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MUMBAI : State Bank of India (SBI), the country’s largest lender, wants to use granular data generated in its branches every day to predict stress and pre-emptively act to shield its balance sheet. Accordingly, the state-owned lender is looking at ways to use advanced analytics to sift through data and find patterns that indicate incipient stress. In an interview, Ashwini Kumar Tewari, managing director in charge of risk, compliance, and stressed assets at SBI, explained how the bank digitized some stressed asset management processes. Edited excerpts:

What kind of stress are you seeing among retail and small business borrowers?

Most of our retail customers are salaried; therefore, we do not see any challenge. Our non-salaried set, though small, is facing some stress, but the net number taken together is quite under control. While the cashflows to the micro, small and medium enterprise (MSME) segment were clearly impacted but our lending parameters to this segment are very stringent. We do not give them an equivalent loan amount as salaried borrowers, and the loan-to-value is also lower. Even in the salaried segment, people lost jobs and had their salaries cut, but since we do not go down to the low credit score profiles, our overall experience in covid-19 has not been adverse.

Has technology helped turnaround time in stressed asset resolution?

For one-time settlement and compromise, we have an open platform where a person can apply online instead of coming to a branch. Internally we have a dashboard to track this at the operational level as well as the management level. We are thus able to control the turnaround time and see the quantum of recoveries. The legal team is a major component of the stressed assets vertical. We have an application called the Litigation Management System with modules such as the National Company Law Tribunal (NCLT), the debt recovery tribunal, and courts. Here, the entire case history is available and provides reminders for documents that come up for renewal for the next hearing, among other things. We have also digitized the wilful defaulter management system.

What are some of the new technology initiatives your department has planned?

We have so much data in the system. It would be useful to leverage this data not only from the risk perspective but also to see how things are moving in real-time in various parts of the country and different sectors. This is one area where we would like to use artificial intelligence and machine learning. Right now, our analytical teams are embedded in the risk, products divisions and operational risk areas. We get all the non-performing asset (NPA) data from across the country, including individual account data, and the aggregation happens at the circle level. Say there are problems in the steel sector in a particular state; one way to know is to track media reports but is our database showing impending stress from that region? After it becomes NPA, it will have to be dealt with, but if there are early indicators of stress, then this can be handled proactively.

Do you think it is faster to resolve stressed loans outside the purview of the Insolvency and Bankruptcy Code (IBC)?

In a few cases where we realized that getting upfront cash is important and the process itself may take a long time, it is better to sell to asset reconstruction companies.I believe there are certain changes being contemplated in IBC. If they happen, like pre-pack insolvency for corporates, we may have some more cases handled better. Everyone talks about the highlighted cases, but the smaller cases of 5 lakh or 10 lakh are not in the media. There are cases from branches in tier 3 and tier 4 cities which are seeing very good recovery.

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