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The Reserve Bank of India’s (RBI) proposed expected credit loss (ECL) framework marks not just an accounting reform, but a fundamental shift in how banks measure and report credit risk. By replacing regulator-determined provisioning rates with institution-specific, model-based estimates, the RBI is asking banks to price and provide for risk according to their own data and experience. Under this system, every exposure carries a dynamic allowance that rises or falls with the borrower’s evolving credit profile, without waiting for a loan to turn into a non-performing asset. It’s a bold move and brings in a new age of predictive judgement, where dynamic data, analytics, and forward-looking insights become the basis for reporting credit risk.
To estimate ECL, banks would need to shift through a lot of historical data and create models that can predict expected losses. The RBI asks for the use of at least five years of loss experience to avoid cyclical distortions, and calculation of probability of default, loss given default, and exposure at default based on that.
But ECL would not be based on historical loss experience alone. Under the draft, ECL must be a probability-weighted average of multiple future scenarios. Possible future scenarios that may need to be predicted are changes in economic cycles (like a downturn/recession), possibility of regulatory changes or tariffs, climate change, inflationary pressure, real estate price shocks, etc. Then banks need to consider what the impact of these events would be on the credit risk of their portfolio. This is not a quants-only task and economics, strategy, and credit teams must be in constant dialogue.
ECL also expects borrower-specific analysis to be done, especially for large corporate borrowers. Provisions may need to be changed for borrower-specific events such as changes in business conditions, management quality, sector outlook. or behavioural signals.
With this shift, the RBI is also specifying governance expectations. The proposed directions place direct accountability on boards and senior management to oversee model design, validation, and performance. Banks must set up dedicated ECL oversight committees, involving the CFO and CRO, to review assumptions, methodologies, and results.
This elevates credit provisioning from a back-office accounting function to a board-level strategic discussion. Questions like “what is our forecast on inflation and how would it impact defaults in our unsecured personal loan portfolio?” or “which borrowers will be affected by US tariffs and how have we incorporated that risk in our provisions?” will increasingly shape both capital allocation and business planning.
We expect that ECL can bring an improved focus on credit risk for finance, risk, analytics, and audit functions, and possibly also the boards. This cross-functional integration and stronger coordination on the topic of credit risk can be a transformative aspect of ECL implementation.
The RBI is also expected to keep a close look at the ECL and related monitoring frameworks, being implemented by the banks and the quality of models, estimates, and judgements.
Once implemented, the ECL framework has the potential to bring transformative change. It can fundamentally strengthen the risk and capital architecture of Indian banks.
Implementation will be expensive and possibly uneven to start with. Quality might be inconsistent, but we have seen that it improves over a period. For larger banks, the imperative is to couple model builds with business reengineering so that pricing, origination, and recovery operations are aware of ECL from day one. Learn the ECL language early, and the regulatory obligation can turn into a strategic advantage. Those that don’t may find themselves paying the price in capital and credibility when the next downturn arrives.
This article first appeared in the Financial Express on 18 November 2025.
