RBI may introduce expected loss approach for bad loan provisioning in 2023-24

31 May 2023 , 09:51 AM

As one of its initiatives to improve the ecosystem for handling bad loans, the RBI is recommending that the predicted loss-based strategy for provisioning be implemented in 2023–2024. A more recent system of setting aside money for lending will allow banks to create their own credit loss models and spread the larger provisions over a five-year period.

A thorough review of the prudential framework (including the guidelines on the resolution of stress in respect of projects under implementation) and the finalization of guidelines on the securitization of stressed assets are also likely to be undertaken during the year with the aim of further strengthening the resolution ecosystem.

The RBI stated in its Annual Report 2022–23 that ‘…policy measures, such as guidelines on the introduction of expected loss-based approach for provisioning, are likely to be announced during 2023–24.’

A discussion paper on the predicted loss-based approach to provisioning was published by the RBI in January of this year.

Depending on the estimated credit losses associated with them, the banks will have to categorize financial assets, such as primary loans, irrevocable loan commitments, and investments classified as held-to-maturity or available for sale, into one of three categories: Stage 1, Stage 2, or Stage 3.

According to the statement, banks must make the required arrangements. The classification must be completed at the time of initial recognition as well as on each subsequent reporting date.

Even though the Reserve Bank of India suggests leaving it up to the banks to create the model, it lists a number of mitigating concerns about model risk and taking into account the large unpredictability that may occur in its document.

Even though the Reserve Bank of India suggests leaving it up to the banks to create the model, it lists a number of mitigating concerns about model risk and taking into account the large unpredictability that may occur in its document.

The report noted that the current upheaval in the financial sector in the US and Europe has made it necessary to evaluate risks to the financial stability and resilience of financial institutions in the light of tighter monetary policy.

Even if Indian banks and non-banking financial intermediaries are still strong and resilient, it was said that they must conduct a stress test to account for these fresh shocks.

Therefore, the capital buffer and liquidity situation need to be continually assessed and improved.

According to the report, an Advanced Supervisory Analytics Group (ASAG) has been formed to further improve supervisory inputs.

According to ASAG, machine learning models are being built for use cases like social media analytics, KYC compliances, and governance effectiveness.

In order to improve supervisory efficacy, the RBI is now developing efficient SupTech tools using machine learning and artificial intelligence.

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