Team Hacker House Builds GraphRAG Fraud Detection Agent Using TigerGraph and Claude

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A developer team called Hacker House Goa 2026 has built an autonomous fraud investigation system named FraudLens, using TigerGraph Savanna as its core graph database. The system addresses two major weaknesses in traditional fraud detection: high false-positive rates that block legitimate customers and an inability to detect coordinated syndicate activity spread across many accounts. FraudLens runs an eight-step state machine that traverses multi-hop graph relationships, measures evidence sufficiency, and recommends regulatory actions with full audit trails. The system integrates TigerGraph's native GSQL algorithms, LangGraph, Anthropic's Claude, FastAPI, and React for its full stack. In benchmark testing across 20 cases, the agent achieved 100% schema and logic compliance, correctly flagging two cases for regulatory filing while safely clearing the remaining eighteen.

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