The Reserve Bank of India (RBI) has taken a significant step forward in integrating artificial intelligence (AI) and machine learning (ML) into its supervisory functions. After a thorough evaluation process outlined in the Expression of Interest (EOI) document, the central bank shortlisted seven candidates to participate in the Request for Proposal (RFP) process, aiming to select consultants for this transformative initiative.
As a result of this rigorous selection process, the RBI has chosen two globally renowned consultancy firms, McKinsey and Company India LLP, and Accenture Solutions Pvt Ltd India, to spearhead the development of systems leveraging AI and ML. These systems will play a pivotal role in bolstering the RBI’s regulatory oversight over banks and non-banking financial companies (NBFCs), ultimately leading to enhanced efficiency and accuracy.
The RBI’s strategic intent revolves around harnessing advanced analytics, AI, and ML to dissect its extensive database and refine its supervisory capabilities. The objective is to harness the power of data-driven insights to strengthen regulatory surveillance across the financial sector. To actualize this vision, the central bank recognized the need for external expertise and invited expressions of interest last September to engage consultants specializing in advanced analytics, AI, and ML for generating supervisory inputs.
From the array of applicants, which included distinguished names like 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, McKinsey and Company India LLP and Accenture Solutions Private Limited India emerged as the chosen partners.
The contract awarded to these two firms holds a value of approximately Rs 91 crore. This substantial investment underlines the RBI’s commitment to embracing cutting-edge technology to augment its supervisory role. While the RBI has already embarked on utilizing AI and ML in its supervisory processes, the intention now is to scale up these initiatives, ensuring that the Department of Supervision reaps the rewards of advanced analytics.
Previously, the Department of Supervision employed linear models and a limited number of machine-learned models for its supervisory examinations. However, the new direction is to delve into the data to identify attributes that can be harnessed to generate innovative and improved supervisory insights. This forward-looking approach aligns with the RBI’s objective of preserving financial stability and safeguarding the interests of depositors through thorough evaluation of financial institutions.
The RBI’s supervisory ambit extends across a range of entities including banks, urban cooperative banks, NBFCs, payment banks, small finance banks, local area banks, credit information companies, and select all Indian financial institutions. The oversight involves comprehensive assessments of various dimensions such as financial soundness, solvency, asset quality, governance framework, liquidity, and operational viability.
By incorporating on-site inspections and off-site monitoring, the RBI continuously supervises these entities, ensuring a comprehensive understanding of their operations. Globally, the application of machine learning techniques for regulatory and supervisory activities, often referred to as ‘suptech’ and ‘regtech’, is gaining momentum. These technologies are employed for real-time data reporting, data management, data analytics, and risk assessment.
In a landscape where data-driven insights are becoming increasingly integral to decision-making, the RBI’s strategic collaboration with McKinsey and Company India LLP and Accenture Solutions Private Limited India positions it at the forefront of leveraging AI and ML for an efficient and robust supervisory framework. This initiative is poised to redefine supervisory practices and catalyze innovative solutions in the realm of financial oversight.
