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In a strategic move, the Reserve Bank of India (RBI) has tapped global consultancy firms McKinsey and Company India LLP, along with Accenture Solutions Pvt Ltd India, to spearhead the development of advanced AI and machine learning systems for its supervisory functions.
The central bank is poised to leverage cutting-edge technologies to delve into its extensive database, enhancing regulatory oversight over banks and NBFCs (non-banking financial companies). External experts are set to be employed in this endeavor.
A Strategic Initiative: EoI and RFP Process
The RBI's journey into advanced analytics, AI, and machine learning was initiated when it invited expressions of interest (EoI) in September of the previous year. Seven distinguished firms, including Accenture Solutions Private Limited, Boston Consulting Group (India) Pvt Ltd, Deloitte Touche Tohmatsu India LLP, Ernst and Young LLP, KPMG Assurance and Consulting Services LLP, McKinsey and Company, and Pricewaterhouse Coopers Pvt Ltd, emerged as contenders through the scrutiny and evaluation outlined in the EoI document. Subsequently, McKinsey and Company India LLP and Accenture Solutions Private Limited India secured the contract, a significant deal valued at around Rs 91 crore.
Scaling Up for Enhanced Supervision
While the RBI has already embraced AI and ML in its supervisory processes, the objective is to elevate these capabilities to empower the Department of Supervision within the central bank. By harnessing the potential of advanced analytics, the RBI aims to identify valuable attributes within its data that can generate novel and improved supervisory inputs. The Department of Supervision, which currently employs linear and select machine-learned models for examinations, is keen to unlock the data's untapped potential.
Supervision Spanning Multiple Fronts
The RBI's supervisory jurisdiction extends over a broad spectrum of financial entities, encompassing banks, urban cooperative banks, NBFCs, payment banks, small finance banks, local area banks, credit information companies, and a selection of Indian financial institutions. Its supervisory responsibilities encompass diverse dimensions, including evaluating financial soundness, solvency, asset quality, governance framework, liquidity, and operational viability. This comprehensive approach aims to safeguard depositors' interests and ensure financial stability.
Envisioning a Data-Driven Future
Embracing a global trend, regulatory and supervisory bodies worldwide are increasingly adopting machine learning techniques, often referred to as 'suptech' and 'regtech,' to bolster their supervisory and regulatory endeavors. While these techniques are still exploratory, their rapid growth in popularity and scale is evident. Notably, AI and ML technologies facilitate real-time data reporting, effective data management, and dissemination, all of which contribute to more robust analytics. These advanced techniques are employed for monitoring firm-specific risks (e.g., liquidity, market, and credit exposures), analyzing misconduct, and detecting product mis-selling.