FraudGraph AI Uses TigerGraph and GraphRAG to Build Explainable Fraud Investigations

A team built FraudGraph AI, an agentic fraud investigation platform, as part of a recent hackathon project. The system moves beyond single transaction scoring by mapping relationships across customers, cards, merchants, and historical cases using TigerGraph as its graph investigation layer. GraphRAG supplies structured graph context to a downstream reasoning pipeline, enabling the system to trace connected entities and identify non-obvious fraud patterns. A dedicated Risk and Uncertainty Engine separately evaluates fraud probability, confidence, and uncertainty to avoid premature or irreversible decisions. The platform also includes a Next Best Action Engine that produces deterministic, policy-aligned recommendations such as monitoring, blocking, or requesting verification.