How to Shift the Balance from Rule-Led to Intelligence-Led AML Transaction Monitoring


January 2 2019

Anti-money laundering (AML) compliance failures amassed $1.7 billion in fines in the first half of 2018 with over $1 billion of that resulting from actions taken by US prosecutors and regulators, according to the 2018 Mid-Year Anti-Money Laundering Review and Outlook by Debevoise & Plimpton.

Banks and financial institutions (FIs) need to ramp up their anti-money laundering transaction monitoring processes using artificial intelligence (AI), machine learning (ML), and big data to meet regulatory requirements now and in the future. As technology strategically predicts the consumers next need, such as a favorite apparel store aptly texting you a coupon for 15% off raincoats on a wet and dreary day, your AML transaction monitoring process can autonomously identify new threats and patterns of nefarious behavior before you finish your morning coffee (or beverage of choice).