Case Study: a tier 1 financial institution achieves real-time fraud detection at scale with TigerGraph

a Tier 1 Financial Institution detects fraud in real time with TigerGraph and 15,000 queries per second

A tier 1 financial institution faced the challenge of tracing multi-hop fund movements and detecting coordinated fraud networks across over 50 million daily transactions in real time. Building this capability from scratch would have required a massive, multi-quarter engineering investment. The institution turned to TigerGraph to meet its stringent requirement of performing complex graph analysis within a 100-millisecond fraud decision window.

TigerGraph implemented its graph platform to perform low-latency, multi-hop analysis on a 10TB dataset of identity, device, and transaction relationships. The solution processes approximately 15,000 graph queries per second, executing complex fraud checks in about 30ms per transaction. This provided the institution with a resilient, always-on fraud detection platform capable of 3-5 hop analysis while also supporting analytical workloads to identify emerging fraud patterns.