Pandemic spurs AI adoption in financial institutions

One-third of financial institutions are accelerating artificial intelligence (AI) and machine learning (ML) within their anti-money laundering technology in response to the Covid-19 pandemic, according to a report by SAS, KPMG, and the Association of Certified Anti-Money Laundering Specialists.


In its report, Acceleration Through Adversity: The State of AI and Machine Learning Adoption in Anti-Money Laundering Compliance, it said AI and ML have emerged as key technologies for professionals within the industry to fight financial crimes and money laundering

The report said 39% of compliance professionals will continue their AI and ML plans despite disruptions from the pandemic, while 57% have deployed the two in their processes, and the rest have either already piloted AI solutions or have plans to implement them in the next 12 to 18 months.


ACAMS Chief Analyst and Director of Editorial Content Kieran Beer said as regulators across the world increasingly judge financial institutions’ compliance efforts based on the effectiveness of the intelligence provided to law enforcement, it was no surprise 66% of respondents believed regulators wanted their institutions to leverage AI and ML.

While many in the anti-financial crime world, 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,” he said.

KPMG Principal U.S. Solution Leader for Financial Crimes and America Forensic Technology Services, Tom Keegan said 28% of large financial institution with assets of more than US$1 billion consider themselves innovators and fast-adopters of AI technology. .


“Encouragingly, 16% of smaller financial institutions including those valued below US$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 beyond the reach of smaller financial organisations. With both smaller and larger organisations subject to the same level of regulatory scrutiny, it’s important that these numbers continue to rise,” Keegan noted.


Meanwhile, SAS Director of Financial Crimes and Compliance David Stewart said the radical shift in consumer behaviour due to the pandemic forced financial institutions to realise that static rules-based monitoring strategies are not as accurate or adaptive as behavioral decisioning systems.


“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 opined.


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