What is contained in the paper proposal released by RBI about the Loan Loss Provisions? What are the framework and benefits of this approach? What are the problems associated with it? Read further to know.
The Reserve Bank of India has released a discussion paper proposing the use of the expected credit loss (ECL) method for making provisions on bad loans, which could lead to increased capital requirements for banks, according to analysts.
The proposed approach would require banks to assess the likelihood of default at the outset and make provisions accordingly, in contrast to the current method of making provisions after a loan has defaulted.
As per the RBI, the increase in provisioning requirement on common equity tier-I (CET1) capital for loan loss, which will be incurred by scheduled commercial banks due to the transition to the expected credit loss (ECL) model, will be phased out in five years.
The proposed ECL approach is used in International Financial Reporting Standards (IFRS) 9 that has prescribed guidelines for loss provisioning by banks.
What are the Loan Loss Provisions?
The RBI said that banks would be allowed to design and implement their own models for measuring ECL for the purpose of estimating loss provisions in line with the proposed principles.
To cover the losses partially or entirely, banks reserve a proportion of anticipated loan repayments from all the loans in their portfolio. In case of a loss, banks can use their loan loss reserves to cover it, rather than incurring a loss in their cash flows.
Since not all loans are expected to become impaired, loan loss reserves usually have enough funds to cover the loss for any one or a few loans when needed.
In short, an increase in the balance of reserves is known as a loan loss provision. The level of loan loss provision is established to ensure the safety and soundness of the bank, based on the expected level.
As per the proposal, Regional rural banks and smaller cooperative banks (based on a threshold) will be kept out of the above framework.
Framework for Loan Loss Provisions
The Reserve Bank of India has proposed a new framework for loan loss provisioning that requires banks to estimate expected credit losses based on forward-looking estimations. This shift moves away from the current method where loss provisions are made after a default.
Under the proposed framework, banks must classify financial assets into one of three categories: Stage 1, Stage 2, or Stage 3, depending on the assessed credit losses at the time of initial recognition and on each subsequent reporting date.
Stage 1 assets have low credit risk or have not had a significant increase in credit risk since initial recognition. For these assets, 12-month expected credit losses are recognized, and interest revenue is calculated on the gross carrying amount of the asset.
Stage 2 assets have had a significant increase in credit risk since initial recognition, but there is no objective evidence of impairment. Lifetime expected credit losses are recognized for these assets, but interest revenue is still calculated on the gross carrying amount of the asset.
Stage 3 assets have objective evidence of impairment at the reporting date. Lifetime expected credit loss is recognized for these assets, and interest revenue is calculated on the net carrying amount.
Benefits of Loan Loss Provision Approach
Significant benefits of this approach are:
- The Reserve Bank of India (RBI) stated in a discussion paper that the forward-looking expected credit losses approach is likely to enhance the banking system’s resilience, which is in line with globally accepted norms.
- The expected credit losses approach involves banks estimating the credit losses they may incur in the future based on forward-looking estimations.
- This approach is an improvement over the incurred loss approach, where banks wait for credit losses to occur before making corresponding loss provisions.
- According to the RBI, the expected credit loss approach is likely to result in excess provisions as compared to the shortfall in provisions seen in the incurred loss approach.
- Excess provisions can help banks absorb potential future losses and maintain financial stability.
- The RBI’s statement emphasizes the importance of adopting a forward-looking approach to credit losses to enhance the banking system’s resilience.
Problems Associated With This Approach
The discussion paper proposing a shift to an expected credit loss (ECL) method for making provisions on bad loans could raise capital requirements significantly for banks, particularly government-owned banks. The probability of default over the last 5-10 years has been high for the banking sector, which could result in higher eventual ECL provisions.
While the impact on individual banks is difficult to assess, some large banks with strong specific and contingent buffers could benefit from the ECL-based norms, while small private sector banks may have to accelerate provision buffers and even replenish capital levels faster than planned.
The model to calculate the expected credit loss is to be decided by individual banks but is subject to independent evaluation and a floor on provisions set by the regulator.
Despite potential challenges, analysts at Emkay Global Research believe that this is an opportune time to introduce ECL norms for banks and strengthen their provision buffers before the next asset-quality shock.
In conclusion, the Reserve Bank of India’s proposal to shift towards the expected credit loss (ECL) method for loan loss provisioning is a positive step towards enhancing the resilience of the banking system. By making provisions for potential future losses, banks can maintain excess provisions, which can help absorb any future losses and maintain financial stability.
However, it remains to be seen how effectively banks will be able to design and implement their own ECL models and comply with the proposed framework. Nonetheless, the RBI’s emphasis on adopting a forward-looking approach to credit losses is a step in the right direction toward ensuring the safety and soundness of the banking system.
Article Written By: Priti Raj