Lynx, a leading provider of Artificial Intelligence (AI) software that detects and prevents fraud and financial crimes, today announces the launch of Lynx Mule Account Detection, a real-time mule detection solution for banks and financial institutions to stop trillions of illicit funds flowing through the global financial system each year.
Lynx Mule Account Detection streamlines threat intelligence applications effectively across teams, enabling swift identification of mules, preventing fraud and facilitating real-time reporting of suspicious activity – all without requiring a wholesale integration of fraud and AML teams.
Organised Crime Groups (OCGs) are increasingly utilising money mules – accounts used to wash money obtained from illicit means. Cifas, the not-for-profit UK fraud prevention service, estimates that in the UK alone, there were 37,000 British bank accounts exhibiting behaviour associated with muling in 2023. These accounts are linked to approximately £10 billion of laundering each year in the UK, of which around 23% is done by individuals under 21 and 65% by those under 30.
Financial institutions are struggling to keep up with the rapid rise in money mule accounts, leading to both financial losses and compliance risks. In the US, money mules account for an estimated $3billion in fraudulent transfers every six months. Law enforcement from 25 countries prevented just €17.5million from being laundered by money mules over a three-month period. Using machine learning and automated attacks by OCGs makes detecting mule accounts increasingly challenging as they can easily create hundreds of accounts. In addition, the widespread adoption of instant payments reduces the window to identify and block money mule payments.
Digital onboarding, intended to streamline the identification and verification (ID&V) process, has inadvertently facilitated the proliferation of mule accounts. This issue is exacerbated by the rise of deep fakes – which saw a 10x increase globally from 2022 to 2023. To prevent real-time money mule account creation, the industry needs a real-time money mule prevention solution.
Lynx Mule Account Detection uses supervised machine learning to identify illicit sources of funds and mule accounts in real time and provides actionable insights to enable financial institutions (FIs) to react in real-time. Additionally, it provides a 360-degree holistic view, enabling analysts to make swift fraud prevention decisions, reducing time spent reviewing alerts to report mules quicker. This streamlines investigations by mule defence teams and optimizes the time to investigate accounts.
The model integrates both incoming and outgoing transactions, enabling the solution to flag if the account receiving and/or sending funds is a mule account and block transactions. For example, the model can identify if there are irregular sources of funds received into the account, which could be derived from authorised push payment fraud (APPF) or other types of fraud, flagging the mule account in real time. In turn, FIs benefit from reduced financial losses, preventing payments from exiting the account.
Dan Dica, CEO of Lynx, comments, “Stopping money mules doesn’t just matter for financial institutions; it matters for everyone. Money mules are a critical link in the chain of financial crime, as they facilitate the movement of illicit funds across the globe. By disrupting this flow, we not only protect countless victims but also cripple the operational capacity of criminal enterprises.”
The product stands apart from competitors thanks to its deployment of its proprietary Daily Adaptive Model. The models update continually based on the latest financial behaviour enabling the accurate identification of genuine users and criminals. Ongoing updates maintain highest accuracy while dramatically reducing false positives and their associated cost.
The launch comes ahead of growing regulatory movements globally that require financial institutions to accept financial responsibility for APPF transactions – such as UK regulation coming into force on 7th October that will require financial institutions to refund victims for any APPF transactions.
Dan Dica adds: “Even with an existing fraud solution in place, leveraging Lynx’s money mule model scoring enhances the detection of money mules, addressing this specific challenge effectively without the need for complex integrations. What this solution makes possible is a world where criminal rings can’t operate, because their financial pipelines are blocked at every turn.”
The launch follows the news that Lynx was named Best of Breed Name and Transaction Screening Solution in the 2024 Chartis RiskTech Quadrant® for Name and Transaction Screening Solutions.
