The pandemic has changed how criminals hide their cash—and AI tools are trying to sniff it out
Profits from organized crime are typically passed through legitimate businesses, often exchanging hands several times and crossing borders, until there is no clear trail back to its source—a process known as money laundering.
But with many businesses closed, or seeing smaller revenue streams than usual, hiding money in plain sight by mimicking everyday financial activity became harder. “The money is still coming in but there’s nowhere to put it,” says Isabella Chase, who works on financial crime at RUSI, a UK-based defense and security think tank.
The pandemic has forced criminal gangs to come up with new ways to move money around. In turn, this has upped the stakes for anti-money laundering (AML) teams tasked with detecting suspicious financial transactions and following them back to their source.
Key to their strategies are new AI tools. While some larger, older financial institutions have been slower to adapt their rule-based legacy systems, smaller, newer firms are using machine learning to look out for anomalous activity, whatever it might be.