A third of financial institutions have increased AI and ML in response to money laundering
According to new research, a third of financial institutions are accelerating their AI and machine learning (ML) adoption for anti-money laundering (AML) technology in response to COVID-19.
At the same time, 39% of compliance professionals say their AI/ML adoption plans will continue unchanged, despite the pandemic's disruption.
The results are from an AML technology study focusing on industry trends conducted 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, along with a complementing survey, examines results from over 850 ACAMS members globally.
The survey asked each respondent how their employer used technology to detect money laundering, which is estimated to be in the range of 2% to 5% of global GDP or US$800 billion to US$2 trillion annually.
According to the survey, AI and ML have emerged as key technologies for compliance professionals, streamlining the AML compliance processes. Over 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 worldwide increasingly judge financial institution's compliance efforts based on the effectiveness of the intelligence they give law enforcement, its no surprise 66% of respondents believe regulators want their institutions to leverage AI and machine learning," says ACAMS chief analyst and director of editorial content, Kieran Beer.
"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 shared hope these tools will produce effective financial intelligence to catch bad actors."
The largest financial institutions are not the only ones leading the charge on technology adoption. The report found 28% of large financial institutions, those with assets greater than $1 billion, consider themselves innovators and fast adopters of AI technology. However, 16% of smaller financial institutions (those valued below $1 billion) also view themselves as industry leaders in AI adoption.
"Seeing a strong percentage of smaller financial organisations label themselves industry leaders debunks the myth that advanced technological solutions are beyond the reach of smaller financial organisations," says KPMG principal U.S. solution leader for financial crimes and American forensic technology services, Tom Keegan.
"With both smaller and larger organisations subject to the same level of regulatory scrutiny, it's important these numbers continue to rise."
Despite institution size, pressure on banks to meet COVID-19s disruption head-on while boosting accuracy and productivity is the likely impetus to the industry 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 decision-making systems," says 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."
He says early adopters are becoming more efficient while helping their institutions comply with rising regulatory expectations.