Experian launches new service to prevent ‘Money Mule’ account fraud

Experian launches new service to prevent ‘Money Mule’ account fraud

Consumer credit company, Experian, has announced a new service which will help banks and building societies identify and close ‘money mule’ accounts which are used to house fraudulently-obtained funds.

Money mules are individuals who have agreed to let their bank accounts be used by criminals in exchange for cash. According to new insights from Experian, 42% of first-party current account fraud is now mule-related, with the fraud rate for current accounts rising by 13% in the first three months of the year.

Money laundering is estimated to cost the UK economy more than £100 billion each year, while Authorised Push Payment (APP) fraud losses reached £485 million in 2022.

The funds deposited in these accounts are often the proceeds from APP fraud – with the victim is tricked into transferring money to various mule accounts to hide the origin of money – before then being distributed onto the fraudster’s own accounts.

Currently, banks and other account providers don’t have information on where the money is being received from or being sent to except for confirmation of the payee, making it difficult for them to identify and investigate accounts potentially being used in this way.

Experian Mule Score aims to solve this problem. By analysing account opening history and turnover activity, Experian bureau data, and the modelled characteristics of more than 200,000 confirmed mule cases, the Machine Learning-powered solution enables banks to assess their entire portfolio so they can easily spot questionable account activity.

In proof-of-concept trials, the solution was able to accurately identify more than 50% of the highest risk ‘mule’ accounts. The solution will help banks avoid onboarding suspicious accounts at the point of opening, reduce fraud losses and operational costs, support consumers who are at risk, as well as preventing fraudulent funds entering the mainstream financial system.

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