# Fraud & Risk Intelligence

Fraud in Indian fintech is not what it was five years ago. Synthetic identities, mule account networks, first-party fraud, and industrial-scale UPI scams have replaced the simpler document-forgery attacks that digital KYC was designed to catch. Fraud teams need a wider signal set and a faster response loop than ever before.

This hub covers the operational reality of fintech fraud — what the current typologies look like, how attackers probe different product lines, which signals actually catch which attacks, and how device and behavioral intelligence layer on top of identity and transaction data to build a real defense.

Deepvue's fraud and intelligence stack includes identity fraud detection, device fingerprinting and behavioral signals, mule account detection patterns, UPI and payment-fraud analysis, and synthetic identity indicators. The content here reflects what we see working in production across lending, payments, and onboarding workflows for 60+ Indian fintech customers.

Featured content walks through specific fraud typologies — UPI scam patterns, synthetic identity construction, mule account networks, first-party fraud in lending — with detection approaches grounded in real signals, not generic "look for red flags" advice. Start with the pieces below.

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Source: https://deepvue.ai/topics/fraud-intelligence/