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Criminals Leveraging Covid-19 to Recruit Money Mules 

First published by The Independent, Ben Chapman interviews Araliya Sammé, Head of Financial Crime at Featurespace, about the increase in money muling activity amid the Covid-19 pandemic. 

Criminals are exploiting the coronavirus pandemic to recruit money mules via social media to launder cash from human trafficking, terrorism financing or drug dealing, experts have warned. 

Social media mule recruitment is being ramped-up in recent weeks after legitimate sources of income, such as hospitality or retail work, dried up almost entirely due to lockdown measures and people have become more vulnerable to scams. 

Fraudsters are also using bereavement scams that target the relatives of people who have died from Covid-19 purporting to be debt collectors recovering debts incurred by the deceased, according to Cifas, the UK’s fraud prevention service. 

There are many different ways to recruit money mules, who pass money from illegitimate sources through their bank accounts to make it appear clean, says Araliya Sammé, the head of financial crime at fraud prevention firm Featurespace. 

These gangs are targeting students and people under 25 because they are particularly likely to be out of work at the moment, she explains. “They are spending much more time in front of their screens waiting for the situation and on social media platforms. It could just be a pop-up promising a quick and simple way to earn money from home.” 

Click here to read the full article.  

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About Featurespace – www.featurespace.com

Headquartered in the U.S. and U.K. and with offices in Atlanta, Cambridge and London, Featurespace™ is the world-leader in fraud prevention and creator of the ARIC™ platform, a real-time AI machine learning software that risk scores events in more than 180 countries.

The ARIC platform combines adaptive behavioural analytics and anomaly detection to automatically identify risk and catch new attacks as they happen. The increased accuracy of understanding behavior strikes the balance between improving fraud and risk detection and operational efficiencies, while also reducing the number of genuine transactions that would be incorrectly declined by as much as 70 percent.

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