Anti-money laundering has never been simple and FSIs have long been tasked with finding the right balance between smooth customer onboarding and stopping criminal activity in its tracks.
But fierce competition between traditional banks and nimble FinTechs, coupled with increasingly onerous AML legislation and emerging factors like cryptocurrency are making this fine balance harder to achieve than ever before.
Meanwhile, organised criminals are innovating rapidly and reaching ever higher levels of sophistication in terms of their methods, but customers’ patience for time consuming onboarding processes and KYC checks is wearing thin.
As a result, FSIs are shifting between adopting a defensive approach when it comes to detecting suspicious activity- which often creates friction on the front end - or an overly offensive strategy which can be costly in both time and effort.
To combat these challenges, many FSIs are looking to data analytics and machine learning to build an end-to-end view of the customer enabling them to monitor account activity in real time and spot signs of suspicious behaviour across the customer lifecycle.
This webinar featuring expert speakers explored the ways in which FSIs are using data to strike the right balance between an offensive and defensive approach to AML.
