Artificial intelligence can cut money laundering’s ‘acceptable losses’

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April 21 2017

Although the dire need to put a stop to money laundering is well understood, an ongoing negotiation regarding what amount of money laundering is an acceptable cost of doing business plagues regulators and those inside who are responsible for the detection and prevention of financial crimes.  The technology can improve “acceptable costs.” Financial institutions and issuers set dollar, volume and velocity thresholds for transaction monitoring. Above these thresholds, they attempt to screen all transactions for money laundering. Below them, they accept that some money laundering, terrorist financing, and other financial crimes might go unaddressed.

This Above the Line, Below the Line (ATLBTL) practice functions on a risk-based transaction monitoring process by which not all transactions are screened for possible money laundering and other financial crimes concerns.