An RTI request to the Reserve Bank of India (RBI) revealed that the amount involved in loan frauds was a whopping Rs 4.92 lakh crore as of Mar. 31, 2021. To put this number in context, the amount involved in loan frauds was 4.5% of current bank credit. Ninety banks and select financial institutions have reported a total of 45,613 cases of loan fraud.
Public sector banks were worst affected by the loan frauds. State Bank of India (SBI) led the amount involved in loan frauds (15.8%), followed by Punjab National Bank (8.1%), Bank of India (6.6%), Union Bank of India (6%), and Bank of Baroda (5.6%). These five public sector banks constituted 42.1% of the total amount involved in loan frauds.
Among private sector banks, ICICI Bank led the amount involved in loan frauds (5.3%), followed by Yes Bank (4.02%) and Axis Bank (2.54%). These three private sector banks constituted 11.87% of the total amount involved in loan frauds. On the other hand, the amount involved in the loan frauds for India’s leading private lender HDFC Bank was 0.55% of the total.
However, the RBI has clarified that ‘Amount Involved’ does not equate with the loss suffered by the reporting bank. Further, the central bank stated the entire amount lent in case of borrowal accounts need not have been diverted by the borrower. In the case of borrower accounts, ‘amount involved’ may refer to the amount outstanding in the books of the reporting bank, it added.
In recent years, loan frauds have emerged as the biggest threat for the banks as it is severely denting the asset quality. The major problem for banks is an unintended faulty selection of large borrowers resulting in loan frauds. In our view, having a dedicated system to detect fraudulent behavior of large value loan accounts is the need of the hour.
Amukha has introduced the Market Intelligence Unit (MIU), which can help banks detect frauds and monitor the health of the large borrowers both at the pre-sanction and monitoring stage.
MIU uses extensive sources, from alternative datasets to the banks’ internal and field intelligence data, to derive early warning signals for the identification of large value accounts potentially fraudulent or credit risk behavior.
MIU offers high-end data analytics to get a comprehensive view on the bank’s large value borrowers by using:
External data triggers: Social media, related party identification, stock market, financial statements, external credit ratings news related data, regulatory triggers, event-based triggers, etc.
Internal data triggers: Transaction behavior, demographics, sectoral info, salary payout data, collateral related info, financial data submitted to the bank, internal ratings, etc.
Field intelligence data: Physical verification of company existence, production facility audit report, end products/services audit report, market intel from shops/people in the vicinity, discreet conversations with employees/ex-employees/ suppliers/customers etc.
In addition, MIU has a rule engine, workflow capabilities viz storage and retrieval of data, logs, and review reports.
Stay tuned to Amukha! Next blog: 147 newly classified wilful defaulters owe Rs 5,786 crore to banks
To know more about Amukha MIU, please email us at firstname.lastname@example.org.