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The Reserve Bank has chosen global consulting companies McKinsey and Company India LLP and Accenture Solutions Pvt Ltd India to create systems for its supervisory tasks that use artificial intelligence and machine learning. The RBI intends to deploy sophisticated analytics, AI, and ML to assess its massive database and better regulatory oversight of banks and NBFCs. For this reason, the central bank intends to hire outside experts.
The RBI solicited expressions of interest (EOI) in September of last year for consultants to apply advanced analytics, artificial intelligence, and machine learning to generate supervisory inputs.
The central bank has shortlisted seven candidates to participate in the request for proposal procedure (RFP) for the selection of consultant(s) based on the scrutiny/evaluation outlined in the EOI document.
One of the seven companies was Accenture Solutions Private Limited. The other six were KPMG Assurance and Consulting Services LLP, Deloitte Touche Tohmatsu India LLP, McKinsey and Company, and Pricewaterhouse Coopers Pvt Ltd.
The contract has been awarded to Accenture Solutions Private Limited India, and McKinsey and Company India LLP according to a Reserve Bank document.
While the RBI is currently employing AI and ML in supervisory operations, it now plans to expand it so that the advantages of advanced analytics may be realised by the central bank's Department of Supervision.
The Department of Supervision has created and utilised certain linear and machine-learnt models for supervisory tests. According to the EoI filed in September, the interest now is to investigate the data to discover its qualities that may be utilised to provide new and enhanced supervisory inputs.
The RBI has regulatory authority over banks, urban cooperative banks, NBFCs, payment banks, small financing banks, community banks, credit information firms, and a subset of all Indian financial institutions.
It supervises these businesses to protect depositors' interests and financial stability by examining their financial soundness, solvency, asset quality, governance structure, liquidity, and operational viability.
According to the EoI, the RBI conducts continual supervision of SEs through on-site inspections and off-site monitoring.
Machine learning methods (also known as'suptech' and'regtech') are being used by regulatory and supervisory bodies throughout the world to aid with supervisory and regulatory operations, according to the report.
Most of these strategies are still in their early stages, but they are fast gaining popularity and size.
AI and ML technologies are utilised in data collecting for real-time data reporting, effective data management, and data distribution.
These are used for monitoring supervised firm-specific risks, including as liquidity risks, market risks, credit exposures, and concentration hazards; misbehaviour analysis; and product mis-selling.
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