The Financial Fraud Risk Indicator (FRI) developed by the Department of Telecommunications (DoT) has identified and blacklisted an estimated 300,000 to 400,000 SIM cards linked to fraudulent activities. This advanced AI-based technology singles out about 2,000 suspicious phone numbers on a daily basis. FRI was launched by the DoT in May and is built upon an analytical framework from the Digital Intelligence Platform, allowing it to spot mobile numbers tied to financial irregularities or likely to be misused.
DoT’s FRI System Cracks Down on Financial Fraud
According to a report from The Economic Times, FRI has successfully identified and flagged up to 400,000 SIM cards since its inception. Government data indicates that this tool is routinely identifying around 2,000 mobile numbers each day that are considered high-risk, particularly those involved in investment or job scams.
A senior official from the DoT confirmed that these flagged numbers are subsequently utilized to uncover additional SIM cards within the network through AI-driven pattern recognition. The official also noted that FRI has significantly assisted popular UPI platforms like GPay, PhonePe, and Paytm in avoiding potentially fraudulent transactions amounting to crores of rupees in just the past month.
In July, the Reserve Bank of India (RBI) urged all Scheduled Commercial Banks, Small Finance Banks, Payments Banks, and Cooperative Banks to implement FRI into their operations. This integration has expedited the response time to fraud accounts to mere hours, according to the official. “This also demonstrates the increasing sophistication of DoT’s Digital Intelligence Platform, which was established to enable real-time data sharing among stakeholders,” the unnamed DoT official stated.
Initially introduced in May, the FRI was meant to address the dynamic nature of financial fraud in India. Unlike conventional systems, which rely on numbers previously associated with scams, the FRI acknowledges that fraudsters often change their contact information frequently. This makes pre-existing systems ineffective.
In contrast, FRI employs a variety of metrics and AI functionalities to identify numbers with a perceived “risk” of involvement in scams. These identified numbers undergo further assessment using government databases, leading to a risk rating that categorizes them as low, medium, or high.
