralised segments – as measured by The yields have, however, moderated marginally the secured overnight rupee rate – moved in tandem after the RBI’s OMO purchases of government with the uncollateralised rate. Yields on three-month securities on December 11 and 18, 2025.29 Compared treasury bills moderated, reflecting the policy repo to a month ago, the yield curve (as on December rate cut and improved liquidity conditions. At the 19) shifted upwards, especially in the middle of same time, interest rates on certificates of deposit the curve. The term spread (difference between and 3-month commercial papers issued by NBFCs the yields of 10-year G-sec and 91-day treasury bill) remained broadly stable (Chart IV.3b). The average inched up marginally during the period (Charts IV.4a risk premium in the money market (the spread and IV.4b).30 between the yields on 3-month commercial paper Corporate Bond Market and 91-day treasury bill) recorded an uptick.28 Corporate bond yields and their spreads generally Government Securities (G-Sec) Market witnessed mixed trends across rating spectrum and In the fixed income segment, the G-sec yields softened tenors (Table IV.1). New corporate bond issuances on the day of the announcement of the policy rate increased marginally in October. On a cumulative cut and the Reserve Bank’s liquidity augmenting basis, total issuances remained higher in the current measures. Thereafter, the yields hardened amidst financial year so far than the same period last year.31 Chart IV.3: Money Market Rates Remained Broadly Stable a. Policy Corridor and Call Rate b. Money Market Rates (Per cent) (Per cent) 7.0 6.5 6.0 5.5 5.36 5.0 4.5 Repo rate Weighted average call rate Standing deposit facility Marginal standing facility 3-month treasury bill 3-month certificate of deposit SORR Rate 3-month commercial paper (NBFC) Sources: RBI; and Bloomberg. 28 Increased to 112 bps during the period from November 16 to December 19, 2025, from 101 bps in the preceding one-month period. 29 The yield on the 10-year benchmark G-sec (6.48 per cent GS 2035) rose to a peak of 6.63 per cent on December 10, before easing to 6.57 per cent on December 18 following the RBI’s OMO purchase of government securities, compared with 6.49 per cent on November 14. 30 The average term spread between the 10-year G-sec and 91-day treasury bill increased by 13 bps during November 16 to December 19 as compared to the period from October 16 to November 15. 31 Increased to ₹0.79 lakh crore in October 2025, compared to ₹0.74 lakh crore in September 2025. On a cumulative basis (April to October), it stood at ₹5.5 lakh crore in 2025-26, up from ₹5.4 lakh crore in the corresponding period of the previous year. 50 RBI Bulletin December 2025 52-beF-41 52-beF-82 52-raM-41 52-raM-82 52-rpA-11 52-rpA-52 52-yaM-9 52-yaM-32 52-nuJ-6 52-nuJ-02 52-luJ-4 52-luJ-81 52-guA-1 52-guA-51 52-guA-92 52-peS-21 52-peS-62 52-tcO-01 52-tcO-42 52-voN-7 52-voN-12 52-ceD-5 52-ceD-91 8.00 7.50 7.00 6.49 6.50 6.06 6.00 5.50 5.45 5.00 4.50 52-beF-41 52-beF-82 52-raM-41 52-raM-82 52-rpA-11 52-rpA-52 52-yaM-9 52-yaM-32 52-nuJ-6 52-nuJ-02 52-luJ-4 52-luJ-81 52-guA-1 52-guA-51 52-guA-92 52-peS-21 52-peS-62 52-tcO-01 52-tcO-42 52-voN-7 52-voN-12 52-ceD-5 52-ceD-91State of the Economy ARTICLE Chart IV.4: Stabilising G-Sec Yields a. Movement in G-sec yield b. G-sec Yield Curve (Per cent) (Per cent, left scale; basis points, right scale) 7.30 7.00 6.70 6.60 6.40 6.35 6.10 6.01 5.80 5.50 Tenor (years) Change (December 19, 2025 over November 19, 2025) (RHS) 3 year 5 year 10 year 19-Nov-2025 19-Dec-2025 Sources: Bloomberg; and RBI staff calculations. Money and Credit expanded at a sequentially higher pace on the back of aggregate deposits and currency with the public During November and December so far (up to (Chart IV.5).33 12th), growth in reserve money (adjusted for CRR) increased in tandem with the growth in currency in With the cumulative reduction of 100 basis circulation.32 The pickup in currency in circulation points in cash reserve ratio (CRR), phased in from was propelled by the ongoing seasonal demand, September 5, banks’ reserve-deposit ratio declined which is typically experienced in the third quarter over the past three months, resulting in a higher of every financial year. Money supply (M3) also money multiplier34 (Chart IV.6). Table IV.1: Corporate Bond Yields and Spreads Generally Softened Interest Rates (Per cent) Spread (bps) Instrument (Over Corresponding Risk-free Rate) October 16, 2025 – November 18, 2025 Variation October 16, 2025 – November 18, 2025 Variation November 17, 2025 – December 17, 2025 (bps) November 17, 2025 – December 17, 2025 1 2 3 (4 = 3-2) 5 6 (7 = 6-5) (i) AAA (1-year) 6.70 6.85 15 107 127 20 (ii) AAA (3-year) 7.03 7.03 0 105 109 4 (iii) AAA (5-year) 7.22 7.18 -4 87 77 -10 (iv) AA (3-year) 8.10 8.03 -7 211 209 -2 (v) BBB- (3-year) 11.79 11.68 -11 574 574 0 Note: Yields and spreads are computed as averages for the respective periods. Source: FIMMDA. 32 Reserve money (adjusted for the first-round impact of changes in the cash reserve ratio) and currency in circulation grew by 9.4 per cent and 9.5 per cent as on December 12, 2025, respectively, up from 6.3 per cent and 6.1 per cent, respectively, a year ago. 33 Money supply grew by 9.9 per cent as on November 28, 2025 as compared to 9.7 per cent a year ago. 34 Money multiplier is defined as the ratio of money supply to reserve money. RBI Bulletin December 2025 51 52-beF-41 52-beF-82 52-raM-41 52-raM-82 52-rpA-11 52-rpA-52 52-yaM-90 52-yaM-32 52-nuJ-60 52-nuJ-02 52-luJ-40 52-luJ-81 52-guA-10 52-guA-51 52-guA-92 52-peS-21 52-peS-62 52-tcO-01 52-tcO-42 52-voN-70 52-voN-12 52-ceD-50 52-ceD-91 7.5 7.35 25 7.33 20 7.0 15 6.5 10 5 6.0 0 5.5 -5 5.0 -10 1 2 3 4 5 6 7 8 9 01 11 21 31 41 51 61 71 81 91 02ARTICLE State of the Economy Credit growth in scheduled commercial banks During 2025-26 so far (up to November 28), the (SCBs) sustained its pace during November (up total flow of financial resources to the commercial to 28th) [Chart IV.7].35 Bank deposits, on the other sector remained strong, bolstered by robust greater hand, registered a significant pickup in growth. non-bank intermediation. Non-bank sources Consequently, the wedge between credit and deposit − corporate bond issuances and foreign direct growth narrowed from 1.5 percentage points in end- investment to India − showed a marked increase in October to 1.3 percentage points in end-November. the year so far (Table IV.2a). As on November 28, the Chart IV.6: Sustained Increase in Money Multiplier (Ratio, per cent) 6.5 16.0 6.1 6.0 15.7 5.5 15.4 5.0 4.5 15.1 14.9 4.0 14.8 3.5 3.3 3.0 14.5 Money multiplier Reserves-deposit ratio (per cent) Currency-deposit ratio (per cent) [RHS] Source: RBI. 35 SCBs’ credit and deposit growth stood at 11.5 per cent and 10.2 per cent, respectively, as on November 28, 2025. 52 RBI Bulletin December 2025 52-naJ-01 52-naJ-42 52-beF-70 52-beF-12 52-raM-70 52-raM-12 52-rpA-40 52-rpA-81 52-yaM-20 52-yaM-61 52-yaM-03 52-nuJ-31 52-nuJ-72 52-luJ-11 52-luJ-52 52-guA-80 52-guA-22 52-peS-50 52-peS-91 52-tcO-30 52-tcO-71 52-tcO-13 52-voN-41 52-voN-82 Chart IV.5: Growth in Reserve Money and Money Supply (M3) Picked Up (Y-o-y, per cent) 11 9.9 10 9.5 9.4 9 8 7 6 5 52-naJ-01 52-naJ-42 52-beF-70 52-beF-12 52-raM-70 52-raM-12 52-rpA-40 52-rpA-81 52-yaM-20 52-yaM-61 52-yaM-03 52-nuJ-31 52-nuJ-72 52-luJ-11 52-luJ-52 52-guA-80 52-guA-22 52-peS-50 52-peS-91 52-tcO-30 52-tcO-71 52-tcO-13 52-voN-41 52-voN-82 52-ceD-21 Reserve money (CRR adjusted) Money Supply Currency in Circulation Source: RBI.State of the Economy ARTICLE Chart IV.7: Credit Expansion Steady, Deposit Growth Increased (Y-o-y, per cent) 12.0 11.5 11.5 11.0 10.5 10.2 10.0 9.5 9.0 8.5 Credit growth Deposit growth Note: SCBs’ data are inclusive of regional rural banks. Data include the impact of the merger of a non-bank with a bank. Source: Fortnightly Section 42 Returns, RBI. total outstanding credit to the commercial sector rose The credit to the services sector recorded buoyant by 13.2 per cent, with non-bank sources registering a double-digit growth, driven by a steep rise in banks’ growth of 17.0 per cent (Table IV.2b). lending to NBFCs. An uptick in personal loans growth Bank credit growth strengthened across key came from housing and vehicle loans. Notably, loans sectors in October, namely, industry, services, and against gold jewellery have surged and continued to personal loans (Chart IV.8).36 The pick-up in industrial record triple-digit growth rates since February 2025. credit growth was driven by robust growth in credit The sharp expansion may be attributed to a surge in to micro, small and medium enterprises (MSMEs). Table IV.2b: Outstanding Credit to the Commercial Sector (₹ crore; Figures in parentheses are y-o-y percentage changes) Table IV.2a: Flow of Financial Resources to the Source At End-March As on November 28 Commercial Sector (₹ crore) 2024 2025 2024 2025 P April-March Up to November 28 A. Non-Food Bank 1,64,09,0831,82,07,4411,74,57,7021,94,47,512 Source Credit (20.2) (11.0) (10.6) (11.4) 2023-24 2024-25 2024-25 2025-26 P B. Non-Bank Sources 77,56,314 88,85,434 81,96,473 95,90,566 A. Non-Food Bank Credit 21,40,243 17,98,32110,48,619 12,40,071 (B1+B2) (4.2) (14.6) (12.2) (17.0) B. Non-Bank Sources 12,63,721 17,10,457 7,86,083 10,16,620 B1. Domestic 56,59,037 66,37,411 60,08,758 71,98,292 (B1+B2) Sources (4.9) (17.3) (15.6) (19.8) B1. Domestic Sources 10,20,302 13,85,609 5,85,742 7,48,761 B2. Foreign Sources 20,97,277 22,48,023 21,87,714 23,92,274 B2. Foreign Sources 2,43,419 3,24,848 2,00,341 2,67,859 (2.4) (7.2) (3.8) (9.4) C. Total Flow of Resources C. Total Credit (A+B) 2,41,65,3972,70,92,8752,56,54,1752,90,38,078 34,03,964 35,08,77818,34,702 22,56,691 (A+B) (14.5) (12.1) (11.1) (13.2) P: Provisional. P: Provisional. Note: For detailed notes, please refer to Current Statistics Table No: 18(a). Note: For detailed notes, please refer to Current Statistics Table No: 18(b). Sources: RBI; SEBI; and AIFIs. Sources: RBI; SEBI; and AIFIs. 36 Sectoral non-food credit data is based on sector-wise and industry-wise bank credit (SIBC) return, which covers select banks accounting for about 95 per cent of total non-food credit extended by all SCBs, pertaining to the last reporting Friday of the month. Data are provisional. The bank groups covered under the SIBC return are – Public Sector Banks, Private Sector Banks, Foreign Banks, and Small Finance Banks. Data includes the impact of the merger of a non-bank with a bank. RBI Bulletin December 2025 53 52-naJ-01 52-naJ-42 52-beF-70 52-beF-12 52-raM-70 52-raM-12 52-rpA-40 52-rpA-81 52-yaM-20 52-yaM-61 52-yaM-03 52-nuJ-31 52-nuJ-72 52-luJ-11 52-luJ-52 52-guA-80 52-guA-22 52-peS-50 52-peS-91 52-tcO-30 52-tcO-71 52-tcO-13 52-voN-41 52-voN-82ARTICLE State of the Economy Chart IV.8: Bank Credit Growth Strengthened across Key Sectors (Y-o-y, per cent) a. Credit: Agriculture b. Credit: Industry 20.0 17.5 15.0 12.5 10.0 7.5 8.9 5.0 c. Credit: Services d. Credit: Personal Loans Note: Transmission during February to August 2025 is calculated by subtracting the weighted average lending and deposit rates of January 2025 from those of August 2025. Source: RBI. gold prices. Despite the high growth rate, the share interest rates of outstanding deposits was gradual, of gold loans in overall non-food credit remains reflecting the effect of longer tenor of term deposits relatively low, albeit with a rise over last year.37 at fixed rates (Table IV.3). Deposit and Lending Rates The decline in the weighted average lending rate on fresh and outstanding rupee loans was higher In response to the cumulative 100 basis points in the case of private banks relative to public sector reduction in the policy repo rate during February banks (Chart IV.9). On the deposit side, transmission – October 2025, banks have reduced their external was higher for public sector banks compared to benchmark-based lending rates on fresh loans linked private banks in case of fresh term deposits. to repo rate by the same magnitude. The weighted Equity Markets average lending rates on both fresh and outstanding rupee loans also eased during this period. On the Indian equity markets witnessed a rebound deposit side, banks reduced interest rates on fresh in the first half of November and exhibited bi- term deposits significantly. The pass-through to the directional movements thereafter. While healthy 37 The share of gold loans in the overall non-food credit was 1.8 per cent in October 2025, relative to 0.9 per cent in October 2024. Share of gold loans in personal loans was 5.2 per cent in October 2025. 54 RBI Bulletin December 2025 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 12.5 10.0 10.0 7.5 5.0 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 15.0 13.0 12.5 10.0 7.5 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 15.0 14.0 12.5 10.0 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcOState of the Economy ARTICLE Table IV.3: Transmission to Banks’ Deposit and Lending Rates (Basis points) Term Deposit Rates Lending Rates Period Repo Rate WADTDR- WADTDR- EBLR 1-Year MCLR WALR - Fresh Rupee Loans WALR- Fresh Outstanding (Median) Outstanding Deposits Deposits Rupee Loans Overall Interest Rate Effect # (1) (2) (3) (4) (5) (6) (7) (8) (9) Tightening Period 250 259 206 250 175 182 191 115 May 2022 to Jan 2025 Easing Phase -100 -105 -32 -100 -50 -69 -78 -63 Feb 2025 to Oct* 2025 *: Data on MCLR as in November 2025. #: Calculated at January 2025 weights. WALR: Weighted average lending rate; WADTDR; Weighted average domestic term deposit rate. MCLR: Marginal cost of funds-based lending rate; EBLR: External benchmark-based lending rate. Note: Data on EBLR pertain to 32 domestic banks. Source: RBI. corporate results for Q2:2025-26 and policy rate cut External Sources of Finance by the Reserve Bank and US Fed supported equity During April-October 2025, FDI remained markets, muted foreign portfolio flows primarily higher than last year both in gross and net terms. due to uncertainty surrounding the India-US trade Gross inward FDI remained steady in October with deal and negative global cues from concerns on Singapore, Mauritius and the US accounting for artificial intelligence stock valuations weighed on more than 70 per cent of total FDI inflows (Chart market sentiments. Domestic institutional investors IV.11a). The highest recipients (around 60 per (DIIs) remained net buyers in equity markets, while cent) of FDI inflows were the financial services foreign portfolio investors (FPIs) turned net sellers sector, followed by manufacturing, electricity, and (Chart IV.10). communication services. However, net FDI was Chart IV.9: Transmission across Bank Groups (February - October 2025) a. Lending Rates b. Deposit Rates (Basis points) (Basis points) 0 0 -28 -28 -40 -40 -57 -80 -70 -68 -80 -74 -90 -93 -97 -99 -104 -120 -105 -120 WALR WALR WADTDR WADTDR (Fresh Rupee Loans) (Outstanding Rupee Loans) (Fresh Deposits) (Outstanding Deposits) Publicsectorbanks Private banks Foreign banks Public sector banks Private banks Foreign banks Note: Transmission during February to October 2025 is calculated by subtracting the weighted average lending and deposit rates of January 2025 from those of October 2025. Source: RBI. RBI Bulletin December 2025 55ARTICLE State of the Economy outward FDI (Chart IV.11b). Sector specific Chart IV.10: Sustained Capital Flows to Domestic Equity Markets breakdown suggests that around 90 per cent of (Index, left scale; ₹ thousand crore, right scale) outward FDI was in financial, insurance, and business 89000 14 84,482 services, followed by wholesale, retail trade and 12 86000 10 manufacturing. 8 83000 During 2025-26 so far (up to December 18), net 6 80000 4 FPI registered outflows, driven by equity segment.38 2 FPI flows turned negative in December following 77000 0 inflows in the previous two months (Chart IV.12). -2 74000 -4 The uncertainty surrounding India-US trade deal and 71000 -6 investors’ caution around high domestic valuations kept net FPI flows to India muted in recent months. BSE Sensex (LHS) FPI+DII flows (RHS) The registrations of external commercial Sources: Bloomberg; BSE; and NSE. borrowings (ECBs) moderated during April–October 2025, reflecting a slowdown in offshore fund raising negative in October, mainly due to high repatriation activity.39 Net inflows from ECBs also stood lower and outward FDI. The key destinations for outward than last year (Chart IV.13). A significant portion40 FDI were Singapore, followed by the US and the UAE, of the ECBs was mobilised for capital expenditure together accounting for more than half of total purpose. 38 Net FPI outflows to the tune of US$ 2.1 billion during 2025–26 so far (up to December 18). 39 The registrations of external commercial borrowings moderated to US$ 20.7 billion during April–October 2025, from US$ 30.9 billion in the corresponding period a year ago. 40 around 45 per cent. 56 RBI Bulletin December 2025 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voN 52-ceD Chart IV:11: Steady Gross Foreign Direct Investment Inflows a. Gross and Net FDI b. Country-Wise Outward FDI in October 2025 (US$ billion) (US$ billion) 15 10 6.5 5 0 -1.5 -5 -10 Net outward FDI Repatriation/Disinvestment Gross Inward FDI Net FDI Source: RBI. 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO Singapore US UAE South Africa Netherlands UK 0.0 0.2 0.4 0.6 0.8State of the Economy ARTICLE 6 4 2 0.7 0 -2 -2.3 -4 -6 -8 -10 Equity Debt Total *: Data up to December 18. Note: Debt includes investments under the hybrid instruments. Source: National Securities Depository Limited (NSDL). India’s current account deficit moderated leading to a depletion in foreign exchange reserves.41 in Q2:2025-26 over the same period last year, Nonetheless, India’s foreign exchange reserves supported by a lower merchandise trade deficit, remain adequate, providing a cover for more than robust services exports and strong remittance 11 months of goods imports and a cover for more receipts (Chart IV.14). However, net capital inflows than 92 per cent of the external debt outstanding fell short of current account financing requirements, (Chart IV.15).42 41 There was a depletion of US$ 10.9 billion from the foreign exchange reserves (on a BoP basis) in Q2:2025-26 as against an accretion of US$ 18.6 billion in Q2:2024-25. 42 As on December 12,2025, the import cover for goods and services was around nine months. RBI Bulletin December 2025 57 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voN *52-ceD Chart IV.12: Foreign Portfolio Investment Flows Declined in December (US$ billion) Chart IV.13: External Commercial Borrowings - Registrations and Flows (US$ billion) 30 25 20.7 20 15 9.5 10 2.2 5 1.2 0 -5 -10 Registrations Net inflows Source: RBI. 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 4202 tcO-rpA 5202 tcO-rpAARTICLE State of the Economy Foreign Exchange Market from a month ago and remained relatively lower than most major currencies. In December so far (up The Indian rupee (INR) depreciated against the US to 19), the INR depreciated by 0.8 per cent over its dollar in November, pressured by the strengthening end-November level. of the US dollar, muted foreign portfolio flows, and In real effective terms, the Indian rupee remained uncertainty surrounding the India-US trade deal stable in November, as depreciation of the INR in (Chart IV.16). The volatility of INR, as measured by nominal effective terms was offset by higher prices in the coefficient of variation, moderated in November India vis-à-vis its major trading partners (Chart IV.17). Chart IV.16: Movements in Major Currencies against the US Dollar in November (Per cent, m-o-m, left scale; per cent, right scale) 2 2 1 1 0 0 -1 -1 -2 -2 -3 -3 58 RBI Bulletin December 2025 )YXD( ralloD SU xednI ycnerruC EME tiggnir naisyalaM laer nailizarB thab dnaliahT dnar nacirfA htuoS nauy esenihC osep nacixeM gnod esemanteiV rallod gnoK gnoH eepur naidnI haipur naisenodnI oruE osep enippilihP dnuop KU ney esenapaJ now naeroK Chart IV.14: India’s Current Account Chart IV.15: India’s Foreign Exchange Deficit Moderated Reserves Adequate (US$ billion, left scale; per cent, right scale) (US$ billion, left scale; months, right scale) 750 13 40 3 688.9 30 2 650 20 1.3 12 1 10 0.5 0 0 550 -0.5 -- 21 00 -1.0 -1.3 -1.1 -1.1 -0.3 -1.3 -1 450 11.1 11 -2 -30 -2.2 -40 -3 350 10 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 2023-24 2024-25 2025-26 Change in reserves on a BoP basis (- increase/+ decrease) Foreign exchange reserves Import cover (RHS) Current account balance (-deficit/+surplus) Capital account balance (-deficit/+surplus) *: As on December 12, 2025. Note: The import cover data is based on annualised merchandise imports as per Current account balance to GDP ratio (RHS) the balance of payments statistics. Source: RBI. Source: RBI. Percentage change (+ appreciation/ - depreciation) Volatility (RHS) Notes: 1. Appreciation/depreciation (m-o-m) calculated using monthly average exchange rates. 2. US dollar (DXY) measures the movements of the US dollar against a basket of major currencies (Euro, Japanese yen, British pound, Canadian dollar, Swedish krona, Swiss franc). 3. For each currency, volatility is measured as the coefficient of variation (100*Standard Deviation/Mean) using daily exchange rate data for November 2025. Sources: FBIL; Thomson Reuters; and RBI staff calculations. 42-raM 42-nuJ 42-peS 42-ceD 52-raM 52-nuJ 52-tpeS 52-tcO 52-voN *52-ceDState of the Economy ARTICLE Chart IV.17: Movements in the 40-Currency Real Effective Exchange Rate a. Monthly Changes b. Decomposition of Monthly Changes (Index (2015-16 = 100), left scale; per cent, right scale) (Per cent) 110 4 108 106 2 104 102 100 0 98 -0.001 96 97.5 -2 94 92 90 -4 Relative price effect Change in REER Change in REER(RHS) REER Nominal exchange rate effect Note: Positive change indicates an appreciation of the nominal and real exchange rate and negative change indicates a depreciation. Source: RBI. V. Conclusion The Indian economy was not fully immune to the external sector headwinds. Coordinated fiscal, The year 2025 brought about an unprecedented monetary and regulatory policies have helped to shift in global trade policies, marked by a move build resilience over the year. Bolstered by strong towards bilateral renegotiations on tariffs and terms domestic demand, the economic growth has been of trade. Its ripple effects on global trade flows and robust.43 Benign inflation outlook provided adequate supply chains are still unfolding. This has led to space for monetary policy to support growth.44 heightened global uncertainties and concerns about Continued focus on macroeconomic fundamentals the prospects for global growth. Equity markets, on and economic reforms should help unlock efficiencies the other hand, remained ebullient during much and productivity gains to firmly keep the economy of the year on Big Tech optimism, though concerns on the high-growth trajectory amidst a fast-changing about high valuations have, of late, given rise to some global environment. risk-off sentiments in the equity markets. Portfolio flows to emerging markets are also witnessing a slowdown in recent months. 43 The Monetary Policy Committee (MPC) resolution of December 5, 2025, revised upward the growth projections for 2025-26 by 50 basis points to 7.3 per cent from 6.8 per cent projected at the time of the October bi-monthly review. 44 The CPI inflation projection for 2025-26 was revised downward by 60 basis points to 2.0 per cent in the December MPC meeting from the earlier projection of 2.6 per cent. RBI Bulletin December 2025 59 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voN 4 2 0.3 0 -0.001 -0.3 -2 -4 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peS 52-tcO 52-voNARTICLE State of the Economy Annex Table A1: Real Gross Domestic Product (GDP) Growth (Y-o-y, per cent) Components Share in 2024-25 Weighted Contribution 2024-25 2025-26 (Per cent) in 2024-25 Q1 Q2 Q3 Q4 Q1 Q2 (Percentage points) I. Total Consumption Expenditure 65.6 4.3 7.0 6.1 8.3 4.7 7.1 6.5 Private 56.5 4.0 8.3 6.4 8.1 6.0 7.0 7.9 Government 9.1 0.2 -0.3 4.3 9.3 -1.8 7.4 -2.7 II. Gross Capital Formation 36.8 2.5 6.2 7.7 4.9 7.8 7.3 5.1 Fixed investment 33.7 2.4 6.7 6.7 5.2 9.4 7.8 7.3 III. Net Exports -0.9 2.3 Exports 21.6 1.4 8.3 3.0 10.8 3.9 6.3 5.6 Imports 22.5 -0.9 -1.6 1.0 -2.1 -12.7 10.9 12.8 GDP 100.0 6.5 6.5 5.6 6.4 7.4 7.8 8.2 Note: Components may not add up to total due to other remaining items. Sources: NSO. Table A2: Real Gross Value Added (GVA) Growth (Y-o-y, per cent) Sectors Share in 2024-25 Weighted Contribution 2024-25 2025-26 (Per cent) in 2024-25 Q1 Q2 Q3 Q4 Q1 Q2 (Percentage points) I. Agriculture and allied activities 14.4 0.7 1.5 4.1 6.6 5.4 3.7 3.5 II. Industry 21.5 1.0 7.8 2.1 3.5 4.7 5.8 7.9 Mining and quarrying 2.0 0.1 6.6 -0.4 1.3 2.5 -3.1 -0.04 Manufacturing 17.2 0.8 7.6 2.2 3.6 4.8 7.7 9.1 Electricity, gas, water supply and other 2.4 0.1 10.2 3.0 5.1 5.4 0.5 4.4 utility services III. Services 64.1 4.8 7.2 7.4 7.5 7.9 9.0 9.0 Construction 9.1 0.8 10.1 8.4 7.9 10.8 7.6 7.2 Trade, hotels, transport, communication, 18.5 1.1 5.4 6.1 6.7 6.0 8.6 7.4 and services related to broadcasting Financial, real estate and professional 23.8 1.7 6.6 7.2 7.1 7.8 9.5 10.2 services Public administration, defence and other 12.7 1.1 9.0 8.9 8.9 8.7 9.8 9.7 services GVA at basic prices 100.0 6.4 6.5 5.8 6.5 6.8 7.6 8.1 Sources: NSO; and RBI staff calculations. 60 RBI Bulletin December 2025Government Finances 2025-26: A Half-Yearly Review ARTICLE Government Finances 2025-26: than 4.0 per cent of GDP as per the revised estimates (RE) for 2024-25. A Half-Yearly Review Further, towards incentivising States’ capital by Amrita Basu, Akash Raj, spending, allocation under the scheme 'Special Harshita Yadav, Debapriya Saha, Assistance to States for Capital Investment' was enhanced from the previous year2. The revenue Aayushi Khandelwal, Anoop K Suresh, expenditure of the Centre was budgeted to increase Shromona Ganguly and Atri Mukherjee^ marginally from 10.9 per cent of GDP in 2024-25 (provisional accounts, PA) to 11.0 per cent of GDP in The fiscal position of the Centre and States remained 2025-26 (budget estimates, BE). Overall, the Union resilient during H1:2025-26. Their receipts were broadly Budget aimed at fiscal consolidation, in line with the in line with trends observed during H1: 2024-25. Both medium-term target to bring the gross fiscal deficit the Centre and States have demonstrated commitment (GFD) below 4.5 per cent of the GDP by 2025-263. to prudent fiscal management through containment Recognising the importance of analysing sub- of revenue expenditure, while maintaining capital annual public finances for efficient fiscal and macro- expenditure. This has resulted in improvement in the economic outcomes, this article presents a synoptic quality of expenditure for the Centre as well as States, view of the half yearly fiscal position for the Centre which bodes well for medium-term growth prospects and as well as States. During H1:2025-26, Centre's GFD fiscal consolidation. stood at 36.5 per cent of BE in comparison with 29.4 Introduction per cent of BE in H1:2024-25, mainly attributable to The Union Budget 2025–26 reaffirmed the robust growth in capital expenditure. On the receipts Government’s commitment to fiscal discipline while side, higher collections through non-tax sources and fostering inclusive, long-term economic growth non-debt capital receipts helped in offsetting the in line with the vision of Viksit Bharat. Under moderation of tax revenue for the Centre. In the case the four engines of growth - agriculture, MSMEs, of States, the GFD stood at 37.6 per cent of their BE in investment, and exports, the Budget contained H1:2025-26, marginally higher than its level recorded several measures balancing the socio-economic needs during H1:2024-25, mainly attributable to sluggish with the long-term structural transformation of the growth in their revenue receipts. On the expenditure economy. Continuing the thrust on infrastructure front, States sustained the pace of their revenue development, the Budget 2025-26 provisioned ₹11.2 expenditure while capital expenditure recorded a lakh crore (3.1 per cent of GDP) for capital expenditure. marginal growth4,5. Similarly, the effective capital expenditure1 was 2 The allocation for the scheme 'Special Assistance to States for Capital budgeted at 4.3 per cent of GDP for 2025-26, higher Investment' was enhanced from ₹1.25 lakh crore in 2024-25 (RE) to ₹1.5 lakh crore in 2025-26 (BE). ^ This article is prepared under the overall guidance of Smt. Sangeeta Das. The authors are working in the Department of Economic and Policy 3 As announced in the Union Budget, 2021-22. Research of the Reserve Bank of India. Views expressed in this article are 4 The data pertains to 23 States for which the data for April-September of the authors and do not represent the views of the Reserve Bank of India. 2025 are available. GFD-GDP ratio is estimated using GSDP data for the 1 Effective capital expenditure is the sum of capital expenditure and same 23 States. the grants-in-aid for creation of capital assets. For 2024-25, the latest data 5 Detailed statements on half yearly and quarterly financial position of available on effective capital expenditure is the revised estimates. the Centre as well as the States are provided in Appendix Tables (I to IV). RBI Bulletin December 2025 61ARTICLE Government Finances 2025-26: A Half-Yearly Review The rest of the article is structured as follows: from Centre6 and slower growth in States’ goods and Section II analyses the receipt and expenditure of the services tax (SGST). On the expenditure side, States Centre and States (at a quarterly frequency) during have expended 38.2 per cent of their budgeted outlay H1:2025-26. Section III deals with the outcomes in during H1:2025-26, remaining aligned with their past terms of deficit indicators and their financing for the spending patterns (Chart 1b). Centre as well as States. Section IV presents estimates a. Receipts on General government (Centre plus States) finances The Centre’s total receipts (i.e., 'total non-debt for H1:2025-26. Section V sets out the concluding receipts') comprise revenue receipts and non-debt observations. capital receipts. During H1:2025-26, the total non- II. Fiscal Outcome in Q1 and Q2 debt receipts of the Central government stood at 49.5 During H1:2025-26, the Central government per cent of BE, with the revenue receipts and non-debt collected nearly 50 per cent of its total budgeted capital receipts attaining 49.6 per cent and 45.8 per receipts, slightly below the collections in the past cent, respectively, of their budgeted target. Primarily year. On a year-on-year (y-o-y) basis, total receipts on account of lower growth in tax receipts, the during H1:2025-26 rose by 5.7 per cent. The Centre’s Centre’s receipts (as per cent of BE) during H1:2025- total expenditure was contained below 50 per cent 26 stood marginally below the corresponding figure of the BE in H1:2025-26, in line with the pattern attained during H1:2024-25. During Q1:2025-26, the observed during the past three years (Chart 1a and y-o-y growth in revenue receipts was slower than b). States' total receipts as per cent of BE witnessed that of Q1:2024-25, which was partially offset by the moderation in comparison to the previous year (Chart strong growth of non-debt capital receipts7. However, 1a). This was attributable to contraction in grants in Q2:2025-26, both revenue receipts and non-debt Chart 1: Total Receipts and Expenditure in H1 a. Total Receipts b. Total Expenditure (Per cent of BE) (Per cent of BE) 60 50 45.5 43.8 51.0 45 49.5 50 40 39.0 38.2 40 39.4 38.3 35 30 30 25 20 20 15 10 10 5 0 0 2022-23 2023-24 2024-25 2025-26 2022-23 2023-24 2024-25 2025-26 Centre States Centre States Sources: Controller General of Accounts (CGA); Comptroller and Auditor General (CAG); and Union Budget Documents. 6 Grants from the Centre continued to decline partly due to tapering of Finance Commission grants. 7 Non-debt capital receipts include recoveries of loans and advances and miscellaneous capital receipts (viz., disinvestment and other receipts). 62 RBI Bulletin December 2025Government Finances 2025-26: A Half-Yearly Review ARTICLE Chart 2: Quarterly Breakup of Centre’s Non-Debt Receipts a. Revenue Receipts b. Non-Debt Capital Receipts (Per cent of BE, left scale; y-o-y growth, right scale) (Per cent of BE, left scale; y-o-y growth, right scale) 60 45 519.9 60 550 50 40 500 50 35 450 40 40 36.9 400 30 350 30 26.7 22.9 25 30 300 20 20 20 8.9 250 10 10.1 15 10 12 50 00 10 100 0 0 5 50 -10 -1.3 0 -10 -33.0 -0 50 -20 -5 -20 -100 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 2023-24 2024-25 2025-26 2023-24 2024-25 2025-26 Per cent of BE Y-o-Y growth Per cent of BE Y-o-Y growth Sources: CGA; and Union Budget documents. capital receipts recorded contraction on y-o-y basis of revenue receipts exhibited a growth of 7.3 per (Chart 2a and b). cent and 11.1 per cent in Q1:2025-26 and Q2:2025- 26, respectively. At the same time, States’ non-debt States’ revenue receipts posted modest growth of 6.3 per cent in H1:2025-26, partly due to the capital receipts8 registered robust growth in both the weak momentum in SGST collections (Chart 3a). Tax quarters (Chart 3b). revenue, which accounts for more than two-third Chart 3: Quarterly Breakup of States' Receipts a. Revenue Receipts b. Non-Debt Capital Receipts (Per cent of BE, left scale; y-o-y growth, right scale) (Per cent of BE, left scale; y-o-y growth, right scale) 35 18 100 600 16 500 30 14 75 400 25 12 20 18.9 19.7 10 300 6.6 8 50 127.5 200 15 6 100 106.0 10 6.0 4 25 0 2 5 0 6.3 5.9 -100 0 -2 0 -200 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 2023-24 2024-25 2025-26 2023-24 2024-25 2025-6 Per cent of BE Y-o-Y growth Per cent of BE Y-o-Y growth Sources: CAG; and Budget documents of State governments. 8 Non-debt capital receipts of States comprise recoveries of loans and advances disbursed by them to subordinate/ parastatal entities and other miscellaneous capital receipts. RBI Bulletin December 2025 63ARTICLE Government Finances 2025-26: A Half-Yearly Review The Centre’s direct tax collections grew by 3.0 per collection contracted on a y-o-y basis across all indirect cent on y-o-y basis in H1:2025-26, primarily led by an tax categories in Q2:2025-26, except union excise increase of 4.7 per cent in income tax collections while duties. Overall, in H1:2025-26, the Centre could corporate tax collections registered a growth of 1.1 collect 44.6 per cent of its budgeted indirect taxes as per cent. Similar to the pattern witnessed in H1:2024- compared to 46.6 per cent during H1:2024-25. 25, income tax collections exceeded the corporate The gross GST collections (Centre plus States) in tax collections in H1:2025-26, reflecting, inter alia, H1:2025-26 amounted to ₹ 11.9 lakh crore, registering measures towards improving taxpayers’ compliance a y-o-y growth of 9.8 per cent (9.5 per cent growth and broadening the tax base9 (Chart 4a). States’ recorded in H1:2024-25), with average monthly own direct tax collection (comprising land revenue collections of ₹2.1 lakh crore and ₹1.9 lakh crore in and receipts from stamp duty and registration fees) Q1:2025-26 and Q2:2025-26, respectively (Chart 5). registered a steady growth driven largely by robust GST revenues continue to draw support from reforms collections from stamp duty (Chart 4b). in digital integration, eased compliance processes The Centre’s indirect tax collections grew by and rate rationalisation measures undertaken since 2.6 per cent (y-o-y) in H1:2025-2610. This was mainly its inception in 2017 (Box A). attributed to growth in GST and excise duties, while revenue from customs declined. In particular, In the case of States, the moderation in growth robust GST collections (y-o-y growth of 16.1 per cent) of tax revenues primarily reflected the impact of contributed to double-digit growth of 11.3 per cent in one-time negative settlement of SGST in April 2025 total indirect taxes in Q1:2025-26. However, revenue on collection of States’ GST (SGST) (Chart 6a)11. Chart 4: Quarterly Direct Tax Collections a. Centre’s Direct Taxes b. States' Own Direct Taxes (₹ thousand crore) (₹ thousand crore) Corporation tax Income tax Other taxes Sources: CGA; and CAG. 9 https://www.pib.gov.in/PressNoteDetails.aspx?id=154926&NoteId=154926&ModuleId=3 10 During H1:2024-25. Centre’s indirect tax collections grew by 8.4 per cent over H1:2023-24. 11 States’ GST is the sum of GST revenues of the States/UTs and their share in IGST. During April 2025, ₹23,000 crore was settled to clear an old IGST shortfall, resulting in a decline in GST revenue for the States. 64 RBI Bulletin December 2025 682 371 503 492 700 600 500 400 300 200 100 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 2023-24 2024-25 2025-26 6.06 6.56 80 70 60 50 40 30 20 10 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 2023-24 2024-25 2025-26 Land revenue Stamp duty and Registration feesGovernment Finances 2025-26: A Half-Yearly Review ARTICLE Chart 5: Gross GST Collections (Centre plus States) (₹ thousand crore) 250 199 181 200 150 100 50 0 Note: The blue line represents the average monthly GST collections in H1:2024-25 and H1:2025-26. Sources: Press Information Bureau (PIB); and GST Website. Box A: Tracing Eight Years of GST Reforms in India The goods and services tax (GST), rolled out on July 1, reforms by various stakeholders and addressing issues 2017, pan India, had replaced multiple taxes such as of inverted duty structure12 through rate rationalisation central value added tax, central sales tax, state sales tax measures. and octroi. Eight years since its launch, GST has firmly The introduction of a single indirect tax system under established itself as simpler and more transparent GST marked a major digital transformation in India’s tax framework, with recent evidence indicating its administration by streamlining compliance and creating progressive distributional impact (Mukherjee, 2025). The the foundation for integration of multiple government consistent rise in revenue collections and a growing base databases [through the establishment of goods and of over 1.5 crore active taxpayers stand as testimony to its services tax network (GSTN), the central digital backbone of India’s indirect tax ecosystem]. Through the common success. Average monthly GST collections have depicted portal, GSTN supports taxpayers’ registration, return an increasing trend over the years and stood at `1.98 lakh filing, payments, and other compliances. The GSTN is crore for the period April-October 2025, up from `1.82 a shared infrastructure between the Centre and States lakh crore attained during April-October 2024. Net GST which aids transparency in tax collections, thereby collections (gross GST collections less refunds) are largely promoting fiscal federalism (Government of India, in consonance with the trend in gross GST collections 2019). (Chart A.1 and A.2). The e-way bill13 system, introduced in 2018, significantly Since its inception, the GST framework has been improved ease of doing business by enabling smooth inter- continuously evolving towards establishing a streamlined state and intra-state movement of goods, and reducing and comprehensive digital infrastructure; enhancing ease check-post paperwork. Subsequently, in September of compliance for taxpayers; augmenting a transparent 2019, the GST Council approved the introduction of and efficient federal structure; ensuring adherence to (Contd.) 12 Inverted duty structure refers to the situation where the tax on output is lower than tax on inputs, resulting in accumulation of unutilised input tax credit (ITC), which may have implication on working capital and liquidity of firms. GST law allows refund of accumulated ITC due to inverted duty structure under Section 54 (3) of the CGST Act, 2017, except certain specific cases. 13 E-way bill is a compliance mechanism wherein, by way of a digital interface the person causing the movement of goods (with a consignment value of more than ₹50,000) uploads the relevant information prior to the commencement of movement of goods. An e-way bill consists of details such as name of consignor, consignee, transporter, the point of origin of the movement of goods and its destination. RBI Bulletin December 2025 65 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 52-nuJ 52-luJ 52-guA 52-peSARTICLE Government Finances 2025-26: A Half-Yearly Review Chart A.2: Trends in GST Returns Filed a. Average Number of Monthly Returns Filed under Form GSTR-1 b. Average Number of Monthly Returns Filed under Form GSTR-3B (Lakh crore) (Lakh crore) 120 99.5 100 80 60 40 20 0 *: For 2025-26, data pertains to the period April-October 2025. Notes: 1. Form GSTR-1 is a monthly statement furnished by taxpayers containing details of outward supplies of goods and services or both. 2. Form GSTR-3B is a simplified summary return for taxpayers to declare their summary GST liabilities for a particular tax period and discharge these liabilities. Source: GST Statistics, Government of India, States and Union Territories. e-invoicing14, initially applicable to businesses with an Beyond these, within system improvements, GSTN also annual aggregate turnover of ₹500 crore and above. The connects with other government platforms for specified threshold has since been reduced to ₹5 crore, making purposes. For instance, the Indian customs electronic the system more comprehensive. The introduction of gateway (ICEGATE) and GST systems exchange data e-invoicing has automated and simplified compliance necessary for processes such as input tax credit on as data from registered invoices is now auto-populated imports and refund on exports. Similarly, the Udyam into GST returns such as form GSTR-3B. Furthermore, the registration15 portal for micro, small and medium system is integrated with the e-way bill portal, enabling enterprises (MSMEs) draws on PAN/GST linked databases faster and more accurate generation of e-way bills. (Contd.) 14 E-invoicing involves reporting details of specified GST documents to a government notified portal and obtaining a reference number. 15 The Udyam registration is an optional registration mechanism for MSMEs. It supports MSMEs in availing the benefits of schemes of the Ministry of MSME such as credit guarantee scheme, public procurement policy, and additional edge in government tenders and protection against delayed payments, and in availing priority sector lending [Registration of Micro, Small and Medium Enterprises (MSMEs) in India, 2020-22, Ministry of MSME, GoI]. 66 RBI Bulletin December 2025 81-7102 91-8102 02-9102 12-0202 22-1202 32-2202 42-3202 52-4202 *62-5202 120 98.5 100 80 60 40 20 0 81-7102 91-8102 02-9102 12-0202 22-1202 32-2202 42-3202 52-4202 *62-5202 Chart A.1: Trends in GST Collections a. Average Monthly Gross GST Collections b. GST Revenue Collection (₹ lakh crore) (₹ lakh crore) 2.4 2.2 1.96 2.0 1.8 1.69 1.6 1.4 1.2 1.0 Gross GST collections Net GST collections *: For 2025-26, data pertains to the period April-October 2025. Note: Net GST collections refer to gross GST collections less refunds. Source: GST Statistics, Government of India, States and Union Territories. 32-nuJ 32-guA 32-tcO 32-ceD 42-beF 42-rpA 42-nuJ 42-guA 42-tcO 42-ceD 52-beF 52-rpA 52-nuJ 52-guA 52-tcO 1.98 2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 81-7102 91-8102 02-9102 12-0202 22-1202 32-2202 42-3202 52-4202 *62-5202Government Finances 2025-26: A Half-Yearly Review ARTICLE Chart A.3: Type-wise GST Registrations a. Taxpayers Registered under GST as at end-March 2025 b. Active Taxpayers as at end-October 2025 Proprietorship Partnership Private limited company Government department Normal taxpayers Composition taxpayers Others Tax deductor at source Others Notes: 1. Others in chart 3a include limited liability partnership, society/club/trust/AOP, local authority, public limited company and hindu undivided family. 2. Other taxpayers in chart 3b include input service distributors, casual taxpayers, tax collector at source, and non-resident taxpayers Source: GST Statistics, Government of India, States and Union Territories. making it easier for enterprises to access government was highest in Andhra Pradesh (19.9 per cent), followed schemes. These digital linkages have reduced data gaps, by Chhattisgarh (15.8 per cent), Bihar and Uttar Pradesh streamlined coordination between tax and trade systems, (15.5 per cent in each case). Cross-country experience and strengthened transparency. suggests that simplified tax regimes, when designed Out of 1.5 crore registered taxpayers under GST16, 77.6 carefully, can potentially reduce compliance costs for per cent are proprietorships, reflecting predominance of small enterprises (Engelschalk and Loeprick, 2015). small businesses in the tax base and underscoring the Over the past eight years, continuous efforts have been need for simplified compliance mechanisms (Chart A.3a). made to strengthen the tax system through periodic Ease of compliance for small taxpayers is a key reform review of rates by the GST Council for addressing issues undertaken through the GST framework, paving the such as inverted duty structure, and to ensure due way for taxpayer-friendly formalisation of the economy. compliance by various stakeholders19. A key milestone in The GST composition scheme was introduced with the this direction was the reforms announced in September objective of easing the compliance burden on small 2025, following the recommendations of the 56th GST taxpayers by allowing them to file GST returns based on Council meeting, which marked a shift from a four-slab annual turnover rather than individual transactions17. rate structure20 to a simplified two-slab GST framework21. These composition taxpayers constitute about 9.3 per cent of total registered taxpayers under GST as on end- The reforms aim to reduce costs for consumers, ease October 2025 (Chart A.3b). Around 6.2 per cent of total compliance for traders and enhance competitiveness composition taxpayers were from the special category for Indian businesses. Going forward, the resultant States18. Excluding the special category States, number rationalisation of GST rates is expected to stimulate of composition taxpayer, as per cent of total taxpayers demand and support economic activity. (Contd.) 16 As on March 31, 2025. 17 The scheme is optional. It essentially provides for a turnover tax regime for small taxpayers, with facility for filing of return on an annual basis along with quarterly payment of tax. Under this scheme, a registered taxable person, whose aggregate annual turnover has not exceeded ₹1.5 crore in case of goods (₹75 lakh in case of Uttarakhand and 7 North Eastern States) in the previous financial year, may opt for this scheme. For service providers, the turnover ceiling is ₹50 lakh in the preceding financial year. 18 As defined in Section 22, CGST Act, 2017. 19 Recent measures to improve compliance include establishment of Goods and Services Appellate Tribunal, nationwide drives against fake registrations by the Centre and State tax authorities in 2023 and 2024 and the introduction of auto-populated, non-editable Form-3B to ensure accurate matching of liability with outward supplies. 20 Broadly consisting of four slabs, viz., 5,12, 18 and 28 per cent. 21 Broadly consisting of two-slabs, viz., 5 and 18 per cent, along with a special rate of 40 per cent on certain sin and luxury goods. RBI Bulletin December 2025 67ARTICLE Government Finances 2025-26: A Half-Yearly Review To sum up, India’s GST framework has evolved as a Government of India. Press Information Bureau. Various dynamic and adaptive system, responding to the needs of Press Releases. its key stakeholders, viz., the Centre, States, businesses, Engelschalk, M., and Loeprick, J. (2015). MSME and consumers. The reform journey continues with focus Taxation in Transition Economies: Country Experience on simplification, transparency, and efficiency, aligning on the Costs and Benefits of Introducing Special Tax the structure progressively with international best Regimes (Policy Research Working Paper No. 7449). World practices while preserving the spirit of fiscal cooperation Bank. between the Centre and States. Mukherjee, S. (2025). Distributional Effects of GST in References India: Evidence from the 2022-23 Household Government of India (2019). The GST Saga: A Story of Consumption Expenditure Survey. Economic and Political Extraordinary National Ambition, Ministry of Finance, Weekly. Government of India. In H1:2025-26, the assignment to States (i.e., tax cent and 20.5 per cent, respectively. The non-debt devolution from the Centre to States) recorded a capital receipts22 recorded robust growth in H1:2025- growth of 14.2 per cent over the corresponding period 26 (Chart 7). of the previous year (Chart 6b). b. Expenditure During H1:2025-26, on the back of higher surplus In 2025-26, the total expenditure of the Central transfer from the Reserve Bank, the Centre’s receipts government is budgeted to grow by 8.8 per cent over from non-tax revenue sources recorded strong 2024-25 (PA) with revenue expenditure and capital growth which helped in offsetting the moderation in tax receipts. During Q1:2025-26 and Q2:2025-26, expenditure growth budgeted at 9.5 per cent and non-tax revenue recorded a y-o-y growth of 33.2 per 6.6 per cent, respectively. In H1:2025-26, revenue Chart 6: Quarterly Performance of SGST and Tax Devolution from Centre a. SGST b. Tax Devolution from Centre (Per cent of BE, left scale; y-o-y growth, right scale) (Per cent of BE, left scale; y-o-y growth, right scale) 29 25 40 80 28 35 70 20 60 27 30 50 26 15 25 40 25 20 18.8 19.1 30 23.7 24 23.6 10 15 15.7 20 7.4 10 23 10 5 12.6 0 22 3.8 5 -10 21 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 0 -20 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 2023-24 2024-25 2025-26 2023-24 2024-25 2025-26 Per cent of BE Y-o-Y growth Per cent of BE Y-o-Y growth Source: CAG. 22 Including disinvestment receipts. 68 RBI Bulletin December 2025Government Finances 2025-26: A Half-Yearly Review ARTICLE Chart 7: Non-Tax Revenue and Non-Debt Capital Chart 8: Expenditure Trends of Centre in H1 Receipts of the Centre (Per cent of BE) (Per cent of BE) 60 70 64.0 51.8 60 50 43.7 50 40 40 36.9 30 30 20 20 16.0 10 8.9 10 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 0 2022-23 2023-24 2024-25 2025-26 Revenue expenditure Capital expenditure Non-Tax revenue Non-Debt capital receipts 2023-24 2024-25 2025-26 Sources: CGA; and Union Budget documents. Sources: CGA; and Union Budget documents. expenditure as per cent of BE stood lower than the 2025-26 during the winter session of parliament which corresponding period of the previous year, on account involves a net cash outgo of ₹41,455 crore. Going of decline in food subsidies. Capital expenditure forward, in comparison to H2:2024-25, the growth as per cent of BE was significantly higher than the in total expenditure in H2:2025-26 is likely to be previous year23, led by growth in loans and advances moderate, as the Centre aims to adhere to its budgeted as well as capital outlay24 (Chart 8). deficit target for 2025-26. During H2:2025-26, the growth in revenue expenditure is expected to be Capital expenditure of the top 5 ministries, higher than the growth recorded in H1:2025-26 to which together comprise nearly 90 per cent of the total budgeted capital expenditure of the Centre for Chart 9: Capital Expenditure of Key Ministries in H1 2025-26, stood at 49.3 per cent of their BE during (Per cent of BE) H1:2025-26, higher than 37.1 per cent of BE during 70 62.8 H1:2024-25 (Chart 9). The Ministry of Road Transport 56.9 60 53.8 and Highways, and Ministry of Railways which 51.6 50.1 50 together comprise 46.8 per cent of the total budgeted capital expenditure of the Centre for 2025-26 have 40 34.4 31.8 registered a y-o-y growth of 21.7 per cent and 5.6 per 26.7 30 cent, respectively, in H1:2025-26. 17.3 20 The Union government had also proposed the first batch of supplementary demand for grants for 10 6.5 0 23 Lower capital expenditure as per cent of budget estimates during Road Transport Railways Finance Defence Communication H1:2024-25 was mainly attributable to the imposition of model code of and Highways conduct (in Q1:2024-25) in view of general elections and heavy monsoon 2024-25 2025-26 rains (in Q2: 2024-25). Sources: CGA; and Union Budget documents. 24 Capital outlay is capital expenditure less loans and advances. RBI Bulletin December 2025 69ARTICLE Government Finances 2025-26: A Half-Yearly Review meet the budgeted revenue expenditure target for Chart 10: Expenditure Growth of Centre in H2 2025-26. Since the major portion of budgeted capex (Per cent, y-o-y growth) 50 for 2024-25 was undertaken during H2:2024-25, the capex growth during H2:2025-26 is likely to slow 40 down on a year-on-year basis reflecting the base 30 effect (Chart 10). 20 The outgo of the Central government on major 10 subsidies, comprising food, fuel and fertilisers stood at 0 52.8 per cent of BE in H1:2025-26 as compared to 56.3 -10 per cent of BE in H1:2024-25. This decline in major subsidies is primarily attributable to contraction in -20 Total expenditure Revenue expenditure Capital expenditure food subsidy. Fertiliser subsidy stood at 63.9 per cent 2022-23 2023-24 2024-25 2025-26 Note: Expenditure growth for H2:2025-26 is the implied growth rate based on of its budgeted amount in H1:2025-26 due to, inter alia, actuals up to September 2025 and the budget estimates for 2025-26 plus expenditure proposals in the first supplementary demand for grants rising international prices of urea and nutrient based announced in December 2025. Sources: CGA; Union Budget documents; and RBI staff estimates. subsidy25. Petroleum subsidy, primarily comprising subsidy spending under the Pradhan Mantri Ujjwala in line with the spending behaviour of the previous Yojana26 stood at 55.5 per cent of its budgeted amount year, States have exhausted 40.6 per cent of their during H1:2025-26 (Chart 11). budgeted revenue expenditure in H1:2025-26. States’ revenue expenditure remained healthy Meanwhile, capital expenditure grew at 5.5 per with y-o-y growth in H1:2025-26 (Chart 12a). Keeping cent during H1:2025-26, witnessing strong growth Chart 11: Half-yearly Expenditure on Major Subsidies by the Central Government (Per cent of BE) 180 160 140 120 100 80 63.9 60 55.5 43.4 40 20 0 H1 H2 H1 H2 H1 H2 H1 2022-23 2023-24 2024-25 2025-26 Food Fertilisers Petroleum Note: In H2:2023-24, petroleum subsidy amounted to 492.7 per cent of the budgeted figures for 2023-24 on account of provisioning of higher LPG subsidy to Pradhan Mantri Ujjwala Yojana beneficiaries. Being an outlier, the petroleum subsidy figures for H2:2023-24 has not been depicted in the chart. Sources: CGA; and Union Budget documents. 25 Monthly Bulletin, Department of Fertilisers, September 2025. 26 Pradhan Mantri Ujjwala Yojana was announced on May 1, 2016, to provide subsidised liquified petroleum gas (LPG) connections to eligible households to help them switch from traditional cooking methods to LPG which is a cleaner fuel. 70 RBI Bulletin December 2025Government Finances 2025-26: A Half-Yearly Review ARTICLE Chart 12: Quarterly Expenditure of State Governments a. Revenue Expenditure b. Capital Expenditure (Per cent of BE, left scale; y-o-y growth, right scale) (Per cent of BE, left scale; y-o-y growth, right scale) 50 18 45 100 16 40 80 10.8 5.9 14 35 60 30 12 30 19.3 21.3 10 25 22.1 40 8 20 16.0 20 10 6 15 11.1 0 4 10 2 5 -3.6 -20 -10 0 0 -40 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 2023-24 2024-25 2025-26 2023-24 2024-25 2025-26 Per cent of BE Y-o-Y growth Per cent of BE Y-o-Y growth Sources: CAG; and Budget documents of State governments. in Q1 on account of a lower base, while registering through Centre's interest free loan scheme for a contraction in Q2 (Chart 12b). Going forward, capital investment and the typical year-end spending capital expenditure is likely to gather momentum, concentration (Box B). Box B: Seasonal Concentration of Fiscal Aggregates across Subnational Governments The seasonal concentration of fiscal aggregates is a central Chart B.1: Average Monthly Concentration aspect of cash flow management across Indian States, of Reserve Bank's Short-Term Facilities often shaping their short-term borrowing needs. When the (2019-20 to 2024-25) timing of revenue receipts and expenditure commitments (Per cent) diverges, States face temporary gaps that must be bridged 10 to maintain payment continuity. Accordingly, States rely 8 on their intermediate treasury balances before turning to 6 Reserve Bank of India’s liquidity facilities27, namely the special drawing facility (SDF), ways and means advances 4 (WMA), and overdraft (OD). Between 2019-20 to 2024-25, 2 there has been a steady rise in SDF usage till September. 0 WMA usage peaks in October ahead of festive quarter, while Overdraft usage gathers pace in January-March, aligning with early stages of the year-end spending cycle, when expenditures typically record their year-end peak Source: RBI staff estimates. (Chart B.1). (Contd.) 27 SDF allows States to access funds linked to their quantum of investments in instruments such as the consolidated sinking fund (CSF), guarantee redemption fund (GRF) and against investments in government security (G-sec)/auction treasury bills (ATB). WMA provides temporary advances to smooth routine cash-flow gaps, while OD, which carries a penal rate above the repo rate, is invoked only when WMA limits are exceeded and indicates sharper cash stress. RBI Bulletin December 2025 71 lirpA yaM enuJ yluJ tsuguA rebmetpeS rebotcO rebmevoN rebmeceD yraunaJ yraurbeF hcraM SDF WMA OverdraftARTICLE Government Finances 2025-26: A Half-Yearly Review Chart B.2. Average Monthly Concentration in Components of Receipts and Expenditure (2019-20 to 2024-25) a. Receipts b. Expenditure (Per cent) (Revenue expenditure, per cent, left scale; capital expenditure, per cent, right scale) 20 15 10 5 0 Share in union tax SGST Grants-in-aid Revenue receipts Source: RBI staff estimates. To analyse how the mismatch between receipts and overall spending activity remains subdued as observed expenditure shapes States’ short-term liquidity needs, across various States. From June onwards, expenditure monthly concentration of States’ revenue receipts along begins to pick up. State government expenditure witness with its major components such as tax devolution, States’ year-end surge in February and March when departments goods and services tax (SGST) and grants from the Centre expedite project execution, following the flow of funds are considered for the period 2019-2025 (Chart B.2a). The from schemes under Grants and departments also overall pattern reveals a clear year-end concentration clear pending bills to avoid lapse of funds. The sharp in aggregate receipts, reflecting the influence of both administrative and cyclical factors. Within components, bunching of spending in these final months, especially the tax devolution from the Centre peaks in March, in capital expenditure, intensifies liquidity pressures, coinciding with the year-end settlement of Central tax often compelling States to rely on short-term borrowing. devolution and advance tax inflow. This arises because With regular cheaper borrowing facilities such as SDF Centre’s corporate tax and income tax collections are and WMA nearing exhaustion, several States resort themselves clustered around advance payment schedule to overdraft mechanisms to bridge temporary cash and finalisation of accounts (Srivastava and Trehan, gaps. This reinforces the need for smoother intra-year 2018; Srivastava et al., 2025). Grants-in-aid record a expenditure calibration to reduce reliance on temporary distinct local peak28 in June, followed by milder peaks borrowing facilities. in September and December, and a pronounced year- end surge in March, reflecting the typical bunching of References scheme-related transfers. In contrast, SGST collections, Srivastava, D. K., and Trehan, R. (2018). Managing being closely linked to consumption and economic Central Government Finances: Asymmetric Seasonality activity, show relatively stable inflows with mild festive- in Receipts and Expenditures. Global Business season peaks. Review, 19(5), 1322-1344. The month-wise expenditure pattern of States displays Srivastava, D. K., Bharadwaj, M., Kapur, T., and Trehan, a distinct back-loaded concentration (Chart B.2b) with revenue expenditure remaining relatively stable, as a R. (2025). Seasonal Concentration of Fiscal Aggregates: large part of it is committed in nature. In April and May, Case Study of India. Modern Economy, 16(9). 28 A local peak is a month where the concentration is higher than the months immediately before and after it. 72 RBI Bulletin December 2025 lirpA yaM enuJ yluJ tsuguA rebmetpeS rebotcO rebmevoN rebmeceD yraunaJ yraurbeF hcraM 25 25 20 20 15 15 10 10 5 5 0 0 lirpA yaM enuJ yluJ tsuguA rebmetpeS rebotcO rebmevoN rebmeceD yraunaJ yraurbeF hcraM Interest payments Revenue expenditure Subsidy Capital expenditureGovernment Finances 2025-26: A Half-Yearly Review ARTICLE III. Fiscal Deficit and its Financing 2024-25 (RE). States have exhausted a marginally Central Government higher proportion of their budgeted GFD in Q1:2025- a. Fiscal Deficit 26 and Q2:2025-26, respectively, as compared to The Central government budgeted for a GFD of Q1 and Q2 of 2024-25. Correspondingly, the fiscal 4.4 per cent of GDP in 2025-26 as compared with space available to States for H2:2025-26 has slightly 4.8 per cent in 2024-25 (PA), in line with the glide reduced to 62.4 per cent of their budgeted GFD, as path to achieve medium term GFD target of below against 62.9 per cent available during H2:2024-25 4.5 per cent of GDP by 2025-26. While GFD-GDP ratio (Chart 14a and b). in Q1:2025-26 was higher than the corresponding b. Financing of GFD quarter of the previous year, the trend reversed in Q2:2025-26. During H1:2025-26, the GFD of the States' net market borrowings during H1:2025- Central government stood at 36.5 per cent of the BE, 26 registered a growth of 22.3 per cent over the higher than 29.4 per cent recorded during H1:2024- corresponding period of the previous year. During 25, reflecting higher growth in Centre’s capital this period, States utilised 35.9 per cent of their expenditure (Chart 13a and b). budgeted net market borrowings, up from 32.1 b. Financing of GFD per cent in the same period of 2024-25. Seventeen In H1:2025-26 (up to September 26, 2025), the States utilised a higher proportion of their budgeted Central government completed 48.2 per cent of the net borrowings as compared to the corresponding budgeted net market borrowings for 2025-26 (as period of the previous year (Chart 15a and b). Gross against 43.9 per cent in the corresponding period last market borrowings increased by 21.0 per cent over year), which financed a major chunk of its GFD. the previous year, representing 37.5 per cent of the State Government budgeted amount. a. Fiscal Deficit The financial accommodation availed by States States budgeted a consolidated GFD of 3.3 per through various facilities provided by the Reserve cent of GDP for 2025-26, lower than 3.5 per cent in Bank increased by 52.7 per cent in H1:2025-26 over Chart 13: Centre’s Gross Fiscal Deficit a. Per cent of GDP b. Quarterly Share of Annual Budgeted GFD (Per cent) 12 120 10 100 8 80 6 60 4 3.3 3.4 40 18.6 2 20 17.9 0 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 2022-23 2023-24 2024-25 2025-26 2022-23 2023-24 2024-25 2025-26 Q1 Q2 Q3 Q4 Sources: CGA; and Union Budget Documents. RBI Bulletin December 2025 73ARTICLE Government Finances 2025-26: A Half-Yearly Review Chart 14: States’ Gross Fiscal Deficit a. Per cent of GDP b.QuarterlyShareofAnnualBudgetedGFD (Percent) 6.0 120 5.0 100 4.0 80 3.0 3.0 60 2.0 1.8 40 1.0 23.5 20 14.1 0.0 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 2022-23 2023-24 2024-25 2025-26 2022-23 2023-24 2024-25 2025-26 Q1 Q2 Q3 Q4 Sources: CAG; and Budget documents of State governments. the corresponding period of the previous year. The three facilities viz., special drawing facility, ways and ways and means advances (WMA) limits were revised means advances and overdraft rose during H1:2025- effective from July 1, 2024. The aggregate WMA limit 26 over the corresponding period of the previous year for States/UTs now stands at ₹60,118 crore, an increase (Chart 16a and b). of 27.9 per cent over the earlier limit of ₹47,010 crore. Quality of Expenditure – Centre and States States utilised 8.1 per cent of the permissible WMA limit in Q1:2025-26 and 10.6 per cent in Q2:2025- The revenue expenditure to capital outlay (RECO) 26. The average utilisation by States under all the ratio of the Centre declined to 3.7 in H1:2025-26 from Chart 15: State/UT-wise Market Borrowings a. Gross Market Borrowing b. Net Market Borrowing (Borrowings in H1:2025-26, vertical axis; (Borrowings in H1:2025-26, vertical axis; borrowings in H1:2024-25, horizontal axis) borrowings in H1:2024-25, horizontal axis) 110 MN 90 MN 100 90 TR TL 70 80 TR HP MH 70 BH HP TL 50 BH KL PB 60 A MP H All States MG MZ AP 50 MG KL PB TN J&K 40 MPAll States AM MP RJ J&K 30 OD GJ Goa AMHRRJ OD 30 GJ WB HTN R MZ SK JH UK WB SK2 JH0 CG 10 UP NL CG KA1 00 0Go Na L UK KA -20 -10 0 10 20 30 40 50 60 70 80 90 100 -10 -10 10 30 50 70 90 UP -10 -20 Notes: 1. Size of bubble corresponds to the share of the State in H1:2025-26 market borrowing. 2. The 45-degree line corresponds to no change. Sources: RBI; and Budget documents of States/UTs. 74 RBI Bulletin December 2025Government Finances 2025-26: A Half-Yearly Review ARTICLE Chart 16: Financial Accommodation availed by the States Under Various Facilities with the Reserve Bank a. Average Daily Utilisation by States b. Average Daily WMA Utilisation (₹ crores) (Per cent of the limit allowed) 35,000 80 70 30,000 60 50 25,000 40 30 20,000 20 10 15,000 0 10,000 5,000 0 H1:2024-25 H1:2025-26 WMA SDF OD Sources: Various issues of RBI Bulletin; and RBI staff estimates. 4.7, a year ago (i.e., in H1:2024-25), lowest in more IV. General Government Finances than a decade29, reflecting the continued impetus In continuation of the effort to provide timely of the government in improving the quality of its fiscal data on the general government, the quarterly expenditure (Chart 17a). Similarly, in the case of fiscal position of the general government has States, the expenditure quality has been improving been compiled till Q2:2025-26. In Q1:2025-26, the as reflected in declining RECO ratio in H1:2025-26 increase in combined expenditure of the Centre compared to the previous year (Chart 17b). and States, mainly on account of higher growth RBI Bulletin December 2025 75 hsedarP arhdnA anayraH hsedarP lahcamiH TU rimhsaK & ummaJ alareK rupinaM ayalahgeM dnalagaN bajnuP nahtsajaR anagnaleT dnahkarattU H1:2024-25 Q1:2025-26 Q2:2025-26 Chart 17: Gross Fiscal Deficit and Quality of Expenditure a. Centre b. States (Per cent, left scale; ratio, right scale) (Per cent, left scale; ratio, right scale) 45 6 50 12 40 45 5 10 35 4.6 40 8.9 30 4 35 8 25 3.0 30 6.6 20 17.9 18.6 3 25 23.5 6 20 15 2 14.1 4 15 10 1 10 5 2 5 0 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 0 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 2023-24 2024-25 2025-26 2023-24 2024-25 2025-26 GFD asper cent ofBE RECO Ratio GFD asper cent ofBE RECO Ratio Sources: CGA; CAG; and Budget documents of the Centre and States. 29 A lower RECO ratio implies improvement in the quality of expenditure for the government.ARTICLE Government Finances 2025-26: A Half-Yearly Review in capital expenditure, resulted in an uptick of V. Conclusion GFD. However, in Q2:2025-26, the GFD as percent During H1:2025-26, moderation in tax receipts of GDP moderated on a y-o-y basis, primarily was partially offset by robust non-tax revenue as attributable to the containment of revenue well as non-debt capital receipts of the Centre. expenditure (Chart 18). Overall, the Centre has collected almost half Chart 18: General Government Gross Fiscal Deficit of its budgeted revenue in H1:2025-26 while (Per cent of GDP) containing its expenditure to less than half of the 12 budget estimates for 2025-26. This augurs well for 10 the Centre to meet its GFD target of 4.4 per cent of GDP for 2025-26. In the case of States, their GFD as a 8 per cent of BE during H1:2025-26 was only marginally 6 5.0 higher than that of H1:2024-25 mainly attributable to lower growth in their revenue receipts. On 4 3.6 the expenditure front, the States sustained their 2 revenue expenditure while maintaining capex. 0 Going forward, States need to maintain their capex Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 momentum alongside fiscal consolidation to ensure 2023-24 2024-25 2025-26 overall stability. Note: For all the quarters depicted in the chart, the combined GFD-GDP ratio is for Centre plus 23 States. Source: RBI staff estimates. 76 RBI Bulletin December 2025Government Finances 2025-26: A Half-Yearly Review ARTICLE Appendix Tables Table I: Budgetary Position of the Central Government during April-September Item (₹ thousand crore) (Per cent) Actuals: H1 Budget Estimates (BE) Per cent of BE Y-o-Y Growth 2024-25 2025-26 2024-25 2025-26 2024-25 2025-26 2024-25 2025-26 (1) (2) (3) (4) (5) (6) (7) (8) (9) 1. Revenue Receipts 1,622.4 1,695.4 3,129.2 3,420.4 51.8 49.6 16.1 4.5 (i) Net Tax Revenue 1,265.2 1,229.4 2,583.5 2,837.4 49.0 43.3 9.0 -2.8 (ii) Non-Tax Revenue 357.2 466.1 545.7 583.0 65.5 79.9 50.9 30.5 (iii) Interest Receipts 20.4 18.0 38.2 47.7 53.3 37.7 17.6 -11.5 2. Non-Debt Capital Receipts 14.6 34.8 78.0 76.0 18.7 45.8 -27.6 138.1 (i) Recovery of Loans 11.4 11.4 28.0 29.0 40.8 39.1 -13.5 -0.7 (ii) Miscellaneous Capital Receipts 3.2 23.4 50.0 47.0 6.3 49.8 -54.4 639.4 3. Total Receipts (1+2) 1,637.0 1,730.2 3,207.2 3,496.4 51.0 49.5 15.5 5.7 4. Revenue Expenditure 1,696.5 1,722.6 3,709.4 3,944.3 45.7 43.7 4.2 1.5 (i) Interest Payments 515.0 578.2 1,162.9 1,276.3 44.3 45.3 6.3 12.3 5. Capital Expenditure 415.0 580.7 1,111.1 1,121.1 37.3 51.8 -15.4 40.0 (i) Loans and Advances 55.4 118.9 192.4 225.8 28.8 52.6 -25.9 114.6 (ii) Capital Outlay 359.6 461.9 918.7 895.2 39.1 51.6 -13.5 28.5 6. Total Expenditure (4 + 5) 2,111.5 2,303.3 4,820.5 5,065.3 43.8 45.5 -0.4 9.1 7. Revenue Deficit (4 - 1) 74.2 27.1 580.2 523.8 12.8 5.2 -68.0 -63.4 8. Fiscal Deficit (6 - 3) 474.5 573.1 1,613.3 1,568.9 29.4 36.5 -32.4 20.8 9. Gross Primary Deficit {8 - 4(i)} -40.5 -5.1 450.4 292.6 -9.0 -1.7 -118.6 87.5 Note: Negative primary deficit indicates primary surplus. Sources: Controller General of Accounts; and Union Budget Documents. RBI Bulletin December 2025 77ARTICLE Government Finances 2025-26: A Half-Yearly Review Table II: Quarterly Position of the Central Government Finances Item (₹ thousand crore) (Per cent) Actuals Per cent of Budget Estimates Y-o-Y Growth Q1 Q2 Q1 Q2 2025-26 2024-25 2025-26 2024-25 2025-26 2024-25 2025-26 2024-25 2025-26 Q1 Q2 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) 1. Revenue Receipts 829.7 913.4 792.7 782.1 26.5 26.7 25.3 22.9 10.1 -1.3 (i) Net Tax Revenue 549.6 540.3 715.5 689.1 21.3 19.0 27.7 24.3 -1.7 -3.7 (ii) Non-Tax Revenue 280.0 373.1 77.2 93.0 51.3 64.0 14.1 16.0 33.2 20.5 (iii) Interest Receipts 11.7 9.7 8.6 8.3 30.6 20.3 22.6 17.4 -17.2 -3.8 2. Non-Debt Capital Receipts 4.5 28.0 10.1 6.8 5.8 36.9 12.9 8.9 519.9 -33.0 (i) Recovery of Loans 4.5 5.4 6.9 6.0 16.1 18.6 24.7 20.5 19.5 -13.9 (ii) Miscellaneous Capital Receipts 0.0 22.6 3.2 0.8 0.0 48.1 6.3 1.7 5,65,475.0 -74.9 3. Total Receipts (1+2) 834.2 941.4 802.8 788.8 26.0 26.9 25.0 22.6 12.9 -1.7 4. Revenue Expenditure 788.9 947.0 907.7 775.6 21.3 24.0 24.5 19.7 20.0 -14.6 (i) Interest Payments 264.1 386.0 251.0 192.1 22.7 30.2 21.6 15.1 46.2 -23.4 5. Capital Expenditure 181.1 275.1 233.9 305.6 16.3 24.5 21.1 27.3 52.0 30.7 (i) Loans and Advances 30.0 69.8 25.4 49.0 15.6 30.9 13.2 21.7 132.7 93.2 (ii) Capital Outlay 151.0 205.3 208.5 256.6 16.4 22.9 22.7 28.7 35.9 23.0 6. Total Expenditure (4 + 5) 969.9 1,222.1 1,141.6 1081.2 20.1 24.1 23.7 21.3 26.0 -5.3 7. Revenue Deficit (4 - 1) -40.8 33.6 115.0 -6.5 -7.0 6.4 19.8 -1.2 182.4 -105.6 8. Fiscal Deficit (6 - 3) 135.7 280.7 338.8 292.4 8.4 17.9 21.0 18.6 106.9 -13.7 9. Gross Primary Deficit {8 - 4(i)} -128.3 -105.3 87.8 100.2 -28.5 -36.0 19.5 34.3 17.9 14.1 Note: Negative revenue deficit and primary deficit indicate revenue surplus and primary surplus, respectively. Sources: Controller General of Accounts; and Union Budget Documents. 78 RBI Bulletin December 2025Government Finances 2025-26: A Half-Yearly Review ARTICLE Table III: Budgetary Position of the State Governments during April-September 2025 Item (₹ thousand crore) (Per cent) Actuals: H1 Budget Estimates Per cent of BE Y-o-Y Growth 2024-25 2025-26 2024-25 2025-26 2024-25 2025-26 2024-25 2025-26 (1) (2) (3) (4) (5) (6) (7) (8) (9) 1. Revenue Receipts 1,682.8 1,788.5 4,231.3 4,636.0 39.8 38.6 7.2 6.3 1.1. Tax Revenue 1,395.3 1,523.6 3,244.7 3,605.8 43.0 42.3 12.1 9.2 1.2. Non-Tax Revenue 123.3 133.7 372.1 411.1 33.1 32.5 -7.5 8.4 1.3. Grants-in-aid and Contributions 164.2 131.3 614.6 619.1 26.7 21.2 -14.2 -20.1 2. Non-Debt Capital Receipts 2.8 6.0 43.7 48.9 6.3 12.2 -30.9 116.6 2.1. Recovery of Loans and Advances 2.7 5.9 20.6 24.0 13.1 24.7 -26.0 119.9 2.2. Other Miscellaneous Capital 0.1 0.0 23.1 24.9 0.3 0.2 -82.1 -27.9 Receipts 3. Total Receipts 1,685.6 1,794.5 4,275.1 4,684.9 39.4 38.3 7.1 6.5 4. Revenue Expenditure 1,780.1 1,925.8 4,326.4 4,740.2 41.1 40.6 10.0 8.2 4.1 Interest Payments 230.6 257.9 527.8 586.1 43.7 44.0 11.8 11.8 5. Capital Expenditure 269.9 284.7 931.3 1,051.4 29.0 27.1 -3.7 5.5 5.1 Capital Outlay 233.9 255.4 850.9 972.2 27.5 26.3 -8.7 9.2 6. Total Expenditure 2,050.1 2,210.5 5,257.7 5,791.6 39.0 38.2 7.9 7.8 7. Revenue Deficit (4-1) 97.3 137.3 95.0 104.2 102.4 131.7 98.2 41.0 8. Fiscal Deficit (6-3) 364.5 416.0 982.6 1,106.7 37.1 37.6 12.1 14.1 9. Gross Primary Deficit (8 - 4.1) 133.9 158.1 454.8 520.6 29.4 30.4 12.4 18.1 Note: Data Pertains to 23 States. Source: Comptroller and Auditor General of India. RBI Bulletin December 2025 79ARTICLE Government Finances 2025-26: A Half-Yearly Review Table IV: Quarterly Position of State Government Finances Item (₹ thousand crore) (Per cent) Actuals Per cent of BE Y-o-Y Growth Q1 Q2 Q1 Q2 2025-26 2024-25 2025-26 2024-25 2025-26 2024-25 2025-26 2024-25 2025-26 Q1 Q2 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) 1. Revenue Receipts 820.4 874.3 862.4 914.2 19.4 18.9 20.4 19.7 6.6 6.0 1.1. Tax Revenue 701.2 752.5 694.0 771.0 21.6 20.9 21.4 21.4 7.3 11.1 1.2. Non-Tax Revenue 62.2 64.9 61.1 68.8 16.7 15.8 16.4 16.7 4.4 12.5 1.3. Grants-in-aid and Contributions 57.0 56.8 107.2 74.5 9.3 9.2 17.4 12.0 -0.4 -30.5 2. Non-Debt Capital Receipts 1.4 3.1 1.4 2.9 3.1 6.3 3.2 5.9 127.5 106.0 2.1. Recovery of Loans and Advances 1.3 3.1 1.4 2.9 6.4 12.7 6.6 11.9 130.4 109.8 2.2. Other Miscellaneous Capital 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 -6.8 -45.6 Receipts 3. Total Receipts 821.8 877.4 863.8 917.1 19.2 18.7 20.2 19.6 6.8 6.2 4. Revenue Expenditure 827.1 916.8 953.0 1,009.0 19.1 19.3 22.0 21.3 10.8 5.9 4.1 Interest Payments 101.0 106.3 129.7 151.5 19.1 18.1 24.6 25.9 5.3 16.9 5. Capital Expenditure 95.7 116.8 174.3 167.9 10.3 11.1 18.7 16.0 22.1 -3.6 5.1. Capital Outlay 82.6 103.5 151.3 151.8 9.7 10.6 17.8 15.6 25.3 0.3 6. Total Expenditure 922.8 1,033.6 1127.3 1,176.9 17.6 17.8 21.4 20.3 12.0 4.4 7. Revenue Deficit 6.7 42.5 90.7 94.8 7.0 40.8 95.4 91.0 537.4 4.5 8. Fiscal Deficit (6-3) 101.0 156.2 263.5 259.8 10.3 14.1 26.8 23.5 54.7 -1.4 9. Gross Primary Deficit (8 - 4.1) 0.0 49.9 133.9 108.3 0.0 9.6 29.4 20.8 - -19.1 Note: Data pertains to 23 States. Source: Comptroller and Auditor General of India. 80 RBI Bulletin December 2025Composite Leading Indicator for GVA-Manufacturing for India ARTICLE Composite Leading Indicator for refinements of Stock and Watson (1989). Subsequent research by Moore (1982) and Zarnowitz & Boschan GVA-Manufacturing for India (1975) underscored the importance of cyclical synchronisation across economic indicators, setting by Anirban Sanyal, Shivangee Misra and the stage for systematic development of leading Sanjay Singh^ business cycle indicators across advanced and emerging economies. International experience This paper develops a quarterly Composite highlights considerable heterogeneity: in Italy, Leading Indicator (CLI) for GVA–Manufacturing monetary and financial variables have been found using a two-stage procedure that combines systematic to lead domestic cycles by 12–16 months, with variable selection with subsequent aggregation. The international cycles exhibiting a high degree of co- indicator set—comprising commodity prices, survey- movement (Altissimo et al., 2000); for Turkey, a based expectations, industrial credit flows, and global leading indicator index was constructed from nine variables—is identified through multiple validation key economic series spanning imports, monetary techniques and then incorporated into machine-learning aggregates, and fiscal expenditures (Murutoglu, models, notably Random Forest and XGBoost. The 1999). Many such indicators draw on business and resulting CLI exhibits a stronger leading property, consumer survey data, with evidence—such as yielding a cross-correlation of 0.86 at a one-quarter lead, Finland’s industry survey—demonstrating strong compared with 0.72 contemporaneously. Its turning correlations between forward-looking expectations points consistently precede those of manufacturing GVA and subsequent industrial production (Penna Urrila, by one quarter, highlighting its usefulness for short-term 2001). Collectively, composite leading indicators monitoring and forecasting. have proven useful in anticipating turning points in Introduction reference series, thereby strengthening short-term forecasting and policy assessment (Altissimo et al., Business cycle leading indicators are a vital 2000; Murutoglu, 1999). component of macroeconomic surveillance, offering timely insights into emerging shifts in economic In the Indian context, Roy and Biswas (2012) momentum. In particular, the leading business cycle developed a composite leading indicator (CLI) for the indicators enable the identification of prospective Index of Industrial Production (IIP), employing both turning points in the business cycle of the reference growth-cycle and growth-rate-cycle approaches to series, thereby providing early signals on evolving track turning points in overall industrial activity. That economic conditions. Against this backdrop, this indicator, constructed for the 2004–05 base, served article introduces a new leading indicator designed to as a timely gauge of cyclical dynamics of industrial track the real gross value added (GVA) growth of the growth in India at the time. Since then, however, manufacturing sector in India. the role of IIP in national accounts has diminished, and the index itself has undergone a base revision to Business cycle analysis has a long intellectual 2011–12. Given the centrality of the manufacturing lineage, tracing its roots to the seminal contributions sector in gross value added (GVA) and the need for of Burns and Mitchell (1946) and the later empirical more robust high-frequency cyclical assessment, this ^ The authors are from the Department of Statistics and Information article proposes a composite leading indicator for Management. The views expressed in the article are of the authors and do not represent the views of the Reserve Bank of India.. GVA-manufacturing at a quarterly frequency. RBI Bulletin December 2025 81ARTICLE Composite Leading Indicator for GVA-Manufacturing for India The construction of the CLI for GVA– supports forward-looking decision-making. As such, manufacturing in this study follows a structured the leading indicator provides policymakers, financial two-step framework, supported by a range of cross- analysts, investors, and firms with a systematic means validation techniques. In the first stage, potential of anticipating shifts in macroeconomic momentum. leading variables are identified on the basis of When used in conjunction with the coincident their signal strength vis-à-vis the reference series, index, the leading economic indicator enhances the complemented by a machine-learning-based kitchen- monitoring architecture for the Indian economy sink approach to further refine the selection. The and delivers early warning signals of prospective cyclical characteristics of the shortlisted indicators are expansions or contractions in activity (Dua and subsequently examined through wavelet analysis to Banerji, 1999). ensure robustness of their leading properties. In the The analytical foundations of this approach trace second stage, these selected variables are combined back to Mintz’s (1969, 1972 and 1974) development of using multiple aggregation methods to derive the the growth-cycle methodology for identifying cyclical composite indicator. The resulting CLI encompasses turning points. Earlier work by Burns and Mitchell indicators reflecting cost pressures, external demand, (1967) established the empirical significance of policy uncertainty, and credit flows to industry, and coincident and leading indicators for business-cycle the proposed CLI exhibits a lead of one quarter over analysis. Building on these contributions, Klein and the growth rate cycle of GVA manufacturing. Moore (1985) advanced the study of economic cycles Rest of the article is organised as follows – at the National Bureau of Economic Research, setting Section II provides background and current practice the precedent for modern indicator-based monitoring of CLI. The empirical framework is noted in Section systems. III. Section IV documents the data sources and Among the existing studies for India, Chitre frequency. Empirical findings are listed in Section (1982) documents substantial synchronicity among V. Within empirical findings, the variables selected a wide range of Indian macroeconomic indicators through various approaches are mentioned, followed around their long-run trends using a growth-cycle by the findings of the wavelet analysis. Later, CLI framework. His analysis spans non-agricultural net is constructed using the selected variables through national product, industrial output, capital formation, various aggregation approaches. The validation of monetary aggregates, and bank credit, among others, the leading property of each CLI is assessed through from which fifteen variables were ultimately selected turning point analysis. Lastly, the findings are to construct a composite index intended to proxy summarised in the concluding remarks in Section VI. aggregate economic activity. The study identifies II. Literature Review and Current Practice of five distinct growth cycles for the Indian economy Composite Leading Indicator between 1951 and 1975. Using annual data from The construction of the leading indicator is 1950 to 1985, Hatekar (1993) similarly identifies guided by the requirement that it attain its turning turning points in major macroeconomic aggregates points—both peaks and troughs—ahead of the and examines their comovement patterns within a coincident index, which captures contemporaneous growth-cycle perspective. Dua and Banerji (1999), economic conditions. This property underpins its applying the traditional NBER methodology, derived usefulness in forecasting near-term fluctuations and both classical business cycles and growth-rate 82 RBI Bulletin December 2025Composite Leading Indicator for GVA-Manufacturing for India ARTICLE cycles for India and develop a composite leading aggregated to derive CLI in the phase 2. The variable index drawing on indicators from the monetary, selection is carried out through signal extractions construction, and corporate sectors. Expanding the where the leading property of each variable is tested empirical base, Chitre (2001) analyzes 94 monthly individually and in a collective manner. The signal series for 1951–1982, and derived a reference cycle strength of each HFI is validated using cross correlation from eleven indicators using diffusion indexes, analysis, regression estimates using ordinary composite indexes, and principal components least squares (OLS), quantile regression, mutual methods. information criteria and dynamic time warping (DTW). This paper is closely related to Roy and Biswas Using the kitchen sink approach the information (2012) which proposes a CLI for the Index of on the leading properties of multiple indicators is Industrial Production using eight high-frequency assessed through recursive feature eliminations indicators (HFIs) (Table 1). To account for differences (RFE) with k-nearest neighbour (k-NN), random forest in scale across the HFIs and the IIP, the authors apply and XGBoost approach. Further, different sets of HFIs a cumulative density function transformation prior are generated from the common variables selected to aggregation. Lead–lag relationships are assessed by various methods. Lastly, HFIs having high wavelet through cross-correlation analysis between each coherence are selected as additional group of the candidate series and the reference series. Following selected variables. Additionally, indicators appearing indicator selection, the target series (IIP) is regressed in at least one criteria are taken together as separate on lagged values of the individual indicators; the sets of variables through various combinations to resulting adjusted R2 values—interpreted as the share improve the information contents. A brief discussion of variation in the target explained by each indicator of the methods used for variable selection is provided and its lags—serve as a metric of leading performance. in Annex I. These adjusted R2 values are subsequently employed The aggregation of the selected indicators is as weights in the construction of the composite index. conducted through various methods, namely, simple III. Empirical Framework average, weighted average with various choices of The CLI for GVA-Manufacturing, proposed in this weights and dynamic factor models (DFMs). The article has been constructed in two phases. In the first weighted average approach is developed using inverse phase, the HFIs are selected using various variable standard deviations and correlation as weights. selection methods. The selected indicators are DFM is employed to extract the common signal strength from the selected variables. Lastly, the CLI Table 1: Indicators Used in CLI for Industry is smoothened using HP filter to remove the irregular Sr. No. Indicator Weight variations in the data. The lambda value in the HP 1 Commercial Motor Vehicle Production 11.4 filter (lambda=4) is selected based on the cross- 2 Dollar/Rupee Exchange Rate (Monthly Average) 13.3 3 Monetary Aggregate M1 19.7 validation technique used by Grehmann and Yetman 4 Non-Oil Imports 10.8 (2018). Lastly, the performance of the proposed CLI 5 Railway Freight 6.3 is carried out using cross-correlation, coherence and 6 BSE SENSEX Index 15.8 turn-around point analysis proposed by Bry and 7 Steel Production 18.0 Boschan (1971) and later, modified for quarterly data 8 CP Spread 4.8 Source: Roy and Biswas (2012). by Harding & Pagan (2012). RBI Bulletin December 2025 83ARTICLE Composite Leading Indicator for GVA-Manufacturing for India IV. Data Used Table 2: Cross Correlation Estimates of GVA- The high frequency economic indicators which Manufacturing Growth with Top 10 HFIs are likely to influence the economic activities with Variable Pearson Kendall Spearman IMF Crude Oil Price (-2) -0.48 -0.40 -0.53 a lead period, are selected from major dimensions, IMF industrial Input (-2) -0.50 -0.39 -0.56 namely, i) Domestic demand condition; ii) Domestic IMF All Commodity Price (-2) -0.48 -0.38 -0.53 industrial production; iii) Domestic price conditions; IMF All (Excl. Gold) Commodity Price (-2) -0.48 -0.38 -0.54 iv) Foreign trade; v) Employment condition; (vi) Trade, Non-oil exports (-1) 0.49 0.38 0.54 transport and other services indicators; (vii) Public Real Credit to Industry (-2) 0.47 0.37 0.51 IMF Metal Prices (-2) -0.41 -0.37 -0.49 finance and payment Indicators; (viii) Exchange rate; Merchandize Imports (-2) -0.44 -0.35 -0.52 (ix) Global commodity price; (x) Policy uncertainty; (xi) US Non-farm Payroll Employment SA (-1) 0.34 0.43 0.57 Forward looking survey – Industrial Outlook Survey WPI Industrial Raw Material (-2) -0.42 -0.33 -0.45 and PMI Manufacturing; (xiii) Cost of borrowing Note: The number indicated in the parentheses indicate the lags of the variables, measured in quarters. proxy; and (xiv) Global economic indicators. The Source: Authors’ calculation. variables are transformed into year-on-year (y-o-y) growth except for the borrowing cost (i.e. interest sector with a lag of one quarter. Among the global rate) proxy, policy uncertainty and exchange rate. variables, US non-farm payroll employment has The interest rate proxies, and policy uncertainties are positive correlation with GVA manufacturing with used in level values. Exchange rates are transformed one quarter lead (Table 2). into quarter-on-quarter (q-o-q) annualized growth The variable selection using regression estimates rate. The detailed list of the HFIs considered within is carried out using OLS regression and quantile each segment is provided in Annex II. regression (for median). The regression includes the The data used for this analysis spans from April lagged value of GVA - manufacturing as additional 2013 to December 2024. As the reference series (i.e., regressor to knock out any time persistent effects in GVA-manufacturing) is available at quarterly interval, the data generating process of GVA - manufacturing. the variable selection is carried out at quarterly The regression coefficient attached to the HFI is frequency and the CLI is also calculated at quarterly extracted if the coefficient estimate is statistically frequency. significant at 10 per cent level of significance.1 V . Empirical Findings The regression estimates show similar effects of commodity prices on GVA – manufacturing V.1 Variable Selection growth. Railway freight and petroleum consumption The correlation analysis of the HFIs show very appear to have significant positive relation with high negative correlation of global commodity prices GVA - manufacturing. Non-food credit and real with GVA manufacturing. Within commodity prices, credit to industry also improves the manufacturing crude oil prices affect the manufacturing growth growth with a lead of 2 quarters. The borrowing with lag of 1 – 2 quarters. IMF all commodity prices cost proxy, namely, G-Sec 10-year yield and treasury (excluding gold) also drags manufacturing growth with bill rate increases the borrowing burden and a lag of 1 - 2 quarters. Merchandise imports moderate manufacturing growth in 1-2 quarter lag, while non- 1 The standard errors of the quantile regression are asymptotic standard oil exports improve growth in the manufacturing error. 84 RBI Bulletin December 2025Composite Leading Indicator for GVA-Manufacturing for India ARTICLE Table 3: Regression Coefficients of GVA - Table 4: Variables Selected in Other Criteria Manufacturing with HFIs Variable Cosine DTW MI Variable OLS Quantile Backlogs of Work(-2) 1 0 0 Regression Regression IOS Cost of Raw Material Expectation (-1) 0 1 0 (Median) IOS Cost of Raw Material Expectation (-2) 0 1 0 Indian Basket Crude Oil Price (-1) -1.40 -0.54 Indian Basket Crude Oil Price (-2) 0 0 1 WPI Manufacturing (-1) -1.03 -0.45 CU (-1) 1 1 0 Railway Freight Traffic (-2) 1.03 0.31 CU (-2) 0 1 0 Petroleum Consumption (-1) 0.86 0.26 PMI Employment (-1) 0 0 1 Real Credit to Industry (-2) 0.67 0.23 PMI Employment(-2) 1 0 0 Real Non-food Credit (-2) 0.62 0.22 PMI Future Output_(-1) 0 1 0 G-Sec 10 Yrs Yield (-2) -0.98 -1.10 PMI Future Output(-2) 1 1 0 G-sec 10Yrs Yield (-1) 1 0 0 T-Bill 91 Days Rate (-1) -1.05 -0.94 G-sec 10Yrs Yield (-2) 1 0 0 WPI Headline (-1) 0.64 -0.29 IMF Industrial Input (-1) 0 0 1 Merchandize Imports (-2) -0.43 -0.48 IMF Industrial Input (-2) 0 0 1 Note: The number indicated in the parentheses indicate the lags PMI Input Prices (-1) 0 1 0 of the variables, measured in quarters. Source: Authors’ calculation. PMI Input Prices (-2) 0 1 0 PMI New Export Orders (-2) 1 1 0 thereby, moderates the manufacturing growth. PMI New Orders (-1) 1 1 0 PMI New Orders (-2) 0 1 0 Merchandise imports also moderate the PMI Output Prices (-2) 1 0 0 manufacturing growth (Table 3). PMI Output (-1) 1 1 0 PMI Output (-2) 0 1 0 Lastly, the variable selection using mutual Petroleum Consumption (-1) 0 0 1 information, cosine similarity and (L1 and L2) PMI Index (-1) 1 1 0 PMI Index (-2) 1 1 0 distance measure2 filters capacity utilization, outlook Railway Freight Traffic (-2) 0 0 1 of raw material cost, PMI manufacturing index and its Real Non-food Credit (-1) 0 0 1 components, trade - transport indicators, borrowing Real Non-food Credit(-2) 0 0 1 UPI Payments (-1) 0 1 0 cost proxy and commodity prices (Table 4). UPI Payments (-2) 0 1 0 The variables selected from the signal strength WPI Headline (-1) 0 0 1 WPI Headline (-2) 0 0 1 of the individual HFIs ignores the interactions among WPI Manufactured Products (-1) 0 0 1 HFIs. For that, all variables are used simultaneously WPI Manufactured Products (-2) 0 0 1 in a single framework (with different lags) to identify Note: 1. ‘0’ indicates not selected and 1 stands for selected. 2. The number indicated in the parentheses indicate the the suitable variables. This kitchen-sink approach lags of the variables. Source: Authors’ calculations. uses three broad methods to identify the important variables – recursive feature elimination (RFE), random economic indicators and borrowing cost proxies are forest (RF) and XGBoost. Apart from the commodity also filtered (Table 5). prices, global indicators and policy uncertainties are V.2 Cross Validation of the Business Cycle Properties selected as leading variables of GVA - manufacturing of Selected HFI growth. Real non-food credit and credit to industry Combining the variables selected through are selected in RFE and Random Forest. The domestic various methods provides a comprehensive list of 2 L1 (or Manhattan) distance is the absolute deviation between two HFIs having some leading information about GVA- vectors whereas L2 (or Mahalanobis) distance is the square root of the sum of square deviation between two vectors. manufacturing growth. The information content of RBI Bulletin December 2025 85ARTICLE Composite Leading Indicator for GVA-Manufacturing for India Table 5: Variables Selected in RFE, RF and XGBoost Table 6: Coherence from Cross Wavelet Analysis Variables Lead in Quarters Series Coherence Coherence Period Method = RFE (in quarters) US Non-farm Payroll Employment (SA) 1 Eight Core: Overall 2 0.78 International Air Passenger Traffic 2 Merchandise Export 2 0.75 European EPU 2 IIP Intermediate goods 2 0.73 Real Non-food Credit 1 IIP Primary goods 2 0.73 IOS Cost of Raw Material (Expectation) 1 US Non-farm Payroll (SA) 2 0.68 T-Bill 91 Days Yield 2 IIP Infrastructure/ construction goods 2 0.64 IMF All (Excl. Gold) Commodity Prices 1 Indian Basket Crude Oil Price 2 0.59 Method = Random Forest Cement Production 2 0.59 Real Credit to Industry 1 WPI IRM 2 0.59 Global EPU 1 US IIP 2 0.59 Cement Production 1 Source: Authors’ calculations G-Sec 10 Years Yield 2 farm payroll, Indian basket crude oil price, cement USA EPU 1 WPI Headline 2 production and US IIP (Table 6). Commercial Motor Vehicle Sales 1 The wavelet coherence plot also confirms the India EPU 1 leading property of these indicators with GVA- Method = XGBoost manufacturing in 1-2 quarter lead. This common set International Cargo Traffic 1 Global EPU 1 of indicators having high coherence, are also selected WCMR 1 as separate set of variables (along with various other Exports to Emerging and Developing Asia 2 subsets of variables from the previous selections) Domestic Air Passenger Traffic 1 in the variable selection set (Annex III). A short WPI Manufacturing 1 description of interpretation of the wavelet charts is High Speed Diesel 1 provided in Annex IV. US Non-farm Payroll Data 1 IIP Consumer Durables 1 a. Composite Leading Indicator IIP Consumer Non-durables 1 Source: Authors’ calculations The CLI is constructed using the selected HFIs from different methods. For each selection of HFI, the selected HFIs is verified using wavelet analysis. CLI is constructed using simple average, weighted The cross-wavelet analysis provides the degree of average and DFM. Following this approach, 48 coherence between the HFIs and the benchmark different CLI are constructed and the performance series (i.e., GVA-manufacturing).3 of each CLI is validated using cross-correlation and The wavelet coherence estimates shows that turnaround point analysis for quarterly data. The GVA manufacturing growth shows high coherence cross-correlation is checked with lead of 1 quarter and with eight core industries, merchandise exports, IIP 2 quarters. The cross-correlation results shows that use-based classifications, employment from US Non- variables selected from Random Forest - XGBoost and combined using inverse standard deviation weights, 3 Here, the leading property is not directly sought from the cross- spectrum due to limitation of the length of time series data. The data used provide the highest tracking at 1-2 quarter lead. CLI for this analysis, spans from Q1: 2013-14 till Q3: 2024-25 which includes from random forest also provide a better tracking than disruptions due to COVID pandemic. The lack of business cycle coverage in the selected data, may lead to overfitting of wavelets and may lead to others (Table 7). The detailed list of cross-correlation biased estimate of phase difference. Hence, the coherence measure is used in this context. estimates is provided in Annex V. 86 RBI Bulletin December 2025Composite Leading Indicator for GVA-Manufacturing for India ARTICLE Table 7: Cross Correlation of Selected CLIs with GVA Manufacturing Variable Selection CLI Construction Lag = 1 Lag = 2 Full Sample Excluding COVID Full Sample Excluding COVID RF-XG Boost Simple Average 0.39 0.29 0.16 0.37 RF-XG Boost Weighted Average - SD 0.86 0.85 0.59 0.71 RF-XG Boost Weighted Average - Correlation 0.40 0.23 0.17 0.31 RF-XG Boost Dynamic Factor Model (2) factors) 0.27 0.39 0.00 0.42 RF-XG Boost Dynamic Factor Model (1) factor) 0.46 0.05 0.16 0.09 RF Simple Average 0.62 0.64 0.34 0.61 RF Weighted Average - SD 0.74 0.78 0.61 0.73 RF Weighted Average - Correlation 0.59 0.66 0.28 0.61 RF Dynamic Factor Model (2) factors) 0.07 0.34 0.29 0.32 RF Dynamic Factor Model (1) factor) 0.07 0.51 0.26 0.50 RF-Spearman Simple Average 0.64 0.77 0.54 0.74 RF-Spearman Weighted Average - SD 0.56 0.73 0.64 0.68 RF-Spearman Weighted Average - Correlation 0.58 0.76 0.50 0.75 RF-Spearman Dynamic Factor Model (2) factors) 0.06 0.52 0.24 0.50 RF-Spearman Dynamic Factor Model (1) factor) 0.05 0.48 0.28 0.49 RF-Quantile Simple Average 0.66 0.69 0.39 0.65 RF-Quantile Weighted Average - SD 0.66 0.75 0.69 0.67 RF-Quantile Weighted Average - Correlation 0.70 0.72 0.44 0.69 RF-Quantile Dynamic Factor Model (2) factors) 0.07 0.32 0.24 0.24 RF-Quantile Dynamic Factor Model (1) factor) 0.08 0.54 0.23 0.47 Coherence Simple Average 0.46 0.68 0.51 0.65 Coherence Weighted Average - SD 0.49 0.68 0.55 0.61 Coherence Weighted Average - Correlation 0.39 0.66 0.48 0.63 Coherence Dynamic Factor Model (2) factors) 0.12 0.51 0.32 0.54 Coherence Dynamic Factor Model (1) factor) 0.08 0.47 0.32 0.50 Note: • Highlighted cells have correlation higher than 50 per cent. • The numbers within parentheses indicate number of factors used in DFM. Source: Authors’ calculations Next, the turnaround point analysis was carried economic disruption during COVID pandemic led to out on the proposed CLI and the reference series using broad based slowdown in Indian economy followed Harding & Pagan (2002) approach. The turnaround by a gradual recovery. The extent of recovery varied points of CLI are mapped with the reference series across segments which weakened the leading property to track the leading property. CLI based on Random of CLI during the recent pandemic period (Chart 1). Forest with XGBoost has one quarter lead, whereas the Random Forest has lead of average one to two Following the derivation, CLI is proposed using quarters (Table 8). variables selected from Random Forest - XGBoost criteria and aggregating those using inverse standard Lastly, the time series plot of the proposed CLI and reference series establish the leading properties deviation as weights. The selected variables are listed of the CLI visually except for the COVID period. The in Table 9. RBI Bulletin December 2025 87ARTICLE Composite Leading Indicator for GVA-Manufacturing for India Table 8: Leading property of CLI Variable Selection CLI Construction Peak Trough Random Forest - XGBoost Weighted Average - SD 2015.50 2016.75 Random Forest - XGBoost Weighted Average - SD 2017.75 2020.00 Random Forest - XGBoost Weighted Average - SD 2021.25 2022.25 Random Forest - XGBoost Weighted Average - SD 2023.50 Random Forest Weighted Average - SD 2015.25 2017.00 Random Forest Weighted Average - SD 2018.00 2019.00 Random Forest Weighted Average - SD 2021.25 2022.25 Random Forest Weighted Average - SD 2023.50 Reference Series Reference Series GVA Manufacturing 2015.75 2017.25 GVA Manufacturing 2018.00 2020.00 GVA Manufacturing 2021.25 2022.50 GVA Manufacturing 2023.75 Note: 1. Green shaded CLI is the proposed one and white shaded CLI is the next best one. 2. The timeline of peaks and troughs are provided in fractions. YYYY.00 represents Q1 of year YYYY, YY.25 is Q2 of YYYY, YY.50 is Q3 of YYYY and YY.75 is for Q4 of YYYY. All years are financial years. Source: Authors’ calculations. It may be mentioned that the business cycle which typically last between 5 to 10 years (OECD, exhibits long-term pattern which evolves over time. 2008; Canova, 1998). A longer time series also helps For business cycle analysis using quarterly data, in improving the reliability of statistical methods used it is generally recommended to have a time series in trend-cycle decomposition, filtering techniques length of at least 30 to 50 years (i.e., 120 to 200 (e.g., HP filter), and econometric modelling. In quarterly observations). This duration allows for the this analysis, 12 years data is used for deriving the identification of multiple complete business cycles, leading indicator of GVA-manufacturing which is Chart 1: CLI and Reference Series a. Using Random Forest – XG Boost b. Using Random Forest with Inv. with Inv. SD weights (Proposed) SD weights (Second Best) (Scaled Values using CDF transformation) (Scaled Values using CDF transformation) 1.1 0.9 0.7 0.5 0.3 0.1 -0.1 Target RF-XG Boost_SD Target RF_SD Sources: : Authors’ calculations. 88 RBI Bulletin December 2025 31-nuJ 41-raM 41-ceD 51-peS 61-nuJ 71-raM 71-ceD 81-peS 91-nuJ 02-raM 02-ceD 12-peS 22-nuJ 32-raM 32-ceD 42-peS 1.1 0.9 0.7 0.5 0.3 0.1 -0.1 31-nuJ 41-nuJ 51-nuJ 61-nuJ 71-nuJ 81-nuJ 91-nuJ 02-nuJ 12-nuJ 22-nuJ 32-nuJ 42-nuJComposite Leading Indicator for GVA-Manufacturing for India ARTICLE Reference Table 9: Variables selected in Random Forest and Mutual Information Altissimo, Filippo, Alessandro Bassanetti, Roberto Cement Production WPI Headline Cristadoro, Mario Forni, Marco Hallin, Marco Lippi, Commercial Motor Vehicle Sales WPI Manufacturing and Giovanni Veronese (2000). A Real Time Coincident IIP Consumer Durable G-Sec 10 Years Yield Indicator of the Euro Area Business Cycle. European IIP Consumer Non-durable WCMR Central Bank Working Paper Series No. 42. Frankfurt: High Speed Diesel IMF All (Excl. Gold) Commodity European Central Bank. Prices International Air Cargo Exports to Emerging and Berndt, D. J., and Clifford, J. (1994). Using Dynamic Developing Asia Time Warping to find patterns in time series. Domestic Air Passenger Traffic US Non-farm Payroll Employment Proceedings of the 3rd International Conference Real Credit to Industry Global EPU on Knowledge Discovery and Data Mining (AAAI India EPU Workshop), 359-370. reasonable but may not be sufficient to study longer Boschan, Charlotte (1975). Cyclical Analysis of Time cycles, particularly due to the presence of COVID-19 Series: Selected Procedures and Computer Programs. led disruptions. The post pandemic data spans National Bureau of Economic Research Technical for two years which is insufficient to understand Paper No. 20. New York: NBER. any changes in the data generating process of the Bry, G., & Boschan, C. (1971). Cyclical analysis of time economic variables. Following the data limitations series: Selected procedures and computer programs. and disruptions due to the COVID pandemic, it is New York: National Bureau of Economic Research. recommended to revisit the construction of CLI at Burns, A. F., and Mitchell, W. C. (1946). Measuring regular interval with better data availability. Business Cycles. National Bureau of Economic VI. C oncluding Remarks Research. This paper proposed a composite leading Canova, F. (1998). Detrending and business cycle indicator for tracking the growth rate cycle of facts. Journal of Monetary Economics, 41(3), 475-512. GVA Manufacturing using various high frequency Chitre, V. S. (1982). Growth Cycles in the Indian indicators. Among the high frequency indicators, Economy. Gokhale Institute of Politics & Economics / commodity prices, use-based classification of IIP, Artha Vijnana, 158 pp. forward looking survey-based indicators, credit Chitre, Vikas (2001). Indicators of Business Recessions disbursed to industry, policy uncertainty and global and Revivals in India: 1951-1982. Indian Economic commodity prices appeared to possess leading Review, 36(1), pp. 79–105. property on GVA manufacturing growth. Cover, T. M., and Thomas, J. A. (2006). Elements of The CLI constructed using random forest and Information Theory (2nd ed.). Wiley. XGBoost exhibits the highest tracking power with Diebold, Francis X., & Rudebusch, Glenn D. (1991). cross correlation of 86 per cent at lag of one quarter Forecasting Output with the Composite Leading (contrary to 72 per cent contemporaneous correlation). Index: A Real-Time Analysis. Journal of the American The turnaround points of the constructed CLI leads Statistical Association, 86(415), 603–610. the GVA-manufacturing turnaround points by one Drehmann, Mathias & Yetman, James (2018). Why You quarter. The leading property of the proposed CLI Should Use the Hodrick-Prescott Filter — At Least to shows robustness in the pre-COVID period and post- Generate Credit Gaps. BIS Working Papers No. 744, pandemic recovery period. Bank for International Settlements. RBI Bulletin December 2025 89ARTICLE Composite Leading Indicator for GVA-Manufacturing for India Dua, Pami & Banerji, Anirvan (1999). An Index of Moore, Geoffrey H. (1982). Business Cycles, Inflation, Coincident Economic Indicators for the Indian and Forecasting. 2nd Edition. National Bureau of Economy. Journal of Quantitative Economics, 15, Economic Research (NBER) Studies in Business 177-201. Cycles, No. 24. Chicago: University of Chicago Press. Greene, W. H. (2012). Econometric Analysis (7th ed.). Penna Urrila, M. (2001). Business cycle asymmetry: Pearson. An application of nonlinear models to the Finnish Grehmann, K., & Yetman, J. (2018). How monetary economy. Bank of Finland Discussion Paper No. policy affects economic conditions: Evidence from 19/2001. cross-country data. BIS Working Paper No. 729. Murutoglu, G. (1999). Business cycles: Persistence, Harding, Don & Pagan, Adrian (2002). Dissecting the asymmetries and international transmission. Cycle: A Methodological Investigation. Journal of Unpublished manuscript, Department of Economics, Monetary Economics, 49(2), 365–381. University of Illinois at Urbana–Champaign. Hatekar, N. H. (1993). The short-term dynamics of money and output in India. Mimeograph, University OECD (2008). OECD System of Composite Leading of Bombay, Bombay. Indicators: A Revised Framework. Organisation for Huang, A. (2008). Similarity measures for text Economic Co-operation and Development. document clustering. Proceedings of the Sixth Roesch, A., & Schmidbauer, H. (2018). WaveletComp: New Zealand Computer Science Research Student computational wavelet analysis. R package version, Conference (NZCSRSC), 49-56. 1(1). Klein, Philip A. & Moore, Geoffrey H. (1985). Roy, I., and Biswas, D. (2012). Construction of a Monitoring Growth Cycles in Market-Oriented composite index of leading indicators for the index of Countries: Developing and Using International industrial production in India. Journal of Quantitative Economic Indicators. Cambridge, MA: Ballinger / Economics, 10(1), 17-31. NBER Studies in Business Cycles. Koenker, R., and Bassett, G. (1978). Regression Stock, J. H., and Watson, M. W. (1989). New indexes quantiles. Econometrica, 46(1), 33-50. of coincident and leading economic indicators. NBER Mintz, Ilse (1961). World Imports and United States Macroeconomics Annual, 4, 351-393. Business Cycles. American Exports during Business Stock, J. H., and Watson, M. W. (1999). Business Cycles, 1879–1958, pp. 35–41. National Bureau of cycle fluctuations in US macroeconomic time series. Economic Research. Handbook of Macroeconomics, 1, 3-64. Mintz, I. (1969). Dating postwar business cycles: Urrila, Penna (2001). Suhdanneindikaattoreiden Methods and their application to Western Germany, käyttö talouskehityksen seurannassa. (Working Paper 1950–1967. New York: National Bureau of Economic No. 780). ETLA — Elinkeinoelämän tutkimuslaitos, Research. Helsinki. Mintz, I. (1972). Dating postwar business cycles: Methods and their application to France, 1949–1967. Zarnowitz, Victor & Moore, Geoffrey H. (1986). Major New York: National Bureau of Economic Research. Changes in Cyclical Behavior, The American Business Mintz, I. (1974). Dating postwar business cycles: Cycle: Continuity and Change, edited by Robert J. Methods and their application to Italy, 1950–1967. Gordon, 519–582. Chicago: University of Chicago New York: National Bureau of Economic Research. Press / National Bureau of Economic Research 90 RBI Bulletin December 2025Composite Leading Indicator for GVA-Manufacturing for India ARTICLE Annex I : Methods used for Variable Selection Cross-Correlation: Cosine Similarity Cross-correlation analysis is a statistical technique Cosine similarity is a metric used to measure used to measure the relationship between two time the similarity between two non-zero vectors by computing the cosine of the angle between them. It series at different lags, helping to identify lead-lag is widely applied in text analysis, machine learning, relationships and synchronicity between variables. and economic research to compare patterns in high- In business cycle analysis, it is often employed to dimensional data. Unlike Euclidean distance, cosine examine how economic indicators move in relation similarity focuses on the direction rather than the to the overall cycle, determining whether they are magnitude of vectors, making it useful for comparing leading, coincident, or lagging indicators (Stock and time series with different scales. In business cycle Watson, 1999). A high cross-correlation at a positive analysis, it can be employed to assess the similarity of lag suggests that one variable tends to lead the economic indicators or compare the cyclical patterns other, while a strong correlation at zero lag indicates of different countries over time. A value close to 1 simultaneous movement. This method is widely used indicates high similarity, while a value near 0 suggests in macroeconomic research to assess the predictive no correlation (Huang, 2008). power of economic indicators and understand Mutual Information transmission mechanisms across sectors. Mutual information (MI) is an information- Regression Analysis theoretic measure that quantifies the dependency between two random variables by capturing both Regression analysis using Ordinary Least linear and nonlinear relationships (Cover and Squares (OLS) is a fundamental statistical method Thomas, 2006). Unlike correlation, which only detects for estimating relationships between dependent and linear dependencies, MI assesses the reduction in independent variables in economic and financial uncertainty about one variable given knowledge of research. OLS minimizes the sum of squared residuals another. In business cycle analysis, MI can be used to derive the best-fitting linear equation, making it to evaluate the strength of associations between widely used for business cycle analysis, forecasting, macroeconomic indicators, such as GDP growth and and policy evaluation (Greene, 2012). inflation, across different economic conditions. Quantile Regression Dynamic Time Warping Quantile regression is an econometric technique Dynamic Time Warping (DTW) is an algorithm used to measure the similarity between two time series that extends traditional Ordinary Least Squares (OLS) by allowing non-linear distortions in the time axis regression by estimating the conditional relationship (Berndt and Clifford, 1994). Unlike traditional distance between variables at different points of the outcome metrics, such as Euclidean distance, DTW aligns distribution (Koenker and Bassett, 1978). Unlike OLS, sequences of different lengths or with temporal shifts which models the mean effect, quantile regression by finding an optimal warping path that minimizes provides a more comprehensive view of the data by the cumulative distance between corresponding capturing heterogeneous effects across quantiles. This points. This makes it particularly useful in business is particularly useful in business cycle analysis, where cycle analysis, where economic indicators may exhibit economic relationships may vary during recessions phase shifts or different speeds of fluctuation across and expansions. countries or industries. RBI Bulletin December 2025 91ARTICLE Composite Leading Indicator for GVA-Manufacturing for India Annex II : List of HFI Considered for CLI IIP Data Exchange Rate IIP Manufacturing REER NEER IIP Headline Index INR - USD Exchange Rate IIP Primary Goods Global Commodity Price IIP Capital Goods IMF All Commodity Prices IIP Intermediate Goods IMF Commodity prices excluding Gold IIP Infrastructure Goods IMF Commodity Price of Industrial Raw Material IIP Consumer Durables IMF Commodity Price of Metals IIP Consumer Non-durables IMF Commodity Price of Base Metals Global Trade IMF Commodity Price of Fuel Exports to Emerging and Developing Asia IMF Commodity Price of Crude Oil Exports to Europe IMF Commodity Price of Coal US Non-farm payroll Data World Bank Price - Aluminium US IIP World Bank Price - Iron World Bank Price - Copper China IIP World Bank Price - Lead External Trade World Bank Price - Tin Merchandize Exports World Bank Price - Nickel Merchandize Imports World Bank Price - Zinc Non-oil non-gold imports Indian Basket Crude Oil Price Non-oil exports WTI Crude Oil Price Export of services Brent Crude Oil Price Import of services Dubai Crude Oil Price Import of Capital Goods PMI Data Employment Condition PMI Index CMIE Labour Force Participation - All India PMI Output CMIE Labour Force Participation - Urban PMI New Orders CMIE Labour Force Participation - Rural PMI Employments PMI Supplier Delivery Time CMIE Unemployment Rate - All India PMI Stock of Purchase CMIE Unemployment Rate - Urban PMI Input Prices CMIE Unemployment Rate - Rural PMI Quantity of Purchase CMIE Employment Rate - All India PMI Stocks of Finished Goods CMIE Employment Rate - Urban PMI New Export Orders CMIE Employment Rate - Rural PMI Output Prices NAUKRI Job Speak Index PMI Backlog of Work MGNREGA Work Demand PMI Future Output Payment and Public Finance Eight Core Headline RTGS Payments Coal Production UPI Payments Crude Oil Production E-Way Bills Natural Gas Production Petroleum Products production GST Collection Fertilizers production Revenue Expenditure (less interest payments and subsidy) of Steel Production Central Government Cement Production Fertiliser Sales Electricity Production 92 RBI Bulletin December 2025Composite Leading Indicator for GVA-Manufacturing for India ARTICLE Domestic Price Condition USA Policy Uncertainty - Newspaper Based WPI Headline Index Chine Policy Uncertainty WPI Food Prices European Union Policy Uncertainty - Newspaper WPI Primary Articles Germany Policy Uncertainty - WPI Fuel and Power Italy Policy Uncertainty - WPI Manufactured Items UK Policy Uncertainty - WPI Industrial Raw Material France Policy Uncertainty - CPI Headline Spain Policy Uncertainty - CPI Index excluding Food, Fuel and Beverages PE Ratio of listed companies Consumption Indicators Realized volatility of BSE Companies Finished Steel Consumption IOS and OBICUS Data Petroleum Consumption Industrial Outlook Survey - Production (Expectation) High Speed Diesel Consumption Industrial Outlook Survey - Order Book (Expectation) Motor Spirit Consumption Industrial Outlook Survey - Capacity Utilization (Expectation) Aviation Turbine Fuel Consumption Industrial Outlook Survey - Exports (Expectation) Trade, Transport and Demand Indicators Industrial Outlook Survey - Imports (Expectation) Domestic Air Passenger Traffic Industrial Outlook Survey - Inventory of Raw Material (Expectation) International Air Passenger Traffic Industrial Outlook Survey - Inventory of Finished Goods Domestic Air Cargo (Expectation) International Air Cargo Industrial Outlook Survey - Employment (Expectation) Railway Freight Industrial Outlook Survey - Financial Condition (Expectation) Port Traffic Industrial Outlook Survey - Cost of Finance (Expectation) Passenger Vehicle Sales (Wholesale) Industrial Outlook Survey - Cost of Raw Material (Expectation) Passenger Vehicle Sales (Wholesale) - LMV Industrial Outlook Survey - Selling Price (Expectation) Two Wheeler Sales (Wholesale) Industrial Outlook Survey - Profit Margin (Expectation) Two Wheeler Sales (Retail) Industrial Outlook Survey - Overall Business Condition Three Wheeler Sales (Domestic) Capacity Utilization Tractor Sales Cost of Borrowing Proxy Electricity Demand Weighted Average Call Money Rate Policy Uncertainty 91 days T-Bill Rate Global Policy Uncertainty G-Sec 10 Years Yield India Policy Uncertainty USA Policy Uncertainty - Three factor model RBI Bulletin December 2025 93ARTICLE Composite Leading Indicator for GVA-Manufacturing for India Annex III: Wavelet Coherence Source: Authors’ calculations Source: Authors’ calculations Source: Authors’ calculations Source: Authors’ calculations 94 RBI Bulletin December 2025Composite Leading Indicator for GVA-Manufacturing for India ARTICLE Annex IV : Interpretation of Wavelet Charts Wavelet charts, or wavelet power spectra, are different periodicities. The wavelet charts plot the used to analyze signals in both time and frequency phase differences between two series which help to domains simultaneously. They help in detecting identify the business cycle leading – lagging properties transient features, periodicities, and localized between two economic indicators. The direction of frequency variations in data. The x-axis of the wavelet arrows in the phase diagram indicates the relationship charts plots the time whereas the y-axis shows the between the economic indicators (Chart A2). Chart A2: Phase difference and Interpretation Source: Rosch and Schmidbauer (2018). RBI Bulletin December 2025 95ARTICLE Composite Leading Indicator for GVA-Manufacturing for India Annex V : Cross Correlation Estimates Lag = 1 Lag = 2 Variable CLI Construction Selection Full Sample Excluding COVID Full Sample Excluding COVID RFE Simple Average 0.08 0.43 0.24 0.31 RFE Weighted Average - SD 0.20 0.42 0.37 0.30 RFE Weighted Average - Correlation 0.10 0.43 0.26 0.32 RFE Dynamic Factor Model (2 factors) 0.06 0.34 0.20 0.24 RFE Dynamic Factor Model (1 factor) 0.06 0.51 0.24 0.48 RF Simple Average 0.62 0.64 0.34 0.61 RF Weighted Average - SD 0.74 0.78 0.61 0.73 RF Weighted Average - Correlation 0.59 0.66 0.28 0.61 RF Dynamic Factor Model (2 factors) 0.07 0.34 0.29 0.32 RF Dynamic Factor Model (1 factor) 0.07 0.51 0.26 0.50 XG Boost Simple Average 0.41 0.20 0.17 0.29 XG Boost Weighted Average - SD 0.63 0.44 0.35 0.30 XG Boost Weighted Average - Correlation 0.41 0.18 0.17 0.27 XG Boost Dynamic Factor Model (2 factors) 0.42 0.15 0.15 0.27 XG Boost Dynamic Factor Model (1 factor) 0.46 0.07 0.17 0.08 Pearson Simple Average 0.50 0.53 0.54 0.43 Pearson Weighted Average - SD 0.53 0.43 0.49 0.26 Pearson Weighted Average - Correlation 0.44 0.52 0.51 0.44 Pearson Dynamic Factor Model (2 factors) 0.02 0.44 0.19 0.49 Pearson Dynamic Factor Model (1 factor) 0.08 0.47 0.32 0.50 Kendall Simple Average 0.15 0.53 0.35 0.51 Kendall Weighted Average - SD 0.25 0.55 0.45 0.51 Kendall Weighted Average - Correlation 0.16 0.53 0.35 0.50 Kendall Dynamic Factor Model (2 factors) 0.23 0.57 0.38 0.50 Kendall Dynamic Factor Model (1 factor) 0.06 0.51 0.26 0.50 Spearman Simple Average 0.12 0.53 0.34 0.54 Spearman Weighted Average - SD 0.26 0.60 0.45 0.56 Spearman Weighted Average - Correlation 0.28 0.62 0.46 0.60 Spearman Dynamic Factor Model (2 factors) 0.07 0.44 0.33 0.48 Spearman Dynamic Factor Model (1 factor) 0.06 0.48 0.29 0.49 Quantile Simple Average 0.22 0.39 0.40 0.30 Quantile Weighted Average - SD 0.20 0.12 0.32 0.06 Quantile Weighted Average - Correlation 0.21 0.48 0.40 0.38 Quantile Dynamic Factor Model (2 factors) 0.02 0.14 0.11 0.19 Quantile Dynamic Factor Model (1 factor) 0.03 0.52 0.04 0.53 MI Simple Average 0.66 0.59 0.54 0.55 MI Weighted Average - SD 0.29 0.53 0.30 0.50 MI Weighted Average - Correlation 0.29 0.52 0.41 0.53 96 RBI Bulletin December 2025Composite Leading Indicator for GVA-Manufacturing for India ARTICLE Lag = 1 Lag = 2 Variable CLI Construction Selection Full Sample Excluding COVID Full Sample Excluding COVID MI Dynamic Factor Model (2 factors) 0.15 0.40 0.20 0.38 MI Dynamic Factor Model (1 factor) 0.09 0.56 0.24 0.49 Cosine Simple Average 0.22 0.00 0.14 0.05 Cosine Weighted Average - SD 0.20 0.06 0.15 0.03 Cosine Weighted Average - Correlation 0.18 0.01 0.07 0.06 Cosine Dynamic Factor Model (2 factors) 0.07 0.07 0.09 0.12 Cosine Dynamic Factor Model (1 factor) 0.08 0.06 0.08 0.03 DTW Simple Average 0.15 0.26 0.17 0.30 DTW Weighted Average - SD 0.38 0.21 0.38 0.33 DTW Weighted Average - Correlation 0.15 0.26 0.17 0.30 DTW Dynamic Factor Model (2 factors) 0.15 0.02 0.01 0.07 DTW Dynamic Factor Model (1 factor) 0.10 0.06 0.05 0.02 Union Simple Average 0.14 0.26 0.17 0.30 Union Weighted Average - SD 0.67 0.74 0.67 0.65 Union Weighted Average - Correlation 0.14 0.26 0.17 0.30 Union Dynamic Factor Model (2 factors) 0.07 0.55 0.21 0.55 Union Dynamic Factor Model (1 factor) 0.08 0.47 0.32 0.50 RFE-RF Simple Average 0.43 0.62 0.42 0.50 RFE-RF Weighted Average - SD 0.58 0.70 0.61 0.57 RFE-RF Weighted Average - Correlation 0.67 0.67 0.50 0.58 RFE-RF Dynamic Factor Model (2 factors) 0.05 0.51 0.19 0.46 RFE-RF Dynamic Factor Model (1 factor) 0.07 0.51 0.25 0.49 RFE-XG Boost Simple Average 0.38 0.29 0.15 0.32 RFE-XG Boost Weighted Average - SD 0.53 0.54 0.53 0.38 RFE-XG Boost Weighted Average - Correlation 0.39 0.26 0.16 0.31 RFE-XG Boost Dynamic Factor Model (2 factors) 0.01 0.47 0.20 0.41 RFE-XG Boost Dynamic Factor Model (1 factor) 0.12 0.20 0.17 0.12 RFE-Spearman Simple Average 0.10 0.51 0.29 0.42 RFE-Spearman Weighted Average - SD 0.25 0.58 0.45 0.50 RFE-Spearman Weighted Average - Correlation 0.11 0.54 0.31 0.49 RFE-Spearman Dynamic Factor Model (2 factors) 0.14 0.43 0.40 0.36 RFE-Spearman Dynamic Factor Model (1 factor) 0.06 0.51 0.25 0.49 RFE-Quantile Simple Average 0.08 0.44 0.26 0.32 RFE-Quantile Weighted Average - SD 0.26 0.46 0.45 0.35 RFE-Quantile Weighted Average - Correlation 0.10 0.43 0.28 0.32 RFE-Quantile Dynamic Factor Model (2 factors) 0.07 0.31 0.24 0.24 RFE-Quantile Dynamic Factor Model (1 factor) 0.08 0.54 0.23 0.47 RFE-MI Simple Average 0.23 0.52 0.36 0.41 RFE-MI Weighted Average - SD 0.30 0.58 0.41 0.50 RFE-MI Weighted Average - Correlation 0.33 0.55 0.44 0.46 RBI Bulletin December 2025 97ARTICLE Composite Leading Indicator for GVA-Manufacturing for India Lag = 1 Lag = 2 Variable CLI Construction Selection Full Sample Excluding COVID Full Sample Excluding COVID RFE-MI Dynamic Factor Model (2 factors) 0.09 0.48 0.15 0.42 RFE-MI Dynamic Factor Model (1 factor) 0.08 0.54 0.24 0.49 RFE-Cosine Simple Average 0.10 0.44 0.27 0.33 RFE-Cosine Weighted Average - SD 0.34 0.29 0.46 0.25 RFE-Cosine Weighted Average - Correlation 0.14 0.46 0.30 0.36 RFE-Cosine Dynamic Factor Model (2 factors) 0.08 0.05 0.08 0.01 RFE-Cosine Dynamic Factor Model (1 factor) 0.08 0.06 0.08 0.03 RF-XG Boost Simple Average 0.39 0.29 0.16 0.37 RF-XG Boost Weighted Average - SD 0.86 0.85 0.59 0.71 RF-XG Boost Weighted Average - Correlation 0.40 0.23 0.17 0.31 RF-XG Boost Dynamic Factor Model (2 factors) 0.27 0.39 0.00 0.42 RF-XG Boost Dynamic Factor Model (1 factor) 0.46 0.05 0.16 0.09 RF-Spearman Simple Average 0.64 0.77 0.54 0.74 RF-Spearman Weighted Average - SD 0.56 0.73 0.64 0.68 RF-Spearman Weighted Average - Correlation 0.58 0.76 0.50 0.75 RF-Spearman Dynamic Factor Model (2 factors) 0.06 0.52 0.24 0.50 RF-Spearman Dynamic Factor Model (1 factor) 0.05 0.48 0.28 0.49 RF-Quantile Simple Average 0.66 0.69 0.39 0.65 RF-Quantile Weighted Average - SD 0.66 0.75 0.69 0.67 RF-Quantile Weighted Average - Correlation 0.70 0.72 0.44 0.69 RF-Quantile Dynamic Factor Model (2 factors) 0.07 0.32 0.24 0.24 RF-Quantile Dynamic Factor Model (1 factor) 0.08 0.54 0.23 0.47 RF-MI Simple Average 0.73 0.74 0.45 0.69 RF-MI Weighted Average - SD 0.55 0.65 0.44 0.60 RF-MI Weighted Average - Correlation 0.68 0.68 0.36 0.64 RF-MI Dynamic Factor Model (2 factors) 0.10 0.47 0.24 0.47 RF-MI Dynamic Factor Model (1 factor) 0.07 0.52 0.26 0.50 RF-Cosine Simple Average 0.62 0.62 0.34 0.59 RF-Cosine Weighted Average - SD 0.55 0.43 0.44 0.45 RF-Cosine Weighted Average - Correlation 0.52 0.48 0.21 0.47 RF-Cosine Dynamic Factor Model (2 factors) 0.09 0.00 0.04 0.04 RF-Cosine Dynamic Factor Model (1 factor) 0.08 0.06 0.08 0.03 XG Boost- Spearman Simple Average 0.39 0.26 0.16 0.34 XG Boost- Spearman Weighted Average - SD 0.63 0.76 0.66 0.70 XG Boost- Spearman Weighted Average - Correlation 0.38 0.32 0.14 0.39 XG Boost- Spearman Dynamic Factor Model (2 factors) 0.10 0.52 0.30 0.52 98 RBI Bulletin December 2025Composite Leading Indicator for GVA-Manufacturing for India ARTICLE Lag = 1 Lag = 2 Variable CLI Construction Selection Full Sample Excluding COVID Full Sample Excluding COVID XG Boost- Spearman Dynamic Factor Model (1 factor) 0.04 0.47 0.28 0.49 XG Boost- Quantile Simple Average 0.40 0.20 0.17 0.29 XG Boost- Quantile Weighted Average - SD 0.49 0.33 0.41 0.22 XG Boost- Quantile Weighted Average - Correlation 0.41 0.19 0.17 0.27 XG Boost- Quantile Dynamic Factor Model (2 factors) 0.29 0.19 0.03 0.26 XG Boost- Quantile Dynamic Factor Model (1 factor) 0.46 0.06 0.17 0.08 XG Boost-MI Simple Average 0.40 0.24 0.16 0.32 XG Boost-MI Weighted Average - SD 0.56 0.58 0.47 0.54 XG Boost-MI Weighted Average - Correlation 0.40 0.24 0.16 0.32 XG Boost-MI Dynamic Factor Model (2 factors) 0.30 0.07 0.04 0.13 XG Boost-MI Dynamic Factor Model (1 factor) 0.03 0.49 0.24 0.48 XG Boost- Cosine Simple Average 0.40 0.20 0.17 0.29 XG Boost- Cosine Weighted Average - SD 0.42 0.12 0.26 0.10 XG Boost- Cosine Weighted Average - Correlation 0.41 0.17 0.17 0.26 XG Boost- Cosine Dynamic Factor Model (2 factors) 0.38 0.04 0.09 0.05 XG Boost- Cosine Dynamic Factor Model (1 factor) 0.08 0.06 0.08 0.03 Spearman- Quantile Simple Average 0.13 0.54 0.36 0.53 Spearman- Quantile Weighted Average - SD 0.30 0.50 0.50 0.44 Spearman- Quantile Weighted Average - Correlation 0.28 0.61 0.48 0.57 Spearman- Quantile Dynamic Factor Model (2 factors) 0.08 0.39 0.25 0.31 Spearman- Quantile Dynamic Factor Model (1 factor) 0.08 0.54 0.23 0.47 Spearman-MI Simple Average 0.56 0.59 0.57 0.57 Spearman-MI Weighted Average - SD 0.43 0.56 0.49 0.54 Spearman-MI Weighted Average - Correlation 0.66 0.57 0.57 0.55 Spearman-MI Dynamic Factor Model (2 factors) 0.10 0.43 0.28 0.47 Spearman-MI Dynamic Factor Model (1 factor) 0.06 0.48 0.29 0.49 Spearman- Cosine Simple Average 0.16 0.52 0.37 0.54 Spearman- Cosine Weighted Average - SD 0.34 0.44 0.51 0.45 RBI Bulletin December 2025 99ARTICLE Composite Leading Indicator for GVA-Manufacturing for India Lag = 1 Lag = 2 Variable CLI Construction Selection Full Sample Excluding COVID Full Sample Excluding COVID Spearman- Cosine Weighted Average - Correlation 0.15 0.54 0.38 0.54 Spearman- Cosine Dynamic Factor Model (2 factors) 0.09 0.42 0.27 0.46 Spearman- Cosine Dynamic Factor Model (1 factor) 0.06 0.48 0.29 0.49 Quantile-MI Simple Average 0.66 0.60 0.57 0.55 Quantile-MI Weighted Average - SD 0.40 0.44 0.47 0.40 Quantile-MI Weighted Average - Correlation 0.40 0.47 0.43 0.45 Quantile-MI Dynamic Factor Model (2 factors) 0.07 0.30 0.24 0.22 Quantile-MI Dynamic Factor Model (1 factor) 0.08 0.54 0.23 0.47 Quantile- Cosine Simple Average 0.31 0.20 0.31 0.24 Quantile- Cosine Weighted Average - SD 0.31 0.13 0.34 0.15 Quantile- Cosine Weighted Average - Correlation 0.32 0.12 0.31 0.19 Quantile- Cosine Dynamic Factor Model (2 factors) 0.08 0.21 0.04 0.26 Quantile- Cosine Dynamic Factor Model (1 factor) 0.03 0.52 0.04 0.53 MI-Cosine Simple Average 0.66 0.56 0.55 0.54 MI-Cosine Weighted Average - SD 0.36 0.40 0.39 0.40 MI-Cosine Weighted Average - Correlation 0.59 0.41 0.44 0.44 MI-Cosine Dynamic Factor Model (2 factors) 0.12 0.05 0.01 0.07 MI-Cosine Dynamic Factor Model (1 factor) 0.09 0.06 0.06 0.02 Coherence Simple Average 0.46 0.68 0.51 0.65 Coherence Weighted Average - SD 0.49 0.68 0.55 0.61 Coherence Weighted Average - Correlation 0.39 0.66 0.48 0.63 Coherence Dynamic Factor Model (2 factors) 0.12 0.51 0.32 0.54 Coherence Dynamic Factor Model (1 factor) 0.08 0.47 0.32 0.50 Note: • Highlighted cells have correlation higher than 50 per cent. • The numbers within parentheses indicate number of factors used in DFM. Source: Authors’ calculations. 100 RBI Bulletin December 2025Decoding Safe Asset Volatility Amid Geopolitical Risks Using ARTICLE Neural Networks Decoding Safe Asset Volatility itself as a compelling investment choice during episodes of economic and financial stress. These Amid Geopolitical Risks Using assets are generally highly liquid and benefit from Neural Networks persistent and stable demand factors that contribute to their enduring relevance and resilience against by Ankon Ghosh, Bipul Ghosh and obsolescence or substitution. Sandhya Kuruganti^ Building on this foundational understanding, a substantial body of research has evaluated the The heightened influence of geopolitical tensions historical performance of various safe haven assets on asset market dynamics raises important questions on during significant global disruptions, such as the how safe haven assets respond to changing geopolitical GFC and the Covid-19 pandemic. However, most of risk and whether nonlinear models offer superior this literature adopts a retrospective lens, assessing volatility forecasts, making the issue both topical and asset performance on a post-facto basis. In contrast, policy relevant. We find that while crude oil price this study adopts a forward-looking perspective by volatility is acutely sensitive to such shocks, gold price forecasting the volatility of widely acknowledged safe volatility remains consistently stable. Silver and US haven assets and quantifying their relative sensitivity Treasury securities exhibit intermediate behaviour, to external shocks, with a particular emphasis on reflecting mixed properties of industrial exposure and geopolitical risk. flight-to-safety demand. The analysis further shows that Among the various exogenous forces influencing neural network based models, particularly nonlinear markets, geopolitical tensions have emerged as frameworks incorporating country specific geopolitical potent volatility drivers. Events such as terrorism risk indices, outperform traditional econometric models and international conflicts carry substantial in forecasting volatility. These results indicate that safe implications for asset price dynamics. The conflicts haven assets react heterogeneously to geopolitical stress between Russia and Ukraine since February 2022, and that nonlinear amplification effects are economically as well as persistent unrest in the Middle East, have meaningful. Hence, investors and policymakers need to exemplified significant market disruptions arising recognise asset specific risk transmission channels and from geopolitical instability. avoid overreliance on linear frameworks. The Global Financial Stability Report (GFSR) Introduction dated April 2025 identifies two principal transmission Since the Global Financial Crisis (GFC) of 2007- mechanisms through which geopolitical risk affects 2008, the concept of safe haven assets has attracted asset volatility, namely the economic and market scholarly and practitioner interest, as market sentiment channels. According to the GFSR, prices participants increasingly seek shelter during periods of key commodities including safe haven assets of elevated uncertainty. A safe haven asset is typically typically rise in response to geopolitical shocks, while characterised as one that either retains or appreciates US Treasury yields tend to fall, reflecting a flight-to- in value amidst market turmoil, thereby positioning safety response. ^ The authors are from the Data Sciences Lab. The views expressed in the Prior studies, including those by Apergis article are of the authors and do not represent the views of the Reserve Bank of India. et al. (2017) and Gkillas et al. (2018), corroborate RBI Bulletin December 2025 101ARTICLE Decoding Safe Asset Volatility Amid Geopolitical Risks Using Neural Networks the predictive value of geopolitical risk indicators in II. Historical Overview and Stylised Facts on Safe explaining volatility patterns. Haven Assets Building upon these insights, the present study In this section, we trace the historical incorporates geopolitical risk into asset volatility development of safe haven assets and highlight the forecasting models by employing the news-based stylised facts that underscore their behaviour through Geopolitical Risk Index (GPR) developed by Caldara recent geopolitical crises. and Iacoviello (2022). The analysis focuses on four Historical Overview of Safe Haven Assets widely recognised safe haven assets – gold, silver, crude oil and US Treasury securities. The concept of safe haven assets has evolved significantly over time, with gold, silver, crude oil Against this backdrop, the study addresses and US Treasury securities emerging as primary three key questions: how safe haven assets respond instruments sought during episodes of economic or to geopolitical risk, whether nonlinear neural- geopolitical turbulence for their stability and low risk network models provide superior volatility forecasts characteristics. Among these, gold and silver have compared with linear econometric benchmarks and served as mediums of exchange and store of value how sensitive each asset is to escalating geopolitical across ancient and modern civilisations, prized for tensions. In brief, the study finds that gold remains their intrinsic worth, scarcity and durability. the most stable asset, crude oil exhibits pronounced sensitivity, silver and US Treasuries display As financial systems matured, early instruments intermediate behaviour and neural-network models such as goldsmith-issued bills of exchange gradually consistently outperform traditional approaches. gave way to more sophisticated forms of credit These results demonstrate that safe haven assets and government-backed securities. The industrial exhibit heterogeneous volatility responses and that revolution and the expansion of global trade further incorporating geopolitical risk within nonlinear heightened the need for assets that could preserve frameworks significantly enhances forecast accuracy. value and ensure liquidity in times of stress. During periods of systemic disruption such as the World War Furthermore, the study simulates the dynamic responses of these assets to escalating levels of I and the 1929 stock market crash, gold and sovereign geopolitical risk, highlighting their relative sensitivity bonds played a critical role in maintaining market to such shocks. By doing so, the study contributes confidence and financial stability. a practical framework that enables investors to Crude oil, although not traditionally viewed as evaluate and select safe haven assets tailored to their a monetary safe haven, rose to strategic importance risk preferences and investment objectives. during the 20th century. The World War I – marked The remainder of this paper is organised as a turning point, as oil became indispensable to follows. Section II provides a historical overview of military logistics and industrial production, thereby safe haven assets and discusses key stylised facts elevating its economic status. In the 1970s, a series pertaining to their behaviour. Section III surveys of geopolitical shocks, particularly conflicts in the the relevant literature. Section IV outlines the data Middle East, disrupted global oil supplies, leading employed in the analysis. Section V describes the to dramatic price spikes and cementing oil’s role methodological framework and presents the empirical as a crisis responsive commodity. This behavioural findings. Section VI concludes the study. pattern among investors persists today, as evidenced 102 RBI Bulletin December 2025Decoding Safe Asset Volatility Amid Geopolitical Risks Using ARTICLE Neural Networks by sharp surges in crude oil prices during the Russia - Chart 1: Gold Price Ukraine conflict in 2022. (USD per troy ounce) 3000 The 21st century has been characterised by recurring financial crises and escalating 2500 geopolitical instability, reinforcing the relevance 2000 of safe haven assets in both institutional and retail investment portfolios. Events such as the GFC and 1500 recent military conflicts in the Middle East have led 1000 to pronounced increase in the value of traditional safe haven assets, notably gold, silver and crude oil. 500 Central banks and sovereign institutions continue to 0 hold these assets as part of their risk management and macroprudential frameworks, while individual Note: Shaded regions denote major events, from left to right – GFC, COVID-19, investors seek them to hedge against uncertainty and Israel Gaza Conflict. Source: World Gold Council. systemic shocks. As market volatility becomes an enduring feature Silver, although more volatile, shares many of of the global financial landscape, the identification gold’s safe haven characteristics. As seen in Chart 2, and comparative evaluation of effective safe haven silver experienced dramatic spikes during the 1980 assets have become critical components of strategic Hunt Brothers crisis, the 2010-11 commodity boom asset allocation and portfolio resilience. and periods of pandemic-related supply disruptions. Stylised Facts on Safe Haven Assets Its industrial utility, especially in renewable energy, adds a demand channel that amplifies its price Safe haven assets preserve or increase in value during episodes of financial instability and volatility during geopolitical shocks. geopolitical unrest. They are typically liquid, low risk and sought after in times of crisis. Historical price trajectories and volatility responses reveal several key stylised facts that underscore their distinct behaviours under stress. Price Dynamics of Safe Haven Assets Gold continues to serve as the archetypal safe haven asset. Its long run price trend reveals strong upward momentum with sharp surges during the early 1980s, the GFC and the Covid-19 pandemic (Chart 1). The recent rally in 2022-25 further reflects investors’ response to systematic uncertainty and global tensions. Gold’s reputation as a hedge against inflation and a store of value makes it attractive to central banks and institutional investors. RBI Bulletin December 2025 103 77-voN 08-beF 28-yaM 48-guA 68-voN 98-beF 19-yaM 39-guA 59-voN 89-beF 00-yaM 20-guA 40-voN 70-beF 90-yaM 11-guA 31-voN 61-beF 81-yaM 02-guA 22-voN 52-beF Chart 2: Silver Price (USD per troy ounce) 45 40 35 30 25 20 15 10 5 0 Note: Shaded regions denote major events, from left to right – Hunt Brothers Crisis, COVID-19. Source: World Bank “The Pink Sheet”. 77-voN 08-beF 28-yaM 48-guA 68-voN 98-beF 19-yaM 39-guA 59-voN 89-beF 00-yaM 20-guA 40-voN 70-beF 90-yaM 11-guA 31-voN 61-beF 81-yaM 02-guA 22-voN 52-beFARTICLE Decoding Safe Asset Volatility Amid Geopolitical Risks Using Neural Networks Chart 3: Crude Oil Price (USD per barrel) 140 120 100 80 60 40 20 0 Note: Shaded regions denote major events, from left to right – Gulf War, GFC, Russia – Ukraine conflict. Source: World Bank “The Pink Sheet”. Crude oil reflects a different behavioural pattern. heightened volatility (Chart 5). The results highlight It is highly sensitive to global supply chains, making distinct patterns across events and asset classes. The it more vulnerable to geopolitical disruptions than GFC triggered a broad based surge in volatility, with demand side contractions. Sharp volatility around the silver experiencing the most pronounced increase. Gulf War, the GFC, and the Russia-Ukraine conflict is Events such as the Gulf War and the Russia-Ukraine clearly visible (Chart 3). While not a conventional safe conflict disproportionately affected crude oil, haven, crude oil is often used to hedge inflationary reflecting heightened supply side risk and geopolitical risk stemming from supply shocks. sanctions. US Treasury securities (10 year treasury bill) conversely, exhibit classic countercyclical safe haven properties. Their yields have trended downward over the long term, with steep declines during major crises, reflecting heightened demand amid flight- to-safety behaviour (Chart 4). Their deep liquidity and sovereign backing make them the most widely accepted risk free asset. Volatility Response to Geopolitical Events Geopolitical shocks frequently lead to sharp increases in asset price volatility. This is evident in the ratio of the coefficient of variation (CV) of asset prices during major geopolitical events relative to the pre-event period, where a ratio above 1 denotes 104 RBI Bulletin December 2025 77-voN 08-beF 28-yaM 48-guA 68-voN 98-beF 19-yaM 39-guA 59-voN 89-beF 00-yaM 20-guA 40-voN 70-beF 90-yaM 11-guA 31-voN 61-beF 81-yaM 02-guA 22-voN 52-beF Chart 4: US Treasury Security Yield (Per cent) 18 16 14 12 10 8 6 4 2 0 Note: Shaded regions denote major events, from left to right – GFC, COVID-19. Source: Federal Bank of St. Louis. 77-voN 08-beF 28-yaM 48-guA 68-voN 98-beF 19-yaM 39-guA 59-voN 89-beF 00-yaM 20-guA 40-voN 70-beF 90-yaM 11-guA 31-voN 61-beF 81-yaM 02-guA 22-voN 52-beF Chart 5: Jump in Coefficient of Variation for Safe Haven Assets during Geopolitical Events (Ratio of CV during event over CV before event) Tiananmen Square (Feb-89 to Jul-89) Gulf war (Jul-90 to Apr-91) 9/11 attack (Sep-01 to Apr-02) Iraq war (Mar-03 to Jan-04) Global Financial crisis (Jul-07 to Dec-08) Arab spring (Dec-10 to Mar-13) Russian Ukraine conflict (Jan-22 to Sep-22) Israel Gaza conflict (Oct-23 to May-24) 0 1 2 3 4 5 Gold Silver Crude Oil US Treasury Security Note: For each event, ratio of Coefficient of Variation (CV), calculated for the duration of the event over the CV calculated for period preceding the event is reported. A value of this ratio over 1 denotes jump in volatility for the assets. Source: Authors' Calculations.Decoding Safe Asset Volatility Amid Geopolitical Risks Using ARTICLE Neural Networks Meanwhile, the Israel-Gaza conflict produced Silver also registered significant amplification in significant spikes in the CV of gold and silver, volatility across three analysed events, due to its dual suggesting, in particular, their sensitive to instability role as a hedging instrument and industrial input. in Middle East. In contrast, US Treasuries showed In contrast, gold demonstrated remarkable the most pronounced volatility response during the stability, with only modest increases in conditional Tiananmen Square protests and the Arab Spring, volatility even during acute geopolitical stress. This indicating their exposure to global sentiment and subdued reaction reinforces gold’s reputation as a shifts in risk appetite. These findings underscore reliable safe haven, offering consistency- when other how different safe haven assets respond uniquely to asset classes are more reactive. These differentiated the nature and geography of geopolitical events. volatility responses highlight the importance of asset specific characteristics in risk management and Conditional Volatility from GARCH Models portfolio construction during a crisis. To further assess asset responses to geopolitical III. Reviewed Literature shocks, we estimate monthly conditional volatilities using GARCH models for recent high impact events The complex and evolving relationship between (Table 1). Conditional volatility, a forward looking geopolitical risk and the price volatility of safe haven metric, captures how markets anticipate future assets is well documented in the recent literature. fluctuations based on past variability. The results Gupta et al. (2024) show that incorporating country reveal sharp spikes in volatility for most assets’ specific geopolitical risk (GPR) data into machine price, with crude oil and US Treasuries exhibiting learning models significantly improves forecasts of over threefold increases during the Russia- gold price volatility. Similarly, Gkillas et al. (2018) examine the nonlinear influence of geopolitical Ukraine conflict, reflecting heightened uncertainty uncertainty on volatility spikes in the Dow Jones surrounding energy supply and safe asset demand. Industrial Average, finding that the persistence Table 1: Conditional Volatility during Geopolitical and magnitude of these shocks vary by event and Events time horizon. Building on these insights, this study Event Asset Conditional Volatility employs artificial neural networks (ANNs) to flexibly Minimum Maximum capture such nonlinear dynamics. Crude oil 0.008 0.026 The oil market shows particular sensitivity to Gold 0.001 0.001 Russia Ukraine conflict Silver 0.003 0.007 geopolitical tensions. Liu et al. (2020) quantify the US Treasury 0.008 0.028 impact of extreme geopolitical events on oil prices, security underscoring the need for robust risk mitigation. Crude oil 0.003 0.008 Jiao et al. (2021) identify supply side disruptions and Gold 0.001 0.002 Israel Gaza conflict Silver 0.002 0.006 political instability as the main channels through US Treasury 0.003 0.008 which geopolitical risk affects oil market dynamics. security These findings highlight the need to systematically Crude oil 0.002 0.007 assess how safe haven assets respond to geopolitical Gold 0.001 0.002 US Election Silver 0.002 0.006 developments. US Treasury 0.002 0.005 Kundu et al. (2023) examine the price dynamics security Source: Authors' Calculations. of gold in the Indian context. The authors establish RBI Bulletin December 2025 105ARTICLE Decoding Safe Asset Volatility Amid Geopolitical Risks Using Neural Networks that volatility of returns for gold declines during per troy ounce), are obtained from the World Gold heightened period of risk. In such periods, risk Council. Silver prices (USD per troy ounce) and crude tolerance reduces among investors and a flight to safe oil prices (USD per barrel) are sourced from the World haven commodity like gold is generally observed. Bank’s Pink Sheet database. US Treasury yields, specifically the 10-year constant maturity yields, are IV. Data retrieved from the Federal Reserve Bank of St. Louis Whereas earlier studies often focused on and converted into monthly averages. individual assets using traditional econometric models, this paper applies a comparative framework The empirical analysis covers the period from across multiple safe haven assets using neural January 1978 to February 2025. The selection of 1978 networks. Asset price volatility under evolving as the starting point is motivated by both historical geopolitical conditions is analysed, capturing intricate, context and data stability. It immediately precedes nonlinear relationships with improved accuracy. major geopolitical disruptions such as the Iranian Unlike Gupta et al. (2024), who use both aggregate Revolution and the Soviet invasion of Afghanistan in and all country level geopolitical risk (GPR) indices, 1979, allowing the model to capture asset behaviour the approach followed in this paper relies on relevant before and after these shocks. Furthermore, this date country specific GPR data aligned with each asset’s lies sufficiently beyond the collapse of the Bretton supply-demand structure. A simulation analysis is Woods system (1971) and the OPEC oil embargo used to evaluate volatility responses to geopolitical (1973), by which time commodity and financial shocks. This integrated framework supports forward markets had largely adjusted to the new regime of looking, evidence-based decision making by investors flexible exchange rates and market-driven pricing. and policymakers navigating a climate of protracted Starting in 1978 thus ensures a long, stable sample geopolitical uncertainty. that reflects mature post–Bretton Woods dynamics To capture geopolitical uncertainty, the GPR and historically significant levels of safe-asset developed by Caldara and Iacoviello (2022) is valuation. employed. This index quantifies both global and For robustness, three recursive sub-samples are country specific geopolitical risks using newspaper constructed, each beginning in January 1978. The first based metrics at a monthly frequency. The sample ends in September 2021, while the second methodology identifies the frequency and context and third samples expand sequentially by 12 month of geopolitical terms in major news publications, intervals. For each sample, we generate 12 months measuring both the intensity and salience of ahead forecasts of asset price volatility, which are geopolitical tensions. Notably, the country specific benchmarked against volatility estimates from a GPR covers 44 countries across multiple regions, GARCH (1,1) model. This recursive forecast structure enabling a nuanced understanding of how geopolitics enables a rigorous evaluation of model performance affect asset level volatility. This refined measure under changing geopolitical conditions. enhances our ability to assess the transmission of geopolitical risk across diverse financial markets. V. Methodology and Results Four safe haven assets – gold, silver, crude oil This section establishes the methodological and US Treasury securities are considered for the framework of the study and presents the findings analysis. Gold prices on a monthly frequency (USD from the study. 106 RBI Bulletin December 2025Decoding Safe Asset Volatility Amid Geopolitical Risks Using ARTICLE Neural Networks Methodology The Nonlinear Autoregressive (NAR) model, whose foundations were introduced by Narendra The methodological framework, consisting of and Parthasarathy (1990), extends artificial neural GARCH-based conditional volatility estimation, networks (ANNs) to time series forecasting by neural-network and econometric forecasting models capturing nonlinear dependencies that traditional and a structured simulation of geopolitical risk linear models fail to account for. It models future scenarios, is designed to directly answer the research values as a nonlinear function of past observations: questions posed in the Introduction. y h(y , y ,…., y + e (1) t t t t-d t This study estimates conditional volatility for wh =ere, d–1 is –t2he num )b er of lags, h(.) is the ANN, each safe haven asset using a GARCH (1,1) model. y is the input volatility series and e accounts for The resulting conditional volatility series serves as t random noise. the target variable for forecasting. Detailed volatility Building on the NAR framework, the NARX model estimates and model diagnostics are provided in the enhances forecasting accuracy by incorporating Annexure. Conditional volatility is preferred over external predictors. It estimates volatility as a realised volatility in this context, as it is better suited function of both lagged values of the volatility series for monthly frequency data and effectively captures and lagged values of exogenous variables specifically, the time-varying and persistent nature of financial country specific geopolitical risk indices (GPR): market volatility. y h y , y ,…., y , x , x , …., t t– t– t– , t– , t– Two separate forecasting frameworks are x , ….x , x ,…., x + e (2) , t-d 1c, t 2 c, t– l 1c, t–d1 1 t2 considered: (i) forecasting volatility using the past = ( values of the volatility series; and (ii) framework 1 w1here, ‘y t’– 1is the2 volatilit )y time series and ‘y t– ’, ‘y ’, …. , ‘y ’ are the ‘ ’ lags of volatility series. ‘x ’, augmented by a set of exogenous variables. For these t– t– c,t 1 ‘x ’, …, ‘x ’ are the ‘ ’ lags of geopolitical risk two cases, the traditional econometric benchmarks c,t2– c1, t–d l –1 index specific to cth country, (.) is the underlying are first established - an autoregressive (AR) model for 2 d ANN and ‘e’ accounts for random noise. the univariate case and an autoregressive integrated t h moving average with exogenous variables (ARIMAX) These models are selected for their ability to model complex, nonlinear interactions and to model for the multivariate case. effectively handle high dimensional data, making Subsequently, the nonlinear autoregressive (NAR) them well suited for capturing the dynamics of and nonlinear autoregressive with exogenous inputs geopolitical shocks in financial markets. For the NARX (NARX) models are implemented for the respective model, asset specific set of exogenous variables drawn forecasting scenarios. These models are advanced from country specific GPR indices is constructed, as forms of Artificial Neural Networks (ANNs), well outlined in Table 2. Countries are selected based on suited for capturing nonlinear and dynamic patterns Table 2: Exogenous Variables for NARX Model in time series data.1 Asset Variables 1 ANNs are inspired by the structure and functioning of the human brain, Gold GPR specific to US, China & Russia consisting of multiple interconnected layers made up of processing units Silver GPR specific to US, China, India & Japan called neurons. Each neuron receives input, applies a transformation Crude oil GPR specific to Egypt, Israel, Russia, US & China using an activation function and passes the result forward to the next GPR specific to China, US; GPR index, GPR Threat layer. A standard ANN architecture comprises input, hidden and output US Treasury security index and GPR Act index layers, and is trained through iterative adjustments of the connection weights to minimise prediction error using backpropagation. Source: Authors' Calculations. RBI Bulletin December 2025 107ARTICLE Decoding Safe Asset Volatility Amid Geopolitical Risks Using Neural Networks their significance in the global supply and demand the fitted GARCH models, which form the foundation chain of the respective asset, and from this set, only for both forecasting and simulation. Asset specific those for which GPR data is available are included in volatilities are shown in Charts 6 to 9. the empirical framework. The GPR specific to United Gold exhibits episodic volatility spikes during States is included as an exogenous variable for all four major crises such as the Asian Financial Crisis assets; due to its dominant role in the global market. (1997-98), the GFC and the Covid-19 pandemic The NARX model is trained on the latest (2020-21). Despite these episodes, its overall volatility recursive sample, comprising data from January 1978 remains moderate, reaffirming gold’s role as a stable to September 2023, and is used to forecast monthly hedge (Chart 6). Silver, by contrast, displays a more volatility up to March 2025 in a recursive manner. erratic pattern, with sharper and more frequent Starting in October 2023, a one-step-ahead forecast spikes; particularly in the early 1980s, post-2008, and is generated, the predicted volatility is put back into during the European debt crisis, reflecting its dual the model and the country specific GPR inputs are nature as both a precious and an industrial metal updated at each step to produce the next forecast. (Chart 7). To assess each asset’s sensitivity to geopolitical Crude oil shows the most pronounced volatility, risk, a simulation exercise is conducted by varying with peaks during the 1986 price collapse, the the US specific GPR index across four scenarios Gulf War, the GFC and the Russia-Ukraine conflict, – low, medium, high and extreme – based on driven by geopolitical tensions, supply disruptions the historical distribution of risk. The first three and OPEC decisions (Chart 8). US Treasury correspond to observed levels of geopolitical stress, yields, though typically stable, exhibit noticeable while the extreme scenario simulates unobserved spikes during the GFC, the 2013 taper tantrum and risk conditions. This is operationalised by inflating the 2020 pandemic, reflecting shifts in global risk the historical median and maximum of the US sentiment and expectations around monetary policy specific GPR by 50 per cent, then randomly drawing (Chart 9). GPR values within this inflated range to generate a Overall, the analysis confirms that volatility synthetic extreme scenario. dynamics are asset specific, shaped by both This simulation enables the evaluation of structural traits and external shocks. These GARCH how volatility in each asset responds to escalating based series provide the foundation for evaluating geopolitical tensions. The results offer valuable forecast models, linear (AR, ARIMAX) and nonlinear insights for market participants and policymakers, (NAR, NARX), as well as the geopolitical sensitivity supporting the selection of appropriate safe haven simulations discussed in the next section. assets in alignment with individual risk tolerance and investment strategies. Volatility Forecasts Results To evaluate model effectiveness, Root Mean Squared Errors (RMSE) of each model are compared This section presents the results of the forecasting using a relative performance metric: models and the simulation exercise assessing the sensitivity of safe haven assets to geopolitical risk. It begins with conditional volatility estimates from RMSE(Model A) 1 – RMSE(Model B) 108 RBI Bulletin December 2025Decoding Safe Asset Volatility Amid Geopolitical Risks Using ARTICLE Neural Networks Chart 6: Estimated Volatility of Gold Price (Volatility) 0.006 0.005 0.004 0.003 0.002 0.001 0.000 Source: Authors’ calculations. RBI Bulletin December 2025 109 38-beF 58-beF 78-beF 98-beF 19-beF 39-beF 59-beF 79-beF 99-beF 10-beF 30-beF 50-beF 70-beF 90-beF 11-beF 31-beF 51-beF 71-beF 91-beF 12-beF 32-beF 52-beF Chart 7: Estimated Volatility of Silver Price (Volatility) 0.030 0.025 0.020 0.015 0.010 0.005 0.000 Source: Authors’ calculations. 38-beF 58-beF 78-beF 98-beF 19-beF 39-beF 59-beF 79-beF 99-beF 10-beF 30-beF 50-beF 70-beF 90-beF 11-beF 31-beF 51-beF 71-beF 91-beF 12-beF 32-beF 52-beF Chart 8: Estimated Volatility of Crude Oil Price (Volatility) 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 Source: Authors’ calculations. 38-beF 58-beF 78-beF 98-beF 19-beF 39-beF 59-beF 79-beF 99-beF 10-beF 30-beF 50-beF 70-beF 90-beF 11-beF 31-beF 51-beF 71-beF 91-beF 12-beF 32-beF 52-beF Chart 9: Estimated Volatility of US Treasury Security Yield (Volatility) 0.10 0.08 0.06 0.04 0.02 0.00 Source: Authors’ calculations. 38-beF 58-beF 78-beF 98-beF 19-beF 39-beF 59-beF 79-beF 99-beF 10-beF 30-beF 50-beF 70-beF 90-beF 11-beF 31-beF 51-beF 71-beF 91-beF 12-beF 32-beF 52-beF A positive value indicates Model A outperforms A key observation is the consistent Model B, while a negative value implies the opposite. outperformance of neural networks. Except for one The results confirm the predictive strength of neural instance involving gold, the NAR model performs networks over traditional benchmarks (Table 3). better than the AR model across most assets and Additionally, the forecasted volatilities are compared samples, reflecting its strength in capturing complex, from the NARX model (trained on data from January nonlinear relationships (Chart 10). Similarly, the 1978 to September 2023) with actual volatilities up to NARX model consistently surpasses ARIMAX, February 2025 (Chart 10). even though both use the same set of exogenousARTICLE Decoding Safe Asset Volatility Amid Geopolitical Risks Using Neural Networks Chart 10: Volatility Forecast a. Gold Price b. Silver Price (Volatility) (Volatility) 0.0025 0.0020 0.0015 0.0010 0.0005 0.0000 Actual Prediction Actual Prediction c. Crude Oil Price d. US Treasury Security Yield (Volatility) (Volatility) Actual Prediction Actual Prediction Source: Authors’ calculations. 110 RBI Bulletin December 2025 32-tcO 32-voN 32-ceD 42-naJ 42-beF 42-raM 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 0.008 0.006 0.004 0.002 0.000 32-tcO 32-voN 32-ceD 42-naJ 42-beF 42-raM 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 0.010 0.008 0.006 0.004 0.002 0.000 32-tcO 32-voN 32-ceD 42-naJ 42-beF 42-raM 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 0.008 0.006 0.004 0.002 0.000 32-tcO 32-voN 32-ceD 42-naJ 42-beF 42-raM 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF variables. This shows that neural networks can effects of geopolitical risk compared with traditional better learn and exploit the lagged and nonlinear econometric approaches. Table 3: Comparison of Model Performance The improvement is especially notable when Comparison Metric moving from ARIMAX to NARX , underscoring the Sample Asset NAR vs NARX vs added predictive value of GPR data when used within AR ARIMAX January 1978 - Gold 0.27 0.88 a neural framework. Together, these results highlight September 2021 Silver 0.76 0.65 the effectiveness of neural networks in improving Crude oil 0.28 0.39 US Treasury security 0.34 0.37 forecast accuracy and integrating geopolitical signals, January 1978 - Gold 0.48 0.90 offering practical value to policymakers, investors, September 2022 Silver 0.39 0.67 and risk managers operating in uncertain macro- Crude oil 0.55 0.81 US Treasury security 0.19 0.65 financial conditions. January 1978 - Gold -0.18 0.64 September 2023 Silver 0.71 0.76 The deviation in silver price volatility highlights Crude oil 0.70 0.85 the diverse behaviour of safe assets under changing US Treasury security 0.33 0.75 geopolitical conditions. Unlike crude oil, and US Notes: 1. For each pairing of sample and asset, four models are built. 2. For the comparison metrics, in the first column NAR (Model A) Treasuries, which respond more predictably to is compared with AR (Model B). 3. For the comparison metrics, in the second column NARX geopolitical shocks, silver’s volatility reflects its dual (Model A) is compared with ARIMAX (Model B). role as both a safe-haven and an industrial metal. Its Source: Authors’ calculations.Decoding Safe Asset Volatility Amid Geopolitical Risks Using ARTICLE Neural Networks sensitivity to industrial demand and macroeconomic The sensitivity metric is calculated as: cycles leads to regime shifts that linear models often miss. This reinforces that safe-haven assets 1 ( ) do not react uniformly to global risks, and adaptive w her e, ( is _the numb_er of) risk levels, VOLi nonlinear models like neural networks are better represents the volatility forecast from the simulation suited to capture and forecast such complex, asset- n at ith risk level, and avg_GPRi denotes the average of specific dynamics. the GPR index specific to US from the simulation at Volatility Simulation ith risk level over all the lags as required by the model for each asset. Based on this metric, gold exhibits Each asset responds differently to changes in the lowest sensitivity to GPR changes. Using gold as geopolitical risk. To quantify this responsiveness, the base, we derive a relative sensitivity index for all we compute a sensitivity metric that captures how assets (Table 4), where higher values indicate greater volatility changes in response to variations in the GPR. responsiveness to geopolitical stress. Using the NARX model developed in the forecasting stage, asset volatilities across five GPR levels are Among the assets, crude oil emerges as most simulated. These levels are – observed, low, medium, sensitive to geopolitical shocks. Its price volatility high, and extreme (Chart 11). rises sharply with increased GPR, reflecting Chart 11: Volatility Simulation for March 2025 a. Gold Price b. Silver Price (GPR-US index, left scale; Volatility, right scale; (GPR-US index, left scale; Volatility, right scale; Geopolitical Risk Level, bottom scale) Geopolitical Risk Level, bottom scale) 12 0.004 12 0.008 10 10 0.003 0.006 8 8 6 0.002 6 0.004 4 4 0.001 0.002 2 2 0 0.000 0 0.000 Observed Low Medium High Extreme Observed Low Medium High Extreme Avg_GPR_USA Predicted Volatility Avg_GPR_USA Predicted Volatility c. Crude Oil Price d. US Treasury Security Yield (GPR-US index, left scale; Volatility, right scale; (GPR-US index, left scale; Volatility, right scale; Geopolitical Risk Level, bottom scale) Geopolitical Risk Level, bottom scale) 12 0.15 12 0.010 10 0.12 10 0.008 8 8 0.09 0.006 6 6 0.06 0.004 4 4 2 0.03 2 0.002 0 0.00 0 0.000 Observed Low Medium High Extreme Observed Low Medium High Extreme Avg_GPR_USA Predicted Volatility Avg_GPR_USA Predicted Volatility Note: “Observed” denotes the volatility forecast corresponding to the actual GPR-USA index available. Source: Authors’ calculations. RBI Bulletin December 2025 111ARTICLE Decoding Safe Asset Volatility Amid Geopolitical Risks Using Neural Networks haven assets, providing actionable insights for risk Table 4: Relative Sensitivity of Assets under Simulation for March 2025 (Relative to Gold) managers, policymakers and investors. Using a Asset Relative Sensitivity simulation-based sensitivity framework, the response Gold 1.00 of four major asset class – gold, silver, crude oil and Silver 1.92 US Treasury securities – to escalating geopolitical US Treasury security 2.31 tensions is analysed. The results offer a clearer Crude oil 10.92 Source: Authors’ calculations. understanding of asset behaviour under episodes of uncertainty and summarise the key results emerging exposure to supply disruptions, regional conflicts and sanctions, highlighting its vulnerability to from the analysis. geopolitical instability. In contrast, gold shows The findings show that crude oil is most sensitive minimal sensitivity, reaffirming its role as a safe to geopolitical shocks, consistent with its exposure haven. Investors often shift to gold during global to supply disruptions and regional conflicts. In uncertainty, which stabilises its volatility across risk contrast, gold remains the most stable, reaffirming regimes and supports its continued use in hedging its traditional role as a safe haven asset. Silver lies strategies during crises. in between; more volatile than gold due to industrial Silver exhibits intermediate sensitivity. As both demand exposure, but less sensitive than oil. US a precious metal and an industrial input, its volatility Treasury securities exhibit a steady rise in volatility responds to investor sentiment and geopolitical with increasing geopolitical risk, reflecting their role effects on industrial demand, placing its sensitivity as a flight-to-safety asset during global stress and between gold and crude oil. In contrast, US Treasury confirming the heterogenous volatility response securities show a steady rise in volatility as geopolitical across assets. risk increases2. This reflects flight to safety behaviour, where demand driven price changes lower yields but Importantly, the study also demonstrates generate moderate market volatility due to shifting the forecasting superiority of neural network capital flows. models, particularly the nonlinear neural network Overall, the simulation results reveal clear architecture. The empirical assessment highlights heterogeneity in the response of safe haven assets the nonlinear, time dependent effects of geopolitical to geopolitical risk. Crude oil is highly reactive, risk on asset price volatility. By incorporating gold remains stable, while silver and Treasuries country specific geopolitical risk indices, the occupy intermediate positions. These findings offer nonlinear autoregressive neural network model valuable guidance for portfolio diversification, risk with exogenous inputs consistently outperforms management and policy formulation amid growing traditional econometric benchmarks, thus offering a geopolitical uncertainty. more reliable tool for volatility forecasting in volatile VI. Conclusion macro-financial conditions and reinforcing the central This study highlights the complex relationship result that nonlinear approaches outperform linear between geopolitical risk and the volatility of safe models in geopolitical stress environments. 2 Similar steady rise in price volatility is observed for gold as well, although the magnitude of change is less as compared to that for US Treasury securities yield. 112 RBI Bulletin December 2025Decoding Safe Asset Volatility Amid Geopolitical Risks Using ARTICLE Neural Networks Annexure Reference Apergis, N., Bonato, M., Gupta, R., & Kyei, C. (2017). This section provides additional details on the Does geopolitical risks predict stock returns and volatility estimation methodology. volatility of leading defense companies? Evidence Volatility estimates from GARCH from a nonparametric approach. Defence and Peace Economics, 28(5), 542–554. Monthly log returns on asset prices (or yields) Baur, D. G., & Smales, L. A. (2020). Hedging geopolitical are used to estimate conditional volatility via GARCH risk with precious metals. Journal of Banking & models. ACF/PACF plots guide lag selection, while ADF, Finance, 112, 105217. KPSS, and Engle’s ARCH tests confirm stationarity Caldara, D., & Iacoviello, M. (2022). Measuring and heteroscedasticity (Table 5). Final GARCH model geopolitical risk. American Economic Review, 112 (4), parameters for each asset are reported in Table 6. 1194–1225. Table 5: Statistical Tests Gkillas, K., Gupta, R., & Wohar, M. E. (2018). Volatility Asset Test Test P-Value Result jumps: The role of geopolitical risks. Finance Research Statistic Letters, 24, 1–7. Gold ADF -12.83 0.001 Stationary Gupta, R., Karmakar, S., & Pierdzioch, C. (2024). KPSS 0.17 0.100 Stationary Engle’s ARCH 20.06 0.000 Conditional Safe havens, machine learning, and the sources of Heteroscedasticity geopolitical risk: A forecasting analysis using over a Silver ADF -13.06 0.001 Stationary century of data. Journal of International Money and KPSS 0.07 0.100 Stationary Finance, 126, 102653. Engle’s ARCH 65.83 0.000 Conditional Heteroscedasticity International Monetary Fund. (2025). Geopolitical Crude oil ADF -12.88 0.001 Stationary risks, implications for asset prices and financial KPSS 0.04 0.100 Stationary stability. In Global financial stability report, April 2025 Engle’s ARCH 84.68 0.000 Conditional Heteroscedasticity (Chapter 2). International Monetary Fund US Treasury ADF -12.00 0.001 Stationary Jiao, J.-W., Yin, J.-P., Xu, P.-F., Zhang, J., & Liu, Y. (2021). security KPSS 0.07 0.100 Stationary Transmission mechanisms of geopolitical risks to the Engle’s ARCH 31.18 0.000 Conditional Heteroscedasticity crude oil market: A pioneering two-stage geopolitical Note: Significance level of all tests are 5 Per cent. risk analysis approach. Energy, 223, 120063. Source: Authors’ calculations. Kundu, S., Dilip, A (2023). Changing Risk Appetite and Table 6: Parameter Estimates from GARCH Models Price Dynamics of Gold Vis-a-Vis Real and Financial Asset Parameter Value Standard t P-Value Assets: Perspective from the Indian Market. J. Quant. Error Statistic Econ. 21, 899–923. Constant 0.00008 0.000023 3.6358 0.00028 Liu, J., Ma, F., Tang, Y., & Zhang, Y. (2020). Geopolitical Gold GARCH{1} 0.80708 0.027795 29.037 0.00000 ARCH{1} 0.15318 0.022013 6.9588 0.00000 risk and oil volatility: A new insight. Energy Economics, Constant 0.00038 0.000091 4.1533 0.00003 92, 104934. Silver GARCH{1} 0.73466 0.045191 16.2569 0.00000 Narendra, K. S., & Parthasarathy, K. (1990). ARCH{1} 0.21311 0.044073 4.8355 0.00000 Constant 0.00088 0.000195 4.4927 0.00001 Identification and control of dynamical systems Crude oil GARCH{1} 0.49786 0.040391 12.3259 0.00000 using neural networks. IEEE Transactions on Neural ARCH{1} 0.50214 0.049362 10.1727 0.00000 Networks, 1(1), 4–27. US Constant 0.00021 0.000058 3.6589 0.00025 Zhang, Y., He, J., He, M., & Li, S. (2022). Geopolitical Treasury GARCH{1} 0.70876 0.032924 21.527 0.00000 security ARCH{1} 0.29124 0.030584 9.5223 0.00000 risk and stock market volatility: A global perspective. Source: Authors’ calculations Global Finance Journal, 54, 100639. RBI Bulletin December 2025 113CURRENT STATISTICS Select Economic Indicators Reserve Bank of India Money and Banking Prices and Production Government Accounts and Treasury Bills Financial Markets External Sector Payment and Settlement Systems Occasional SeriesCURRENT STATISTICS Contents No. Title Page 1 Select Economic Indicators 117 Reserve Bank of India 2 RBI – Liabilities and Assets 118 3 Liquidity Operations by RBI 119 4 Sale/ Purchase of U.S. Dollar by the RBI 120 4A Maturity Breakdown (by Residual Maturity) of Outstanding Forwards of RBI (US$ Million) 121 5 RBI's Standing Facilities 121 Money and Banking 6 Money Stock Measures 122 7 Sources of Money Stock (M) 123 3 8 Monetary Survey 124 9 Liquidity Aggregates 125 10 Reserve Bank of India Survey 126 11 Reserve Money – Components and Sources 126 12 Commercial Bank Survey 127 13 Scheduled Commercial Banks' Investments 127 14 Business in India – All Scheduled Banks and All Scheduled Commercial Banks 128 15 Deployment of Gross Bank Credit by Major Sectors 129 16 Industry-wise Deployment of Gross Bank Credit 130 17 State Co-operative Banks Maintaining Accounts with the Reserve Bank of India 131 18 (a) Flow of Financial Resources to Commercial Sector in India 132 18 (b) Outstanding Credit to Commercial Sector in India 133 Prices and Production 19 Consumer Price Index (Base: 2012=100) 134 20 Other Consumer Price Indices 134 21 Monthly Average Price of Gold and Silver in Mumbai 134 22 Wholesale Price Index 135 23 Index of Industrial Production (Base: 2011-12=100) 139 Government Accounts and Treasury Bills 24 Union Government Accounts at a Glance 139 25 Treasury Bills – Ownership Pattern 140 26 Auctions of Treasury Bills 140 Financial Markets 27 Daily Call Money Rates 141 28 Certificates of Deposit 142 29 Commercial Paper 142 RBI Bulletin December 2025 115No. Title Page 30 Average Daily Turnover in Select Financial Markets 142 31 New Capital Issues by Non-Government Public Limited Companies 143 External Sector 32 Foreign Trade 144 33 Foreign Exchange Reserves 144 34 Non-Resident Deposits 144 35 Foreign Investment Inflows 145 36 Outward Remittances under the Liberalised Remittance Scheme (LRS) for Resident Individuals 145 37 Indices of Nominal Effective Exchange Rate (NEER) and Real Effective Exchange Rate (REER) of the Indian Rupee 146 38 External Commercial Borrowings (ECBs) – Registrations 147 39 India’s Overall Balance of Payments (US $ Million) 148 40 India's Overall Balance of Payments (` Crore) 149 41 Standard Presentation of BoP in India as per BPM6 (US $ Million) 150 42 Standard Presentation of BoP in India as per BPM6 (` Crore) 151 43 India’s International Investment Position 152 Payment and Settlement Systems 44 Payment System Indicators 153 Occasional Series 45 Small Savings 155 46 Ownership Pattern of Central and State Governments Securities 156 47 Combined Receipts and Disbursements of the Central and State Governments 157 48 Financial Accommodation Availed by State Governments under various Facilities 158 49 Investments by State Governments 159 50 Market Borrowings of State Governments 160 51 (a) Flow of Financial Assets and Liabilities of Households - Instrument-wise 161 51 (b) Stocks of Financial Assets and Liabilities of Households- Select Indicators 164 Notes: .. = Not available. – = Nil/Negligible. P = Preliminary/Provisional. PR = Partially Revised. 116 RBI Bulletin December 2025CURRENT STATISTICS No. 1: Select Economic Indicators 2024-25 2025-26 Item 2024-25 Q1 Q2 Q1 Q2 1 2 3 4 5 1 Real Sector (% Change) 1.1 GVA at Basic Prices 6.4 6.5 5.8 7.6 8.1 1.1.1 Agriculture 4.6 1.5 4.1 3.7 3.5 1.1.2 Industry 4.5 7.8 2.1 5.8 7.9 1.1.3 Services 7.5 7.2 7.4 9.0 9.0 1.1a Final Consumption Expenditure 6.5 7.0 6.1 7.1 6.5 1.1b Gross Fixed Capital Formation 7.1 6.7 6.7 7.8 7.3 2024 2025 2024-25 Sep. Oct. Sep. Oct. 1 2 3 4 5 1.2 Index of Industrial Production 4. 0 3. 2 3 . 7 4 . 6 0 . 4 2 Money and Banking (% Change) 2.1 Scheduled Commercial Banks 2.1.1 Deposits 10.3 10.4 11.5 9.4 9.8 2.1.2 Credit # 11.0 12.3 11.8 10.8 11.3 2.1.2.1 Non-food Credit # 11.0 12.4 11.8 10.7 11.1 2.1.3 Investment in Govt. Securities 9. 7 6. 8 8 . 1 6 . 5 5 . 1 2.2 Money Stock Measures 2.2.1 Reserve Money (M0) 4.3 6.0 9.0 4.5 2.0 2.2.2 Broad Money (M3) 9.4 10.4 10.7 9.2 10.3 3 Ratios (%) 3.1 Cash Reserve Ratio 4.00 4.50 4.50 3.75 3.50 3.2 Statutory Liquidity Ratio 18.00 18.00 18.00 18.00 18.00 3.3 Cash-Deposit Ratio 4.3 5.1 5.2 4.1 3.8 3.4 Credit-Deposit Ratio 80.8 79.2 79.4 80.2 80.2 3.5 Incremental Credit-Deposit Ratio # 86.1 61.6 66.2 69.0 72.1 3.6 Investment-Deposit Ratio 29.7 29.6 29.9 28.8 28.5 3.7 Incremental Investment-Deposit Ratio 28.1 26.2 30.6 13.2 12.0 4 Interest Rates (%) 4.1 Policy Repo Rate 6.25 6.50 6.50 5.50 5.50 4.2 Fixed Reverse Repo Rate 3.35 3.35 3.35 3.35 3.35 4.3 Standing Deposit Facility (SDF) Rate * 6.00 6.25 6.25 5.25 5.25 4.4 Marginal Standing Facility (MSF) Rate 6.50 6.75 6.75 5.75 5.75 4.5 Bank Rate 6.50 6.75 6.75 5.75 5.75 4.6 Base Rate 9.10/10.40 9.10/10.40 9.10/10.40 8.50/10.30 8.35/10.00 4.7 MCLR (Overnight) 8.15/8.45 8.15/8.45 8.15/8.45 7.80/8.00 7.80/8.00 4.8 Term Deposit Rate >1 Year 6.00/7.25 6.00/7.25 6.00/7.25 5.85/6.60 5.85/6.60 4.9 Savings Deposit Rate 2.70/3.00 2.70/3.00 2.70/3.00 2.50/2.50 2.50/2.50 4.10 Call Money Rate (Weighted Average) 6.35 6.61 6.63 5.57 5.58 4.11 91-Day Treasury Bill (Primary) Yield 6.52 6.65 6.51 5.47 5.46 4.12 182-Day Treasury Bill (Primary) Yield 6.52 6.72 6.64 5.58 5.60 4.13 364-Day Treasury Bill (Primary) Yield 6.47 6.70 6.60 5.61 5.58 4.14 10-Year G-Sec Par Yield (FBIL) 6.62 6.78 6.81 6.61 6.50 5 Reference Rate and Forward Premia 5.1 INR-US$ Spot Rate (Rs. Per Foreign Currency) 85.5 8 83.6 7 84.0 8 88.7 2 88.7 2 5.2 INR-Euro Spot Rate (Rs. Per Foreign Currency) 92.32 93.46 90.96 103.62 102.67 5.3 Forward Premia of US$ 1-month (%) 3.12 1.65 1.49 2.19 1.94 3-month (%) 2.56 1.74 1.69 2.17 1.98 6-month (%) 2.28 2.11 2.01 2.23 2.14 6 Inflation (%) 6.1 All India Consumer Price Index 4.6 5.5 6.2 1.4 0.3 6.2 Consumer Price Index for Industrial Workers 3.39 4.2 4.4 2.8 2.2 6.3 Wholesale Price Index 2.3 1.9 2.8 0.2 -1.2 6.3.1 Primary Articles 5.2 6.5 8.3 -3.1 -6.2 6.3.2 Fuel and Power -1.3 -3.9 -4.3 -2.6 -2.6 6.3.3 Manufactured Products 1.7 1.1 1.8 2.3 1.5 7 Foreign Trade (% Change) 7.1 Imports 6.9 8.3 3.2 18.0 16.9 7.2 Exports 0. 1 -1. 0 16 . 6 6 . 2 -11 . 9 Note : Financial Benchmark India Pvt. Ltd. (FBIL) has commenced publication of the G-Sec benchmarks with effect from March 31, 2018 as per RBI circularFMRD.DIRD. 7/14.03.025/2017-18 dated March 31, 2018. FBIL has started dissemination of reference rates w.e.f. July 10, 2018. #: Bank credit growth and related ratios for all fortnights from December 3, 2021 to November 18, 2022 are adjusted for past reporting errors by select scheduled commercial banks (SCBs). Data include the impact of merger of a non-bank with a bank w.e.f. July 1, 2023. *: As per Press Release No. 2022-2023/41 dated April 08, 2022. RBI Bulletin December 2025 117Reserve Bank of India No. 2: RBI - Liabilities and Assets * (₹ Crore) Item As on the Last Friday/ Friday 2024-25 2024 2025 Nov. Oct. 31 Nov. 07 Nov. 14 Nov. 21 Nov. 28 1 2 3 4 5 6 7 1 Issue Department 1.1 Liabilities 1.1.1 Notes in Circulation 3683836 3511550 3780994 3803571 3810583 3822597 3827317 1.1.2 Notes held in Banking Department 11 14 12 11 16 13 16 1.1/1.2 Total Liabilities (Total Notes Issued) or Assets 3683847 3511564 3781006 3803582 3810599 3822610 3827333 1.2 Assets 1.2.1 Gold 235379 200142 320090 319088 336117 330350 335390 1.2.2 Foreign Securities 3448129 3311092 3460480 3484132 3474192 3492063 3491411 1.2.3 Rupee Coin 340 330 436 362 289 197 531 1.2.4 Government of India Rupee Securities - - - - - - - 2 Banking Department 2.1 Liabilities 2.1.1 Deposits 1709285 1441830 1542156 1507764 1515124 1500969 1416438 2.1.1.1 Central Government 100 101 100 100 100 100 100 2.1.1.2 Market Stabilisation Scheme - - - - - - 2.1.1.3 State Governments 42 42 42 42 42 43 42 2.1.1.4 Scheduled Commercial Banks 943060 1023815 842947 770670 782080 781205 778275 2.1.1.5 Scheduled State Co-operative Banks 7776 8311 7077 6721 6753 6691 6733 2.1.1.6 Non-Scheduled State Co-operative Banks 5963 5297 4612 4556 4717 4449 4586 2.1.1.7 Other Banks 46963 50545 43820 40117 39668 39828 40059 2.1.1.8 Others 593085 232464 481530 513339 499939 492222 417108 2.1.1.9 Financial Institution Outside India 112296 121255 162026 172219 181825 176433 169535 2.1.2 Other Liabilities 2150508 1914051 2574393 2562492 2620935 2635356 2670951 2.1/2.2 Total Liabilities or Assets 3859793 3355881 4116549 4070257 4136059 4136324 4087389 2.2 Assets 2.2.1 Notes and Coins 11 14 12 11 16 13 16 2.2.2 Balances Held Abroad 1413591 1532888 1581443 1529194 1544929 1552434 1520068 2.2.3 Loans and Advances 2.2.3.1 Central Government - - - - - - - 2.2.3.2 State Governments 26284 16465 20016 36937 31808 27060 18966 2.2.3.3 Scheduled Commercial Banks 251984 21293 5489 916 2158 15485 2144 2.2.3.4 Scheduled State Co-op.Banks - - - - - - - 2.2.3.5 Industrial Dev. Bank of India - - - - - - - 2.2.3.6 NABARD - - - - - - - 2.2.3.7 EXIM Bank - - - - - - - 2.2.3.8 Others 36426 8428 11539 9154 8167 9612 9659 2.2.3.9 Financial Institution Outside India 111768 120491 162524 172524 182380 176434 169769 2.2.4 Bills Purchased and Discounted 2.2.4.1 Internal - - - - - - - 2.2.4.2 Government Treasury Bills - - - - - - - 2.2.5 Investments 1560630 1272720 1732352 1720286 1734003 1733052 1734211 2.2.6 Other Assets 459101 383580 603174 601235 632598 622234 632557 2.2.6.1 Gold 429510 365807 582971 581146 612161 601658 610837 * Data are provisional. 118 RBI Bulletin December 2025CURRENT STATISTICS No. 3: Liquidity Operations by RBI (₹ Crore) Date Standing OMO (Outright) Net Injection (+)/ Liquidity Absorption (-) Liquidity Adjustment Facility Facilities (1+3+5+7+9-2-4-6 -8) Sale Purchase Variable Variable Reverse Rate Repo Rate MSF SDF Repo Reverse Repo Repo 1 2 3 4 5 6 7 8 9 10 Oct. 1, 2025 - - 7370 - 651 184677 - - - -176656 Oct. 2, 2025 - - - - 204 181620 - - - -181416 Oct. 3, 2025 - - - - 1512 201622 153 - - -199957 Oct. 4, 2025 - - - - 313 178791 - - - -178478 Oct. 5, 2025 - - - - 157 160593 - - - -160436 Oct. 6, 2025 - - - - 1158 169737 -768 - - -169347 Oct. 7, 2025 - - - - 1430 158517 -719 - - -157806 Oct. 8, 2025 - - - - 1231 139538 -4 - - -138311 Oct. 9, 2025 - - - 46860 15771 133799 0 - - -164888 Oct. 10, 2025 - - 37929 - 2783 194925 1176 - - -153037 Oct. 11, 2025 - - - - 1780 165273 - - - -163493 Oct. 12, 2025 - - - - 2367 171513 - - - -169146 Oct. 13, 2025 - - - - 14585 154542 - - - -139957 Oct. 14, 2025 - - - - 3164 140996 - - - -137832 Oct. 15, 2025 - - - 16285 2357 126237 -240 - - -140405 Oct. 16, 2025 - - - - 3956 139276 498 - - -134822 Oct. 17, 2025 - - 2750 - 7783 120474 585 - - -109356 Oct. 18, 2025 - - - - 5530 61374 - - - -55844 Oct. 19, 2025 - - - - 5942 61891 - - - -55949 Oct. 20, 2025 - - 163113 - 424 104425 - - - 59112 Oct. 21, 2025 - - - - 397 109627 - - - -109230 Oct. 22, 2025 - - - - 85 119420 - - - -119335 Oct. 23, 2025 - - 475 - 431 160431 - - - -159525 Oct. 24, 2025 - - 30750 - 7026 79899 - - - -42123 Oct. 25, 2025 - - - - 14304 78878 - - - -64574 Oct. 26, 2025 - - - - 16390 82049 - - - -65659 Oct. 27, 2025 - - 101810 - 3040 95046 - - - 9804 Oct. 28, 2025 - - 125521 - 529 129424 - - - -3374 Oct. 29, 2025 - - 58512 - 615 85235 460 - - -25648 Oct. 30, 2025 - - 100012 - 624 120630 1 - - -19993 Oct. 31, 2025 - - - - 5489 140138 - - - -134649 RBI Bulletin December 2025 119No. 4: Sale/ Purchase of U.S. Dollar by the RBI i) Operations in onshore / offshore OTC segment Item 2024 2025 2024-25 Oct. Sep. Oct. 1 2 3 4 1 Net Purchase/ Sale of Foreign Currency (US $ Million) (1.1-1.2) -34511 -9275 -7910 -11877 1.1 Purchase (+) 364200 27503 2200 17685 1.2 Sale (–) 398711 36778 10110 29562 2 ₹ equivalent at contract rate (₹ Crores) -291233 -77969 -69884 -104818 3 Cumulative (over end-March) (US $ Million) -34511 -728 -21702 -33579 (₹ Crore) -291233 -7023 -191488 -296306 4 Outstanding Net Forward Sales (-)/ Purchase (+) at the end of month (US -84345 -49180 -59405 -63605 $ Million) ii) Operations in currency futures segment Item 2024 2025 2024-25 Oct. Sep. Oct. 1 2 3 4 1 Net Purchase/ Sale of Foreign Currency (US $ Million) (1.1-1.2) 0 0 0 0 1.1 Purchase (+) 31415 2531 1311 2274 1.2 Sale (–) 31415 2531 1311 2274 2 Outstanding Net Currency Futures Sales (-)/ Purchase (+) at the end of 0 -3229 -1605 -1447 month (US $ Million) 120 RBI Bulletin December 2025CURRENT STATISTICS No. 4 A : Maturity Breakdown (by Residual Maturity) of Outstanding Forwards of RBI (US $ Million) Item As on October 31 , 2025 Long (+) Short (-) Net (1-2) 1 2 3 1. Upto 1 month 0 17060 -17060 2. More than 1 month and upto 3 months 0 19760 -19760 3. More than 3 months and upto 1 year 0 610 -610 4. More than 1 year 0 26175 -26175 Total (1+2+3+4) 0 63605 -63605 No. 5: RBI’s Standing Facilities (₹ Crore) Item As on the Last Reporting Fortnights 2024-25 2024 2025 Nov. 29 Jun. 27 Jul. 25 Aug. 22 Sep. 19 Oct. 31 Nov. 28 1 2 3 4 5 6 7 8 1 MSF 9961 18513 1065 1906 1818 310 5489 2144 2 Export Credit Refinance for Scheduled Banks 2.1 Limit - - - - - - - - 2.2 Outstanding - - - - - - - - 3 Liquidity Facility for PDs 3.1 Limit 9900 9900 14900 14900 14900 14900 14900 14900 3.2 Outstanding 9517 8428 7010 10299 10985 10319 11518 9637 4 Others 4.1 Limit 76000 76000 76000 76000 76000 76000 76000 76000 4.2 Outstanding - - - - - - - - 5 Total Outstanding (1+2.2+3.2+4.2) 19478 26941 8075 12205 12803 10629 17007 11781 RBI Bulletin December 2025 121Money and Banking No. 6: Money Stock Measures (₹ Crore) Item Outstanding as on March 31/last reporting Fortnights of the month/ reporting Fortnights 2024-25 2024 2025 Oct. 18 Oct. 03 Oct. 17 Oct. 31 1 2 3 4 5 1 Currency with the Public (1.1 + 1.2 + 1.3 – 1.4) 3630751 3415233 3698492 3729092 3720545 1.1 Notes in Circulation 3687816 3483562 3761894 3790325 3780994 1.2 Circulation of Rupee Coin 35889 34090 38121 38121 38488 1.3 Circulation of Small Coins 743 743 743 743 743 1.4 Cash on Hand with Banks 93696 103162 102266 100096 99680 2 Deposit Money of the Public 2953329 2786278 3330428 3233822 3360984 2.1 Demand Deposits with Banks 2840023 2687986 3216575 3118912 3245815 2.2 'Other' Deposits with Reserve Bank 113307 98292 113853 114910 115169 3 M1 (1 + 2) 6584081 6201510 7028920 6962914 7081529 4 Post Office Saving Bank Deposits 212331 200909 212331 212331 212331 5 M2 (3 + 4) 6796412 6402419 7241251 7175245 7293860 6 Time Deposits with Banks 20702508 20087772 21866350 21751523 21915977 7 M3 (3 + 6) 27286589 26289282 28895269 28714438 28997506 8 Total Post Office Deposits 1443555 1386751 1443555 1443555 1443555 9 M4 (7 + 8) 28730144 27676033 30338824 30157993 30441061 122 RBI Bulletin December 2025CURRENT STATISTICS No. 7 : Sources of Money Stock (M) 3 (₹ Crore) Sources Outstanding as on March 31/last reporting Fortnights of the month/reporting Fortnights 2024-25 2024 2025 Oct. 18 Oct. 03 Oct. 17 Oct. 31 1 2 3 4 5 1 Net Bank Credit to Government 8510825 7925482 8734167 8693936 8739870 1.1 RBI’s net credit to Government (1.1.1–1.1.2) 1508105 1132433 1538514 1491026 1529911 1.1.1 Claims on Government 1591591 1336185 1757512 1765985 1750740 1.1.1.1 Central Government 1558903 1312788 1735375 1735890 1730724 1.1.1.2 State Governments 32688 23398 22137 30095 20016 1.1.2 Government deposits with RBI 83485 203752 218998 274959 220829 1.1.2.1 Central Government 83443 203710 218955 274916 220786 1.1.2.2 State Governments 42 42 43 42 42 1.2 Other Banks’ Credit to Government 7002720 6793050 7195653 7202910 7209958 2 Bank Credit to Commercial Sector 19068129 18005269 20068221 20023678 20203749 2.1 RBI’s credit to commercial sector 38246 9175 12613 14936 13603 2.2 Other banks’ credit to commercial sector 19029883 17996094 20055608 20008742 20190146 2.2.1 Bank credit by commercial banks 18243972 17237674 19261332 19212429 19393655 2.2.2 Bank credit by co-operative banks 766659 737425 773813 775269 776084 2.2.3 Investments by commercial and co-operative banks in other securities 19252 20994 20463 21044 20407 3 Net Foreign Exchange Assets of Banking Sector (3.1 + 3.2) 6148527 5992868 6622726 6589610 6532531 3.1 RBIs net foreign exchange assets (3.1.1 - 3.1.2) 5550947 5630470 6035678 6002562 5945483 3.1.1 Gross foreign assets 5550956 5630473 6035678 6002564 5945482 3.1.2 Foreign liabilities 9 3 0 2 0 3.2 Other banks’ net foreign exchange assets 597580 362398 587048 587048 587048 4 Government’s Currency Liabilities to the Public 36632 34833 38864 38864 39231 5 Banking Sector’s Net Non-monetary Liabilities 6477524 5669170 6568708 6631649 6517874 5.1 Net non-monetary liabilities of RBI 2147427 1926618 2569200 2609138 2559728 5.2 Net non-monetary liabilities of other banks (residual) 4330098 3742552 3999508 4022511 3958146 M₃(1+2+3+4–5) 27286589 26289282 28895269 28714438 28997506 RBI Bulletin December 2025 123No. 8: Monetary Survey (₹ Crore) Item Outstanding as on March 31/last reporting Fortnights of the month/reporting Fortnights 2024-25 2024 2025 Oct. 18 Oct. 03 Oct. 17 Oct. 31 1 2 3 4 5 Monetary Aggregates NM₁ (1.1+1.2.1+1.3) 6584081 6201510 7028920 6962914 7081529 NM₂ (NM₁ + 1.2.2.1) 15768688 15117666 16730466 16613637 16803647 NM₃ (NM₂ +1.2.2.2 + 1.4 = 2.1 + 2.2 + 2.3 – 2.4 – 2.5) 27909568 26880587 29443842 29269762 29532475 1 Components 1.1 Currency with the Public 3630751 3415233 3698492 3729092 3720545 1.2 Aggregate Deposits of Residents 23250261 22501665 24775567 24564962 24850520 1.2.1 Demand Deposits 2840023 2687986 3216575 3118912 3245815 1.2.2 Time Deposits of Residents 20410239 19813679 21558992 21446050 21604705 1.2.2.1 Short-term Time Deposits 9184607 8916155 9701546 9650722 9722117 1.2.2.1.1 Certificates of Deposits (CDs) 527375 1138455 503933 508803 470625 1.2.2.2 Long-term Time Deposits 11225631 10897523 11857446 11795327 11882588 1.3 'Other' Deposits with RBI 113307 98292 113853 114910 115169 1.4 Call/Term Funding from Financial Institutions 915248 865397 855930 860798 846241 2 Sources 2.1 Domestic Credit 28802443 27114284 30048946 29999579 30220503 2.1.1 Net Bank Credit to the Government 8510825 7925482 8734167 8693936 8739870 2.1.1.1 Net RBI credit to the Government 1508105 1132433 1538514 1491026 1529911 2.1.1.2 Credit to the Government by the Banking System 7002720 6793050 7195653 7202910 7209958 2.1.2 Bank Credit to the Commercial Sector 20291618 19188801 21314780 21305643 21480633 2.1.2.1 RBI Credit to the Commercial Sector 38246 9175 12613 14936 13603 2.1.2.2 Credit to the Commercial Sector by the Banking System 20253372 19179626 21302166 21290707 21467030 2.1.2.2.1 Other Investments ( Non-SLR Securities) 1208294 1171485 1228317 1265649 1257601 2.2 Government's Currency Liabilities to the Public 36632 34833 38864 38864 39231 2.3 Net Foreign Exchange Assets of the Banking Sector 5605462 5495204 6185610 6066521 6054269 2.3.1 Net Foreign Exchange Assets of the RBI 5550947 5630470 6035678 6002562 5945483 2.3.2 Net Foreign Currency Assets of the Banking System 54514 -135266 149932 63959 108786 2.4 Capital Account 4481192 4450085 5375020 5383253 5349171 2.5 Other items (net) 2053777 1313649 1454558 1451948 1432356 124 RBI Bulletin December 2025CURRENT STATISTICS No. 9: Liquidity Aggregates (₹ Crore) Aggregates 2024-25 2024 2025 Oct. Aug. Sep. Oct. 1 2 3 4 5 1 NM₃ 27896780 26880587 28871731 28906851 29532475 2 Postal Deposits 756787 732774 798148 812817 812817 3 L₁ ( 1 + 2) 28653567 27613361 29669879 29719668 30345292 4 Liabilities of Financial Institutions 95148 68842 116169 116595 123930 4.1 Term Money Borrowings 10 31 5 5 5 4.2 Certificates of Deposit 80810 55520 100855 101105 108215 4.3 Term Deposits 14328 13291 15310 15485 15711 5 L₂ (3 + 4) 28748715 27682202 29786048 29836262 30469222 6 Public Deposits with Non-Banking Financial Companies 121178 .. .. 131730 .. 7 L₃ (5 + 6) 28869893 .. .. 29967993 .. Note : Figures in the columns might not add up to the total due to rounding off of numbers. RBI Bulletin December 2025 125No. 10: Reserve Bank of India Survey (₹ Crore) Item Outstanding as on March 31/last reporting Fortnights of the month/reporting Fortnights 2024-25 2024 2025 Oct. 18 Oct. 3 Oct. 17 Oct. 31 1 2 3 4 5 1 Components 1.1 Currency in Circulation 3724448 3518394 3800758 3829188 3820225 1.2 Bankers’ Deposits with the RBI 991488 1047801 941748 882417 898457 1.2.1 Scheduled Commercial Banks 926001 984541 883596 827461 842947 1.3 ‘Other’ Deposits with the RBI 113307 98292 113853 114910 115169 Reserve Money (1.1 + 1.2 + 1.3 = 2.1 + 2.2 + 2.3 – 2.4 – 2.5) 4829243 4664487 4856359 4826515 4833851 2 Sources 2.1 RBI’s Domestic Credit 1389090 925802 1351017 1394227 1408865 2.1.1 Net RBI credit to the Government 1508105 1132433 1538514 1491026 1529911 2.1.1.1 Net RBI credit to the Central Government (2.1.1.1.1 + 2.1.1.1.2 + 2.1.1.1.3 + 2.1.1.1.4 – 2.1.1.1.5) 1475460 1109078 1516420 1460973 1509938 2.1.1.1.1 Loans and Advances to the Central Government - - - - - 2.1.1.1.2 Investments in Treasury Bills - - - - - 2.1.1.1.3 Investments in dated Government Securities 1558574 1312480 1734994 1735337 1730288 2.1.1.1.3.1 Central Government Securities 1558574 1312480 1734994 1735337 1730288 2.1.1.1.4 Rupee Coins 329 308 381 553 436 2.1.1.1.5 Deposits of the Central Government 83443 203710 218955 274916 220786 2.1.1.2 Net RBI credit to State Governments 32646 23355 22094 30053 19974 2.1.2 RBI’s Claims on Banks -157261 -215806 -200110 -111735 -134649 2.1.2.1 Loans and Advances to Scheduled Commercial Banks -157261 -215806 -200110 -111735 -134649 2.1.3 RBI’s Credit to Commercial Sector 38246 9175 12613 14936 13603 2.1.3.1 Loans and Advances to Primary Dealers 9182 7223 10529 11058 11518 2.1.3.2 Loans and Advances to NABARD - - - - - 2.2 Government’s Currency Liabilities to the Public 36632 34833 38864 38864 39231 2.3 Net Foreign Exchange Assets of the RBI 5550947 5630470 6035678 6002562 5945483 2.3.1 Gold 668162 567032 876896 954886 903062 2.3.2 Foreign Currency Assets 4882794 5063441 5158782 5047677 5042421 2.4 Capital Account 1875114 1868537 2418756 2415361 2379213 2.5 Other Items (net) 272313 58081 150444 193777 180515 No. 11: Reserve Money - Components and Sources (₹ Crore) Item Outstanding as on March 31/last Fridays of the month/Fridays 2024-25 2024 2025 Oct. 25 Oct. 3 Oct. 10 Oct. 17 Oct. 24 Oct. 31 1 2 3 4 5 6 7 Reserve Money (1.1 + 1.2 + 1.3 = 2.1 + 2.2 + 2.3 + 2.4 + 2.5 – 2.6) 4829243 4738791 4856359 4810686 4826515 4826831 4833851 1 Components 1.1 Currency in Circulation 3724448 3534780 3800758 3809041 3829188 3834849 3820225 1.2 Bankers' Deposits with RBI 991488 1107212 941748 887906 882417 878170 898457 1.3 ‘Other’ Deposits with RBI 113307 96799 113853 113739 114910 113812 115169 2 Sources 2.1 Net Reserve Bank Credit to Government 1508105 1060149 1538514 1461246 1491026 1434476 1529911 2.2 Reserve Bank Credit to Banks -157261 -57604 -200110 -154373 -111735 -44622 -134649 2.3 Reserve Bank Credit to Commercial Sector 38246 10761 12613 12459 14936 15641 13603 2.4 Net Foreign Exchange Assets of RBI 5550947 5605308 6035678 6011205 6002562 5933939 5945483 2.5 Government's Currency Liabilities to the Public 36632 35180 38864 38864 38864 38864 39231 2.6 Net Non- Monetary Liabilities of RBI 2147427 1915002 2569200 2558715 2609138 2551467 2559728 126 RBI Bulletin December 2025CURRENT STATISTICS No. 12: Commercial Bank Survey (₹ Crore) Item Outstanding as on last reporting Fortnights of the month/ reporting Fortnights of the month 2024-25 2024 2025 Oct. 18 Oct. 3 Oct. 17 Oct. 31 1 2 3 4 5 1 Components 1.1 Aggregate Deposits of Residents 22288331 21534239 23791283 23577819 23864485 1.1.1 Demand Deposits 2698049 2544608 3071596 2973698 3100947 1.1.2 Time Deposits of Residents 19590283 18989631 20719688 20604121 20763538 1.1.2.1 Short-term Time Deposits 8815627 8545334 9323859 9271855 9343592 1.1.2.1.1 Certificates of Deposits (CDs) 527375 1138455 503933 508803 470625 1.1.2.2 Long-term Time Deposits 10774655 10444297 11395828 11332267 11419946 1.2 Call/Term Funding from Financial Institutions 915248 865397 855930 860798 846241 2 Sources 2.1 Domestic Credit 26156690 24903515 27375469 27370769 27551750 2.1.1 Credit to the Government 6697298 6490267 6875701 6884459 6889415 2.1.2 Credit to the Commercial Sector 19459392 18413248 20499768 20486310 20662335 2.1.2.1 Bank Credit 18243972 17237674 19261332 19212429 19393655 2.1.2.1.1 Non-food Credit 18207441 17219020 19218673 19159939 19323284 2.1.2.2 Net Credit to Primary Dealers 15458 12311 18505 16580 19546 2.1.2.3 Investments in Other Approved Securities 630 741 577 615 495 2.1.2.4 Other Investments (in non-SLR Securities) 1199332 1162522 1219354 1256686 1248639 2.2 Net Foreign Currency Assets of Commercial Banks (2.2.1-2.2.2-2.2.3) 54514 -135266 149932 63959 108786 2.2.1 Foreign Currency Assets 529621 312870 597784 514163 563826 2.2.2 Non-resident Foreign Currency Repatriable Fixed Deposits 292270 274093 307357 305474 311272 2.2.3 Overseas Foreign Currency Borrowings 182837 174043 140495 144730 143768 2.3 Net Bank Reserves (2.3.1+2.3.2-2.3.3) 791777 1291615 1173785 1026944 1065159 2.3.1 Balances with the RBI 882415 984541 883596 827461 842947 2.3.2 Cash in Hand 81874 91269 90080 87747 87563 2.3.3 Loans and Advances from the RBI 172512 -215806 -200110 -111735 -134649 2.4 Capital Account 2581908 2557377 2932094 2943722 2945787 2.5 Other items (net) (2.1+2.2+2.3-2.4-1.1-1.2) 1217493 1102851 1119880 1079333 1069182 2.5.1 Other Demand and Time Liabilities (net of 2.2.3) 878795 776573 906345 947686 938999 2.5.2 Net Inter-Bank Liabilities (other than to PDs) 118268 120447 102888 94449 97709 No. 13: Scheduled Commercial Banks’ Investments (₹ Crore) Item As on 2024 2025 March 21, 2025 Oct. 18 Sep. 19 Oct. 17 Oct. 31 1 2 3 4 5 1 SLR Securities 6697928 6491008 6846281 6885074 6889910 2 Other Government Securities (Non-SLR) 165500 158905 161725 163000 163460 3 Commercial Paper 63163 63415 74766 69682 64138 4 Shares issued by 4.1 PSUs 13874 14003 15049 15350 15125 4.2 Private Corporate Sector 95984 96676 99999 100886 100197 4.3 Others 7664 7515 7440 7508 7507 5 Bonds/Debentures issued by 5.1 PSUs 130308 119242 134665 131208 129333 5.2 Private Corporate Sector 248138 232143 249218 252590 251222 5.3 Others 150000 148322 165211 175594 175725 6 Instruments issued by 6.1 Mutual funds 119867 137472 142908 139967 138228 6.2 Financial institutions 204865 185401 204084 200903 203705 Note: Data against column Nos. (1), (2) & (3) are Final and for column Nos. (4) & (5) data are Provisional. Data include the impact of merger of a non-bank with a bank w.e.f. July 1, 2023. RBI Bulletin December 2025 127No. 14: Business in India - All Scheduled Banks and All Scheduled Commercial Banks (₹ Crore) Item As on the Last Reporting Fortnights (in case of March)/ Last Fortnights All Scheduled Banks All Scheduled Commercial Banks 2024 2025 2024 2025 2024-25 2024-25 Oct. Sep. Oct. Oct. Sep. Oct. 1 2 3 4 5 6 7 8 Number of Reporting Banks 208 208 196 196 135 135 121 121 1 Liabilities to the Banking System 458011 461959 465871 444760 451305 456793 457666 437163 1.1 Demand and Time Deposits from Banks 315675 299445 348667 331729 309414 294684 341020 324592 1.2 Borrowings from Banks 112027 138138 86883 85106 111976 138074 86864 85106 1.3 Other Demand and Time Liabilities 30310 24377 30320 27926 29916 24034 29783 27465 2 Liabilities to Others 25053097 24168976 26255947 26628147 24557481 23695315 25739212 26104765 2.1 Aggregate Deposits 23055487 22268274 24277740 24679611 22580601 21811286 23781174 24175757 2.1.1 Demand 2748263 2576598 3081919 3151638 2698049 2527554 3032021 3100947 2.1.2 Time 20307224 19691676 21195821 21527972 19882552 19283733 20749153 21074810 2.2 Borrowings 920568 922304 868196 850802 915248 917220 863308 846241 2.3 Other Demand and Time Liabilities 1077042 978397 1110011 1097733 1061632 966808 1094730 1082768 3 Borrowings from Reserve Bank 311466 30948 84836 5489 311466 30948 84836 5489 3.1 Against Usance Bills /Promissory Notes - - - - - - - - 3.2 Others 311466 30948 84836 5489 311466 30948 84836 5489 4 Cash in Hand and Balances with Reserve Bank 985044 1156513 1001948 950304 964289 1133410 981473 930510 4.1 Cash in Hand 84399 93424 86480 90383 81874 90430 83965 87563 4.2 Balances with Reserve Bank 900645 1063089 915468 859921 882415 1042981 897509 842947 5 Assets with the Banking System 432645 415954 458289 448553 348496 347173 367869 359000 5.1 Balances with Other Banks 273720 267325 314423 312351 215801 214836 251766 246578 5.1.1 In Current Account 13239 11859 22907 19796 10619 8521 20472 16006 5.1.2 In Other Accounts 260481 255466 291516 292555 205182 206314 231293 230572 5.2 Money at Call and Short Notice 44772 31346 39992 32904 25838 18904 18667 15790 5.3 Advances to Banks 43856 47217 31135 33545 39504 46589 30082 32719 5.4 Other Assets 70296 70066 72739 69753 67353 66845 67354 63913 6 Investment 6850574 6666871 7023056 7058968 6697928 6514977 6855716 6889910 6.1 Government Securities 6842024 6657864 7013124 7049263 6697298 6513979 6855258 6889415 6.2 Other Approved Securities 8550 9007 9932 9705 630 998 458 495 7 Bank Credit 18708286 17768822 19546159 19876054 18243972 17315981 19072256 19393655 7a Food Credit 87145 72843 95969 122345 36531 22204 43995 70371 7.1 Loans, Cash-credits and Overdrafts 18370704 17451631 19188757 19510008 17909851 17002083 18716640 19029403 7.2 Inland Bills-Purchased 76523 69489 81825 86157 74963 67977 81591 85941 7.3 Inland Bills-Discounted 222320 209055 239707 244557 221059 207905 238721 243556 7.4 Foreign Bills-Purchased 15357 15841 13237 12904 15122 15597 13036 12717 7.5 Foreign Bills-Discounted 23382 22807 22632 22428 22977 22419 22268 22039 Note: Data in column Nos. (4) & (8) are Provisional Data include the impact of merger of a non-bank with a bank w.e.f. July 1, 2023. 128 RBI Bulletin December 2025CURRENT STATISTICS No. 15: Deployment of Gross Bank Credit by Major Sectors (₹ Crore) Outstanding as on Growth(%) Mar. 21, Financial Sector 2025 2024 2025 year so far Y-o-Y Oct. 18 Sep. 19 Oct. 31 2025-26 2025 1 2 3 4 % % I. Bank Credit (II + III) 18243972 17419532 18902934 19390500 6.3 11.3 II. Food Credit 36531 30055 45284 70371 92.6 134.1 III. Non-food Credit 18207441 17389477 18857649 19320128 6.1 11.1 1. Agriculture & Allied Activities 2287060 2205579 2361595 2402610 5.1 8.9 2. Industry (Micro and Small, Medium and Large) 3985660 3812250 4136178 4192700 5.2 10.0 2.1 Micro and Small 798473 757113 924702 953572 19.4 25.9 2.2 Medium 363245 338367 385991 398071 9.6 17.6 2.3 Large 2823942 2716770 2825485 2841057 0.6 4.6 3. Services 5093565 4729329 5144227 5345246 4.9 13.0 3.1 Transport Operators 261575 249128 270335 275525 5.3 10.6 3.2 Computer Software 32915 30581 37978 39584 20.3 29.4 3.3 Tourism, Hotels & Restaurants 83366 80012 88240 91529 9.8 14.4 3.4 Shipping 7304 7782 9585 9959 36.3 28.0 3.5 Aviation 46072 46200 46332 47560 3.2 2.9 3.6 Professional Services 195957 186260 195597 200511 2.3 7.7 3.7 Trade 1184550 1078651 1196397 1227077 3.6 13.8 3.7.1. Wholesale Trade¹ 646099 570094 638058 655867 1.5 15.0 3.7.2 Retail Trade 538451 508557 558339 571210 6.1 12.3 3.8 Commercial Real Estate 523264 499115 564592 569245 8.8 14.1 3.9 Non-Banking Financial Companies (NBFCs)² of which, 1635102 1535999 1588698 1703567 4.2 10.9 3.9.1 Housing Finance Companies (HFCs) 323182 321159 324982 332125 2.8 3.4 3.9.2 Public Financial Institutions (PFIs) 228678 198419 205393 247504 8.2 24.7 3.10 Other Services³ 1123459 1015601 1146472 1180689 5.1 16.3 4. Personal Loans 5971696 5664806 6273708 6455946 8.1 14.0 4.1 Consumer Durables 23201 23415 22110 23646 1.9 1.0 4.2 Housing 3010477 2871841 3132868 3187475 5.9 11.0 4.3 Advances against Fixed Deposits 141842 127906 143924 150287 6.0 17.5 4.4 Advances to Individuals against share & bonds 10080 9060 9835 10006 -0.7 10.4 4.5 Credit Card Outstanding 284366 281392 281823 303073 6.6 7.7 4.6 Education 137456 130308 147176 149442 8.7 14.7 4.7 Vehicle Loans 622793 601970 646242 677349 8.8 12.5 4.8 Loan against gold jewellery⁴ 206284 147724 315684 337580 63.6 128.5 4.9 Other Personal Loans 1535197 1471189 1574047 1617089 5.3 9.9 5. Priority Sector (Memo) (i) Agriculture & Allied Activities⁵ 2287794 2200716 2327799 2437756 6.6 10.8 (ii) Micro & Small Enterprises⁶ 2239409 2077001 2520121 2613611 16.7 25.8 (iii) Medium Enterprises⁷ 601451 557808 627019 649366 8.0 16.4 (iv) Housing 746651 752218 974644 997896 33.6 32.7 (v) Education Loans 62826 62673 70834 74071 17.9 18.2 (vi) Renewable Energy 10325 7122 14842 10836 5.0 52.1 (vii) Social Infrastructure 1316 1122 939 921 -30.0 -17.9 (viii) Export Credit 12479 12239 11755 11533 -7.6 -5.8 (ix) Others 49552 58049 43467 41409 -16.4 -28.7 (x) Weaker Sections including net PSLC- SF/MF 1864606 1788692 1873464 1946670 4.4 8.8 Notes: (1) Data are provisional. Bank credit, Food credit and Non-food credit data are based on Section-42 return, which covers all scheduled commercial banks (SCBs), while sectoral non-food credit data are based on sector-wise and industry-wise bank credit (SIBC) return, which covers select banks accounting for about 95 per cent of total non-food credit extended by all SCBs, pertaining to the last reporting Friday of the month. Bank credit, Food credit and Non-food credit given for the period October 18, 2024 pertains to November 1, 2024. (2) Data since July 28, 2023 include the impact of the merger of a non-bank with a bank. 1 Wholesale trade includes food procurement credit outside the food credit consortium. 2 NBFCs include HFCs, PFIs, Microfinance Institutions (MFIs), NBFCs engaged in gold loan and others. 3 “Other Services” include Mutual Fund (MFs), Banking and Finance other than NBFCs and MFs, and other services which are not indicated elsewhere under services. 4 Since May 2024, a bank has changed the classification of a category of agricultural loan into “Loans against gold jewellery” under retail segment. 5 “Agriculture and Allied Activities” under the priority sector also include priority sector lending certificates (PSLCs). 6 “Micro and Small Enterprises” under the priority sector include credit to micro and small enterprises in industry and services sectors and also include PSLC. 7 “Medium Enterprises” under the priority sector include credit to medium enterprises in industry and services sectors. RBI Bulletin December 2025 129No. 16: Industry-wise Deployment of Gross Bank Credit (₹ Crore) Outstanding as on Growth(%) Financial 2024 2025 Y-o-Y Mar. 21, year so far Industry 2025 Oct. 18 Sep. 19 Oct. 31 2025-26 2025 1 2 3 4 % % 2 Industries (2.1 to 2.19) 3985660 3812250 4136178 4192700 5.2 10.0 2.1 Mining & Quarrying (incl. Coal) 56818 50177 59384 61980 9.1 23.5 2.2 Food Processing 219525 190279 207237 209696 -4.5 10.2 2.2.1 Sugar 28522 17191 16861 15165 -46.8 -11.8 2.2.2 Edible Oils & Vanaspati 20927 17331 19696 21111 0.9 21.8 2.2.3 Tea 5084 6429 5110 5115 0.6 -20.4 2.2.4 Others 164992 149328 165570 168304 2.0 12.7 2.3 Beverage & Tobacco 35515 31288 38050 35394 -0.3 13.1 2.4 Textiles 277267 256861 275090 280339 1.1 9.1 2.4.1 Cotton Textiles 107495 93127 97466 100513 -6.5 7.9 2.4.2 Jute Textiles 4288 4254 4708 4843 12.9 13.9 2.4.3 Man-Made Textiles 49186 47848 49881 50247 2.2 5.0 2.4.4 Other Textiles 116298 111632 123035 124736 7.3 11.7 2.5 Leather & Leather Products 12980 12639 13441 13327 2.7 5.4 2.6 Wood & Wood Products 27826 25320 28366 29080 4.5 14.8 2.7 Paper & Paper Products 52848 50090 54707 55870 5.7 11.5 2.8 Petroleum, Coal Products & Nuclear Fuels 154179 152974 185288 170576 10.6 11.5 2.9 Chemicals & Chemical Products 267815 259944 285196 291749 8.9 12.2 2.9.1 Fertiliser 32011 31511 31450 31699 -1.0 0.6 2.9.2 Drugs & Pharmaceuticals 88524 88282 91265 93054 5.1 5.4 2.9.3 Petro Chemicals 28797 27852 34840 36166 25.6 29.9 2.9.4 Others 118482 112299 127640 130830 10.4 16.5 2.10 Rubber, Plastic & their Products 103465 95675 105424 106769 3.2 11.6 2.11 Glass & Glassware 13443 12483 13782 13553 0.8 8.6 2.12 Cement & Cement Products 59753 60805 60968 62009 3.8 2.0 2.13 Basic Metal & Metal Product 433501 422884 461069 478319 10.3 13.1 2.13.1 Iron & Steel 300156 300264 312584 324416 8.1 8.0 2.13.2 Other Metal & Metal Product 133345 122621 148485 153903 15.4 25.5 2.14 All Engineering 240136 219696 267361 274831 14.4 25.1 2.14.1 Electronics 52863 50261 63242 61010 15.4 21.4 2.14.2 Others 187273 169435 204118 213821 14.2 26.2 2.15 Vehicles, Vehicle Parts & Transport Equipment 119450 113926 129500 127057 6.4 11.5 2.16 Gems & Jewellery 85814 92541 100437 102059 18.9 10.3 2.17 Construction 160037 147046 157658 162317 1.4 10.4 2.18 Infrastructure 1364369 1329328 1395706 1391028 2.0 4.6 2.18.1 Power 692160 653291 728187 743940 7.5 13.9 2.18.2 Telecommunications 123850 126896 109843 110034 -11.2 -13.3 2.18.3 Roads 334147 339979 348310 337545 1.0 -0.7 2.18.4 Airports 9156 8117 7761 5953 -35.0 -26.7 2.18.5 Ports 5916 5823 7847 7588 28.3 30.3 2.18.6 Railways 13415 11071 9894 7197 -46.3 -35.0 2.18.7 Other Infrastructure 185726 184150 183864 178770 -3.7 -2.9 2.19 Other Industries 300921 288294 297512 326746 8.6 13.3 Note: (1) Data since July 28, 2023 include the impact of the merger of a non-bank with a bank. 130 RBI Bulletin December 2025CURRENT STATISTICS No. 17: State Co-operative Banks Maintaining Accounts with the Reserve Bank of India (₹ Crore) Item As on Reporting Day 2024 2025 2024-25 Sep. 27 Jul. 25 Aug. 08 Aug. 22 Aug. 29 Sep. 05 Sep. 19 Sep. 26 1 2 3 4 5 6 7 8 9 Number of Reporting Banks 34 34 34 34 34 34 34 34 34 1 Aggregate Deposits (2.1.1.2+2.2.1.2) 146871.0 133236.7 146816.8 149137.5 146904.8 146892.1 147446.2 151034.0 148551.8 2 Demand and Time Liabilities 2.1 Demand Liabilities 2921 5.6 27646.4 26588.4 26595.4 26751.4 27698.5 27 979.4 2759 7.3 27650 .6 2.1.1 Deposits 2.1.1.1 Inter-Bank 9022.9 7743.1 7217.4 7296.8 7221.0 7278.0 7647.1 7310.3 7368.7 2.1.1.2 Others 14063.9 13473.1 13008.8 13510.1 13379.0 13202.4 13658.7 13625.5 13622.1 2.1.2 Borrowings from Banks 700.0 179.9 760.2 54.0 271.4 829.1 456.2 792.5 608.7 2.1.3 Other Demand Liabilities 5428.9 6250.3 5602.1 5734.4 5880.1 6389.0 6217.4 5869.0 6051.0 2.2 Time Liabilities 201100.7 181476.5 198088.7 199385.4 199285.7 197195.3 197317.4 201723.4 200770.1 2.2.1 Deposits 2.2.1.1 Inter-Bank 66874.3 59406.1 62813.5 62249.7 62174.4 62001.7 61996.9 62785.7 61947.2 2.2.1.2 Others 132807.1 119763.6 133808.0 135627.4 133525.8 133689.6 133787.5 137408.6 134929.7 2.2.2 Borrowings from Banks 643.9 1143.3 614.7 614.7 2738.9 611.7 611.7 611.2 611.2 2.2.3 Other Time Liabilities 775.4 1163.5 852.5 893.6 846.5 892.2 921.3 917.9 3282.0 3 Borrowing from Reserve Bank 699.5 944.5 1153.0 1143.0 1144.5 1054.4 999.5 1039.5 4 Borrowings from a notified bank / Government 126928.5 87696.9 114530.1 113046.3 114575.4 112260.4 113516.6 115950.8 116165.0 4.1 Demand 53459.8 23412.8 50687.4 50570.5 51208.4 49982.9 49983.0 52968.9 52721.9 4.2 Time 73468.7 64284.1 63842.7 62475.8 63367.0 62277.5 63533.6 62981.9 63443.0 5 Cash in Hand and Balances with Reserve Bank 13390.9 12368.8 12394.2 11984.9 11467.2 11065.3 11724.6 11915.4 11251.0 5.1 Cash in Hand 1052.1 780.9 807.2 833.6 747.0 437.3 780.3 944.9 785.4 5.2 Balance with Reserve Bank 12338.8 11587.9 11587.0 11151.3 10720.1 10628.0 10944.3 10970.6 10465.7 6 Balances with Other Banks in Current Account 1656.3 1658.2 1180.3 1048.6 908.6 981.1 1038.2 1071.2 1372.6 7 Investments in Government Securities 77220.1 73488.7 83374.4 84320.6 85538.8 86245.8 86480.7 86633.1 85526.0 8 Money at Call and Short Notice 26531.1 15615.3 20692.8 21553.9 21350.7 20842.1 21095.5 23026.6 24402.8 9 Bank Credit (10.1+11) 174828.8 138973.3 170198.2 170459.0 171092.8 170084.7 171363.2 171716.7 171610.0 10 Advances 10.1 Loans, Cash-Credits and Overdrafts 174590.4 138795.8 169936.2 170193.2 170854.0 169841.2 171115.2 171600.4 171489.2 10.2 Due from Banks 12460 7.6 143516.4 116943.7 116598.0 116930.7 1 18007.5 118 549.0 12061 8.4 120950 .7 11 Bills Purchased and Discounted 238.4 177.5 261.9 265.8 238.8 243.5 248.0 116.3 120.8 RBI Bulletin December 2025 131No. 18 (a): Flow of Financial Resources to Commercial Sector in India (₹ Crore) April-March Up to November 28 Source 2023-24 2024-25 2024-25 2025-26 P 1 2 3 4 5 1 Non-Food Bank Credit 21,40,243 17,98,321 10,48,619 12,40,071 2 Non-Bank Sources (2.1+2.2) 12,63,721 17,10,457 7,86,083 10,16,620 2.1 Domestic Sources 10,20,302 13,85,609 5,85,742 7,48,761 2.1.1 Equity Issuances by Non-Financial Entities 1,35,008 3,81,161 2,25,409 1,77,782 2.1.2 Corporate Bond Issuances by Non-Financial Entities 1,67,374 1,97,795 46,489 2,60,963 2.1.3 Hybrid Instruments (REITs/ InvITs) by Non-Financial Entities 39,024 31,442 10,611 10,098 2.1.4 Commercial Paper Issuances by Non-Financial Entities 19,712 18,819 73,382 75,932 2.1.5 Credit by Housing Finance Companies (Net of Bank Borrowings) 1,41,816 1,34,852 -20,202 -1,776 2.1.6 Credit by RBI-regulated All India Financial Institutions 73,386 99,501 9,903 -26,576 2.1.7 Credit by Non-Banking Financial Companies (Net of Bank Borrowings) 4,43,982 5,22,037 2,40,150 2,52,338 2.2 Foreign Sources 2,43,419 3,24,848 2,00,341 2,67,859 2.2.1 External Commercial Borrowings by Non-Financial Entities 27,916 19,201 7,066 26,454 2.2.2 ADR/GDR by Non-Financial Entities 0 0 0 0 2.2.3 Short-term Credit from Abroad -6,741 58,859 63,150 24,960 2.2.4 Foreign Direct Investment to India 2,22,244 2,46,788 1,30,126 2,16,445 3 Total Flow of Resources (1+2) 34,03,964 35,08,778 18,34,702 22,56,691 P: Provisional. The coverage of data for columns 4 and 5 from Sources No.: 2.1.1, 2.1.2, 2.1.3, 2.1.5, 2.1.6, 2.2.1 and 2.2.2: Up to October. 2.1.7, 2.2.3 and 2.2.4: Up to September. Notes: i) Non-food bank credit pertains to scheduled commercial banks (SCBs) and excludes credit extended by co-operative banks. ii) Credit extended by banks, NBFCs and HFCs is inclusive of personal loans. iii) Data on all items are presented on net basis, except equity and hybrid instruments which are on gross basis. iv) All India Financial Institutions (AIFIs) include National Bank for Agriculture and Rural Development (NABARD), National Housing Bank (NHB), Small Industries Development Bank of India (SIDBI), Export-Import Bank of India (EXIM Bank), and National Bank for Financing Infrastructure and Development (NaBFID). Credit extended by AIFIs excludes refinancing to SCBs, NBFCs, and HFCs, and direct loans to domestic and foreign governments/institutions. v) Data pertaining to HDFC Limited, which merged with HDFC Bank effective from July 1, 2023, is included under credit by Housing Finance Companies prior to its merger while it is included under bank credit post-merger. vi) D ata on credit by Housing Finance Companies (HFCs) and Non-Banking Financial Companies (NBFCs) has been adjusted for the conversion of some HFCs into NBFCs. Sources: RBI; SEBI; AIFIs; and RBI staff estimates. 132 RBI Bulletin December 2025No. 18 (b): Outstanding Credit to Commercial Sector in India (₹ crore) Percentage Variation At End-March As on November 28 At End-March As on November 28 Source 2024 2025 2024 2025 2023 2024 2025 2023 2024 2025 P over over o ver over 2023 2024 2023 2024 P 1 2 3 4 5 6 7 8 9 10 11 1 Non-Food Bank Credit 1,36,55,330 1,64,09,083 1,82,07,441 1,57,83,763 1,74,57,702 1,94,47,512 20.2 11.0 10.6 11.4 2 Non-Bank Sources (2.1+2.2) 74,43,0 91 77,56, 314 88,8 5,434 73, 03,121 81 ,96,473 9 5,90,566 4.2 14.6 12.2 17.0 2.1 Domestic Sources 53,95,038 56,59,037 66,37,411 51,96,143 60,08,758 71,98,292 4.9 17.3 15.6 19.8 2.1.1 Corporate Bond Issuan ces by Non-Financial 16,58,140 18,25,514 20,23,310 16,81,580 18,72,003 22,84,273 10.1 10.8 11.3 22.0 Entities 2.1.2 Commercial Paper Issuances by Non-Financial 89,816 1,09,528 1,28,347 1,19,66 6 1,82,9 09 2,04 ,279 21.9 17.2 52.8 11.7 Ent ities 2.1.3 Credit by Housing Finance Companies 10,39,420 5,98,965 6,27,125 5,77,200 5,78,763 6,25,350 -42.4 4.7 0.3 8.0 (Net of Bank Borrowings) 2.1.4 Cre dit by RBI-regu lated All India Financial Institutions 3,51,224 4,24,610 5,24,111 3,25,30 3 4,34,5 13 4,97 ,535 20.9 23.4 33.6 14.5 2.1.5 Credit by Non-Bankin g Financial Companies 22,56,439 27,00,421 33,34,518 24,92,39 4 29,40,5 71 35,86 ,856 19.7 23.5 18.0 22.0 (Net of Bank Borrowings) 2.2 Foreign Sources 20,48,053 20,97,277 22,48,023 21,06,978 21,87,714 23,92,274 2.4 7.2 3.8 9.4 2.2.1 Ext ernal Commercial Borrowings by 10,29,403 10,71,240 11,33,592 10,74,240 10,93,328 12,10,664 4.1 5.8 1.8 10.7 Non-Financial Entities 2.2.2 Short-term Credit from Abroad 10,18,650 10,26,037 11,14,432 10,32,738 10,94,386 11,81,610 0.7 8.6 6.0 8.0 3 Total Credit (1+2) 2,10,98,421 2,41,65,397 2,70,92,875 2,30,86,884 2,56,54,175 2,90,38,078 14.5 12.1 11.1 13.2 P: Provisional. The coverage of data for columns 5, 6 and 7 from Sources No.: 2.1.1, 2.1.3, 2.1.4 and 2.2.1: As at end-October. 2.1.5 and 2.2.2: As at end-September. Notes: i) Non-food bank credit pertains to scheduled commercial banks (SCBs) and excludes credit extended by co-operative banks. Including credit extended by co-operative banks (viz., urban co-operative banks, state co-operative banks, and district central co-operative banks), non-food bank credit at end- March 2023 and 2024 stood at ₹1,46,22,252 crore and ₹1,74,63,724 crore, respectively. Accordingly, total outstanding credit at end-March 2023 and 2024 stood at ₹2,20,65,343 crore and ₹2,52,20,038 crore, respectively. ii) Data on non-bank sources excludes issuances of equities and hybrid instruments under domestic sources and foreign direct investment in equities under foreign sources. iii) In case of corporate bonds, the outstanding data for end-March 2024 and 2025 are based on SEBI’s new series of data on bonds issued by financial and non-financial corporations. The outstanding data for end-March 2023 is worked out by adjusting the flow of 2023-24 from outstanding data for end- March 2024. iv) Flows based on outstanding data may not tally with the flows provided in Table 1 due to: (a) Merger of HDFC Limited with HDFC Bank on July 1, 2023; (b) Conversion of some Housing Finance Companies into Non-Banking Financial Companies; and (c) Valuation effect in case of foreign sources. v) Data is exclusive of current and non-current trade payables representing domestic liabilities in case of non-financial non-government public and private limited companies as data are not available. Sources: RBI; SEBI; AIFIs; and RBI staff estimates. RBI Bulletin December 2025 133Prices and Production No. 19: Consumer Price Index (Base: 2012=100) Group/Sub group 2024-25 Rural Urban Combined Rural Urban Combined Nov.24 Oct.25 Nov.25 (P) Nov.24 Oct.25 Nov.25 (P) Nov.24 Oct.25 Nov.25 (P) 1 2 3 4 5 6 7 8 9 10 11 12 1 Food and beverages 198.6 205.3 201.1 206.2 198.8 199.7 212.3 206.4 207.5 208.4 201.6 202.6 1.1 Cereals and products 195.0 193.7 194.6 198.1 197.2 197.4 195.5 197.9 197.8 197.3 197.4 197.5 1.2 Meat and fish 222.3 231.9 225.7 220.9 224.2 225.2 229.8 236.5 237.7 224.0 228.5 229.6 1.3 Egg 192.8 197.5 194.6 199.3 196.6 207.5 204.8 201.8 211.5 201.4 198.6 209.0 1.4 Milk and products 186.3 187.0 186.6 187.1 190.9 191.1 187.8 193.3 193.6 187.4 191.8 192.0 1.5 Oils and fats 175.4 165.5 171.8 186.8 202.4 202.4 172.8 185.0 185.0 181.7 196.0 196.0 1.6 Fruits 188.3 194.2 191.0 190.7 208.4 205.7 193.7 205.9 204.8 192.1 207.2 205.3 1.7 Vegetables 222.1 269.6 238.2 260.0 196.6 201.3 315.4 240.4 247.2 278.8 211.5 216.9 1.8 Pulses and products 208.0 213.5 209.8 214.5 180.4 180.4 219.4 184.4 184.9 216.2 181.7 181.9 1.9 Sugar and confectionery 130.4 132.6 131.2 131.1 136.8 136.6 133.2 138.0 138.2 131.8 137.2 137.1 1.10 Spices 228.5 223.9 227.0 229.9 221.3 222.3 224.4 219.3 219.8 228.1 220.6 221.5 1.11 Non-alcoholic beverages 185.2 173.9 180.5 186.0 191.2 191.0 174.7 180.8 180.5 181.3 186.9 186.6 1.12 Prepared meals, snacks, sweets 199.4 209.7 204.2 200.5 207.2 207.5 210.8 218.8 219.0 205.3 212.6 212.8 2 Pan, tobacco and intoxicants 207.3 212.6 208.7 208.1 213.6 213.9 212.1 219.3 219.7 209.2 215.1 215.4 3 Clothing and footwear 197.9 186.7 193.5 199.0 201.4 201.7 187.4 190.8 190.7 194.4 197.2 197.3 3.1 Clothing 198.8 188.8 194.9 199.9 202.6 203.0 189.6 193.5 193.5 195.8 199.0 199.3 3.2 Footwear 192.7 174.7 185.2 193.4 194.0 193.4 175.5 175.7 175.2 186.0 186.4 185.8 4 Housing -- 181.5 181.5 -- -- -- 183.0 188.1 188.4 183.0 188.1 188.4 5 Fuel and light 181.2 169.7 176.9 180.8 183.8 184.4 169.6 174.5 174.6 176.6 180.3 180.7 6 Miscellaneous 189.3 180.7 185.1 190.4 201.4 201.7 181.8 191.0 191.3 186.2 196.4 196.7 6.1 Household goods and services 185.7 177.1 181.6 186.4 189.0 189.3 178.0 182.4 182.5 182.4 185.9 186.1 6.2 Health 198.4 193.2 196.4 199.3 206.2 206.5 194.0 200.9 201.0 197.3 204.2 204.4 6.3 Transport and communication 175.5 164.8 169.9 176.6 178.2 178.4 165.7 166.9 167.0 170.9 172.3 172.4 6.4 Recreation and amusement 180.1 175.5 177.5 181.0 182.9 183.1 176.4 178.7 178.8 178.4 180.5 180.7 6.5 Education 190.8 186.2 188.1 192.0 197.6 197.7 187.8 194.8 194.7 189.5 196.0 195.9 6.6 Personal care and effects 204.3 206.2 205.1 206.0 254.9 255.9 207.7 255.7 257.2 206.7 255.2 256.4 General Index (All Groups) 194.9 190.0 192.6 199.4 199.0 199.6 193.2 195.4 195.9 196.5 197.3 197.9 Source: National Statistical Office, Ministry of Statistics and Programme Implementation, Government of India. P: Provisional No. 20: Other Consumer Price Indices Item Base Year Linking 2024-25 2024 2025 Factor Oct. Sep. Oct. 1 2 3 4 5 6 1 Consumer Price Index for Industrial Workers 2016 2.88 142.6 144.5 147.3 147.7 2 Consumer Price Index for Agricultural Labourers 2019 9.69 - 1315.0 136.2 136.4 3 Consumer Price Index for Rural Labourers 2019 9.78 - 1326.0 136.4 136.5 Source: Labour Bureau, Ministry of Labour and Employment, Government of India. CPI-AL and RL indices for 2024 (Base Year 2019) are calculated using the published inflation rates. No. 21: Monthly Average Price of Gold and Silver in Mumbai Item 2024-25 2024 2025 Oct. Sep. Oct. 1 2 3 4 1 Standard Gold (₹ per 10 grams) 75842 76713 109591 121908 2 Silver (₹ per kilogram) 89131 93352 129257 155904 Source: India Bullion & Jewellers Association Ltd., Mumbai for Gold and Silver prices in Mumbai. 134 RBI Bulletin December 2025CURRENT STATISTICS No. 22: Wholesale Price Index (Base: 2011-12 = 100) Commodities Weight 2024-25 2024 2025 Nov. Sep. Oct.(P) Nov.(P) 1 2 3 4 5 6 1 ALL COMMODITIES 100.000 154.9 156.4 155.0 154.8 155.9 1.1 PRIMARY ARTICLES 22.618 192.5 197.9 189.4 188.2 192.1 1.1.1 FOOD ARTICLES 15.256 205.3 213.7 200.0 199.8 204.8 1.1.1.1 Food Grains (Cereals+Pulses) 3.462 210.1 214.7 204.5 204.4 205.3 1.1.1.2 Fruits & Vegetables 3.475 241.4 271.9 219.2 216.7 234.5 1.1.1.3 Milk 4.440 185.8 185.2 191.0 191.2 191.4 1.1.1.4 Eggs, Meat & Fish 2.402 173.4 173.1 175.3 174.0 176.7 1.1.1.5 Condiments & Spices 0.529 232.7 244.3 202.1 206.2 210.8 1.1.1.6 Other Food Articles 0.948 213.6 216.8 216.3 223.0 224.5 1.1.2 NON-FOOD ARTICLES 4.119 161.7 162.8 168.1 164.4 166.5 1.1.2.1 Fibres 0.839 161.4 159.4 169.2 168.0 163.6 1.1.2.2 Oil Seeds 1.115 181.5 185.6 202.5 196.8 203.3 1.1.2.3 Other non-food Articles 1.960 138.7 140.1 140.1 139.5 138.6 1.1.2.4 Floriculture 0.204 277.4 270.0 244.5 212.1 244.9 1.1.3 MINERALS 0.833 229.0 229.4 242.5 242.4 253.3 1.1.3.1 Metallic Minerals 0.648 219.2 219.8 236.1 235.8 248.5 1.1.3.2 Other Minerals 0.185 263.4 263.2 265.0 265.7 270.2 1.1.4 CRUDE PETROLEUM & NATURAL GAS 2.410 151.3 146.7 140.5 136.2 134.0 1.2 FUEL & POWER 13.152 150.0 149.9 143.4 145.0 146.5 1.2.1 COAL 2.138 135.6 135.5 136.1 136.1 136.1 1.2.1.1 Coking Coal 0.647 143.4 143.4 146.4 146.4 146.4 1.2.1.2 Non-Coking Coal 1.401 125.8 125.8 126.6 126.6 126.6 1.2.1.3 Lignite 0.090 232.4 230.9 208.5 209.0 209.0 1.2.2 MINERAL OILS 7.950 156.2 154.0 148.7 149.7 148.7 1.2.3 ELECTRICITY 3.064 144.1 149.4 134.9 138.8 148.1 1.3 MANUFACTURED PRODUCTS 64.231 142.6 143.1 145.2 145.1 145.0 1.3.1 MANUFACTURE OF FOOD PRODUCTS 9.122 172.0 177.5 178.9 179.0 178.6 1.3.1.1 Processing and Preserving of meat 0.134 155.7 154.1 158.3 158.7 157.9 1.3.1.2 Processing and Preserving of fish, Crustaceans, Molluscs and products thereof 0.204 144.9 148.9 148.5 151.4 150.4 1.3.1.3 Processing and Preserving of fruit and Vegetables 0.138 132.6 132.7 135.1 135.5 134.4 1.3.1.4 Vegetable and Animal oils and Fats 2.643 168.5 183.2 186.9 186.8 185.7 1.3.1.5 Dairy products 1.165 180.8 182.0 185.1 185.9 187.6 1.3.1.6 Grain mill products 2.010 186.9 190.4 186.5 185.5 184.7 1.3.1.7 Starches and Starch products 0.110 167.0 169.0 150.8 149.6 148.4 1.3.1.8 Bakery products 0.215 170.5 173.1 176.9 177.2 177.0 1.3.1.9 Sugar, Molasses & honey 1.163 139.1 138.1 143.8 144.4 144.6 1.3.1.10 Cocoa, Chocolate and Sugar confectionery 0.175 160.6 160.6 176.8 174.4 175.5 1.3.1.11 Macaroni, Noodles, Couscous and Similar farinaceous products 0.026 156.7 158.1 159.9 161.2 163.9 1.3.1.12 Tea & Coffee products 0.371 190.7 190.2 189.1 189.9 188.5 1.3.1.13 Processed condiments & salt 0.163 192.6 194.5 189.3 188.7 190.7 1.3.1.14 Processed ready to eat food 0.024 152.7 152.8 156.4 156.4 155.7 1.3.1.15 Health supplements 0.225 185.1 192.0 189.6 192.4 190.5 1.3.1.16 Prepared animal feeds 0.356 204.1 205.6 204.4 205.3 204.3 1.3.2 MANUFACTURE OF BEVERAGES 0.909 134.1 134.7 135.7 135.9 135.7 1.3.2.1 Wines & spirits 0.408 136.0 137.1 139.6 139.4 138.7 1.3.2.2 Malt liquors and Malt 0.225 138.7 139.1 140.6 140.7 140.6 1.3.2.3 Soft drinks; Production of mineral waters and Other bottled waters 0.275 127.5 127.7 125.9 126.6 127.3 1.3.3 MANUFACTURE OF TOBACCO PRODUCTS 0.514 177.8 177.0 181.3 181.6 181.4 1.3.3.1 Tobacco products 0.514 177.8 177.0 181.3 181.6 181.4 RBI Bulletin December 2025 135No. 22: Wholesale Price Index (Contd.) (Base: 2011-12 = 100) Commodities Weight 2024-25 2024 2025 Nov. Sep. Oct.(P) Nov.(P) 1 2 3 4 5 6 1.3.4 MANUFACTURE OF TEXTILES 4.881 136.3 136.1 138.2 138.5 138.7 1.3.4.1 Preparation and Spinning of textile fibres 2.582 121.4 120.8 120.4 120.2 119.8 1.3.4.2 Weaving & Finishing of textiles 1.509 158.3 158.7 164.8 165.5 167.0 1.3.4.3 Knitted and Crocheted fabrics 0.193 124.0 122.7 126.7 127.9 125.9 1.3.4.4 Made-up textile articles, Except apparel 0.299 160.4 159.7 160.7 161.0 161.8 1.3.4.5 Cordage, Rope, Twine and Netting 0.098 142.7 143.2 162.9 164.3 165.3 1.3.4.6 Other textiles 0.201 134.9 136.8 133.9 134.4 133.8 1.3.5 MANUFACTURE OF WEARING APPAREL 0.814 153.4 153.7 156.1 156.5 157.1 1.3.5.1 Manufacture of Wearing Apparel (woven), Except fur Apparel 0.593 150.9 151.0 153.9 154.8 154.9 1.3.5.2 Knitted and Crocheted apparel 0.221 160.1 161.2 162.0 161.0 162.8 1.3.6 MANUFACTURE OF LEATHER AND RELATED PRODUCTS 0.535 125.3 125.8 127.4 127.3 127.4 1.3.6.1 Tanning and Dressing of leather; Dressing and Dyeing of fur 0.142 106.1 108.1 109.3 108.7 108.8 1.3.6.2 Luggage, HandbAgs, Saddlery and Harness 0.075 142.5 142.6 142.7 142.9 143.2 1.3.6.3 Footwear 0.318 129.7 129.8 131.8 131.9 131.9 1.3.7 MANUFACTURE OF WOOD AND PRODUCTS OF WOOD AND CORK 0.772 149.2 148.5 150.2 151.1 151.0 1.3.7.1 Saw milling and Planing of wood 0.124 141.1 142.9 141.3 143.3 142.3 1.3.7.2 Veneer sheets; Manufacture of plywood, Laminboard, Particle board and Other panels and Boards 0.493 148.6 147.2 149.5 150.3 150.4 1.3.7.3 Builder's carpentry and Joinery 0.036 215.3 214.2 215.3 215.4 213.9 1.3.7.4 Wooden containers 0.119 140.6 139.8 142.7 143.4 143.9 1.3.8 MANUFACTURE OF PAPER AND PAPER PRODUCTS 1.113 139.2 138.5 140.2 140.3 140.5 1.3.8.1 Pulp, Paper and Paperboard 0.493 144.6 143.4 144.3 145.0 145.6 1.3.8.2 Corrugated paper and Paperboard and Containers of paper and Paperboard 0.314 147.3 148.5 150.2 149.9 149.9 1.3.8.3 Other articles of paper and Paperboard 0.306 122.4 120.2 123.4 122.7 122.7 1.3.9 PRINTING AND REPRODUCTION OF RECORDED MEDIA 0.676 187.3 186.7 190.7 190.1 189.9 1.3.9.1 Printing 0.676 187.3 186.7 190.7 190.1 189.9 1.3.10 MANUFACTURE OF CHEMICALS AND CHEMICAL PRODUCTS 6.465 136.5 136.4 137.0 136.8 136.5 1.3.10.1 Basic chemicals 1.433 138.6 138.6 141.1 141.2 140.6 1.3.10.2 Fertilizers and Nitrogen compounds 1.485 143.1 143.5 143.0 143.2 143.5 1.3.10.3 Plastic and Synthetic rubber in primary form 1.001 133.6 133.2 134.4 132.8 132.0 1.3.10.4 Pesticides and Other agrochemical products 0.454 128.8 129.3 130.8 132.1 130.6 1.3.10.5 Paints, Varnishes and Similar coatings, Printing ink and Mastics 0.491 139.5 138.5 138.3 137.9 138.0 1.3.10.6 Soap and Detergents, Cleaning and Polishing preparations, Perfumes and Toilet preparations 0.612 139.7 139.9 142.2 142.1 142.2 1.3.10.7 Other chemical products 0.692 135.4 135.3 132.5 132.3 132.7 1.3.10.8 Man-made fibres 0.296 104.9 103.0 102.7 102.1 100.9 1.3.11 MANUFACTURE OF PHARMACEUTICALS, MEDICINAL CHEMICAL AND BOTANICAL PRODUCTS 1.993 144.3 144.1 145.9 146.2 146.1 1.3.11.1 Pharmaceuticals, Medicinal chemical and Botanical products 1.993 144.3 144.1 145.9 146.2 146.1 1.3.12 MANUFACTURE OF RUBBER AND PLASTICS PRODUCTS 2.299 129.0 128.6 129.1 128.9 128.5 1.3.12.1 Rubber Tyres and Tubes; Retreading and Rebuilding of Rubber Tyres 0.609 115.6 116.7 114.7 114.6 113.8 1.3.12.2 Other Rubber Products 0.272 112.1 111.7 113.3 112.6 112.9 1.3.12.3 Plastics products 1.418 138.1 137.0 138.3 138.2 137.8 1.3.13 MANUFACTURE OF OTHER NON-METALLIC MINERAL PRODUCTS 3.202 131.5 131.4 133.3 133.0 132.2 1.3.13.1 Glass and Glass products 0.295 163.2 162.1 162.7 162.8 163.2 1.3.13.2 Refractory products 0.223 121.6 123.5 124.0 123.4 124.5 1.3.13.3 Clay Building Materials 0.121 124.4 127.5 134.8 133.9 134.1 1.3.13.4 Other Porcelain and Ceramic Products 0.222 124.6 124.6 125.6 126.1 126.1 1.3.13.5 Cement, Lime and Plaster 1.645 130.4 130.1 132.6 132.0 130.2 136 RBI Bulletin December 2025CURRENT STATISTICS No. 22: Wholesale Price Index (Contd.) (Base: 2011-12 = 100) Commodities Weight 2024-25 2024 2025 Nov. Sep. Oct.(P) Nov.(P) 1 2 3 4 5 6 1.3.13.6 Articles of Concrete, Cement and Plaster 0.292 139.2 139.6 139.3 139.9 138.8 1.3.13.7 Cutting, Shaping and Finishing of Stone 0.234 134.4 135.2 139.3 140.0 140.2 1.3.13.8 Other Non-Metallic Mineral Products 0.169 95.2 93.7 91.9 91.6 92.7 1.3.14 MANUFACTURE OF BASIC METALS 9.646 139.7 138.6 137.7 137.1 136.9 1.3.14.1 Inputs into steel making 1.411 133.6 132.1 132.4 131.6 131.3 1.3.14.2 Metallic Iron 0.653 141.8 138.7 127.6 126.4 126.1 1.3.14.3 Mild Steel - Semi Finished Steel 1.274 117.9 117.5 115.4 114.6 114.1 1.3.14.4 Mild Steel -Long Products 1.081 140.4 140.2 135.6 134.4 133.8 1.3.14.5 Mild Steel - Flat products 1.144 134.2 131.9 130.6 129.2 127.4 1.3.14.6 Alloy steel other than Stainless Steel- Shapes 0.067 135.4 133.7 127.7 126.3 124.3 1.3.14.7 Stainless Steel - Semi Finished 0.924 131.1 126.8 122.7 118.4 118.8 1.3.14.8 Pipes & tubes 0.205 164.7 163.5 161.9 162.1 161.2 1.3.14.9 Non-ferrous metals incl. precious metals 1.693 157.4 157.7 164.9 167.7 169.2 1.3.14.10 Castings 0.925 144.9 145.4 143.5 143.7 144.1 1.3.14.11 Forgings of steel 0.271 172.2 172.8 176.3 173.7 173.5 1.3.15 MANUFACTURE OF FABRICATED METAL PRODUCTS, EXCEPT MACHINERY AND EQUIPMENT 3.155 136.0 135.3 137.0 137.0 136.0 1.3.15.1 Structural Metal Products 1.031 130.8 129.3 131.9 130.7 129.7 1.3.15.2 Tanks, Reservoirs and Containers of Metal 0.660 149.5 146.9 149.8 152.6 149.8 1.3.15.3 Steam generators, Except Central Heating Hot Water Boilers 0.145 109.8 111.3 113.5 113.8 113.1 1.3.15.4 Forging, Pressing, Stamping and Roll-Forming of Metal; Powder Metallurgy 0.383 138.0 141.5 132.8 131.6 132.1 1.3.15.5 Cutlery, Hand Tools and General Hardware 0.208 102.0 102.2 104.8 104.2 104.4 1.3.15.6 Other Fabricated Metal Products 0.728 144.9 144.3 148.5 148.6 147.9 1.3.16 MANUFACTURE OF COMPUTER, ELECTRONIC AND OPTICAL PRODUCTS 2.009 121.5 121.3 121.9 122.5 121.4 1.3.16.1 Electronic Components 0.402 117.9 117.3 120.3 120.8 121.1 1.3.16.2 Computers and Peripheral Equipment 0.336 134.2 133.6 129.7 129.7 129.7 1.3.16.3 Communication Equipment 0.310 146.0 145.9 147.2 147.6 147.6 1.3.16.4 Consumer Electronics 0.641 101.1 100.2 99.6 100.6 97.2 1.3.16.5 Measuring, Testing, Navigating and Control equipment 0.181 119.9 120.9 126.6 126.8 127.8 1.3.16.6 Watches and Clocks 0.076 167.9 172.7 175.2 175.0 175.0 1.3.16.7 Irradiation, Electromedical and Electrotherapeutic equipment 0.055 114.4 115.2 114.1 118.4 114.7 1.3.16.8 Optical instruments and Photographic equipment 0.008 107.4 108.7 117.9 117.9 118.8 1.3.17 MANUFACTURE OF ELECTRICAL EQUIPMENT 2.930 133.7 133.8 135.4 135.8 136.0 1.3.17.1 Electric motors, Generators, Transformers and Electricity distribution and Control apparatus 1.298 132.3 132.5 133.3 133.5 133.2 1.3.17.2 Batteries and Accumulators 0.236 141.3 141.7 145.2 144.8 145.5 1.3.17.3 Fibre optic cables for data transmission or live transmission of images 0.133 118.6 117.5 116.3 117.3 117.3 1.3.17.4 Other electronic and Electric wires and Cables 0.428 154.4 154.5 160.8 162.5 163.8 1.3.17.5 Wiring devices, Electric lighting & display equipment 0.263 118.4 117.8 118.5 118.6 118.6 1.3.17.6 Domestic appliances 0.366 131.8 131.8 131.3 131.5 131.9 1.3.17.7 Other electrical equipment 0.206 123.4 124.8 126.5 126.0 126.7 1.3.18 MANUFACTURE OF MACHINERY AND EQUIPMENT 4.789 130.8 130.5 132.4 132.6 133.0 1.3.18.1 Engines and Turbines, Except aircraft, Vehicle and Two wheeler engines 0.638 132.8 133.6 137.3 138.2 138.6 1.3.18.2 Fluid power equipment 0.162 134.5 134.6 134.7 134.7 135.2 1.3.18.3 Other pumps, Compressors, Taps and Valves 0.552 118.5 118.7 120.6 120.7 121.0 1.3.18.4 Bearings, Gears, Gearing and Driving elements 0.340 128.5 128.1 130.4 131.0 131.9 1.3.18.5 Ovens, Furnaces and Furnace burners 0.008 86.6 86.5 88.2 87.5 88.4 1.3.18.6 Lifting and Handling equipment 0.285 130.0 130.0 130.5 131.0 131.9 RBI Bulletin December 2025 137No. 22: Wholesale Price Index (Concld.) (Base: 2011-12 = 100) Commodities Weight 2024-25 2024 2025 Nov. Sep. Oct.(P) Nov.(P) 1 2 3 4 5 6 1.3.18.7 Office machinery and Equipment 0.006 130.2 130.2 130.2 130.2 130.2 1.3.18.8 Other general-purpose machinery 0.437 145.3 142.8 140.7 140.9 142.8 1.3.18.9 Agricultural and Forestry machinery 0.833 145.5 145.6 146.0 145.5 145.9 1.3.18.10 Metal-forming machinery and Machine tools 0.224 123.2 123.1 127.4 127.6 127.4 1.3.18.11 Machinery for mining, Quarrying and Construction 0.371 89.8 89.5 92.9 93.0 93.4 1.3.18.12 Machinery for food, Beverage and Tobacco processing 0.228 126.1 126.0 126.4 126.4 126.8 1.3.18.13 Machinery for textile, Apparel and Leather production 0.192 141.4 138.2 146.9 147.4 143.8 1.3.18.14 Other special-purpose machinery 0.468 144.9 144.3 147.7 147.6 147.6 1.3.18.15 Renewable electricity generating equipment 0.046 69.2 68.6 69.3 69.3 69.3 1.3.19 MANUFACTURE OF MOTOR VEHICLES, TRAILERS AND SEMI-TRAILERS 4.969 129.9 129.4 130.8 130.4 130.4 1.3.19.1 Motor vehicles 2.600 130.6 129.7 131.2 130.3 130.1 1.3.19.2 Parts and Accessories for motor vehicles 2.368 129.1 129.0 130.4 130.5 130.8 1.3.20 MANUFACTURE OF OTHER TRANSPORT EQUIPMENT 1.648 145.2 145.7 152.1 152.1 151.7 1.3.20.1 Building of ships and Floating structures 0.117 180.5 177.9 190.7 190.7 190.7 1.3.20.2 Railway locomotives and Rolling stock 0.110 108.9 107.8 110.0 110.7 110.7 1.3.20.3 Motor cycles 1.302 146.0 147.0 153.4 153.3 152.9 1.3.20.4 Bicycles and Invalid carriages 0.117 134.9 133.3 137.8 137.8 138.0 1.3.20.5 Other transport equipment 0.002 163.2 162.9 165.9 166.5 167.0 1.3.21 MANUFACTURE OF FURNITURE 0.727 160.3 162.9 164.1 164.5 164.1 1.3.21.1 Furniture 0.727 160.3 162.9 164.1 164.5 164.1 1.3.22 OTHER MANUFACTURING 1.064 183.8 183.8 236.6 236.2 240.7 1.3.22.1 Jewellery and Related articles 0.996 185.4 185.3 241.5 241.0 245.8 1.3.22.2 Musical instruments 0.001 201.9 205.2 198.3 205.4 206.3 1.3.22.3 Sports goods 0.012 164.9 167.8 172.7 172.7 173.0 1.3.22.4 Games and Toys 0.005 163.1 163.6 165.8 166.8 168.9 1.3.22.5 Medical and Dental instruments and Supplies 0.049 158.6 158.6 160.9 162.1 162.1 2 FOOD INDEX 24.378 192.9 200.2 192.1 192.0 195.0 Source: Office of the Economic Adviser, Ministry of Commerce and Industry, Government of India. 138 RBI Bulletin December 2025CURRENT STATISTICS No. 23: Index of Industrial Production (Base:2011-12=100) Industry Weight 2023-24 2024-25 April-October October 2024-25 2025-26 2024 2025 1 2 3 4 5 6 7 General Index 100.00 146.7 152.6 149.5 153.6 150.3 150.9 1 Sectoral Classification 1.1 Mining 14.37 128.9 132.8 123.7 121.4 128.5 126.2 1.2 Manufacturing 77.63 144.7 150.6 147.4 153.2 148.4 151.1 1.3 Electricity 7.99 198.3 208.6 215.9 215.8 207.8 193.4 2 Use-Based Classification 2.1 Primary Goods 34.05 147.7 153.5 150.3 150.4 149.8 148.9 2.2 Capital Goods 8.22 106.6 112.6 108.4 115.8 109.2 111.8 2.3 Intermediate Goods 17.22 157.3 164.0 161.7 169.4 165.0 166.5 2.4 Infrastructure/ Construction Goods 12.34 176.3 188.2 182.8 198.4 184.2 197.2 2.5 Consumer Durables 12.84 118.6 128.0 128.0 133.2 129.8 129.2 2.6 Consumer Non-Durables 15.33 153.7 151.4 147.3 144.1 146.4 139.9 Source : Central Statistics Office, Ministry of Statistics and Programme Implementation, Government of India. Government Accounts and Treasury Bills No. 24: Union Government Accounts at a Glance (₹ Crore) Financial Year April – October 2025-26 Percentage to Budget Item (Budget 2025-26 2024-25 Estimates (Actuals) (Actuals) Estimates) 2025-26 2024-25 1 2 3 4 5 1 Revenue Receipts 3420409 1763380 1704267 51.6 54.5 1.1 Tax Revenue (Net) 2837409 1274301 1304973 44.9 50.5 1.2 Non-Tax Revenue 583000 489079 399294 83.9 73.2 2 Non Debt Capital Receipt 76000 37095 18807 48.8 24.1 2.1 Recovery of Loans 29000 13392 13275 46.2 47.4 2.2 Other Receipts 47000 23703 5532 50.4 11.1 3 Total Receipts (excluding borrowings) (1+2) 3496409 1800475 1723074 51.5 53.7 4 Revenue Expenditure 3944255 2007876 2007353 50.9 54.1 of which : 4.1 Interest Payments 1276338 673715 596347 52.8 51.3 5 Capital Expenditure 1121090 617743 466545 55.1 42.0 6 Total Expenditure (4+5) 5065345 2625619 2473898 51.8 51.3 7 Revenue Deficit (4-1) 523846 244496 303086 46.7 52.2 8 Fiscal Deficit (6-3) 1568936 825144 750824 52.6 46.5 9 Gross Primary Deficit (8-4.1) 292598 151429 154477 51.8 34.3 Source: Controller General of Accounts (CGA), Ministry of Finance, Government of India and Union Budget 2025-26. RBI Bulletin December 2025 139No. 25: Treasury Bills – Ownership Pattern (₹ Crore) 2024-25 2024 2025 Item Nov. 1 Sep. 26 Oct. 3 Oct. 10 Oct. 17 Oct. 24 Oct. 31 1 2 3 4 5 6 7 8 1 91-day 1.1 Banks 26554 3961 11815 10660 11602 10319 9715 9157 1.2 Primary Dealers 25258 12580 19755 23671 20571 20971 21139 20086 1.3 State Governments 40315 94833 73862 72886 74186 76186 83886 86636 1.4 Others 115688 79259 108330 103569 103727 102610 101046 99657 2 182-day 2.1 Banks 44887 39229 54592 55121 53652 55590 53119 52288 2.2 Primary Dealers 62218 31156 41109 36101 42238 37158 40008 38487 2.3 State Governments 11078 12339 17780 17780 17780 20230 18930 17930 2.4 Others 104994 80115 67199 72678 69009 73151 73773 77025 3 364-day 3.1 Banks 72304 76754 69483 70539 67256 67296 70652 73818 3.2 Primary Dealers 86939 116452 74274 76499 78714 79774 78381 73811 3.3 State Governments 37389 35195 48138 45266 45951 44695 45103 45149 3.4 Others 162757 171795 167943 164662 167429 166331 164366 165772 4 14-day Intermediate 4.1 Banks 4.2 Primary Dealers 4.3 State Governments 188072 120316 121170 164213 220800 174282 184194 178061 4.4 Others 572 173 1252 1252 542 1614 1709 1058 Total Treasury Bills (Excluding 14 day 790381 753667 754280 749432 752117 754311 760120 759815 Intermediate T Bills) # # 14D intermediate T-Bills are non-marketable unlike 91D, 182D and 364D T-Bills. These bills are ‘intermediate’ by nature as these are liquidated to replenish shortfall in the daily minimum cash balances of State Governments. Note: Primary Dealers (PDs) include banks undertaking PD business. No. 26: Auctions of Treasury Bills (Amount in ₹ Crore) Date of Notified Bids Received Bids Accepted Total Cut- Implicit Yield Auction Amount Total Face Value Total Face Value Issue off at Cut-off Price Number Number (6+7) Price (per cent) Competitive Non- Competitive Non- ( ₹ ) Competitive Competitive 1 2 3 4 5 6 7 8 9 10 91-day Treasury Bills 2025-26 Oct. 1 7000 83 19830 216 34 6984 216 7200 98.65 5.4881 Oct. 8 7000 99 23183 7119 35 6981 7119 14100 98.67 5.4251 Oct. 15 7000 107 23593 9416 53 6985 9416 16400 98.66 5.4350 Oct. 23 7000 85 20721 12810 36 6990 12810 19800 98.66 5.4593 Oct. 29 7000 93 25518 19027 46 6973 19027 26000 98.66 5.4580 182-day Treasury Bills 2025-26 Oct. 1 6000 78 15191 7 33 5993 7 6000 97.29 5.5899 Oct. 8 6000 77 26065 6 21 5994 6 6000 97.31 5.5460 Oct. 15 6000 76 15621 2460 44 5990 2460 8450 97.31 5.5473 Oct. 23 6000 66 22023 2507 36 5993 2507 8500 97.29 5.5863 Oct. 29 6000 69 13005 612 42 5988 612 6600 97.28 5.5990 364-day Treasury Bills 2025-26 Oct. 1 6000 88 22247 22 24 5984 22 6005 94.71 5.5999 Oct. 8 6000 125 28392 4197 27 5977 4197 10174 94.76 5.5494 Oct. 15 6000 100 24783 1329 44 5915 1329 7244 94.76 5.5490 Oct. 23 6000 80 21410 760 45 5990 760 6750 94.73 5.5790 Oct. 29 6000 112 19585 737 60 5988 737 6725 94.73 5.5813 140 RBI Bulletin December 2025CURRENT STATISTICS Financial Markets No. 27: Daily Call Money Rates (Per cent per annum) Range of Rates Weighted Average Rates As on Borrowings/ Lendings Borrowings/ Lendings 1 2 October 01 ,2025 4.75-5.45 5.37 October 03 ,2025 4.75-5.45 5.36 October 04 ,2025 4.75-5.24 5.02 October 06 ,2025 4.75-5.40 5.34 October 07 ,2025 4.85-5.40 5.35 October 08 ,2025 4.75-5.40 5.34 October 09 ,2025 4.75-6.00 5.51 October 10 ,2025 4.75-5.75 5.58 October 13 ,2025 4.75-5.60 5.47 October 14 ,2025 4.85-5.50 5.39 October 15 ,2025 4.75-5.60 5.37 October 16 ,2025 4.85-6.10 5.40 October 17 ,2025 4.85-5.98 5.52 October 18 ,2025 4.85-5.50 5.04 October 20 ,2025 4.50-5.68 5.61 October 23 ,2025 4.40-5.60 5.45 October 24 ,2025 4.85-6.00 5.58 October 27 ,2025 4.85-5.75 5.58 October 28 ,2025 4.85-5.68 5.56 October 29 ,2025 4.85-5.80 5.56 October 30 ,2025 4.85-5.70 5.56 October 31 ,2025 4.75-5.75 5.63 November 01 ,2025 4.85-5.60 5.12 November 03 ,2025 4.70-5.60 5.42 November 04 ,2025 4.75-5.55 5.42 November 06 ,2025 4.80-5.50 5.40 November 07 ,2025 4.85-5.45 5.39 November 10 ,2025 4.75-5.45 5.34 November 11 ,2025 4.85-5.60 5.34 November 12 ,2025 4.80-5.40 5.34 November 13 ,2025 4.85-5.40 5.33 November 14 ,2025 4.50-5.60 5.47 November 15 ,2025 4.80-5.40 5.01 Note: Includes Notice Money. RBI Bulletin December 2025 141No. 28: Certificates of Deposit 2024 2025 Item Nov. 29 Oct. 17 Oct. 31 Nov. 14 Nov. 28 1 2 3 4 5 1 Amount Outstanding (₹ Crore) 491658.72 502668.21 514877.08 534617.43 570508.16 1.1 Issued during the fortnight (₹ Crore) 40434.94 24607.72 24530.39 54948.90 77875.33 2 Rate of Interest (per cent) 6.98-7.60 5.50-6.40 5.76-6.46 5.50-6.63 5.50-6.87 No. 29: Commercial Paper Item 2024 2025 Nov. 30 Oct. 15 Oct. 31 Nov. 15 Nov. 30 1 2 3 4 5 1 Amount Outstanding (₹ Crore) 445122.05 495678.60 479629.50 501658.00 501649.20 1.1 Reported during the fortnight (₹ Crore) 64504.65 30794.65 52397.55 66525.85 69177.70 2 Rate of Interest (per cent) 7.00-12.61 5.71-12.49 5.79-14.93 5.86-9.71 5.79-11.49 No. 30: Average Daily Turnover in Select Financial Markets (₹ Crore) Item 2024-25 2024 2025 Nov. 1 Sep. 26 Oct. 3 Oct. 10 Oct. 17 Oct. 24 Oct. 31 1 2 3 4 5 6 7 8 1 Call Money 18990 16124 31298 21716 27723 29553 23253 27641 2 Notice Money 2506 1374 656 10024 1246 5964 362 7214 3 Term Money 941 685 1038 1907 1768 1380 1461 1782 4 Triparty Repo 692068 781433 738792 856666 683446 855476 631977 896945 5 Market Repo 578912 567993 681777 823769 742310 814505 630603 789909 6 Repo in Corporate Bond 5212 3420 15960 16112 17407 13715 12710 14800 7 Forex (US $ million) 131877 98958 140364 141439 147461 140094 100069 139519 8 Govt. of India Dated Securities 56065 91164 131047 154006 138118 144369 98294 86389 9 State Govt. Securities 3971 4998 7932 9646 7187 6868 5131 6943 10 Treasury Bills 10.1 91-Day 2514 3709 4180 8047 6762 3808 5008 3238 10.2 182-Day 2218 6064 1619 4363 5017 4708 2208 2813 10.3 364-Day 1854 3736 3423 4773 2658 3460 3543 4047 10.4 Cash Management Bills 0 0 0 0 0 0 0 11 Total Govt. Securities (8+9+10) 66622 109670 148202 180835 159742 163214 114184 103429 11.1 RBI 1715 111 1619 561 410 1106 636 609 142 RBI Bulletin December 2025CURRENT STATISTICS No. 31: New Capital Issues by Non-Government Public Limited Companies (Amount in ₹ Crore) 2024-25 2024-25 (Apr.-Oct.) 2025-26 (Apr.-Oct.) * Oct. 2024 Oct. 2025 * Security & Type of Issue No. of Amount No. of Amount No. of Amount No. of Amount No. of Amount Issues Issues Issues Issues Issues 1 2 3 4 5 6 7 8 9 10 1 Equity Shares 464 210190 302 121633 320 128515 47 35653 63 42833 1.1 Public 322 190478 215 109257 239 112956 29 34983 52 41783 1.2 Rights 142 19712 87 12376 81 15559 18 670 11 1050 2 Public Issue of 43 8149 25 5526 25 6113 4 670 3 834 Bonds/ Debentures 3 Total (1+2) 507 218339 327 127159 345 134628 51 36323 66 43667 3.1 Public 365 198627 240 114783 264 119069 33 35653 55 42617 3.2 Rights 142 19712 87 12376 81 15559 18 670 11 1050 * : Data is Provisional Note : 1. Since April 2020, monthly data on equity issues is compiled on the basis of their listing date. 2. Figures in the columns might not add up to the total due to rounding off numbers. 3. The table covers only public and rights issuances of equity and debt. It does not include data on private placement of debt, qualified institutional placements and preferential allotments. Source : Securities and Exchange Board of India. RBI Bulletin December 2025 143CURRENT STATISTICS External Sector No. 32: Foreign Trade 2024 2025 2024-25 Item Unit Oct. Jun. Jul. Aug. Sep. Oct. 1 2 3 4 5 6 7 1 Exports ₹ Crore 3703412 327573 300410 318973 304579 319642 303746 US $ Million 437705 38983 34971 37041 34802 36190 34354 1.1 Oil ₹ Crore 535157 37085 38272 35754 36703 42117 34790 US $ Million 63383 4413 4455 4152 4194 4769 3935 1.2 Non-oil ₹ Crore 3168255 290488 262138 283219 267876 277526 268957 US $ Million 374321 34570 30515 32889 30608 31422 30419 2 Imports ₹ Crore 6089909 546776 464625 558752 542401 612051 672503 US $ Million 720241 65070 54087 64885 61976 69297 76061 2.1 Oil ₹ Crore 1570226 158683 118531 134077 116081 123944 130802 US $ Million 185779 18884 13798 15570 13264 14033 14794 2.2 Non-oil ₹ Crore 4519683 388093 346094 424676 426320 488107 541701 US $ Million 534462 46185 40289 49315 48712 55264 61267 3 Trade Balance ₹ Crore -2386497 -219203 -164214 -239779 -237822 -292408 -368757 US $ Million -282537 -26086 -19116 -27844 -27174 -33107 -41707 3.1 Oil ₹ Crore -1035069 -121597 -80258 -98323 -79378 -81827 -96012 US $ Million -122396 -14471 -9343 -11418 -9070 -9265 -10859 3.2 Non-oil ₹ Crore -1351428 -97606 -83956 -141456 -158444 -210581 -272745 US $ Million -160141 -11616 -9773 -16427 -18104 -23842 -30848 Note: Data in the table are provisional. Source: Directorate General of Commercial Intelligence and Statistics. No. 33: Foreign Exchange Reserves 2024 2025 Item Unit Dec. 06 Oct. 24 Oct. 31 Nov. 07 Nov. 14 Nov. 21 Nov. 28 1 2 3 4 5 6 7 1 Total Reserves ₹ Crore 5546163 6108299 6123031 6091683 6146082 6155363 6137575 US $ Million 654857 695355 689733 687034 692576 688104 686227 1.1 Foreign Currency Assets ₹ Crore 4790434 4976853 5012117 4984258 4989889 5015105 4982046 US $ Million 565623 566548 564591 562137 562290 560600 557031 1.2 Gold ₹ Crore 566898 927080 903062 900234 948278 932008 946227 US $ Million 66936 105536 101726 101531 106857 104182 105795 Volume (Metric Tonnes) 876.18 880.18 880.18 880.18 880.18 880.18 880.18 1.3 SDRs SDRs Million 13705 13709 13709 13709 13712 13712 13712 ₹ Crore 152713 163953 165514 164862 165502 166088 166610 US $ Million 18031 18664 18644 18594 18650 18566 18628 1.4 Reserve Tranche Position in IMF ₹ Crore 36118 40412 42338 42329 42413 42162 42692 US $ Million 4266 4608 4772 4772 4779 4757 4772 * Difference, if any, is due to rounding off Note: Exclude investment in foreign currency denominated bonds issued by IIFC (UK), SDRs transferred by Government of India to RBI, foreign currency received under SAARC and ACU currency swap arrangements and RBI’s contribution to funding of Nexus Global Payments. Foreign currency assets in US dollar take into account appreciation/depreciation of non-US currencies (such as Euro, Sterling, Yen and Australian Dollar) held in reserves. Foreign exchange holdings are converted into rupees at rupee-US dollar RBI holding rates. No. 34: Non-Resident Deposits (US $ Million) Scheme Outstanding Flows 2024 2025 2024-25 2025-26 2024-25 Oct. Sep. Oct. (P) Apr.-Oct. Apr.-Oct.(P) 1 2 3 4 5 6 1 NRI Deposits 164677 162693 165928 168178 11897 8324 1.1 FCNR(B) 32809 31871 33500 34398 6138 1589 1.2 NR(E)RA 100733 100873 100278 100988 3090 3918 1.3 NRO 31135 29949 32150 32792 2669 2817 P: Provisional. 144 RBI Bulletin December 2025CURRENT STATISTICS No. 35: Foreign Investment Inflows (US $ Million) 2024-25 2025-26 (P) 2024 (P) 2025 (P) Item 2024-25 Apr.-Oct. Apr.-Oct. Oct. Sep. Oct. 1 2 3 4 5 6 1.1 Net Foreign Direct Investment (1.1.1-1.1.2) 959 3274 6198 -129 -1664 -1545 1.1.1 Direct Investment to India (1.1.1.1-1.1.1.2) 29130 17336 26666 1764 2390 1542 1.1.1.1 Gross Inflows/Gross Investments 80615 50536 58323 7170 7003 6538 1.1.1.1.1 Equity 50993 34554 40671 4307 4408 3880 1.1.1.1.1.1 Government 2208 529 1550 149 32 5 1.1.1.1.1.2 RBI 34686 24148 28736 3524 3520 2527 1.1.1.1.1.3 Acquisition of shares 13124 9337 8477 550 582 1051 1.1.1.1.1.4 Equity capital of unincorporated bodies 975 542 1909 85 274 298 1.1.1.1.2 Reinvested earnings 22759 12638 14125 1978 2024 2208 1.1.1.1.3 Other capital 6863 3344 3528 884 570 450 1.1.1.2 Repatriation/Disinvestment 51486 33200 31658 5406 4613 4996 1.1.1.2.1 Equity 49525 31902 30104 5212 4422 4761 1.1.1.2.2 Other capital 1960 1298 1554 194 191 235 1.1.2 Foreign Direct Investment by India 28171 14062 20467 1892 4054 3087 (1.1.2.1+1.1.2.2+1.1.2.3-1.1.2.4) 1.1.2.1 Equity capital 16945 8296 12004 985 2746 1825 1.1.2.2 Reinvested Earnings 6846 3994 4439 571 634 634 1.1.2.3 Other Capital 7955 3772 5530 641 935 733 1.1.2.4 Repatriation/Disinvestment 3575 2000 1505 304 262 105 1.2 Net Portfolio Investment (1.2.1+1.2.2+1.2.3-1.2.4) 3564 9868 -718 -10927 -621 3421 1.2.1 GDRs/ADRs - - - - - - 1.2.2 FPIs 3283 9765 573 -10948 -528 3561 1.2.3 Offshore funds and others - - - - - - 1.2.4 Portfolio investment by India -281 -103 1291 -21 93 140 1 Foreign Investment Inflows 4523 13142 5480 -11055 -2285 1876 P: Provisional No. 36: Outward Remittances under the Liberalised Remittance Scheme (LRS) for Resident Individuals (US $ Million) 2024 2025 Item 2024-25 Oct. Aug. Sep. Oct. 1 2 3 4 5 1 Outward Remittances under the LRS 29563.12 2408.01 2642.91 2782.34 2364.45 1.1 Deposit 705.26 39.06 42.75 50.75 47.16 1.2 Purchase of immovable property 322.82 24.96 36.02 42.44 44.64 1.3 Investment in equity/debt 1698.94 149.34 152.18 278.80 273.09 1.4 Gift 2938.69 216.30 190.43 195.09 197.53 1.5 Donations 11.81 0.66 0.78 0.64 0.87 1.6 Travel 16964.57 1454.66 1618.81 1664.82 1352.59 1.7 Maintenance of close relatives 3722.03 283.75 272.05 273.65 273.86 1.8 Medical Treatment 81.19 8.49 3.99 4.18 5.04 1.9 Studies Abroad 2918.91 221.18 319.17 264.34 163.26 1.10 Others 198.90 9.62 6.73 7.63 6.40 RBI Bulletin December 2025 145No. 37: Indices of Nominal Effective Exchange Rate (NEER) and Real Effective Exchange Rate (REER) of the Indian Rupee 2024 2025 2023-24 2024-25 Nov Oct Nov Item 1 2 3 4 5 40-Currency Basket (Base: 2015-16=100) 1 Trade-Weighted 1.1 NEER 90.75 91.01 91.68 84.58 84.35 1.2 REER 103.71 105.24 108.03 97.51 97.51 2 Export-Weighted 2.1 NEER 93.13 93.52 94.16 86.47 86.27 2.2 REER 101.22 102.34 104.92 94.60 94.68 6-Currency Basket (Trade-weighted) 1 Base : 2015-16 =100 1.1 NEER 83.62 82.38 82.78 76.59 76.51 1.2 REER 101.66 102.72 105.40 95.83 96.12 2 Base : 2022-23 =100 2.1 NEER 97.31 95.87 96.34 89.13 89.04 2.2 REER 99.86 100.90 103.53 94.13 94.42 Note: Data for 2024-25 and 2025-26 so far is provisional. 146 RBI Bulletin December 2025CURRENT STATISTICS No. 38: External Commercial Borrowings (ECBs) – Registrations (Amount in US $ Million) Item 2024-25 2024 2025 Oct. Sep. Oct. 1 2 3 4 1 Automatic Route 1.1 Number 1328 135 127 79 1.2 Amount 47800 5029 2393 1915 2 Approval Route 2.1 Number 51 1 1 2 2.2 Amount 13384 470 406 291 3 Total (1+2) 3.1 Number 1379 136 128 81 3.2 Amount 61184 5499 2799 2206 4 Weighted Average Maturity (in years) 5.05 6.70 5.00 5.10 5 Interest Rate (per cent) 5.1 Weighted Average Margin over alternative reference rate (ARR) for Floating Rate Loans@ 1.48 1.58 1.27 2.11 5.2 Interest rate range for Fixed Rate Loans 0.00-11.67 0.00-11.00 0.00-10.00 0.00-10.63 Borrower Category I. Corporate Manufacturing 13900 926 1097 762 II. Corporate-Infrastructure 15462 2941 377 418 a.) Transport 614 200 215 0 b.) Energy 6900 1449 3 243 c.) Water and Sanitation 28 1 0 0 d.) Communication 13 0 0 0 e.) Social and Commercial Infrastructure 184 63 0 0 f.) Exploration,Mining and Refinery 5356 850 100 175 g.) Other Sub-Sectors 2367 378 59 0 III. Corporate Service-Sector 3226 86 273 150 IV. Other Entities 1026 0 0 0 a.) units in SEZ 26 0 0 0 b.) SIDBI 0 0 0 0 c.) Exim Bank 1000 0 0 0 V. Banks 0 0 0 0 VI. Financial Institution (Other than NBFC ) 0 0 0 0 VII. NBFCs 26318 1436 1051 831 a). NBFC- IFC/AFC 12389 285 528 191 b). NBFC-MFI 459 120 67 0 c). NBFC-Others 13470 1031 456 640 VIII. Non-Government Organization (NGO) 0 0 0 0 IX. Micro Finance Institution (MFI) 0 0 0 0 X. Others 1252 110 1 45 Note: Based on applications for ECB/Foreign Currency Convertible Bonds (FCCBs) which have been allotted loan registration number during the period. @ With effect from July 01, 2023, the benchmark rate is changed to Alternative Reference Rate (ARR) RBI Bulletin December 2025 147No. 39: India’s Overall Balance of Payments (US$ Million) Jul-Sep 2024 Jul-Sep 2025 (P) Credit Debit Net Credit Debit Net Item 1 2 3 4 5 6 Overall Balance Of Payments (1+2+3) 563182 544568 18614 640815 651732 -10917 1 Current Account (1.1+ 1.2) 245798 266660 -20862 266736 279046 -12310 1.1 Merchandise 100645 189176 -88530 109397 196840 -87443 1.2 Invisibles (1.2.1+1.2.2+1.2.3) 145153 77485 67668 157339 82206 75133 1.2.1 Services 93406 48945 44461 101622 50734 50888 1.2.1.1 Travel 7635 9367 -1732 6813 9457 -2645 1.2.1.2 Transportation 8668 9188 -520 7768 8726 -958 1.2.1.3 Insurance 885 786 100 964 724 240 1.2.1.4 G.n.i.e. 147 316 -169 154 306 -152 1.2.1.5 Miscellaneous 76070 29288 46782 85923 31520 54402 1.2.1.5.1 Software Services 44164 4539 39624 49523 5640 43883 1.2.1.5.2 Business Services 25176 15548 9628 29471 16129 13342 1.2.1.5.3 Financial Services 2190 1265 926 1816 615 1200 1.2.1.5.4 Communication Services 519 497 21 732 548 184 1.2.2 Transfers 35275 2875 32400 39041 2603 36438 1.2.2.1 Official 28 311 -283 35 225 -190 1.2.2.2 Private 35247 2564 32683 39006 2378 36628 1.2.3 Income 16472 25665 -9193 16677 28870 -12193 1.2.3.1 Investment Income 14477 24643 -10166 14518 27759 -13241 1.2.3.2 Compensation of Employees 1995 1023 972 2159 1111 1048 2 Capital Account (2.1+2.2+2.3+2.4+2.5) 317384 277459 39924 373261 372686 575 2.1 Foreign Investment (2.1.1+2.1.2) 203245 186216 17029 161520 164391 -2871 2.1.1 Foreign Direct Investment 21137 23958 -2821 25940 23065 2876 2.1.1.1 In India 20589 15622 4967 25155 13839 11317 2.1.1.1.1 Equity 13846 15016 -1171 17373 13265 4107 2.1.1.1.2 Reinvested Earnings 5435 5435 6073 6073 2.1.1.1.3 Other Capital 1309 606 702 1709 573 1136 2.1.1.2 Abroad 548 8336 -7788 785 9226 -8441 2.1.1.2.1 Equity 548 4583 -4035 785 5373 -4588 2.1.1.2.2 Reinvested Earnings 0 1712 -1712 0 1902 -1902 2.1.1.2.3 Other Capital 0 2041 -2041 0 1951 -1951 2.1.2 Portfolio Investment 182108 162258 19850 135580 141327 -5747 2.1.2.1 In India 181433 161618 19815 134786 140255 -5468 2.1.2.1.1 FIIs 181433 161618 19815 134786 140255 -5468 2.1.2.1.1.1 Equity 160273 149590 10683 113496 122643 -9147 2.1.2.1.1.2 Debt 21160 12028 9132 21290 17612 3678 2.1.2.1.2 ADR/GDRs 0 0 0 0 0 0 2.1.2.2 Abroad 675 640 35 794 1072 -279 2.2 Loans (2.2.1+2.2.2+2.2.3) 40856 31392 9464 167163 163783 3379 2.2.1 External Assistance 3726 1577 2148 2182 1695 486 2.2.1.1 By India 6 26 -20 6 11 -5 2.2.1.2 To India 3720 1551 2168 2176 1685 491 2.2.2 Commercial Borrowings 17481 15485 1995 147344 147389 -45 2.2.2.1 By India 5059 8028 -2969 140445 142094 -1649 2.2.2.2 To India 12421 7457 4964 6899 5295 1604 2.2.3 Short Term to India 19650 14330 5320 17638 14699 2938 2.2.3.1 Buyers' credit & Suppliers' Credit >180 days 15107 14330 777 15831 14699 1132 2.2.3.2 Suppliers' Credit up to 180 days 4543 0 4543 1807 0 1807 2.3 Banking Capital (2.3.1+2.3.2) 52432 46345 6087 34260 32370 1891 2.3.1 Commercial Banks 52112 46345 5767 34260 32317 1943 2.3.1.1 Assets 17627 18853 -1226 10699 7986 2714 2.3.1.2 Liabilities 34485 27492 6993 23561 24332 -771 2.3.1.2.1 Non-Resident Deposits 28921 22753 6167 23330 20876 2454 2.3.2 Others 319 0 319 0 52 -52 2.4 Rupee Debt Service 0 2 -2 0 1 -1 2.5 Other Capital 20850 13504 7346 10318 12140 -1822 3 Errors & Omissions 0 448 -448 818 0 818 4 Monetary Movements (4.1+ 4.2) 0 18614 -18614 10917 0 10917 4.1 I.M.F. 0 0 0 0 0 0 4.2 Foreign Exchange Reserves (Increase - / Decrease +) 0 18614 -18614 10917 0 10917 Note: P: Preliminary. 148 RBI Bulletin December 2025CURRENT STATISTICS No. 40: India’s Overall Balance of Payments (₹ Crore) Jul-Sep 2024 Jul-Sep 2025 (P) Credit Debit Net Credit Debit Net Item 1 2 3 4 5 6 Overall Balance Of Payments (1+2+3) 4717571 4561652 155919 5595501 5690827 -95326 1 Current Account (1.1+ 1.2) 2058962 2233718 -174756 2329098 2436589 -107491 1.1 Merchandise 843069 1584657 -741588 955235 1718776 -763542 1.2 Invisibles (1.2.1+1.2.2+1.2.3) 1215892 649061 566832 1373864 717813 656050 1.2.1 Services 782427 409991 372436 887346 443000 444345 1.2.1.1 Travel 63958 78464 -14506 59486 82579 -23093 1.2.1.2 Transportation 72610 76965 -4355 67832 76194 -8362 1.2.1.3 Insurance 7417 6581 836 8416 6323 2093 1.2.1.4 G.n.i.e. 1228 2643 -1415 1348 2675 -1326 1.2.1.5 Miscellaneous 637214 245338 391875 750263 275229 475034 1.2.1.5.1 Software Services 369945 38026 331920 432424 49247 383177 1.2.1.5.2 Business Services 210894 130244 80650 257337 140839 116498 1.2.1.5.3 Financial Services 18349 10595 7754 15855 5374 10482 1.2.1.5.4 Communication Services 4345 4167 177 6394 4787 1607 1.2.2 Transfers 295485 24079 271406 340897 22726 318171 1.2.2.1 Official 232 2601 -2369 304 1964 -1660 1.2.2.2 Private 295252 21478 273775 340593 20762 319831 1.2.3 Income 137980 214990 -77010 145621 252086 -106466 1.2.3.1 Investment Income 121268 206423 -85155 126769 242388 -115619 1.2.3.2 Compensation of Employees 16712 8568 8145 18851 9698 9153 2 Capital Account (2.1+2.2+2.3+2.4+2.5) 2658609 2324178 334431 3259261 3254238 5024 2.1 Foreign Investment (2.1.1+2.1.2) 1702512 1559865 142647 1410371 1435441 -25070 2.1.1 Foreign Direct Investment 177057 200687 -23630 226507 201396 25112 2.1.1.1 In India 172466 130862 41604 219652 120836 98816 2.1.1.1.1 Equity 115979 125784 -9805 151696 115832 35864 2.1.1.1.2 Reinvested Earnings 45525 0 45525 53031 0 53031 2.1.1.1.3 Other Capital 10961 5078 5884 14926 5004 9922 2.1.1.2 Abroad 4591 69825 -65234 6855 80560 -73705 2.1.1.2.1 Equity 4591 38393 -33802 6855 46915 -40060 2.1.1.2.2 Reinvested Earnings 0 14337 -14337 0 16612 -16612 2.1.1.2.3 Other Capital 0 17095 -17095 0 17033 -17033 2.1.2 Portfolio Investment 1525455 1359178 166277 1183864 1234045 -50181 2.1.2.1 In India 1519799 1353816 165984 1176935 1224684 -47749 2.1.2.1.1 FIIs 1519799 1353816 165984 1176935 1224684 -47749 2.1.2.1.1.1 Equity 1342550 1253064 89486 991031 1070898 -79866 2.1.2.1.1.2 Debt 177250 100752 76498 185903 153786 32117 2.1.2.1.2 ADR/GDRs 0 0 0 0 0 0 2.1.2.2 Abroad 5656 5363 293 6929 9361 -2432 2.2 Loans (2.2.1+2.2.2+2.2.3) 342239 262961 79279 1459640 1430132 29508 2.2.1 External Assistance 31210 13212 17997 19050 14804 4246 2.2.1.1 By India 52 217 -166 52 94 -42 2.2.1.2 To India 31158 12995 18163 18998 14710 4288 2.2.2 Commercial Borrowings 146429 129714 16715 1286582 1286978 -396 2.2.2.1 By India 42379 67249 -24870 1226344 1240743 -14399 2.2.2.2 To India 104050 62465 41585 60238 46235 14003 2.2.3 Short Term to India 164601 120034 44566 154008 128350 25658 2.2.3.1 Buyers' credit & Suppliers' Credit >180 days 126546 120034 6511 138232 128350 9882 2.2.3.2 Suppliers' Credit up to 180 days 38055 0 38055 15776 0 15776 2.3 Banking Capital (2.3.1+2.3.2) 439202 388217 50985 299155 282647 16508 2.3.1 Commercial Banks 436527 388217 48311 299155 282190 16965 2.3.1.1 Assets 147657 157925 -10268 93424 69730 23694 2.3.1.2 Liabilities 288870 230292 58579 205730 212460 -6729 2.3.1.2.1 Non-Resident Deposits 242259 190597 51662 203712 182285 21427 2.3.2 Others 2675 0 2675 0 457 -457 2.4 Rupee Debt Service 0 15 -15 0 13 -13 2.5 Other Capital 174656 113120 61536 90095 106005 -15909 3 Errors & Omissions 0 3756 -3756 7142 0 7142 4 Monetary Movements (4.1+ 4.2) 0 155919 -155919 95326 0 95326 4.1 I.M.F. 0 0 0 0 0 0 4.2 Foreign Exchange Reserves (Increase - / Decrease +) 0 155919 -155919 95326 0 95326 Note: P: Preliminary. RBI Bulletin December 2025 149No. 41: Standard Presentation of BoP in India as per BPM6 (US$ Million) Item Jul-Sep 2024 Jul-Sep 2025 (P) Credit Debit Net Credit Debit Net 1 2 3 4 5 6 1 Current Account (1.A+1.B+1.C) 245798 266630 -20832 266735 279027 -12292 1.A Goods and Services (1.A.a+1.A.b) 194051 238120 -44069 211018 247574 -36555 1.A.a Goods (1.A.a.1 to 1.A.a.3) 100645 189176 -88530 109397 196840 -87443 1.A.a.1 General merchandise on a BOP basis 100660 168484 -67825 109128 177811 -68683 1.A.a.2 Net exports of goods under merchanting -14 0 -14 268 0 268 1.A.a.3 Nonmonetary gold 20691 -20691 19029 -19029 1.A.b Services (1.A.b.1 to 1.A.b.13) 93406 48945 44461 101622 50734 50888 1.A.b.1 Manufacturing services on physical inputs owned by others 276 20 256 193 29 164 1.A.b.2 Maintenance and repair services n.i.e. 90 263 -172 102 359 -258 1.A.b.3 Transport 8668 9188 -520 7768 8726 -958 1.A.b.4 Travel 7635 9367 -1732 6813 9457 -2645 1.A.b.5 Construction 1263 951 312 1317 959 358 1.A.b.6 Insurance and pension services 885 786 100 964 724 240 1.A.b.7 Financial services 2190 1265 926 1816 615 1200 1.A.b.8 Charges for the use of intellectual property n.i.e. 448 3877 -3428 423 4493 -4070 1.A.b.9 Telecommunications, computer, and information services 44772 5333 39439 50359 6398 43961 1.A.b.10 Other business services 25176 15548 9628 29471 16129 13342 1.A.b.11 Personal, cultural, and recreational services 1107 1794 -688 1363 1591 -228 1.A.b.12 Government goods and services n.i.e. 147 316 -169 154 306 -152 1.A.b.13 Others n.i.e. 747 238 509 879 945 -66 1.B Primary Income (1.B.1 to 1.B.3) 16472 25665 -9193 16677 28870 -12193 1.B.1 Compensation of employees 1995 1023 972 2159 1111 1048 1.B.2 Investment income 13047 24205 -11158 12257 26432 -14174 1.B.2.1 Direct investment 2923 12884 -9961 2965 15098 -12133 1.B.2.2 Portfolio investment 78 4152 -4074 103 4444 -4341 1.B.2.3 Other investment 1168 6945 -5778 1106 6723 -5617 1.B.2.4 Reserve assets 8878 223 8655 8084 168 7916 1.B.3 Other primary income 1430 438 992 2261 1327 933 1.C Secondary Income (1.C.1+1.C.2) 35275 2844 32430 39040 2584 36456 1.C.1 Financial corporations, nonfinancial corporations, households, and NPISHs 35247 2564 32683 39006 2378 36628 1.C.1.1 Personal transfers (Current transfers between resident and/non-resident households) 34422 1803 32619 38157 1748 36410 1.C.1.2 Other current transfers 826 761 64 848 630 218 1.C.2 General government 27 280 -253 34 206 -172 2 Capital Account (2.1+2.2) 186 197 -11 213 370 -157 2.1 Gross acquisitions (DR.)/disposals (CR.) of non-produced nonfinancial assets 7 68 -61 25 268 -242 2.2 Capital transfers 179 129 50 188 103 86 3 Financial Account (3.1 to 3.5) 317198 295906 21292 383966 372334 11631 3.1 Direct Investment (3.1A+3.1B) 21137 23958 -2821 25940 23065 2876 3.1.A Direct Investment in India 20589 15622 4967 25155 13839 11317 3.1.A.1 Equity and investment fund shares 19280 15016 4264 23446 13265 10180 3.1.A.1.1 Equity other than reinvestment of earnings 13846 15016 -1171 17373 13265 4107 3.1.A.1.2 Reinvestment of earnings 5435 5435 6073 6073 3.1.A.2 Debt instruments 1309 606 702 1709 573 1136 3.1.A.2.1 Direct investor in direct investment enterprises 1309 606 702 1709 573 1136 3.1.B Direct Investment by India 548 8336 -7788 785 9226 -8441 3.1.B.1 Equity and investment fund shares 548 6295 -5747 785 7275 -6490 3.1.B.1.1 Equity other than reinvestment of earnings 548 4583 -4035 785 5373 -4588 3.1.B.1.2 Reinvestment of earnings 1712 -1712 1902 -1902 3.1.B.2 Debt instruments 0 2041 -2041 0 1951 -1951 3.1.B.2.1 Direct investor in direct investment enterprises 2041 -2041 1951 -1951 3.2 Portfolio Investment 182108 162258 19850 135580 141327 -5747 3.2.A Portfolio Investment in India 181433 161618 19815 134786 140255 -5468 3.2.1 Equity and investment fund shares 160273 149590 10683 113496 122643 -9147 3.2.2 Debt securities 21160 12028 9132 21290 17612 3678 3.2.B Portfolio Investment by India 675 640 35 794 1072 -279 3.3 Financial derivatives (other than reserves) and employee stock options 6359 11892 -5533 5820 9441 -3621 3.4 Other investment 107594 79185 28409 205708 198502 7206 3.4.1 Other equity (ADRs/GDRs) 0 0 0 0 0 0 3.4.2 Currency and deposits 29240 22753 6487 23330 20928 2402 3.4.2.1 Central bank (Rupee Debt Movements; NRG) 319 0 319 0 52 -52 3.4.2.2 Deposit-taking corporations, except the central bank (NRI Deposits) 28921 22753 6167 23330 20876 2454 3.4.2.3 General government 0 0 3.4.2.4 Other sectors 0 0 3.4.3 Loans (External Assistance, ECBs and Banking Capital) 44398 40654 3744 160456 160526 -70 3.4.3.A Loans to India 39333 32600 6733 20005 18421 1584 3.4.3.B Loans by India 5065 8054 -2989 140451 142105 -1654 3.4.4 Insurance, pension, and standardized guarantee schemes 47 3 44 45 65 -21 3.4.5 Trade credit and advances 19650 14330 5320 17638 14699 2938 3.4.6 Other accounts receivable/payable - other 14259 1444 12814 4241 2284 1957 3.4.7 Special drawing rights 0 0 0 0 3.5 Reserve assets 0 18614 -18614 10917 0 10917 3.5.1 Monetary gold 0 0 3.5.2 Special drawing rights n.a. 0 0 0 0 3.5.3 Reserve position in the IMF n.a. 0 0 3.5.4 Other reserve assets (Foreign Currency Assets) 0 18614 -18614 10917 0 10917 4 Total assets/liabilities 317198 295906 21292 383966 372334 11631 4.1 Equity and investment fund shares 187183 183437 3746 144385 153761 -9376 4.2 Debt instruments 115757 92412 23345 224422 216289 8134 4.3 Other financial assets and liabilities 14259 20058 -5799 15158 2284 12874 5 Net errors and omissions 0 448 -448 818 0 818 Note: P: Preliminary. 150 RBI Bulletin December 2025CURRENT STATISTICS No. 42: Standard Presentation of BoP in India as per BPM6 (₹ Crore) Jul-Sep 2024 Jul-Sep 2025 (P) Item Credit Debit Net Credit Debit Net 1 2 3 4 5 6 1 Current Account (1.A+1.B+1.C) 2058959 2233464 -174505 2329091 2436427 -107336 1.A Goods and Services (1.A.a+1.A.b) 1625497 1994649 -369152 1842580 2161777 -319196 1.A.a Goods (1.A.a.1 to 1.A.a.3) 843069 1584657 -741588 955235 1718776 -763542 1.A.a.1 General merchandise on a BOP basis 843190 1411333 -568142 952892 1552621 -599729 1.A.a.2 Net exports of goods under merchanting -121 0 -121 2342 0 2342 1.A.a.3 Nonmonetary gold 0 173325 -173325 0 166155 -166155 1.A.b Services (1.A.b.1 to 1.A.b.13) 782427 409991 372436 887346 443000 444345 1.A.b.1 Manufacturing services on physical inputs owned by others 2316 169 2147 1683 253 1430 1.A.b.2 Maintenance and repair services n.i.e. 755 2199 -1444 890 3139 -2249 1.A.b.3 Transport 72610 76965 -4355 67832 76194 -8362 1.A.b.4 Travel 63958 78464 -14506 59486 82579 -23093 1.A.b.5 Construction 10580 7963 2616 11499 8374 3125 1.A.b.6 Insurance and pension services 7417 6581 836 8416 6323 2093 1.A.b.7 Financial services 18349 10595 7754 15855 5374 10482 1.A.b.8 Charges for the use of intellectual property n.i.e. 3754 32473 -28719 3693 39235 -35543 1.A.b.9 Telecommunications, computer, and information services 375037 44672 330366 439727 55864 383863 1.A.b.10 Other business services 210894 130244 80650 257337 140839 116498 1.A.b.11 Personal, cultural, and recreational services 9269 15029 -5760 11899 13895 -1995 1.A.b.12 Government goods and services n.i.e. 1228 2643 -1415 1348 2675 -1326 1.A.b.13 Others n.i.e. 6260 1994 4266 7679 8256 -577 1.B Primary Income (1.B.1 to 1.B.3) 137980 214990 -77010 145621 252086 -106466 1.B.1 Compensation of employees 16712 8568 8145 18851 9698 9153 1.B.2 Investment income 109290 202753 -93463 107030 230798 -123768 1.B.2.1 Direct investment 24485 107928 -83443 25888 131832 -105944 1.B.2.2 Portfolio investment 653 34776 -34123 901 38803 -37902 1.B.2.3 Other investment 9783 58180 -48396 9655 58701 -49046 1.B.2.4 Reserve assets 74369 1870 72499 70587 1463 69124 1.B.3 Other primary income 11978 3669 8309 19739 11590 8149 1.C Secondary Income (1.C.1+1.C.2) 295482 23825 271657 340890 22564 318327 1.C.1 Financial corporations, nonfinancial corporations, households, and NPISHs 295252 21478 273775 340593 20762 319831 1.C.1.1 Personal transfers (Current transfers between resident and/non-resident households) 288337 15102 273235 333185 15259 317926 1.C.1.2 Other current transfers 6915 6376 539 7408 5503 1905 1.C.2 General government 230 2347 -2117 297 1801 -1504 2 Capital Account (2.1+2.2) 1558 1649 -91 1863 3233 -1370 2.1 Gross acquisitions (DR.)/disposals (CR.) of non-produced nonfinancial assets 57 570 -513 220 2338 -2117 2.2 Capital transfers 1501 1079 422 1642 895 747 3 Financial Account (3.1 to 3.5) 2657054 2478702 178352 3352732 3251167 101565 3.1 Direct Investment (3.1A+3.1B) 177057 200687 -23630 226507 201396 25112 3.1.A Direct Investment in India 172466 130862 41604 219652 120836 98816 3.1.A.1 Equity and investment fund shares 161505 125784 35720 204726 115832 88894 3.1.A.1.1 Equity other than reinvestment of earnings 115979 125784 -9805 151696 115832 35864 3.1.A.1.2 Reinvestment of earnings 45525 0 45525 53031 0 53031 3.1.A.2 Debt instruments 10961 5078 5884 14926 5004 9922 3.1.A.2.1 Direct investor in direct investment enterprises 10961 5078 5884 14926 5004 9922 3.1.B Direct Investment by India 4591 69825 -65234 6855 80560 -73705 3.1.B.1 Equity and investment fund shares 4591 52730 -48139 6855 63527 -56672 3.1.B.1.1 Equity other than reinvestment of earnings 4591 38393 -33802 6855 46915 -40060 3.1.B.1.2 Reinvestment of earnings 0 14337 -14337 0 16612 -16612 3.1.B.2 Debt instruments 0 17095 -17095 0 17033 -17033 3.1.B.2.1 Direct investor in direct investment enterprises 0 17095 -17095 0 17033 -17033 3.2 Portfolio Investment 1525455 1359178 166277 1183864 1234045 -50181 3.2.A Portfolio Investment in India 1519799 1353816 165984 1176935 1224684 -47749 3.2.1 Equity and investment fund shares 1342550 1253064 89486 991031 1070898 -79866 3.2.2 Debt securities 177250 100752 76498 185903 153786 32117 3.2.B Portfolio Investment by India 5656 5363 293 6929 9361 -2432 3.3 Financial derivatives (other than reserves) and employee stock options 53269 99618 -46349 50820 82434 -31614 3.4 Other investment 901273 663300 237973 1796215 1733292 62922 3.4.1 Other equity (ADRs/GDRs) 0 0 0 0 0 0 3.4.2 Currency and deposits 244933 190597 54337 203712 182742 20971 3.4.2.1 Central bank (Rupee Debt Movements; NRG) 2675 0 2675 0 457 -457 3.4.2.2 Deposit-taking corporations, except the central bank (NRI Deposits) 242259 190597 51662 203712 182285 21427 3.4.2.3 General government 0 0 0 0 0 0 3.4.2.4 Other sectors 0 0 0 0 0 0 3.4.3 Loans (External Assistance, ECBs and Banking Capital) 371907 340546 31361 1401074 1401687 -613 3.4.3.A Loans to India 329476 273079 56397 174678 160850 13828 3.4.3.B Loans by India 42431 67467 -25036 1226396 1240837 -14441 3.4.4 Insurance, pension, and standardized guarantee schemes 393 25 368 389 569 -180 3.4.5 Trade credit and advances 164601 120034 44566 154008 128350 25658 3.4.6 Other accounts receivable/payable - other 119439 12098 107341 37031 19945 17086 3.4.7 Special drawing rights 0 0 0 0 0 0 3.5 Reserve assets 0 155919 -155919 95326 0 95326 3.5.1 Monetary gold 0 0 0 0 0 0 3.5.2 Special drawing rights n.a. 0 0 0 0 0 0 3.5.3 Reserve position in the IMF n.a. 0 0 0 0 0 0 3.5.4 Other reserve assets (Foreign Currency Assets) 0 155919 -155919 95326 0 95326 4 Total assets/liabilities 2657054 2478702 178352 3352732 3251167 101565 4.1 Equity and investment fund shares 1567963 1536583 31380 1260751 1342621 -81870 4.2 Debt instruments 969652 774102 195550 1959624 1888601 71023 4.3 Other financial assets and liabilities 119439 168016 -48578 132357 19945 112412 5 Net errors and omissions 0 3756 -3756 7142 0 7142 Note: P: Preliminary. RBI Bulletin December 2025 151No. 43: India’s International Investment Position (US$ Million) Item As on Financial Year/Quarter End 2024-25 2024 2025 Jun. Mar. Jun. Assets Liabilities Assets Liabilities Assets Liabilities Assets Liabilities 1 2 3 4 5 6 7 8 1. Direct investment Abroad/in India 270441 556903 246653 552829 270441 556903 278867 571227 1.1 Equity Capital* 173559 521931 156635 520605 173559 521931 179580 535378 1.2 Other Capital 96882 34972 90018 32224 96882 34972 99287 35849 2. Portfolio investment 15426 272042 12410 277347 15426 272042 16305 272544 2.1 Equity 10391 141938 10665 160898 10391 141938 13111 147392 2.2 Debt 5034 130104 1745 116449 5034 130104 3193 125152 3. Other investment 186700 641155 140909 588623 186700 641155 195426 657723 3.1 Trade credit 33422 131164 32822 125907 33422 131164 33782 131887 3.2 Loan 25891 250109 20803 224491 25891 250109 24464 259789 3.3 Currency and Deposits 79332 167598 57747 160628 79332 167598 82528 171749 3.4 Other Assets/Liabilities 48055 92285 29537 77597 48055 92285 54651 94298 4. Reserves 668326 651997 668326 698118 5. Total Assets/ Liabilities 1140893 1470099 1051969 1418799 1140893 1470099 1188715 1501494 6. Net IIP (Assets - Liabilities) -329206 -366830 -329206 -312779 Note: * Equity capital includes share of investment funds and reinvested earnings. 152 RBI Bulletin December 2025CURRENT STATISTICS Payment and Settlement Systems No. 44: Payment System Indicators PART I - Payment System Indicators - Payment & Settlement System Statistics System Volume (Lakh) Value (₹ Crore) FY 2024-25 2024 2025 FY 2024-25 2024 2025 Oct. Sep. Oct. Oct. Sep. Oct. 1 2 3 4 5 6 7 8 A. Settlement Systems Financial Market Infrastructures (FMIs) 1 CCIL Operated Systems (1.1 to 1.3) 47.40 3.59 4.95 4.25 296218030 25730864 30270023 30434601 1.1 Govt. Securities Clearing (1.1.1 to 1.1.3) 17.87 1.69 1.75 1.63 185733719 16664120 18003263 18365111 1.1.1 Outright 10.56 1.04 1.04 0.95 16056018 1626397 1499643 1439939 1.1.2 Repo 4.72 0.41 0.48 0.46 77286611 6573748 7926471 8365990 1.1.3 Tri-party Repo 2.58 0.23 0.23 0.23 92391091 8463975 8577149 8559182 1.2 Forex Clearing 28.06 1.74 3.11 2.51 100639565 8046345 11417001 11161871 1.3 Rupee Derivatives @ 1.46 0.16 0.09 0.11 9844746 1020399 849759 907620 B. Payment Systems I Financial Market Infrastructures (FMIs) - - - - - - - - 1 Credit Transfers - RTGS (1.1 to 1.2) 3024.55 267.92 280.83 296.76 201387682 17070975 19836942 18732702 1.1 Customer Transactions 3010.32 266.69 279.64 295.56 181153129 15418778 18220475 17108666 1.2 Interbank Transactions 14.23 1.23 1.19 1.20 20234553 1652197 1616467 1624036 II Retail 2 Credit Transfers - Retail (2.1 to 2.6) 2061014.91 185187.17 213074.92 224318.23 79881976 7358283 7543380 7851867 2.1 AePS (Fund Transfers) @ 3.64 0.31 0.26 0.27 190 17 12 12 2.2 APBS $ 32964.43 4021.91 2542.90 2745.64 554034 69157 41746 43353 2.3 IMPS 56249.68 4668.23 3943.79 4035.88 7139110 629382 596847 641964 2.4 NACH Cr $ 16938.86 1463.68 1850.43 1736.26 1670223 157479 149729 165141 2.5 NEFT 96198.05 9183.38 8403.21 8790.97 44461464 4152428 4265310 4273608 2.6 UPI @ 1858660.25 165849.66 196334.33 207009.21 26056955 2349821 2489737 2727791 2.6.1 of which USSD @ 17.24 1.64 0.94 1.14 185 18 10 13 3 Debit Transfers and Direct Debits (3.1 to 3.3) 21659.95 1871.73 1926.97 1964.66 2208583 189818 222919 223881 3.1 BHIM Aadhaar Pay @ 230.08 24.54 18.90 20.58 6907 773 591 661 3.2 NACH Dr $ 19762.28 1710.21 1786.47 1812.26 2199327 188844 222164 223048 3.3 NETC (linked to bank account) @ 1667.59 136.98 121.60 131.82 2349 202 164 172 4 Card Payments (4.1 to 4.2) 63861.15 5759.31 5999.80 6279.14 2605110 248619 253483 256373 4.1 Credit Cards (4.1.1 to 4.1.2) 47740.76 4332.14 4952.41 5182.90 2109197 201789 216707 214230 4.1.1 PoS based $ 24571.10 2196.73 2416.15 2609.42 795022 79293 72544 88357 4.1.2 Others $ 23169.66 2135.41 2536.26 2573.48 1314175 122496 144163 125873 4.2 Debit Cards (4.2.1 to 4.2.1 ) 16120.39 1427.17 1047.39 1096.25 495914 46830 36776 42143 4.2.1 PoS based $ 11980.33 1060.17 777.56 828.79 332556 32091 22773 29104 4.2.2 Others $ 4140.06 367.00 269.83 267.46 163358 14738 14003 13039 5 Prepaid Payment Instruments (5.1 to 5.2) 70254.08 5977.88 8551.51 8939.26 216751 20419 22637 24227 5.1 Wallets 52898.40 4425.20 6871.58 7281.56 154066 13074 17183 18515 5.2 Cards (5.2.1 to 5.2.2) 17355.68 1552.68 1679.93 1657.70 62686 7345 5454 5712 5.2.1 PoS based $ 8240.14 718.88 688.72 649.16 11512 981 1092 1274 5.2.2 Others $ 9115.54 833.81 991.22 1008.54 51174 6365 4362 4437 6 Paper-based Instruments (6.1 to 6.2) 6095.38 546.98 464.86 452.12 7113350 624057 570467 574554 6.1 CTS (NPCI Managed) 6095.38 546.98 464.86 452.12 7113350 624057 570467 574554 6.2 Others 0.00 – – – – – – – Total - Retail Payments (2+3+4+5+6) 2222885.46 199343.07 230018.06 241953.42 92025771 8441196 8612885 8930903 Total Payments (1+2+3+4+5+6) 2225910.01 199610.99 230298.89 242250.18 293413453 25512171 28449827 27663605 Total Digital Payments (1+2+3+4+5) 2219814.63 199064.01 229834.03 241798.06 286300103 24888114 27879360 27089051 RBI Bulletin December 2025 153PART II - Payment Modes and Channels System Volume (Lakh) Value (₹ Crore) FY 2024-25 2024 2025 FY 2024-25 2024 2025 Oct. Sep. Oct. Oct. Sep. Oct. 1 2 3 4 5 6 7 8 A. Other Payment Channels 1 Mobile Payments (mobile app based) (1.1 to 1.2) 1756976.91 154876.80 181008.61 190876.05 39206221 3532243 3618114 3928496 1.1 Intra-bank $ 110801.96 9126.58 10469.49 10981.41 7207439 657333 633733 687557 1.2 Inter-bank $ 1646174.95 145750.22 170539.12 179894.64 31998782 2874910 2984381 3240939 2 Internet Payments (Netbanking / Internet Browser Based) @ (2.1 to 2.2) 47478.09 4259.90 3755.37 3803.42 131858133 11281098 13654298 13199799 2.1 Intra-bank @ 13056.37 1152.19 853.80 872.08 69086996 5801815 7091903 6840494 2.2 Inter-bank @ 34421.72 3107.71 2901.57 2931.34 62771136 5479282 6562395 6359305 B. ATMs 3 Cash Withdrawal at ATMs $ (3.1 to 3.3) 60308.11 5545.04 4395.48 4661.98 3063077 285506 230952 251643 3.1 Using Credit Cards $ 97.25 8.32 6.69 7.12 5084 444 369 404 3.2 Using Debit Cards $ 59965.70 5515.23 4370.90 4636.34 3046987 284076 229713 250321 3.3 Using Pre-paid Cards $ 245.16 21.49 17.89 18.53 11005 985 870 917 4 Cash Withdrawal at PoS $ (4.1 to 4.2) 3.58 0.29 0.12 0.15 37 3 2 2 4.1 Using Debit Cards $ 3.33 0.28 0.10 0.13 35 3 1 2 4.2 Using Pre-paid Cards $ 0.25 0.01 0.02 0.02 3 0 0 0 5 Cash Withrawal at Micro ATMs @ 11640.55 1227.30 1034.96 1084.34 296622 31480 26356 29379 5.1 AePS @ 11640.55 1227.30 1034.96 1084.34 296622 31480 26356 29379 PART III - Payment Infrastructures (Lakh) System As on March 2024 2025 2025 Oct. Sep. Oct. 1 2 3 4 Payment System Infrastructures 1 Number of Cards (1.1 to 1.2) 11006.97 10878.00 11381.99 11411.69 1.1 Credit Cards 1098.85 1068.90 1133.90 1140.18 1.2 Debit Cards 9908.12 9809.11 10248.09 10271.50 2 Number of PPIs @ (2.1 to 2.2) 13401.46 15503.38 16180.40 17710.95 2.1 Wallets @ 8678.44 11439.31 11478.95 12993.66 2.2 Cards @ 4723.02 4064.07 4701.45 4717.28 3 Number of ATMs (3.1 to 3.2) 2.56 2.56 2.49 2.50 3.1 Bank owned ATMs $ 2.20 2.21 2.12 2.13 3.2 White Label ATMs $ 0.36 0.35 0.37 0.37 4 Number of Micro ATMs @ 14.82 14.51 14.60 14.65 5 Number of PoS Terminals 110.98 95.09 121.24 123.17 6 Bharat QR @ 67.18 64.31 60.95 60.73 7 UPI QR * 6579.30 6168.52 7090.66 7175.25 @: New inclusion w.e.f. November 2019 #: Data reported by Co-operative Banks, LABs and RRBs included with effect from December 2021. $ : Inclusion separately initiated from November 2019 - would have been part of other items hitherto. *: New inclusion w.e.f. September 2020; Includes only static UPI QR Code Note: 1. Data is provisional. 2. ECS (Debit and Credit) has been merged with NACH with effect from January 31, 2020. 3. The data from November 2019 onwards for card payments (Debit/Credit cards) and Prepaid Payment Instruments (PPIs) may not be comparable with earlier months/ periods, as more granular data is being published along with revision in data definitions. 4. Only domestic financial transactions are considered. The new format captures e-commerce transactions; transactions using FASTags, digital bill payments and card-to-card transfer through ATMs, etc.. Also, failed transactions, chargebacks, reversals, expired cards/ wallets, are excluded. Part I-A. Settlement systems 1.1.3: Tri- party Repo under the securities segment has been operationalised from November 05, 2018. Part I-B. Payments systems 4.1.2: ‘Others’ includes e-commerce transactions and digital bill payments through ATMs, etc. 4.2.2: ‘Others’ includes e-commerce transactions, card to card transfers and digital bill payments through ATMs, etc. 5: Available from December 2010. 5.1: includes purchase of goods and services and fund transfer through wallets. 5.2.2: includes usage of PPI Cards for online transactions and other transactions. 6.1: Pertain to three grids – Mumbai, New Delhi and Chennai. 6.2: ‘Others’ comprises of Non-MICR transactions which pertains to clearing houses managed by 21 banks. Part II-A. Other payment channels 1: Mobile Payments – o Include transactions done through mobile apps of banks and UPI apps. o The data from July 2017 includes only individual payments and corporate payments initiated, processed, and authorised using mobile device. Other corporate payments which are not initiated processed, a nd authorised using mobile device are excluded. 2: Internet Payments – includes only e-commerce transactions through ‘netbanking’ and any financial transaction using internet banking website of the bank. Part II-B. ATMs 3.3 and 4.2: only relates to transactions using bank issued PPIs. Part III. Payment systems infrastructure 3: Includes ATMs deployed by Scheduled Commercial Banks (SCBs) and White Label ATM Operators (WLAOs). WLAs are included from April 2014 onwards. 154 RBI Bulletin December 2025CURRENT STATISTICS Occasional Series No. 45: Small Savings (₹ Crore) Scheme 2023-24 2024 2025 Feb. Dec. Jan. Feb. 1 2 3 4 5 1 Small Savings Receipts 232460 14570 11133 12581 11379 Outstanding 1865029 1819758 1982465 1994553 2005585 1.1 Total Deposits Receipts 161344 10025 8734 9178 8077 Outstanding 1298795 1268920 1395484 1404661 1412738 1.1.1 Post Office Saving Bank Deposits Receipts 17229 1520 1090 2702 814 Outstanding 191692 218498 201999 204701 205515 1.1.2 Sukanya Samriddhi Yojna Receipts 35174 2233 2244 2347 2282 Outstanding 157611 109222 177007 179354 181636 1.1.3 National Saving Scheme, 1987 Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.1.4 National Saving Scheme, 1992 Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.1.5 Monthly Income Scheme Receipts 26696 1927 827 1279 1045 Outstanding 269007 267205 282142 283421 284466 1.1.6 Senior Citizen Scheme 2004 Receipts 38167 2153 1531 1922 1952 Outstanding 175472 173476 194605 196527 198479 1.1.7 Post Office Time Deposits Receipts 25341 2632 2125 2853 2108 Outstanding 305776 303000 330912 333764 335872 1.1.7.1 1 year Time Deposits Outstanding 140423 138552 159174 161578 163358 1.1.7.2 2 year Time Deposits Outstanding 11967 11730 14299 14476 14637 1.1.7.3 3 year Time Deposits Outstanding 8932 8782 10308 10487 10645 1.1.7.4 5 year Time Deposits Outstanding 144454 143936 147131 147223 147232 1.1.8 Post Office Recurring Deposits Receipts 18713 -420 1025 -1831 -25 Outstanding 197134 195727 207269 205438 205413 1.1.9 Post Office Cumulative Time Deposits Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.1.10 Other Deposits Receipts 8 -20 -108 -95 -100 Outstanding 1754 1444 1195 1100 1000 1.1.11 PM Care for children Receipts 16 0 0 1 1 Outstanding 349 348 355 356 357 1.2 Saving Certificates Receipts 56069 3940 2226 3019 2858 Outstanding 418021 414597 438074 440601 443112 1.2.1 National Savings Certificate VIII issue Receipts 16853 1446 430 796 762 Outstanding 183905 180181 192621 193417 194179 1.2.2 Indira Vikas Patras Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.2.3 Kisan Vikas Patras Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.2.4 Kisan Vikas Patras - 2014 Receipts 20939 1428 1113 1376 1247 Outstanding 220560 219498 228707 230083 231330 1.2.5 National Saving Certificate VI issue Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.2.6 National Saving Certificate VII issue Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.2.7 M.S. Certificates Receipts 18277 1066 683 847 849 Outstanding 18277 17235 25303 26150 26999 1.2.8 Other Certificates Outstanding -4721 -2317 -8557 -9049 -9396 1.3 Public Provident Fund Receipts 15047 605 173 384 444 Outstanding 148213 136241 148907 149291 149735 Note : Data on receipts from April 2017 are net receipts, i.e., gross receipt minus gross payment. Source: Accountant General, Post and Telegraphs. RBI Bulletin December 2025 155No. 46 : Ownership Pattern of Central and State Governments Securities (Per cent) Central Government Dated Securities 2024 2025 Category Sep. Dec. Mar. Jun. Sep. 1 2 3 4 5 (A) Total (in ₹. Crore) 11271589 11422728 11642652 11854200 12137000 1 Commercial Banks 37.55 37.98 36.18 35.28 35.43 2 Co-operative Banks 1.35 1.36 1.29 1.29 1.32 3 Non-Bank PDs 0.77 0.65 0.76 0.59 0.60 4 Insurance Companies 25.95 26.14 25.81 25.95 25.81 5 Mutual Funds 3.14 3.11 2.68 2.46 2.77 6 Provident Funds 4.25 4.25 4.24 4.35 4.45 7 Pension Funds 4.86 5.05 4.91 4.96 4.90 8 Financial Institutions 0.63 0.64 0.71 0.74 0.76 9 Corporates 1.60 1.45 1.49 1.26 1.25 10 Foreign Portfolio Investors 2.80 2.81 3.12 2.80 2.97 11 RBI 11.16 10.55 12.78 14.21 13.54 12 Others 5.92 6.01 6.01 6.13 6.22 12.1 State Governments 2.19 2.21 2.25 2.29 2.37 State Governments Securities 2024 2025 Category Sep. Dec. Mar. Jun. Sep. 1 2 3 4 5 (B) Total (in ₹. Crore) 5909490 6055711 6399564 6524417 6721556 1 Commercial Banks 34.39 35.11 35.40 35.54 35.00 2 Co-operative Banks 3.29 3.22 3.08 3.02 3.06 3 Non-Bank PDs 0.60 0.53 0.61 0.60 0.65 4 Insurance Companies 25.56 25.16 24.07 24.12 24.12 5 Mutual Funds 1.93 1.89 1.93 1.84 2.16 6 Provident Funds 23.02 22.90 23.60 23.72 23.65 7 Pension Funds 4.87 4.82 5.07 4.96 5.10 8 Financial Institutions 1.57 1.58 1.48 1.59 1.61 9 Corporates 1.95 1.97 2.05 1.93 1.93 10 Foreign Portfolio Investors 0.04 0.03 0.05 0.02 0.02 11 RBI 0.60 0.58 0.55 0.54 0.53 12 Others 2.18 2.19 2.10 2.12 2.17 12.1 State Governments 0.26 0.26 0.25 0.25 0.27 Treasury Bills 2024 2025 Category Sep. Dec. Mar. Jun. Sep. 1 2 3 4 5 (C) Total (in ₹. Crore) 747242 760045 790381 784059 754280 1 Commercial Banks 44.74 40.45 46.58 42.87 39.45 2 Co-operative Banks 1.58 1.22 2.17 1.80 1.58 3 Non-Bank PDs 2.28 1.41 2.09 1.10 2.03 4 Insurance Companies 5.26 4.73 4.23 4.07 4.26 5 Mutual Funds 15.06 15.41 16.15 15.72 17.60 6 Provident Funds 0.26 0.04 0.20 0.09 0.07 7 Pension Funds 0.00 0.00 0.02 0.00 0.00 8 Financial Institutions 6.36 6.77 7.73 6.31 6.34 9 Corporates 4.66 4.56 4.50 3.77 3.80 10 Foreign Portfolio Investors 0.15 0.12 0.09 0.02 0.01 11 RBI 0.00 0.00 0.00 0.00 0.00 12 Others 19.65 25.29 16.23 24.26 24.85 12.1 State Governments 14.95 20.11 11.23 18.34 18.53 Notes: (1) The table format is revised since monthly Bulletin for the month of June 2023. (2) Central Government Dated Securities include special securities and Sovereign Gold Bonds. (3) State Government Securities include special bonds issued under Ujwal DISCOM Assurance Yojana (UDAY). (4) Bank PDs are clubbed under Commercial Banks. (5) The category ‘Others’ comprises State Governments, DICGC, PSUs, Trusts, Foreign Central Banks, HUF/ Individuals etc. (6) Data since September 2023 includes the impact of the merger of a non-bank with a bank. 156 RBI Bulletin December 2025CURRENT STATISTICS No. 47: Combined Receipts and Disbursements of the Central and State Governments (₹ Crore) Item 2019-20 2020-21 2021-22 2022-23 2023-24 RE 2024-25 BE 1 2 3 4 5 6 1 Total Disbursements 5410887 6353359 7098451 7880522 9110725 9800798 1.1 Developmental 3074492 3823423 4189146 4701611 5514584 5862996 1.1.1 Revenue 2446605 3150221 3255207 3574503 3965270 4195108 1.1.2 Capital 588233 550358 861777 1042159 1453849 1526993 1.1.3 Loans 39654 122844 72163 84949 95464 140895 1.2 Non-Developmental 2253027 2442941 2810388 3069896 3467270 3800321 1.2.1 Revenue 2109629 2271637 2602750 2895864 3266628 3537378 1.2.1.1 Interest Payments 955801 1060602 1226672 1377807 1562660 1711972 1.2.2 Capital 141457 169155 175519 171131 196073 259346 1.2.3 Loans 1941 2148 32119 2902 4569 3597 1.3 Others 83368 86995 98916 109015 128871 137481 2 Total Receipts 5734166 6397162 7156342 7855370 9054999 9650488 2.1 Revenue Receipts 3851563 3688030 4823821 5447913 6379349 7209647 2.1.1 Tax Receipts 3231582 3193390 4160414 4809044 5456913 6142276 2.1.1.1 Taxes on commodities and services 2012578 2076013 2626553 2865550 3248450 3631569 2.1.1.2 Taxes on Income and Property 1216203 1114805 1530636 1939550 2204462 2506181 2.1.1.3 Taxes of Union Territories (Without Legislature) 2800 2572 3225 3943 4001 4526 2.1.2 Non-Tax Receipts 619981 494640 663407 638870 922436 1067371 2.1.2.1 Interest Receipts 31137 33448 35250 42975 49552 57273 2.2 Non-debt Capital Receipts 110094 64994 44077 62716 86733 118239 2.2.1 Recovery of Loans & Advances 59515 16951 27665 15970 55895 45125 2.2.2 Disinvestment proceeds 50578 48044 16412 46746 30839 73114 3 Gross Fiscal Deficit [ 1 - ( 2.1 + 2.2 ) ] 1449230 2600335 2230553 2369892 2644642 2472912 3A Sources of Financing: Institution-wise 3A.1 Domestic Financing 1440548 2530155 2194406 2332768 2619811 2456959 3A.1.1 Net Bank Credit to Government 571872 890012 627255 687904 346483 ... 3A.1.1.1 Net RBI Credit to Government 190241 107493 350911 529 -257913 ... 3A.1.2 Non-Bank Credit to Government 868676 1640143 1567151 1644864 2273328 ... 3A.2 External Financing 8682 70180 36147 37124 24832 15952 3B Sources of Financing: Instrument-wise 3B.1 Domestic Financing 1440548 2530155 2194406 2332768 2619811 2456959 3B.1.1 Market Borrowings (net) 971378 1696012 1213169 1651076 1962969 1983757 3B.1.2 Small Savings (net) 209232 458801 526693 358764 434151 447511 3B.1.3 State Provident Funds (net) 38280 41273 28100 13880 21386 19857 3B.1.4 Reserve Funds 10411 4545 42153 68803 52385 -33653 3B.1.5 Deposits and Advances -14227 25682 42203 51989 35819 -10138 3B.1.6 Cash Balances -323279 -43802 -57891 25152 55726 150310 3B.1.7 Others 548753 347643 399980 163104 57374 -100684 3B.2 External Financing 8682 70180 36147 37124 24832 15952 4 Total Disbursements as per cent of GDP 26.9 32.0 30.1 29.2 30.8 30.0 5 Total Receipts as per cent of GDP 28.5 32.2 30.3 29.1 30.7 29.6 6 Revenue Receipts as per cent of GDP 19.2 18.6 20.4 20.2 21.6 22.1 7 Tax Receipts as per cent of GDP 16.1 16.1 17.6 17.8 18.5 18.8 8 Gross Fiscal Deficit as per cent of GDP 7.2 13.1 9.5 8.8 9.0 7.6 … : Not available; RE: Revised Estimates; BE: Budget Estimates Source : Budget Documents of Central and State Governments. Notes: GDP data is based on 2011-12 base. GDP for 2024-25 is from Union Budget 2024-25. Data pertains to all States and Union Territories. 1 & 2: Data are net of repayments of the Central Government (including repayments to the NSSF) and State Governments. 1.3: Represents compensation and assignments by States to local bodies and Panchayati Raj institutions. 2: Data are net of variation in cash balances of the Central and State Governments and includes borrowing receipts of the Central and State Governments. 3A.1.1: Data as per RBI records. 3B.1.1: Borrowings through dated securities. 3B.1.2: Represent net investment in Central and State Governments’ special securities by the National Small Savings Fund (NSSF). This data may vary from previous publications due to adjustments across components with availability of new data. 3B.1.6: Include Ways and Means Advances by the Centre to the State Governments. 3B.1.7: Include Treasury Bills, loans from financial institutions, insurance and pension funds, remittances, cash balance investment account. RBI Bulletin December 2025 157No. 48: Financial Accommodation Availed by State Governments under various Facilities (₹ Crore) During October-2025 Sr. State/Union Territory Special Drawing Ways and Means Overdraft (OD) No Facility (SDF) Advances (WMA) Average Number Average Number Average Number amount of days amount of days amount of days availed availed availed availed availed availed 1 2 3 4 5 6 7 1 Andhra Pradesh 6932.04 31 1894.93 26 1684.23 9 2 Arunachal Pradesh - - - - - - 3 Assam - - - - - - 4 Bihar - - - - - - 5 Chhattisgarh - - - - - - 6 Goa - - - - - - 7 Gujarat - - - - - - 8 Haryana 1061.91 24 692.70 1 - - 9 Himachal Pradesh - - 571.66 24 76.50 2 10 Jammu & Kashmir UT 36.79 9 381.36 8 - - 11 Jharkhand - - - - - - 12 Karnataka - - - - - - 13 Kerala 975.57 9 456.75 3 - - 14 Madhya Pradesh - - - - - - 15 Maharashtra - - - - - - 16 Manipur - - - - - - 17 Meghalaya 204.03 18 - - - - 18 Mizoram - - - - - - 19 Nagaland 33.54 1 - - - - 20 Odisha - - - - - - 21 Puducherry - - - - - - 22 Punjab 5441.34 31 983.80 19 - - 23 Rajasthan 3042.44 12 651.85 6 - - 24 Tamil Nadu - - - - - - 25 Telangana 4711.92 31 508.75 14 - - 26 Tripura - - - - - - 27 Uttar Pradesh - - - - - - 28 Uttarakhand 462.75 31 - - - - 29 West Bengal - - - - - - Notes: 1. SDF is availed by State Governments against the collateral of Consolidated Sinking Fund (CSF), Guarantee Redemption Fund (GRF) & Auction Treasury Bills (ATBs) balances and other investments in government securities. 2. WMA is advance by Reserve Bank of India to State Governments for meeting temporary cash mismatches. 3. OD is advanced to State Governments beyond their WMA limits. 4. Average amount availed is the total accommodation (SDF/WMA/OD) availed divided by number of days for which accommodation was extended during the month. 5.- : Nil. Source: Reserve Bank of India. 158 RBI Bulletin December 2025CURRENT STATISTICS No. 49: Investments by State Governments (₹ Crore) As on end of October 2025 Consolidated Guarantee Sr. State/Union Government Auction Treasury Sinking Fund Redemption Fund No Territory Securities Bills (ATBs) (CSF) (GRF) 1 2 3 4 5 1 Andhra Pradesh 12201 1202 0 0 2 Arunachal Pradesh 3101 8 0 8000 3 Assam 8176 95 0 0 4 Bihar 15088 993 0 16000 5 Chhattisgarh 8667 1008 0 12676 6 Goa 1183 482 0 0 7 Gujarat 16075 702 0 2500 8 Haryana 2747 1798 0 0 9 Himachal Pradesh - - 0 0 10 Jammu & Kashmir UT 56 55 0 0 11 Jharkhand 3154 - 0 0 12 Karnataka 21322 1761 0 41160 13 Kerala 3396 0 0 0 14 Madhya Pradesh - 1342 0 1500 15 Maharashtra 73818 3246 0 0 16 Manipur 73 148 0 0 17 Meghalaya 1341 114 0 0 18 Mizoram 531 84 0 0 19 Nagaland 1997 49 0 0 20 Odisha 19216 2157 0 21260 21 Puducherry 611 - 0 2350 22 Punjab 10585 978 0 0 23 Rajasthan 2960 1457 0 5550 24 Tamil Nadu 3625 - 0 4718 25 Telangana 8321 1826 0 0 26 Tripura 1387 31 0 0 27 Uttarakhand 5965 321 0 0 28 Uttar Pradesh 22769 5539 0 25000 29 West Bengal 15061 1139 0 9000 Total 263427 26536 0 149715 Notes: 1. CSF and GRF are reserve funds maintained by some State Governments with the Reserve Bank of India. 2. ATBs include investment by State Governments in Treasury bills of 91 days, 182 days and 364 days in the primary market. 3. - : Not Applicable (not a member of the scheme). RBI Bulletin December 2025 159No. 50: Market Borrowings of State Governments (₹ Crore) 2025-26 Total amount 2023-24 2024-25 raised, so far in August September October 2025-26 Sr. No. State Gross Net Gross Net Gross Net Gross Net Gross Net Amount Amount Amount Amount Amount Amount Amount Amount Amount Amount Gross Net Raised Raised Raised Raised Raised Raised Raised Raised Raised Raised 1 2 3 4 5 6 7 8 9 10 11 12 13 1 Andhra Pradesh 68400 55330 78205 57123 5000 3800 5000 4000 3900 2400 46072 35572 2 Arunachal Pradesh 902 672 1010 704 - - - - - - - -130 3 Assam 18500 16000 19000 13850 1104 1104 2300 1800 - -500 8304 6354 4 Bihar 47612 29910 47546 30890 6000 6000 14000 11922 5500 4000 31500 27922 5 Chhattisgarh 32000 26213 24500 16913 - - 500 500 2000 - 6470 3770 6 Goa 2550 1560 1050 250 300 200 200 - 200 200 1000 300 7 Gujarat 30500 11947 38200 16280 3500 2500 3000 700 3000 700 22500 9140 8 Haryana 47500 28364 49500 31710 3000 2000 3500 1500 6000 6000 25500 15970 9 Himachal Pradesh 8072 5856 7359 4725 1500 1000 - -200 200 -300 6619 4769 10 Jammu & Kashmir UT 16337 13904 13170 11416 1100 650 700 700 1000 860 6405 4815 11 Jharkhand 1000 -2505 3500 -2005 - - 2000 2000 - -500 2000 500 12 Karnataka 81000 63003 92025 71525 - - - - - -3000 - -4000 13 Kerala 42438 26638 53666 37966 4988 1988 5000 5000 2000 500 28988 17488 14 Madhya Pradesh 38500 26264 63400 47206 8800 7300 7000 5000 8200 8200 39077 33077 15 Maharashtra 110000 79738 123000 90917 12000 9000 8500 5500 19000 16000 85000 68000 16 Manipur 1426 1076 1500 1037 - - 350 350 - - 1350 1000 17 Meghalaya 1364 912 1882 997 300 - 500 500 - -360 1650 770 18 Mizoram 901 641 1169 939 100 100 150 90 110 110 585 450 19 Nagaland 2551 2016 1550 950 - - 400 250 - - 400 50 20 Odisha 0 -4658 20780 17780 2000 2000 1000 1000 1000 1000 7000 7000 21 Puducherry 1100 475 1600 880 - - 350 350 - -125 550 225 22 Punjab 42386 29517 40828 32466 1500 - 2933 1521 4000 2500 29233 20079 23 Rajasthan 73624 49718 75185 49479 6000 5000 3000 500 10000 7980 48100 32518 24 Sikkim 1916 1701 1951 1621 - - 500 500 500 500 1000 1000 25 Tamil Nadu 113001 75970 123625 89894 8000 5600 9000 7500 11000 6525 59300 37175 26 Telangana 49618 39385 56209 42199 8000 7200 12000 10800 5000 3798 50900 39550 27 Tripura 0 -550 0 -150 - - - - - - 800 600 28 Uttar Pradesh 97650 85335 45000 23185 3000 2000 - -2000 5500 1524 17500 -709 29 Uttarakhand 6300 3800 10400 8000 - -500 - -500 1500 1250 4500 2500 30 West Bengal 69910 48910 76500 54600 5500 4000 5500 4000 1500 500 25500 16000 Grand Total 1007058 717140 1073310 753345 81692 60942 87383 63283 91110 59763 557802 381755 - : Nil. Note: The State of J&K has ceased to exist constitutionally from October 31, 2019 and the liabilities of the State continue to remain as liabilities of the new UT of Jammu and Kashmir. Source: Reserve Bank of India. 160 RBI Bulletin December 2025CURRENT STATISTICS No. 51 (a): Flow of Financial Assets and Liabilities of Households - Instrument-wise (Amount in ` Crore) 2022-23 Item Q1 Q2 Q3 Q4 Annual Net Financial Assets (I-II) 287802.7 297217.6 293954.9 451660.3 1330635.4 Per cent of GDP 4.4 4.6 4.3 6.4 4.9 I. Financial Assets 577822.4 632335.6 748109.7 968986.1 2927253.7 Per cent of GDP 8.9 9.8 11.0 13.6 10.9 of which: 1.Total Deposits (a+b) 185429.1 317361.2 280233.1 325852.7 1108876.2 (a) Bank Deposits 163172.4 299532.7 256399.7 307866.8 1026971.5 i. Commercial Banks 158613.3 300565.0 248459.8 284968.0 992606.2 ii. Co-operative Banks 4559.0 -1032.4 7939.8 22898.9 34365.3 (b) Non-Bank Deposits 22256.8 17828.6 23833.5 17985.9 81904.7 of which: Other Financial Institutions (i+ii) 6504.8 2076.7 8081.6 2234.0 18897.1 i. Non-Banking Financial Companies 4230.6 3267.2 3246.9 3945.8 14690.4 ii. Housing Finance Companies 2274.2 -1190.5 4834.7 -1711.8 4206.6 2. Life Insurance Funds 73357.5 151737.1 167581.7 156268.5 548944.9 3. Provident and Pension Funds (including PPF) 146719.1 118171.9 136388.4 216513.6 617793.1 4. Currency 66438.9 -54579.3 76760.1 148990.1 237609.7 5. Investments 51502.6 48530.1 49778.6 64150.6 213961.9 of which: (a) Mutual Funds 35443.5 44484.0 40205.9 58954.5 179087.8 (b) Equity 13560.9 1378.2 6434.1 1664.9 23038.1 6. Small Savings (excluding PPF) 54375.1 51114.5 37367.7 57210.6 200068.0 II. Financial Liabilities 290019.7 335118.0 454154.8 517325.8 1596618.3 Per cent of GDP 4.5 5.2 6.7 7.3 5.9 Loans/Borrowings 1. Financial Corporations (a+b) 289781.5 334879.7 453916.6 517087.5 1595665.3 (a) Banking Sector 234235.0 263450.2 370782.9 383843.2 1252311.4 of which: i. Commercial Banks 230283.8 261265.3 368304.6 331291.0 1191144.8 (b) Other Financial Institutions 55546.4 71429.5 83133.7 133244.3 343353.9 i. Non-Banking Financial Companies 30531.7 36650.3 55791.7 94565.3 217539.1 ii. Housing Finance Companies 22336.7 33031.2 24903.3 36745.8 117017.0 iii. Insurance Corporations 2678.0 1747.9 2438.7 1933.2 8797.8 2. Non-Financial Corporations (Private Corporate Business) 33.7 33.7 33.7 33.7 135.0 3. General Government 204.5 204.5 204.5 204.5 818.0 RBI Bulletin December 2025 161No. 51 (a): Flow of Financial Assets and Liabilities of Households - Instrument-wise (Contd.) (Amount in ` Crore) 2023-24 Item Q1 Q2 Q3 Q4 Annual Net Financial Assets (I-II) 349607.1 283994.4 294431.6 666547.4 1594580.4 Per cent of GDP 4.8 3.9 3.8 8.4 5.3 I. Financial Assets 671244.1 810128.8 805066.2 1187279.1 3473718.2 Per cent of GDP 9.3 11.2 10.4 14.9 11.5 of which: 1.Total Deposits (a+b) 266680.3 407948.0 296931.3 406706.9 1378266.4 (a) Bank Deposits 253004.1 501768.5 277432.0 390720.4 1422924.9 i. Commercial Banks 243833.9 502260.7 280096.7 383460.6 1409651.9 ii. Co-operative Banks 9170.2 -492.2 -2664.7 7259.8 13273.0 (b) Non-Bank Deposits 13676.2 -93820.5 19499.4 15986.5 -44658.5 of which: Other Financial Institutions (i+ii) -485.4 -107982.1 5337.7 1824.9 -101304.9 i. Non-Banking Financial Companies 6119.3 4782.3 4895.8 1942.9 17740.3 ii. Housing Finance Companies -6604.7 -112764.4 441.9 -118.0 -119045.2 2. Life Insurance Funds 157301.9 140356.8 160135.2 189267.6 647061.4 3. Provident and Pension Funds (including PPF) 163686.0 148356.1 153435.1 253882.9 719360.2 4. Currency -48636.2 -36700.8 56719.0 146643.8 118025.7 5. Investments 41014.3 72664.6 79238.2 108336.6 301253.8 of which: (a) Mutual Funds 32085.6 55768.8 60134.6 90973.0 238962.1 (b) Equity 3756.7 7146.3 9941.1 8236.1 29080.1 6. Small Savings (excluding PPF) 91197.8 77504.1 58607.4 82441.4 309750.7 II. Financial Liabilities 321637.1 526134.4 510634.6 520731.7 1879137.8 Per cent of GDP 4.5 7.3 6.6 6.5 6.2 Loans/Borrowings 1. Financial Corporations (a+b) 321519.8 526016.2 510516.4 520613.5 1878665.8 (a) Banking Sector 213606.3 868873.9 402647.1 392330.5 1877457.7 of which: i. Commercial Banks 208026.5 875654.0 389898.0 382557.9 1856136.4 (b) Other Financial Institutions 107913.6 -342857.7 107869.2 128283.0 1208.0 i. Non-Banking Financial Companies 81448.8 59683.7 85031.8 100836.5 327000.7 ii. Housing Finance Companies 23784.0 -404294.0 21233.4 25852.9 -333423.7 iii. Insurance Corporations 2680.7 1752.6 1604.0 1593.6 7631.0 2. Non-Financial Corporations (Private Corporate Business) 33.7 34.7 34.7 34.7 138.0 3. General Government 83.5 83.5 83.5 83.5 334.0 162 RBI Bulletin December 2025CURRENT STATISTICS No. 51 (a): Flow of Financial Assets and Liabilities of Households - Instrument-wise (Concld.) (Amount in ` Crore) 2024-25 Item Q1 Q2 Q3 Q4 Annual Net Financial Assets (I-II) 551994.2 496676.1 271043.1 674489.0 1994202.4 Per cent of GDP 7.0 6.3 3.2 7.6 6.0 I. Financial Assets 840665.3 901135.4 689663.5 1129381.1 3560845.4 Per cent of GDP 10.6 11.5 8.1 12.8 10.8 of which: 1.Total Deposits (a+b) 274567.9 403591.4 158320.8 418183.6 1254663.6 (a) Bank Deposits 254885.4 388328.6 141290.0 401577.5 1186081.4 i. Commercial Banks 251171.1 389734.0 147864.7 395337.4 1184107.2 ii. Co-operative Banks 3714.3 -1405.4 -6574.7 6240.0 1974.2 (b) Non-Bank Deposits 19682.4 15262.8 17030.8 16606.1 68582.2 of which: Other Financial Institutions (i+ii) 7461.4 3041.8 4809.8 4385.1 19698.2 i. Non-Banking Financial Companies 6289.7 3230.0 4444.5 4220.0 18184.2 ii. Housing Finance Companies 1171.7 -188.2 365.4 165.1 1514.0 2. Life Insurance Funds 175427.0 178835.2 90159.4 90393.0 534814.6 3. Provident and Pension Funds (including PPF) 170218.2 170219.6 170758.3 281332.6 792528.6 4. Currency 34212.5 -57615.2 70840.8 162236.1 209674.1 5. Investments 120638.2 152637.1 159255.2 103720.8 536251.4 of which: (a) Mutual Funds 106987.0 137618.0 124132.0 97193.0 465930.0 (b) Equity 14448.0 15645.0 36063.1 7410.3 73566.5 6. Small Savings (excluding PPF) 65601.6 53467.4 40329.0 73515.0 232913.0 II. Financial Liabilities 288671.1 404459.3 418620.4 454892.1 1566642.9 Per cent of GDP 3.7 5.2 4.9 5.2 4.7 Loans/Borrowings 1. Financial Corporations (a+b) 288492.4 404280.6 418441.7 454713.3 1565928.0 (a) Banking Sector 205040.4 322147.7 319626.6 387045.6 1233860.3 of which: i. Commercial Banks 208525.3 321241.4 302569.3 379856.5 1212192.4 (b) Other Financial Institutions 83452.0 82132.9 98815.0 67667.7 332067.7 i. Non-Banking Financial Companies 65813.7 65488.7 75764.5 39833.9 246900.8 ii. Housing Finance Companies 15125.2 14233.6 20561.4 25756.8 75677.0 iii. Insurance Corporations 2513.1 2410.7 2489.1 2077.1 9489.9 2. Non-Financial Corporations (Private Corporate Business) 34.7 34.7 34.7 34.7 139.0 3. General Government 144.0 144.0 144.0 144.0 576.0 Notes : 1. Net Financial Savings of households refer to the net financial assets, which are measured as difference of financial asset and liabilities flows. 2. Preliminary estimates for 2024-25 and revised estimates for 2022-23 and 2023-24. 3. The preliminary estimates for 2024-25 will undergo revision with the release of first revised estimates of national income, consumption expenditure, savings, and capital formation, 2024-25 by the NSO. 4. Non-bank deposits apart from other financial institutions, comprises state power utilities, co-operative non credit societies etc. 5. Figures in the columns may not add up to the total due to rounding off. RBI Bulletin December 2025 163No. 51 (b): Stocks of Financial Assets and Liabilities of Households- Select Indicators (Amount in ` Crore) Item Jun-2022 Sep-2022 Dec-2022 Mar-2023 Financial Assets (a+b+c+d+e+f+g+h) 25621348.1 26423992.1 27187715.6 27844981.1 Per cent of GDP 102.8 102.6 103.3 103.5 (a) Bank Deposits (i+ii) 11843527.1 12143059.7 12399459.4 12707326.2 i. Commercial Banks 10987692.1 11288257.2 11536717.0 11821685.0 ii. Co-operative Banks 855834.9 854802.6 862742.4 885641.2 (b) Non-Bank Deposits of which: Other Financial Institutions 216170.0 218246.7 226328.2 228562.2 i. Non-Banking Financial Companies 74794.2 78061.4 81308.3 85254.0 ii. Housing Finance Companies 141375.8 140185.3 145020.0 143308.2 (c) Life Insurance Funds 5325967.3 5559681.9 5786592.6 5795430.6 (d) Currency 2950343.2 2895763.9 2972524.0 3121514.1 (e) Mutual funds 2048097.3 2260209.7 2355315.8 2367792.5 (f) Public Provident Fund (PPF) 851913.4 858591.1 864730.6 939449.0 (g) Pension Funds 744459.2 796454.0 853412.0 898343.0 (h) Small Savings (excluding PPF) 1640870.6 1691985.1 1729352.9 1786563.5 Financial Liabilities (a+b) 8911860.9 9246740.6 9700657.2 10217744.7 Per cent of GDP 35.8 35.9 36.9 38.0 Loans/Borrowings (a) Banking Sector 7095467.7 7358918.0 7729700.9 8113544.1 of which: i. Commercial Banks 6620073.1 6881338.5 7249643.0 7580934.1 ii. Co-operative Banks 473897.0 476024.8 478486.9 530915.0 (b) Other Financial Institutions 1816393.1 1887822.6 1970956.3 2104200.7 of which: i. Non-Banking Financial Companies 869174.9 905825.3 961617.0 1056182.3 ii. Housing Finance Companies 835181.3 868212.5 893115.8 929861.7 iii. Insurance Corporations 112036.9 113784.8 116223.5 118156.7 164 RBI Bulletin December 2025CURRENT STATISTICS No. 51 (b): Stocks of Financial Assets and Liabilities of Households- Select Indicators (Contd.) (Amount in ` Crore) Item Jun-2023 Sep-2023 Dec-2023 Mar-2024 Financial Assets (a+b+c+d+e+f+g+h) 28754605.9 29637615.0 30737884.8 32025210.0 Per cent of GDP 104.2 104.4 105.0 106.3 (a) Bank Deposits (i+ii) 12960330.3 13462098.8 13739530.7 14130251.1 i. Commercial Banks 12065518.9 12567779.6 12847876.2 13231336.9 ii. Co-operative Banks 894811.4 894319.2 891654.5 898914.3 (b) Non-Bank Deposits of which: Other Financial Institutions 228076.8 120094.7 125432.4 127257.3 i. Non-Banking Financial Companies 91373.3 96155.6 101051.4 102994.3 ii. Housing Finance Companies 136703.5 23939.1 24381.0 24263.0 (c) Life Insurance Funds 6064436.9 6255801.1 6553726.0 6820611.8 (d) Currency 3072877.9 3036177.0 3092896.0 3239539.8 (e) Mutual funds 2626046.1 2829859.3 3156299.3 3387208.3 (f) Public Provident Fund (PPF) 955060.6 960343.6 964851.5 1051376.5 (g) Pension Funds 970016.0 1017975.0 1091276.0 1172651.0 (h) Small Savings (excluding PPF) 1877761.2 1955265.4 2013872.8 2096314.2 Financial Liabilities (a+b) 10539264.5 11065280.7 11575797.1 12096410.5 Per cent of GDP 38.2 39.0 39.6 40.2 Loans/Borrowings (a) Banking Sector 8327150.3 9196024.2 9598671.3 9991001.8 of which: i. Commercial Banks 7788960.6 8664614.6 9054512.6 9437070.5 ii. Co-operative Banks 536409.2 529527.7 542240.6 551852.1 (b) Other Financial Institutions 2212114.2 1869256.5 1977125.7 2105408.7 of which: i. Non-Banking Financial Companies 1137631.1 1197314.8 1282346.6 1383183.0 ii. Housing Finance Companies 953645.7 549351.7 570585.1 596438.0 iii. Insurance Corporations 120837.4 122590.0 124194.0 125787.7 RBI Bulletin December 2025 165No. 51 (b): Stocks of Financial Assets and Liabilities of Households- Select Indicators (Concld.) (Amount in ` Crore) Item Jun-2024 Sep-2024 Dec-2024 Mar-2025 Financial Assets (a+b+c+d+e+f+g+h) 33253098.6 34421189.5 34532805.6 35264710.9 Per cent of GDP 107.9 109.6 107.2 106.6 (a) Bank Deposits (i+ii) 14385136.5 14773465.1 14914755.1 15316332.6 i. Commercial Banks 13482508.0 13872242.0 14020106.6 14415444.1 ii. Co-operative Banks 902628.6 901223.2 894648.5 900888.5 (b) Non-Bank Deposits of which: Other Financial Institutions 134718.7 137760.5 142570.3 146955.5 i. Non-Banking Financial Companies 109284.0 112514.0 116958.5 121178.5 ii. Housing Finance Companies 25434.7 25246.5 25611.9 25777.0 (c) Life Insurance Funds 7123527.6 7385938.1 7272871.3 7293099.1 (d) Currency 3273752.3 3216137.1 3286977.8 3449213.9 (e) Mutual funds 3866386.1 4291914.4 4224091.7 4128924.5 (f) Public Provident Fund (PPF) 1059829.5 1063056.1 1064212.0 1157449.2 (g) Pension Funds 1247832.0 1337535.0 1371615.0 1443509.0 (h) Small Savings (excluding PPF) 2161915.8 2215383.2 2255712.2 2329227.2 Financial Liabilities (a+b) 12384902.9 12789183.5 13207625.1 13662338.5 Per cent of GDP 40.2 40.7 41.0 41.3 Loans/Borrowings (a) Banking Sector 10196042.2 10518189.9 10837816.5 11224862.1 of which: i. Commercial Banks 9645595.7 9966837.1 10269406.4 10649262.8 ii. Co-operative Banks 548284.4 549069.4 566104.4 573131.8 (b) Other Financial Institutions 2188860.7 2270993.6 2369808.7 2437476.4 of which: i. Non-Banking Financial Companies 1448996.8 1514485.5 1590250.0 1630083.9 ii. Housing Finance Companies 611563.2 625796.8 646358.2 672115.0 iii. Insurance Corporations 128300.7 130711.4 133200.5 135277.5 Notes : 1. Data as ratios to GDP have been calculated based on the Provisional Estimates of National Income 2024-25, released by NSO on May 30, 2025. 2. Pension funds comprises funds with the National Pension Scheme. 3. Outstanding deposits with Small Savings are sourced from the Controller General of Accounts, Government of India. 4. Non-bank deposits apart from other financial institutions, comprises state power utilities, co-operative non credit societies etc. Data for outstanding deposits are available only for other financial institutions. 5. Figures in the columns may not add up to the total due to rounding off. 166 RBI Bulletin December 2025CURRENT STATISTICS Explanatory Notes to the Current Statistics Table No. 1 1.2& 6: Annual data are average of months. 3.5 & 3.7: Relate to ratios of increments over financial year so far. 4.1 to 4.4, 4.8,4.9 &5: Relate to the last friday of the month/financial year. 4.5, 4.6 & 4.7: Relate to five major banks on the last Friday of the month/financial year. 4.10 to 4.12: Relate to the last auction day of the month/financial year. 4.13: Relate to last day of the month/ financial year 7.1&7.2: Relate to Foreign trade in US Dollar. Table No. 2 2.1.2: Include paid-up capital, reserve fund and Long-Term Operations Funds. 2.2.2: Include cash, fixed deposits and short-term securities/bonds, e.g., issued by IIFC (UK). Table No. 4 Maturity-wise position of outstanding forward contracts is available at http://nsdp.rbi.org.in under ‘‘Reserves Template’’. Table No. 5 Special refinance facility to Others, i.e. to the EXIM Bank, is closed since March 31, 2013. Table No. 6 For scheduled banks, March-end data pertain to the last reporting Friday. 1.1: Notes in Circulation include CBDC-Retail (R) and CBDC-Wholesale (W). 1.4: Cash on Hand with Banks includes CBDC-W. 2.2: Exclude balances held in IMF Account No.1, RBI employees’ provident fund, pension fund, gratuity and superannuation fund. Table Nos. 7 & 11 3.1 in Table 7 and 2.4 in Table 11: Include foreign currency denominated bonds issued by IIFC (UK). Table No. 8 NM and NM do not include FCNR (B) deposits. 2 3 2.4: Consist of paid-up capital and reserves. 2.5: includes other demand and time liabilities of the banking system. Table No. 9 Financial institutions comprise EXIM Bank, SIDBI, NABARD and NHB. L and L are compiled monthly and L quarterly. 1 2 3 Wherever data are not available, the last available data have been repeated. Table No. 13 Data against column Nos. (1), (2) & (3) are Final and for column Nos. (4) & (5) data are Provisional. RBI Bulletin December 2025 167CURRENT STATISTICS Table No. 14 Data in column Nos. (4) & (8) are Provisional. Table No. 17 2.1.1: Exclude reserve fund maintained by co-operative societies with State Co-operative Banks 2.1.2: Exclude borrowings from RBI, SBI, IDBI, NABARD, notified banks and State Governments. 4: Include borrowings from IDBI and NABARD. Table No. 25 Primary Dealers (PDs) include banks undertaking PD business. Table No. 31 Exclude private placement and offer for sale. 1: Exclude bonus shares. 2: Include cumulative convertible preference shares and equi-preference shares. Table No. 33 Exclude investment in foreign currency denominated bonds issued by IIFC (UK), SDRs transferred by Government of India to RBI and foreign currency received under SAARC and ACU currency swap arrangements. Foreign currency assets in US dollar take into account appreciation/depreciation of non-US currencies (such as Euro, Sterling, Yen and Australian Dollar) held in reserves. Foreign exchange holdings are converted into rupees at rupee-US dollar RBI holding rates. Table No. 35 1.1.1.1.2 & 1.1.1.1.1.4: Estimates. 1.1.1.2: Estimates for latest months. ‘Other capital’ pertains to debt transactions between parent and subsidiaries/branches of FDI enterprises. Data may not tally with the BoP data due to lag in reporting. Table No. 36 1.10: Include items such as subscription to journals, maintenance of investment abroad, student loan repayments and credit card payments. Table No. 37 Increase in indices indicates appreciation of rupee and vice versa. For 6-Currency index, base year 2022-23 is a moving one, which gets updated every year. REER figures are based on Consumer Price Index (combined). The details on methodology used for compilation of NEER/REER indices are available in December 2005, April 2014 and January 2021 issues of the RBI Bulletin. Table No. 38 Based on applications for ECB/Foreign Currency Convertible Bonds (FCCBs) which have been allotted loan registration number during the period. 168 RBI Bulletin December 2025CURRENT STATISTICS Table Nos. 39, 40, 41 & 42 Explanatory notes on these tables are available in December issue of RBI Bulletin, 2012. Table No. 44 Part I-A. Settlement systems 1.1.3: Tri- party Repo under the securities segment has been operationalised from November 05, 2018. Part I-B. Payments systems 4.1.2: ‘Others’ includes e-commerce transactions and digital bill payments through ATMs, etc. 4.2.2: ‘Others’ includes e-commerce transactions, card to card transfers and digital bill payments through ATMs, etc. 5: Available from December 2010. 5.1: includes purchase of goods and services and fund transfer through wallets. 5.2.2: includes usage of PPI Cards for online transactions and other transactions. 6.1: Pertain to three grids – Mumbai, New Delhi and Chennai. 6.2: ‘Others’ comprises of Non-MICR transactions which pertains to clearing houses managed by 21 banks. Part II-A. Other payment channels 1: Mobile Payments – Include transactions done through mobile apps of banks and UPI apps. o The data from July 2017 includes only individual payments and corporate payments initiated, o processed, and authorised using mobile device. Other corporate payments which are not initiated, processed, and authorised using mobile device are excluded. 2: Internet Payments – includes only e-commerce transactions through ‘netbanking’ and any financial transaction using internet banking website of the bank. Part II-B. ATMs 3.3 and 4.2: only relates to transactions using bank issued PPIs. Part III. Payment systems infrastructure 3: Includes ATMs deployed by Scheduled Commercial Banks (SCBs) and White Label ATM Operators (WLAOs). WLAs are included from April 2014 onwards. Table No. 46 (-) represents nil or negligible The table format is revised since monthly Bulletin for the month of June 2023. Central Government Dated Securities include special securities and Sovereign Gold Bonds. State Government Securities include special bonds issued under Ujwal DISCOM Assurance Yojana (UDAY). Bank PDs are clubbed under Commercial Banks. The category ‘Others’ comprises State Governments, DICGC, PSUs, Trusts, Foreign Central Banks, HUF/ Individuals etc. Data since September 2023 includes the impact of the merger of a non-bank with a bank. RBI Bulletin December 2025 169CURRENT STATISTICS Table No. 47 GDP data is based on 2011-12 base. GDP for 2023-24 is from Union Budget 2023-24. Data pertains to all States and Union Territories. 1 & 2: Data are net of repayments of the Central Government (including repayments to the NSSF) and State Governments. 1.3: Represents compensation and assignments by States to local bodies and Panchayati Raj institutions. 2: Data are net of variation in cash balances of the Central and State Governments and includes borrowing receipts of the Central and State Governments. 3A.1.1: Data as per RBI records. 3B.1.1: Borrowings through dated securities. 3B.1.2: Represent net investment in Central and State Governments’ special securities by the National Small Savings Fund (NSSF). This data may vary from previous publications due to adjustments across components with availability of new data. 3B.1.6: Include Ways and Means Advances by the Centre to the State Governments. 3B.1.7: Include Treasury Bills, loans from financial institutions, insurance and pension funds, remittances, cash balance investment account. Table No. 48 SDF is availed by State Governments against the collateral of Consolidated Sinking Fund (CSF), Guarantee Redemption Fund (GRF) & Auction Treasury Bills (ATBs) balances and other investments in government securities. WMA is advance by Reserve Bank of India to State Governments for meeting temporary cash mismatches. OD is advanced to State Governments beyond their WMA limits. Average amount Availed is the total accommodation (SDF/WMA/OD) availed divided by number of days for which accommodation was extended during the month. - : Nil. Table No. 49 CSF and GRF are reserve funds maintained by some State Governments with the Reserve Bank of India. ATBs include Treasury bills of 91 days, 182 days and 364 days invested by State Governments in the primary market. --: Not Applicable (not a member of the scheme). The concepts and methodologies for Current Statistics are available in Comprehensive Guide for Current Statistics of the RBI Monthly Bulletin (https://rbi.org.in/Scripts/PublicationsView.aspx?id=17618) Time series data of ‘Current Statistics’ is available at https://data.rbi.org.in. Detailed explanatory notes are available in the relevant press releases issued by RBI and other publications/releases of the Bank such as Handbook of Statistics on the Indian Economy. 170 RBI Bulletin December 2025RREECCEENNTT PPUUBBLLIICCAATTIIOONNSS Recent Publications of the Reserve Bank of India Name of Publication Price India Abroad 1. 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