RBI Guv flags rise in bank borrowing by NBFCs

New Delhi: Reserve Bank of India (RBI) Governor Shaktikanta Das on Wednesday flagged concerns over the surge in bank borrowings by non-banking financial companies (NBFCs), saying increasing interconnectedness between financial institutions poses a “contagion risk”.

“NBFCs are large net borrowers of funds from the financial system, with their exposure from the banks being the highest. Banks are also one of the key subscribers to the debentures and commercial papers issued by NBFCs,” Das said at a banking event by the industry body FICCI and the Indian Banks’ Association (IBA).

“NBFCs also maintain borrowing relationships with multiple banks simultaneously. Needless to state that such concentrated linkages may create a contagion risk,” he added and asked banks to constantly evaluate their exposure to NBFCs.

The share of borrowings from banks by NBFCs has gone up sharply in recent years. Bank loans to NBFCs logged a compound annual growth rate (CAGR) of 18% over the last five  years, surging to Rs 12.3 lakh crore in September 2023 from Rs 5.5 lakh crore in September 2018, ratings agency CRISIL said in a research note on Wednesday.  

While the RBI Governor underlined that the Indian banking system continues to be resilient backed by improved capital ratios, asset quality and robust earnings growth, there is a need to take precautionary measures to avoid possible crises.

“In good times like these, banks and NBFCs need to reflect and introspect as to where potential risks could possibly originate. Now is the time for them to further strengthen their risk management practices and build additional buffers to face the situation, if the business cycle turns adverse,” Das said, and advised financial institutions to maintain a sustainable level of credit growth and avoid any exuberance.

He also asked banks and NBFCs to be watchful in applying artificial intelligence (AI) or pre-set algorithms in making lending decisions. Highlighting the risks associated with model-based lending through analytics, Das said such models should be tested and re-tested periodically.

“They may require to be calibrated and re-calibrated from time to time based on the changing contours of the financial ecosystem and fresh information. It is necessary to be watchful of any undue risk build up in the system due to information gaps in these models, which may cause dilution of underwriting standards,” he added.