The Reserve Bank of India (RBI) has chosen global consultancy firms McKinsey and Company India LLP and Accenture Solutions Pvt Ltd India to develop systems utilizing artificial intelligence (AI) and machine learning (ML) for enhancing its supervisory capabilities. The RBI aims to harness advanced analytics, AI, and ML to analyze its extensive database and bolster regulatory oversight over banks and non-banking financial companies (NBFCs). The central bank has opted to engage external experts for this purpose.
RBI Aims for Enhanced Regulatory Oversight
In September of last year, the RBI invited consultants to use advanced analytics, AI, and ML for supervisory insights. Seven applicants were shortlisted by the RBI, 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.
Contract Awarded to McKinsey and Accenture
McKinsey and Company India LLP and Accenture Solutions Private Limited India have won the contract. An RBI document confirms this. The contract’s value is about Rs 91 crore.
RBI Expanding AI and ML Utilization
While the RBI already integrates AI and ML in its supervisory processes, its objective is to scale up these technologies to benefit the Department of Supervision within the central bank. The department has been utilizing linear and a few machine-learned models for supervisory examinations. The aim is to delve into the data to identify attributes that can be leveraged to generate enhanced supervisory inputs, according to the EoI issued in September.
Empowering Financial Stability and Oversight
The RBI supervises various entities, such as banks, NBFCs, and payment banks. It checks their financial health through on-site checks and off-site tracking. This involves looking at factors like assets, governance, and liquidity.
Worldwide, regulators are using AI and ML (called ‘suptech’ and ‘regtech’) to enhance supervision. They aid real-time data reporting, data management, and risk analysis in finance.
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