The Reserve Bank of India (RBI) has imposed fines on 80 banks and financial institutions (FIs) in 2021 so far. The central bank has imposed penalties for failure to comply with RBL’s various regulatory and compliance guidelines. The amount of fines imposed on the private, public, co-operative, & sahakari banks and financial institutions ranges from lakhs to a few crores.
Earlier this month, the RBI had asked 14 banks to pay penalties for non-compliance concerning certain provisions of directions issued by the central bank. The RBI has imposed the highest fine of ₹2 crores on the Bank of Baroda for non-compliance with respect to advances sanctioned to IL&FS and its group companies.
Invest in New-Age Credit Risk Application rather than Paying Penalties
The banks can avoid most of the RBI’s regulatory and compliance-related observations and penalties by adopting the automated applications such as the Early Warning System (EWS) and Market Intelligence Unit (MIU).
Amukha has built innovative EWS and MIU applications for helping the banks to comply with the regulatory and compliance-related guidelines issued by the RBI. But, most importantly, our applications help in maintaining a healthy loan portfolio.
Our EWS application identifies distressed companies ahead of time by classifying the bank’s portfolio accounts into a. Standard Assets; b. Sub-standard Assets and c. Doubtful Assets.
Meanwhile, MIU is a dedicated application to monitor credit risk for large value exposures and avoid adverse selection of borrowers. MIU application identifies early warning signals of fraud or credit risk for large value accounts at both the pre-onboarding or monitoring stages.
Amukha application also generates reports and maintains an audit trail for both regulatory reporting and the bank’s own MIS requirements. Moreover, our application can easily scale up to meet both the bank’s custom and new regulatory requirements.
Our application offers the asset classification on the two separate risk scores derived from 1. The bank’s internal data; and 2. Amukha’s external datasets. To derive the risk score, we run hundreds of business rules on the various datasets such as financials, news, provident fund, GST, directors, ownership, credit rating, etc., for each account from the bank’s loan portfolio.
The portfolio companies are bucketed into a high, moderate, and low-risk profile based on the overall risk score. Our application also allows the categorization of portfolio companies into Non-Performing Asset or Clean.
To know more about Amukha’s EWS and MIU applications, please get in touch with us at email@example.com.