RBI Panel Pushes For AI Policy Framework For Finance Sector

SUMMARY

The panel suggests setting up of a shared infrastructure by all the regulated entities to democratise access to data and computing

Terming it as the “7 Sutras” that represent the core principles around AI adoption, the panel notes that these are essentially meant to guide future innovations around risk mitigation

The RBI may consider issuing consolidated AI Guidance to serve as a single point of reference for regulated entities and the broader FinTech ecosystem

With AI-driven innovations rapidly reshaping various sectors, a Reserve Bank of India (RBI) panel has called for a comprehensive AI policy framework for the financial industry.

In the medium term, such a framework would provide flexible, forward-looking guidance around AI-innovation, adoption and risk mitigation.

The panel, set up to develop a framework for responsible and ethical enablement of artificial intelligence (FREE-AI) in the financial sector, suggests setting up of a shared infrastructure by all the regulated entities falling under the RBI to democratise access to data and computing that eventually leads to an AI innovation Sandbox.

Terming it as the “7 Sutras” that represent the core principles around AI adoption, the panel notes that these are essentially meant to guide future innovations around risk mitigation.

“The RBI may consider issuing consolidated AI Guidance to serve as a single point of reference for regulated entities and the broader FinTech ecosystem on the responsible design, development, and deployment of AI solutions,” the panel said in the report

RBI’s Proactive Measures Against Digital Fraud

The RBI, in partnership with banks and other stakeholders, has been adopting multiple strategies to curb and address digital fraud in the financial ecosystem.

The fact that cyber frauds have cost Indians INR 107.21 Cr in the first nine months of FY25 highlights the critical importance of early intervention.

Moreover, the central bank is also deploying AI and ML-driven models to tackle financial fraud across the country. Last year, it introduced an AI/ML-powered model dubbed ‘MuleHunter.AI’ to detect mule bank accounts.

Regulators worldwide are increasingly turning to AI to flag potential market abuses like manipulation and spoofing, where traders intentionally place and cancel orders to deceive others about market demand or supply.