Banks are no longer debating whether artificial intelligence belongs in financial crime and compliance. Instead, they are increasingly focused on how quickly AI can move from experimentation into day-to-day operations.
New research carried out in partnership between Hawk and Chartis shows just how embedded AI has already become across compliance and risk teams, with adoption now extending well beyond isolated pilots.
According to the study, 89% of compliance and risk leaders say their institution actively encourages the use of AI. Meanwhile, 70% report that AI is already being tested or piloted somewhere within their organisation.
The findings are explored in detail in the report AI in Financial Crime and Compliance: Charting the Path from Pilot to Maturity, which examines how banks are using AI today and where they expect the biggest impact in the years ahead.
Fraud prevention stands out as the most advanced use case. A third of banks surveyed say they are already using AI at scale or operationally to combat fraud, while a further 32% are testing or piloting AI-driven solutions.
Another 28% are actively exploring its use, and notably, no respondents reported having no AI usage in their anti-fraud programmes.
AML transaction monitoring follows as the second most mature area, with 22% of institutions reporting operational or at-scale AI deployment. Sanctions screening shows more cautious progress, with 16% using AI at scale, while case management and investigations lag slightly behind at 12%.
Regulatory reporting emerges as the least mature area for AI adoption. Only 9% of banks currently use AI actively in regulatory reporting, while 17% do not use it at all, the highest level of non-adoption across all FCC functions. At the same time, regulatory reporting records the highest level of informal usage, with 31% of respondents saying individuals use AI on an ad hoc basis.
In terms of technology, machine learning remains the backbone of AI adoption across FCC. It is used by 75% of banks in case management and investigations, 66% in fraud prevention and 65% in AML transaction monitoring. Natural language processing is the second most widely adopted technique, particularly in investigations and regulatory reporting, where it supports document analysis and data extraction.
Looking ahead, sentiment among compliance leaders is overwhelmingly positive. Over the next two to three years, 86% expect machine learning to deliver a positive impact across financial crime, fraud and compliance.
For more insights into the growth of AI, download the reports here. There are two editions to the report: Banking and Payment & FinTech.
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