New Delhi, Sept 26 (NationPress) India's strategy for embracing AI in financial services is closely tied to its overarching objective of utilizing technology for inclusive economic development. The country's distinctive digital public infrastructure provides a solid groundwork for AI integration, with the goal of democratizing financial access on an unparalleled scale, as highlighted in the Finance Ministry's monthly review published on Friday.

The RBI’s FREE-AI Framework aims to promote innovation while ensuring effective risk management, emphasizing that these two components are mutually reinforcing and should be pursued in tandem. This framework also bolsters the India AI Mission, enhancing national AI capabilities and aligning with the Digital Personal Data Protection Act to maintain consistency in data governance, according to the review.

In-depth surveys conducted by the RBI reveal that the adoption of AI within Indian finance is still nascent, with merely 21 percent of banks and financial institutions surveyed actively implementing or developing AI solutions.

Adoption is primarily observed among larger banks, whereas smaller urban cooperative banks and many NBFCs encounter resource challenges, including inadequate data infrastructure, a lack of skilled personnel, and limited IT budgets, which impede AI deployment. Furthermore, even among early adopters, the application of AI tends to be basic, often aimed at enhancing process efficiency, customer interactions (such as simple chatbots), lead generation, and internal decision support rather than engaging in more sophisticated autonomous decision-making.

Informed by these principles, the RBI’s FREE AI outlines six strategic pillars for effectively implementing its vision. The Innovation Enablement Framework emphasizes infrastructure, policy, and capacity building. This encompasses the development of shared data and technology infrastructure to democratize AI access (like data lakes or plug-and-play ‘landing zones’ that smaller firms can utilize), crafting adaptable policies, and establishing regulatory sandboxes for secure experimentation, alongside addressing the AI skill gap.

The Risk Mitigation Framework concentrates on governance, protection, and assurance to create transparent governance structures (including board oversight and ethics committees), implement robust safeguards for privacy and security, and mandate ongoing monitoring and validation of AI systems to guarantee reliability, the review concluded.