The Reserve Bank of India (RBI) is planning to extensively use advanced analytics, AI and ML to analyze its huge database and improve regulatory supervision of banks and NBFCs. 

RBI is already using AI and ML in supervisory processes. Now, it plans to ensure that the benefits of advanced analytics can accrue to the Department of Supervision in the central bank. They are also planning to hire external experts for this purpose. 

The department has been developing and using linear and a few ML models for supervisory examinations. The supervisory jurisdiction of the RBI extends over banks, urban cooperative banks (UCB), NBFCs, payment banks, small finance banks, local area banks, credit information companies, and select all Indian financial institutions. 

It undertakes continuous supervision of such entities with the help of on-site inspections and off-site monitoring.  

The central bank has floated an expression of interest (EoI) for engaging consultants in the use of Advanced Analytics, AI and ML for generating supervisory inputs. The selected consultants will be required to explore and profile data with a supervisory focus, among other things. 

The objective of this step is to enhance the data-driven surveillance capabilities of the Reserve Bank, the EoI said. 

Across the world, regulatory and supervisory authorities use ML techniques to assist supervisory and regulatory activities. Most of these techniques are exploratory. However, they are rapidly gaining popularity and scale.  

On the data collection side, AI and ML technologies are used for real-time data reporting, effective data management and dissemination.  

For data analytics, these are used for monitoring supervised firm-specific risks, including liquidity risks, market risks, credit exposure and concentration risks, misconduct analysis, and the mis-spelling of products.