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RBI to publish paper on expected loss-based approach for loan provisioning

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The Reserve Bank of India (RBI) wants banks to adopt the expected credit loss (ECL) regime for provisioning of loan assets and it will shortly come out with a discussion paper on the transition, said Governor on Friday.


Banks in India are currently required to make loan loss provisions on incurred loss model, wherein provisions are made after occurrence of default.


“A more prudent and forward-looking approach is the expected loss-based approach, which requires banks to make provisions based on an assessment of probable losses. As a step towards converging with globally accepted prudential norms, we will issue a discussion paper on the proposed transition for stakeholder comments,” Das said.


The said that the current incurred-loss approach for provisioning of loan assets is inadequate and this was amplified during the global financial crisis (GFC).


“Incurred loss approach is inefficient since it may prove pro-cyclical during economic downturns which can severely impact the health of banks as well as the financial system,” M Rajeshwar Rao, deputy governor at RBI, had said in his address back in June 2022.


Some large non-banking financial companies (NBFCs) follow the forward looking “expected credit loss” approach for estimating credit losses.


In principle, the expected credit-loss approach requires a credit institution to estimate expected credit losses based on forward-looking estimations rather than wait for credit losses to be incurred before making corresponding loss provisions.


The experience of the global financial crisis had prompted the G-20 and the Basel Committee on Banking Supervision (BCBS) to recommend to accounting standard setters to modify the provisioning practices to incorporate a more forward-looking approach rather than to require the losses to happen before they are recognized. This encouraged the move towards adoption of provisioning standards that require the use of expected credit loss (ECL) models rather than incurred loss models.



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