Real-time Fraud Detection Pipeline for a Leading Private Bank

Challenge

The bank's existing fraud detection system relied on batch processing with 2-second average latency. By the time a fraudulent transaction was flagged, the money had already moved. False positive rates exceeded 60%, causing legitimate customers to be blocked and generating thousands of support calls daily.

Solution

We designed a real-time streaming architecture with Redis as the in-memory decision engine. Transaction features are computed and served in under 10ms using Redis as a feature store. The pipeline runs on AWS EKS with auto-scaling based on transaction volume, and New Relic provides end-to-end observability across every hop in the detection chain.

Results