In its latest Annual Report, published last week, the Reserve Bank of India (RBI) outlines an ambitious expansion of AI and machine learning use across its regulatory, supervisory, and policy functions.
To support more responsive and data-driven oversight, the RBI has established an Advanced Supervisory Analytics Group (ASAG), which aims to augment its supervisory capabilities with "a suite of SupTech data tools." The ASAG has already developed a number of such tools, including for microdata analysis, governance assessment, and social media monitoring, among others.
The RBI is also investing in infrastructure to enhance visibility and data quality across the financial system. A new supervisory data quality index (sDQI) aims "to identify and address deficiencies in risk data aggregation capabilities and risk reporting practices" among supervised entities. Meanwhile, it has also established new repositories for Financial Technology (FinTech) and Emerging Technology (EmTech) to collect structured information on relevant entities, their activities, and technology stacks. Both platforms are managed by the Reserve Bank Innovation Hub.
Internally, the RBI is also scaling the use of AI for policy purposes. "The scope of data science [AI/ML] applications in functional areas of the Reserve Bank is being expanded," the report notes, with new applications developed "using traditional and new age data sources." A data governance framework has been prepared, and a committee of external experts has been tasked with recommending a "Framework for Responsible and Ethical Enablement of AI in the financial sector."
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