Many of the Anti Money Laundering (AML) systems within banks are no longer fit for purpose according to a white paper published by NetGuardians, the Swiss anti-financial crime FinTech. Machine learning-based solutions for AML can monitor the ever-growing number of instant payment transactions far more effectively.

The paper, titled ‘The Future of Transaction Monitoring for AML’, exposes the weaknesses of traditional rules-based AML monitoring systems to accurately detect suspicious transactions in the digital age. But even if existing AML monitoring systems were effective, according to NetGuardians, the spread of instant electronic payments means banks’ current systems would come under impossible strain.

Without effective safeguards, instant payments can enable industrial-scale money laundering to occur without banks being aware, despite their legal obligations to prevent it. NetGuardians cites findings from global management consulting firm McKinsey, “For most banks, more than 90% of transaction-monitoring alerts turn out to be false positives. Of those alerts that do result in a suspicious activity report filing, 80% to 90% are not acted upon.” However, transaction monitoring systems based on machine learning result in greater accuracy and fewer false positives, leading to more efficient use of compliance resources.

According to the UN Office on Drugs and Crime, approximately USD$1.6tn, equating to around 3.6% of global GDP, is laundered every year. Alarmingly, however, less than 1% of the proceeds of crime are successfully confiscated each year, according to Europol, suggesting that when AML monitoring systems fail to correctly identify money laundering transactions, the criminals will likely profit from the funds.

NetGuardians predicts that the threat posed by ineffective AML systems to the credibility of national financial regulators will ultimately drive uptake in new technologies that can improve oversight and increase detection and recovery rates.

Thierry Divenot, NetGuardians’ Global Head of Sales & Marketing, said:  “Machine learning solutions for AML transaction monitoring are capable of drastically reducing the instance of money laundering and improving compliance. However, this transformative technology can only reach its full potential if banks and regulators are willing to embrace the future, which requires acceptance and determination across the banking industry. NetGuardians hopes this white paper will serve as a wake-up call and highlight the possibilities that can be achieved by a shift toward modern technology.”

For more information on how banks can make the transition to machine learning-based AML transaction monitoring, read ‘The Future of Transaction Monitoring for AML’ white paper online at the following link (also available for download): https://www.netguardians.ch/all-about-aml-transaction-monitoring/