Identify the key limitations in India’s digital payment security architecture. Examine how predictive intelligence tools like the Financial Fraud Risk Indicator (FRI) aim to bridge these structural gaps.
Kartavya Desk Staff
Topic: Role of media and social networking sites in internal security challenges, basics of cyber security;
Topic: Role of media and social networking sites in internal security challenges, basics of cyber security;
Q5. Identify the key limitations in India’s digital payment security architecture. Examine how predictive intelligence tools like the Financial Fraud Risk Indicator (FRI) aim to bridge these structural gaps. (10 M)
Difficulty Level: Medium
Reference: PIB
Why the question DoT Introduces “Financial Fraud Risk Indicator (FRI)” to strengthen Cyber Fraud Prevention. Key demand of the question The answer must identify core architectural and operational flaws in India’s digital payment security system and examine how predictive intelligence tools like FRI seek to address these issues effectively. Structure of the Answer: Introduction Refer to the exponential growth of UPI and the increasing fraud landscape, making predictive tools like FRI necessary for pre-emptive cyber protection. Body Highlight systemic limitations in digital payment security (lack of real-time sharing, regulatory fragmentation, poor SIM lifecycle control, reactive fraud models, limited user alerts). Examine how FRI addresses these issues (risk scoring of numbers, DIP-based alerts, cross-sector intelligence sharing, early fraud lifecycle intervention, standardised detection models). Conclusion Emphasise FRI as a scalable, preventive governance model. Recommend strengthening legal safeguards and expanding predictive analytics across the fintech ecosystem.
Why the question DoT Introduces “Financial Fraud Risk Indicator (FRI)” to strengthen Cyber Fraud Prevention.
Key demand of the question The answer must identify core architectural and operational flaws in India’s digital payment security system and examine how predictive intelligence tools like FRI seek to address these issues effectively.
Structure of the Answer:
Introduction Refer to the exponential growth of UPI and the increasing fraud landscape, making predictive tools like FRI necessary for pre-emptive cyber protection.
• Highlight systemic limitations in digital payment security (lack of real-time sharing, regulatory fragmentation, poor SIM lifecycle control, reactive fraud models, limited user alerts).
• Examine how FRI addresses these issues (risk scoring of numbers, DIP-based alerts, cross-sector intelligence sharing, early fraud lifecycle intervention, standardised detection models).
Conclusion Emphasise FRI as a scalable, preventive governance model. Recommend strengthening legal safeguards and expanding predictive analytics across the fintech ecosystem.