Catch the account, then explain why: an AI pipeline for money mules
Researchers pair a fraud-detection model with SHAP attribution and an open-weight LLM that writes the case in plain English — and report catching far more mule accounts in live production.
✓ Verified
Source
arXiv preprint (peer review pending) — authors' own production results
⚑ Applied ML
The problemWhat's a money mule?
A money mule is a bank account used to move illicit funds — the middle link that launders stolen money into the wider financial system. Sometimes the account holder is a knowing accomplice; often they've been recruited or duped. Mule accounts are a key enabler of fraud, and catching them at scale is hard because the evidence is a messy blend of transaction patterns, account details, network structure (who pays whom), and timing.