FRAUD RISK INDICATOR (FRI)
FRI: DoT’s New Digital Tool to Combat Financial Fraud
What is the Fraud Risk Indicator (FRI)?
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A risk-based metric developed by the Department of Telecommunications (DoT) under the Digital Intelligence Unit (DIU) project.
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FRI classifies mobile numbers based on financial fraud risk levels:
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Medium Risk
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High Risk
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Very High Risk
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Purpose and Significance
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Helps prevent the misuse of telecom resources for financial fraud and cybercrime.
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Enables stakeholders to take proactive customer protection actions.
Key Stakeholders Using FRI
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Banks
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Non-Banking Financial Companies (NBFCs)
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Unified Payments Interface (UPI) service providers
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Payment Service Operators (PSOs)
Accessed through the Digital Intelligence Platform (DIP).
Regulatory Support and Action
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Reserve Bank of India (RBI) has issued advisories for:
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Integration of FRI into banking and UPI systems.
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Adoption of real-time response protocols, such as:
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Alerts
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Transaction delays
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Transaction decline
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Warnings and red flags
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Launched by DoT to combat cyber fraud and financial crime via telecom networks.
Objective is to devise systems to curb misuse of telecom resources for cybercrime and financial frauds.
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FRI and DIP are core components.
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Budget: ₹228.16 crore
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Duration: 5 years
Broader Implications
For Financial Institutions
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Enables risk-based KYC enhancement.
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Strengthens anti-fraud detection and response.
For Customers
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Adds a layer of protection in real-time digital transactions.
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Reduces the risk of falling prey to SIM swap scams, phishing, OTP frauds, etc.
For National Security
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Strengthens India’s cybersecurity posture in the financial digital ecosystem.
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Ensures inter-agency coordination via centralised fraud risk intelligence.
Challenges and Way Forward
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Need for uniform adoption across all financial institutions, including smaller NBFCs and digital wallet providers.
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Ensure privacy protection and transparency in how risk is calculated.
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Strengthen real-time data sharing protocols across platforms.
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Combine with AI-based fraud prediction tools and telecom-data analytics.