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.

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