The alarmingly low recovery rate from the Insolvency and Bankruptcy Code (IBC) process, recently estimated at just 31 per cent, is closely tied to the flawed way banks calculate their “haircuts”. This issue, often overlooked, has profound implications for the public perception about their efficiency in managing distressed assets. A deeper examination reveals the underlying flaws that contribute to this “low” recovery rate.
In most business practices, the evaluation of losses and gains in transactions with a counterparty is based on a comprehensive assessment of the entire relationship. This approach ensures a balanced view, considering both the periods of profit and loss.
However, banks deviate significantly from this norm. They typically treat the date when a loan is categorised as a non-performing asset (NPA) as the ‘zero date’ for calculation purposes.
This practice, while convenient, overlooks the net income accrued during the years when the transactions were properly conducted, leading to an inflated perception of losses when calculating the haircut — whether under SARFAESI, Debt Recovery Tribunals (DRTs), or IBC proceedings.
Consider a scenario where a borrower defaults on a working capital loan of ₹100 crore after five years.
As of the NPA date, the outstanding amount stands at ₹100 crore, excluding interest. After two years of recovery efforts under the relevant legal provisions, the bank manages to recover ₹40 crore.
The standard method of calculating the haircut would involve adding ₹100 crore plus the interest accrued until the date of recovery, then subtracting ₹40 crore. Assuming an interest of ₹20 crore (simple interest at 10 per cent over two years), the recovery rate would be calculated as 33 per cent (₹40 crore out of ₹120 crore). In practice, compounded interest and additional charges often further inflate the perceived loss, painting an even grimmer picture.
However, this approach is fundamentally flawed because it disregards the net interest margin (NIM) earned while the loan was classified as standard. For instance, if the bank earned a 3 per cent NIM over the five-year period, it would have accrued a 15 per cent return on the exposure. The longer the loan remained standard, the greater the earnings from this exposure. These earnings are not merely incidental; they represent a significant portion of the bank’s income and should logically be factored into the overall calculation.
In our example, if these earnings were considered — as sound logic dictates — the recovery rate would improve significantly to 48 per cent. This adjustment is not just a matter of accounting; it reflects a more accurate and fair assessment of the bank’s financial interaction with the borrower. By failing to include these earnings in their calculations, banks end up presenting an unnecessarily bleak picture of recovery rates. This practice inadvertently contributes to a cycle of negative perception, where banks appear less effective in managing NPAs.
When questions are raised in Parliament and other forums about recovery from non-performing assets, banks risk undermining their own credibility by ignoring the income generated while the loan was performing. The public discourse around bank recoveries is skewed as a result, leading to an incomplete understanding of the issue among policymakers, media, and the public. This skewed calculation has four broader implications.
The implications
Public perception: Banks inadvertently damage their reputation by showcasing lower recoveries, which distorts the public and media’s understanding of the situation. The media, which often chases headlines, may amplify this misperception, further damaging the bank’s public image.
Staff accountability: In internal proceedings against bank officers, the inflated loss figures often overshadow the income these officers helped generate, leading to potentially unjust consequences. Officers who have diligently managed accounts and ensured they generated income during their standard phase may find their contributions ignored. This can have a demoralising effect on bank staff, discouraging prudent risk-taking and long-term relationship building with clients.
Institutional misrepresentation: Institutions like the courts, Parliament, and the public are provided with a distorted view of the bank’s efforts and achievements in income generation through these loans. This misrepresentation can influence policy decisions, potentially leading to stricter regulations or punitive measures that do not address the real issues at hand. A more accurate representation is warranted.
One-time settlements: For cases where business failure, rather than malfeasance, is the cause of default, this method could facilitate more reasonable settlements by offering a clearer picture of the net earnings. Recognising the income generated during the good years can lead to more equitable settlements, where the focus shifts to constructive solutions that help both the bank and the borrower recover.
Moreover, the current method of calculation fails to account for other potential sources of income associated with the loan. For instance, banks often engage in cross-selling of products, such as insurance and investment services, to their borrowers. These additional revenue streams, generated during the period when the loan was performing, contribute to the bank’s overall profitability and should be factored into the calculation of recoveries. Of course, the tax paid on profit may be a deductible in this exercise, a matter of detail.
Given these considerations, it is imperative that banks, either individually or through the Indian Banks’ Association (IBA), adopt a more logical and comprehensive method of calculating haircuts and recoveries.
Such a shift would not only enhance transparency but also align recovery practices with broader business principles, where the entire relationship with the borrower is considered. This change could lead to more rational decision-making, improved public perception, and ultimately, a logical reality-check on loan recoveries.
The writer is a commentator on banking and finance
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