Could Artificial Intelligence Spell Check-Mate for Money Laundering?
Dr Karthik Tadinada, Director of Data Science at Featurespace assesses the potential for machine learning in the fight against financial crime, and separates data-science fact from AI fiction for The Fintech Times.
The finance industry’s traditional rules-based approach to catching money laundering is at breaking point. As little as 1% of laundered money ends up being seized by regulators. Meanwhile, the scale and ambition of money launderers continues to grow. It’s estimated that up to 5% of Global GDP is laundered – that’s equivalent to $2 trillion every year, roughly the annual GDP of Brazil directly funding organised crime and terrorism.
Adaptive Behavioral Analytics with Machine Learning is helping close the gap, Dr Tadinada explains how: continue reading on The Fintech Times.
Discover ARIC for Anti-Money Laundering
The ARIC platform combines adaptive behavioural analytics and anomaly detection to automatically identify risk and catch new attacks as they happen.
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.
Michael Touchton, Featurespace
U.S. Marketing Manager
+1 (423) 364-5491