SAS Study: Finance firms accelerate the use of AI for AML
COVID-19 has driven a surge in fraud and financial crime, and now a third of financial institutions are accelerating their AI and machine learning (ML) adoption for anti-money laundering (AML) technology in response to the pandemic, according to a new AML technology study by SAS, KPMG and the Association of Certified Anti-Money Laundering Specialists (ACAMS).
The report, Acceleration Through Adversity: The State of AI and Machine Learning Adoption in Anti-Money Laundering Compliance, and a complementing survey data dashboard examine insights provided by more than 850 ACAMS members worldwide.
The UN estimates that up to $2tn is moved illegally each year. Criminals use big banks to hide money, which is often linked to organised crime, with funds being used to pay for assets to hide the money’s origin. In the UK, the National Crime Agency (NCA) estimates that money laundering costs the country’s economy £24bn each year.
Fighting financial crime
AI and ML have emerged as key technologies for compliance professionals as they look to streamline their AML compliance processes to fight financial crime and money laundering. More than half (57%) of respondents have either deployed AI/ML into their AML compliance processes, are piloting AI solutions or plan to implement them in the next 12-18 months. Although the report found that 39% of compliance professionals said their AI/ML adoption plans will continue unabated, despite the pandemic's disruption.
"As regulators across the world increasingly judge financial institutions' compliance efforts based on the effectiveness of the intelligence they provide to law enforcement, it's no surprise 66% of respondents believe regulators want their institutions to leverage AI and machine learning," said Kieran Beer, Chief Analyst and Director of Editorial Content at ACAMS. "While many in the anti-financial crime world – the regulators and financial institutions alike – are just coming up to speed on these advanced analytic technologies, there's clearly shared hope that these tools will produce truly effective financial intelligence that catches the bad guys."
Dealing with the disruption the pandemic brought
Regardless of institution size, there has been pressure on banks to meet COVID-19's disruption head-on. 28% of large financial institutions, those with assets greater than $1 billion, consider themselves innovators and fast adopters of AI technology. However, encouragingly, 16% of smaller financial institutions (those valued below $1 billion) also view themselves as industry leaders in AI adoption, the report found.
The two primary drivers of AI and ML adoption, according to respondents, are to:
1) Improve the quality of investigations and regulatory filings (40%).
2) Reduce false positives and resulting operational costs (38%).
"The radical shift in consumer behavior sparked by the pandemic has forced many financial institutions to see that static, rules-based monitoring strategies simply aren't as accurate or adaptive as behavioral decisioning systems," said David Stewart, Director of Financial Crimes and Compliance at SAS. "AI and ML technologies are dynamic by nature, able to intelligently adapt to market changes and emerging risks – and they can be integrated into existing compliance programs quickly, with minimal disruption. Early adopters are gaining significant efficiencies while helping their institutions comply with rising regulatory expectations."
