In order to improve its regulatory control of banks and Non-Banking Financial Corporations (NBFCs), the Reserve Bank of India (RBI) is collaborating with the consulting firms McKinsey and Accenture.
The RBI intends to evaluate its massive database and enhance regulatory oversight of banks and NBFCs using sophisticated analytics, AI, and machine learning. The central bank plans to employ specialists in the area to help in this endeavour.
Although the RBI has already incorporated AI and ML into its supervisory processes, it is now looking to expand these technologies to ensure that the Department of Supervision within the central bank can benefit from advanced analytics.
For supervisory examinations, the Department of Supervision of the RBI has been creating and deploying linear and some machine-learning models. The current objective is to examine the data to find characteristics that can be used to produce fresh and better supervisory insights.
Banks, urban cooperative banks, NBFCs, payment banks, small financing banks, and specific Indian financial organisations are all under the RBI’s supervision.
To protect the interests of depositors and maintain financial stability, the RBI performs an evaluation of these institutions’ financial soundness, solvency, asset quality, governance structure, liquidity, and operational viability as part of its supervisory responsibility.
The RBI’s action fits with the expanding trend of regulatory and supervisory organisations using artificial intelligence (AI) and machine learning (ML) tools, sometimes known as “suptech” and “regtech,” to support their operations.
Real-time data reporting, efficient data administration, data analytics for monitoring different hazards, and other applications make use of these technologies. The estimated cost of the project with McKinsey and Accenture is Rs 91 crore.