Businesses Get Wary Of Trade-Based Money Laundering

All News All News Except Press Releases Fintech Imported

The Financial Action Task Force (FATF) is warning of new ways of money laundering via exports like onions, potatoes, soft fruits or expensive cars, a report from the Financial Times says.

Called trade-based money laundering, the new kind of fraud, according to FATF President Marcus Pleyer, enabled one criminal organization to move over $400 million over several years.

The news outlet reports there are four main forms of trade-based money laundering: the over and under-invoicing of goods, in which prices are falsely labeled to transfer value; the over and under-shipment of goods, including “phantom shipments” where nothing moves; multiple invoicing where goods’ trade documents are reused numerous times, and falsely described goods where the quality is understated to transfer value.

According to a risk assessment by the U.K., the new demand for some goods and services for the fighting of COVID-19 also posed increased risk of money laundering in this way.

The FATF warned that transactions that were supposedly for pharmaceuticals, textiles and other personal protective equipment were more often likely to be used by perpetrators. According to Jonah Anderson, a partner in the white-collar crime practice of law firm White & Case, trade-based money laundering was always a likely alternative as traditional forms of the crime became harder to pull off. Most cases of trade-based money laundering is done via shell companies, although some have involved legitimate businesses, with consequences including criminal investigation or just loss of reputation.

PYMNTS refers to money laundering as the process of converting illegally-gotten funds into legitimate income to be spent without suspicion. With the digital age, both the crime itself and the ways it’s combatted or fought have moved onto the internet.

As PYMNTS writes, it’s often down to payment providers to put a stop to money laundering, with artificial intelligence able to help via analyzing thousands of transactions in a fraction of the time it would take humans to do so.

Source: PYMNTS

Facebook Comments