Three-Quarters of Money Mules Evade Early Detection
By Lauren Hinton · 6 November 2024
According to results of a new research project by data insight specialist, Synectics, inadequate screening at an early stage is not the reason why so many mules are missed.
Instead, the 75% statistic is down to a mismatch between standard application and periodic KYC screening protocols, and current mule behaviours – from how quickly mule accounts are activated, to time taken between offences.
Project premise: understanding the value of perpetual screening.
Working with three major high street banks, Synectics sought to identify what benefits, if any, implementing a continuous customer screening programme (Perpetual KYC or ‘pKYC’) would have on money mule detection.
The organisation applied a continuous AML screening strategy to each bank’s records, using data matching and real-time rules to detect red flags for fraudulent behaviour throughout the customer account lifecycle.
‘Time-to-mule’ a major fraud prevention factor.
The project uncovered a raft of valuable insights regarding the modus operandi of today’s money mules. Perhaps most noticeably that the median ‘time to mule’ is 8 months – proving that seemingly good customers can “turn bad”.
Chris Lewis, Head of Solutions at Synectics commented: “This is hugely significant. The fact that mule accounts typically lay dormant or are used legitimately for around eight months before ‘activation’ means that AML screening strategies should be applied at every point in the customer lifecycle. Based on our figures, at least 75% of accounts that go on to support money mule activity could otherwise go undetected.”
The scam patterns prove problematic for periodic reviews.
‘Time to mule’ was not the only important post application behaviour to indicate a more perpetual approach to customer screening is necessary.
The project also uncovered that once active, mules move hard and fast – offending, on average, 3.6 times across different institutions. Typically, with just 2 weeks between first and third offence.
Chris added: “The typical behaviour pattern of money mules after activation is frenzied and short. This means that while many mules evade early detection, they may well have ‘scammed and run’ before the customer’s next periodic review is scheduled. The only way these mules would be detected, is to have a real-time mechanism in place to flag AML concerns as an when they arise.”
The best route to efficient mule detection
The project also aimed to identify the optimal real-time mechanism to employ for accurate mule detection – the ideal being low referral rates with high degrees of accuracy. This was tested by using a tailorable rules engine in three different ways by the participating banks.
Liese Rushton, Fraud Strategy Consultant at Synectics, explained: “The best results were achieved with three ingredients:
- Fixed data matching with National SIRA and other third-party AML services.
- Using rules that monitored velocity trends - how many times something happens over a particular timeframe.
- Incorporating rules that ‘watched’ for distinct profiles, for example new account holders under a specific age with an income above a certain threshold.”
Companies in this story: Synectics Solutions
People in this story: Chris Lewis, Liese Rushton