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Detecting Mule Accounts : Transaction Monitoring Or Behavioural Biometrics

Mule accounts are a key challenge today for digital and neobanking initiatives. We have often been asked what is the best way to prevent mule accounts, is it onboarding and KYC checks, is it behavioural biometrics and device identifiers or is it transaction monitoring and profiling. Before we answer the above question, we will provide details on strategies to detect mule account behavior for savings & current accounts:

Transaction Monitoring:

  • High Volume & Velocity: Monitor for unusually high transaction frequency (number of transactions) and velocity (transaction amount per unit time) compared to the account's historical behavior or similar account profiles. Mules might exhibit sudden bursts of activity or frequent low-value transfers.

  • Unexplained Deposits & Withdrawals: Look for deposits from unknown sources or frequent withdrawals shortly after deposits, which could indicate money laundering activities.

  • Geographic Inconsistencies: Monitor transactions originating from locations geographically distant from the account holder's usual location. This could be a red flag if the account holder doesn't travel frequently.

Account Activity Analysis:

  • Dormant Accounts with Sudden Activity: Be wary of dormant accounts that suddenly become active with a surge in transactions. This could be a sign of a compromised account being used for money laundering.

  • Limited Account Information: Accounts with minimal or inconsistent personal information associated with the holder might be more susceptible to mule activity.

Network Analysis:

  • Suspicious Connections: Identify accounts with frequent transactions to or from other flagged accounts or entities known to be involved in money laundering. Analyze transaction chains to identify networks of potentially fraudulent accounts.

Machine Learning:

  • Develop Predictive Models: Train machine learning models on historical data to identify patterns and anomalies indicative of mule account behavior. These models can learn from past cases and improve detection accuracy over time.

Additional Considerations:

  • Customer Due Diligence (CDD): Implement robust CDD procedures to verify the identity and legitimacy of account holders during account opening and periodically thereafter.

  • Customer Behavior Monitoring: Monitor customer interactions with the bank (e.g., call center inquiries) for inconsistencies or unusual requests that might suggest account compromise.

  • Alerts & Investigations: Establish clear thresholds and triggers for generating alerts when suspicious activity is detected. Investigate flagged accounts thoroughly and take appropriate actions, which could include account closure or reporting to authorities.

A single red flag might not be conclusive. Combining these techniques with human expertise and investigation is crucial for effectively detecting and mitigating mule account activity.

The Question at hand, What is the best way to prevent mule accounts, is it onboarding and KYC checks, is it behavioural biometrics and device identifiers or is it transaction monitoring and profiling? In our experience, most banks have already implemented onboarding rules and KYC checks, strengthening them further is work in progress but is likely to have significant impact on sales targets. Between behavioural biometrics and transaction monitoring, the clear winner is transaction monitoring and profiling. A look at the article clearly shows that a new transaction monitoring solution with ability to leverage comprehensive profiles is key to winning the battle against mule accounts.

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