Money Mule Detection

The FBI defines a money mule as someone who transfers or moves illegally acquired funds for another person. Some mules knowingly participate; others are recruited through romance, social-media or work-from-home scams and may believe the arrangement is legitimate. Funds can move through bank accounts, checks, digital assets, prepaid cards or money-service businesses. A detection system should therefore look at transaction patterns and recruitment context without assuming a person’s intent from a single payment. Potential signals include rapid pass-through transfers, activity inconsistent with a stated account purpose, many unrelated counterparties, or repeated account openings. FinCEN’s 2025 advisory describes indicators tied to particular Chinese money-laundering networks; those indicators are scoped to that advisory and should not be generalized to a person’s nationality or occupation. FBI guidance also describes work offers that ask individuals to receive and forward funds. No single indicator proves wrongdoing. Investigators need the surrounding facts, transaction history and applicable law. Models can prioritize cases for review, help connect related accounts and identify patterns that manual rules miss. They can also flag legitimate remittances, shared households or business activity. Define what the model predicts, how cases were confirmed and whether data covers both detected and undetected activity. Provide a human escalation path, document evidence and follow the institution’s reporting rules. Do not expose a customer to a conclusion or account restriction solely because a model produced a score; follow applicable law, policy and notice requirements.