A third of financial institutions are accelerating their adoption of AI and machine learning (ML) for anti-money laundering (AML) in response to COVID-19, according to new research.

Over a third – 39 per cent - of compliance professionals said their AI and ML adoption plans will continue unabated despite the pandemic’s disruption according to the report from SAS, KPMG, and the Association of Certified Anti-Money Laundering Specialists (ACAMS).

The research surveyed 850 ACAMS members worldwide about their employer organisations’ use of technology to detect money laundering, the total value of which it estimates is in the range of between 2 per cent to 5 per cent of global GDP – or US$800 billion to US$2 trillion – annually.

AI and ML have emerged as key technologies for compliance professionals according to the study; more than half – 57 per cent - of respondents have either incorporated AI or ML into their AML compliance processes, or they are piloting AI solutions or planning to implement them in the next 12 to 18 months.

It’s not just the largest financial institutions that are adopting AI; 28 per cent of large financial institutions, with assets greater than $1 billion, consider themselves innovators and fast adopters of AI technology according to the report.

In addition, 16 per cent of smaller financial institutions - valued below $1 billion - view themselves as industry leaders in AI adoption.

Improving the quality of investigations and regulatory filings were the primary drivers of AI and ML adoption according to 40 per cent of respondents, while reducing false positives and resulting operational costs was the main driver for 38 per cent.

“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,” said Tom Keegan, principal US solution leader for financial crimes and forensic technology services at KPMG. “With both smaller and larger organisations subject to the same level of regulatory scrutiny, it’s important that these numbers continue to rise.”

“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,” 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 programmes quickly, with minimal disruption.”

He added: “Early adopters are gaining significant efficiencies while helping their institutions comply with rising regulatory expectations.”

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