The global response to financial crime is failing.
Criminals are locked in a technological arms race with authorities. With every new solution created for open banking, faster payments, and consumer control, the opportunities for fraud increase. And illicit financial movements such as money laundering are the fastest growing threats in this emerging fraud landscape.
Traditional anti-money laundering (AML) strategies are no longer enough to counter these attacks. The processes used to detect illicit transactions are based on outdated technology and are ineffective in the world of modern fraud.
Financial institutions that want to decrease their risk need to go beyond the basics and leverage breakthrough technologies that let them re-imagine their fraud detection strategies. Chief among these innovations is machine learning.