Artificial Intelligence-Based Fraud Prevention in Banking

Deputy Governor of the Reserve Bank of India, proposed the development of an AI-based fraud prevention platform for the banking system. This initiative aims to detect and manage frauds effectively by leveraging comprehensive system-wide data.

Key Points of the Proposal

• System-Wide Data Integration: Sankar emphasizes the need for a centralized system that utilizes data across the entire banking ecosystem rather than isolated data sets from individual banks or payment systems.
• Collaboration with RBIH: He advocates for collaboration between banks and the Reserve Bank Innovation Hub to enhance risk management capabilities. The RBIH is developing a Mule Hunter System to identify and act against mule accounts.
• Digital Public Infrastructure: Sankar suggests that a securely controlled digital public infrastructure is necessary to manage data from multiple banks, ensuring privacy and trust.

Fraud Statistics and Concerns

• The incidence of fraud on the UPI platform is about 0.68 per 100,000 transactions, which translates to approximately 4,800 fraudulent transactions or ₹3.7 crore in losses per day.
• Despite the low incidence rate, the large user base makes these numbers significant, emphasizing the need for a zero-fraud environment.

Challenges and Opportunities

Sankar highlights the importance of preventing fraud to maintain trust in the banking system. He also notes that about 48% of the population surveyed by RBI have not adopted digital transactions, pointing to a need for improved inclusion in digital payment systems.