The study, Acceleration Through Adversity: The State of AI and Machine Learning Adoption in Anti-Money Laundering Compliance, also found that another 39% of compliance professionals said their AI/ML adoption plans will continue unabated despite the disruption.
The report was also complemented by a survey data dashboard and examines the insights of more than 850 Acams members worldwide.
The Acams surveyed each about how their organisations used technology to detect money laundering—estimated in the range of 2% to 5% of global GDP—or US$800 billion to US$2 trillion annually.
Compliance professionals have employed AI and ML 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.
“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,” explains Acams chief analyst and director of editorial content Kieran Beer.
“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,” Beer adds.
It’s not just the largest financial institutions leading the charge on technology adoption either, the study notes. 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.
“With both smaller and larger organisations subject to the same level of regulatory scrutiny, it’s important that these numbers continue to rise,” explains KPMG principal US solutions leader for financial crimes and America forensic technology services Tom Keegan.
Regardless of institution size, the pressure on banks to meet COVID-19’s disruption head on, while boosting accuracy and productivity, is the likely impetus to the industry’s accelerating use of advanced analytics for AML.
The two primary drivers of AI and ML adoption, according to respondents, are to:
Improve the quality of investigations and regulatory filings (40%).
Reduce false positives and resulting operational costs (38%).
“The radical shift in consumer behaviour 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 behavioural decisioning systems,” concludes SAS director of financial crimes and compliance David Stewart.
“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,” he says.
