Anti-money laundering
Cybersecurity Europe Trending

Financial Players Must Collaborate to Bring Down the 99% Weekly Success Rate of Money Laundering

Payments 20 (P20), a player in the global payments industry, has published a new report calling for collaborative action within the industry to tackle money laundering by collectively focusing on finding money mules and following the money.

The advocacy group, alongside organisations including NatWest, Mastercard, The Clearing House, McKinsey & Co, Hogan Lovells and Featurespace, has created a new report entitled Focus on Money Mules: A Collaborative Approach to Fighting Financial Crime. The report outlines the various types of money mules, identifies several key challenges in how they operate, and proposes recommendations for the payments industry to help reduce financial crime.

The purpose of money laundering is to obfuscate the source, movement and destination of illicit funds produced through criminal activity which makes anti-money laundering (AML) and detection efforts inherently difficult. According to the UK’s Financial Conduct Authority (FCA), over $40billion dollars is laundered every week while only one per cent of this figure is intercepted and seized.

The report states that crypto has exacerbated this problem by offering new alternatives for criminals to exploit. This is particularly prevalent in over the counter (OTC) exchanges.

To help tackle money laundering, P20 provides the following recommendations:

  • Prevent at the point of application – The most effective strategy is to identify and decline potential mules at the point of their application.
  • Integrated approach to data – Create a holistic view of application and payments by combining any application data with several fraud detection practices including behavioural profiling, lifecycle scoring and retrospective profiling.
  • Applying machine learning to AML – Contemporary data science methods including machine learning can be utilised to support AML efforts. Three of the most significant features are example importance, feature importance and counterfactual.
  • Internal and external collaboration – Untangling complex criminal cases requires greater collaboration across internal functions and with external partners. Through system integration and aggregation of data sources, financial institutions can work together to provide ready timely and cost-effective access to law enforcement
  • Geographical approach – According to Aite, the UK has considerably more formal reporting standards than the US when it comes to money mules, although improvements can still be made in across the board.

Duncan Sandys, chief executive officer at P20, said: “The widespread reliance on money mules for money laundering gives banks and other payment service providers an opportunity to identify a variety of financial crimes. Finding the money mules and following the money can help fight fraud, identity theft and cybercrime, while preventing stolen money ending up in criminals’ hands.

“A focused, collaborative approach to money mules could not only address this crucial link in crime networks but could serve as a model for broader cross-discipline collaboration to fight financial crime.”

Author

  • Francis is a journalist and our lead LatAm correspondent, with a BA in Classical Civilization, he has a specialist interest in North and South America.

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