Threat Actor Profile For The Week: Money Mules

Money mules play a critical role in laundering illicit funds, knowingly or unknowingly moving money through networks of accounts until it is reintegrated into the legitimate economy. Recruitment often occurs via social media, “easy cash” schemes, or scams such as romance fraud.

Identifying mule accounts remains challenging: fraud databases capture only a fraction of cases due to high-proof requirements. A proactive approach is essential to detect risk before fraud occurs.

Mule Personas

Financial institutions can categorize mule activity into five distinct personas, each requiring tailored detection methods:

• The Deceiver (Intentional Fraudster)
      Opens accounts specifically for fraud, often using synthetic identities. Detection requires strong onboarding screening and behavioural monitoring at account creation.
• The Peddler (Selling Access)
      Sells account access rather than laundering funds directly. Accounts may appear legitimate until unusual changes (new devices, unfamiliar users) emerge. External intelligence sources, including dark web monitoring, are key.
• The Accomplice (Willing Middleman)
      Transfers illicit funds knowingly for profit, blending fraudulent activity with normal transactions. Detection hinges on monitoring transaction velocity, payment destinations, and peer-to-peer transfers.
• The Misled (Unwitting Participant)
      Believes transactions are legitimate, often recruited via fake job offers or scams. Detection requires contextual analysis of payment sources and account inconsistencies.
• The Victim (Exploited Account Holder)
      Provides access unknowingly or suffers account takeover. Behavioural monitoring of login anomalies, device usage, and transaction deviations is critical.

Mitigations

• Continuous monitoring from account opening through lifecycle
• Behavioural analytics to flag anomalies in transactions and logins
• Cross-industry data sharing to disrupt mule networks early
• Proactive detection of LOLB in abuse, synthetic identities, and peer-to-peer misuse

Working backward after funds have dispersed across multiple institutions is costly and rarely effective.

By recognizing mule personas early and applying proactive detection, financial institutions can reduce risk, protect customers, and stay ahead of evolving fraud tactics.