Fintech
Lynx Introduces Real-Time Mule Detection Solution for Financial Institutions
Lynxprovider of artificial intelligence (AI) software that detects and prevents fraud and financial crimes, has introduced a real-time mule detection solution for banks and financial institutions.
The solution helps banks quickly identify and prevent money mule activities, responding to global regulatory demands and significant money laundering operations.
Cifathe UK’s non-profit fraud prevention service, estimates that 37,000 UK bank accounts exhibited muling-related behaviour in 2023. These accounts facilitate around £10bn of money laundering each year in the UK, with around 23% of it conducted by individuals under 21 and 65% by those under 30.
In the United States, Money Mule accounts represent up to 0.3 percent of accounts held by financial institutions and approximately $3 billion in fraudulent financial transfers. While in 2022 law enforcement organizations from 25 countries 2,469 money mules arrested in a worldwide crackdown on money laundering.
The use of machine learning and automated tactics by organized crime gangs has made it more difficult to detect mule accounts, as they can effortlessly create hundreds of accounts. Additionally, the widespread adoption of instant payments is reducing the window of time to identify and block mule transactions.
Digital onboarding, designed to streamline the identification and verification (ID&V) process, has unintentionally enabled the proliferation of mule accounts. This problem is compounded by a Tenfold increase in deep falsehoods globally from 2022 to 2023. To effectively prevent real-time creation of mule accounts, the industry requires a real-time money mule prevention solution.
Lynx Detection Tool
The Lynx Mule Account Detection capability enables rapid identification of mules to prevent fraud and facilitate real-time reporting of suspicious activity, without requiring full integration of anti-fraud and AML teams.
The solution uses supervised machine learning to detect illicit funds and mule accounts in real time, providing actionable insights for immediate response. It enables analysts to quickly prevent fraud by reducing the time spent reviewing alerts.
By integrating both incoming and outgoing transactions, the model flags and blocks mule accounts. It identifies irregular sources of funds, such as those resulting from authorized push payment fraud (APPF), and flags mule accounts in real time. Financial institutions benefit from reduced financial losses by preventing fraudulent payments.
This launch coincides with growing global regulatory demands requiring financial institutions to accept financial responsibility for APPF transactions. For example, New UK regulations come into force from 7 October require financial institutions to reimburse victims of APPF fraud, highlighting the critical need for advanced real-time mule detection solutions.
Stop the flow
Let’s sayCEO of Lynx, said: “Stopping money mules is not just important for financial institutions; it is important for everyone. Money mules are a critical link in the financial crime chain, facilitating the movement of illicit funds around the world By interrupting this flow, we not only protect countless victims, but we also cripple the operational capacity of criminal enterprises.”
The product’s proprietary daily adaptive model used continuously updated models based on the latest financial behaviors enabling accurate identification of genuine users and criminals. Continuous updates maintain maximum accuracy while dramatically reducing false positives and associated costs.
“Even with an existing fraud solution in place, leveraging Lynx’s money mule model score improves money mule detection, effectively addressing this specific challenge without the need for complex integrations,” Dica also added. “What this solution enables is a world where criminal networks cannot operate because their financial channels are blocked at every turn.”