Fraud detection and prevention require real-time analysis of transaction patterns and identity signals. Posts cover anomaly detection for financial fraud, AML compliance engineering, and the multi-layered controls that protect financial platforms from fraudulent activity.
2 posts tagged with fraud. ← All posts
Borrower onboarding is the most fraud-prone moment in a P2P platform. The shape that worked: deterministic KYC, parallel bureau pulls with fallback, real-time fraud signals, and a maker-checker approval for every disbursement.
Two signals do most of the work for detecting compromised sessions: impossible travel between consecutive logins, and credential-stuffing density across an IP range. The Go implementation.
All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.