Improved behavioral analytics
AI will be able to develop more detailed profiles of customer behavior over time at a faster speed , allowing for quicker , more accurate detection of anomalous behavior . Victor Tay , co-founder of the regulatory technology company Minerva , which helps mitigate risk and combat financial crime , summarizes this causeand-effect relationship well . He observes , “ I foresee a balanced application of AI that may not negatively impact the job market . AI tools will enhance organizational efficiency and improve the identification of new typologies and risks . This improvement will generate more complex alerts and work that require human review and investigation . As AI takes over simpler tasks , such as detecting structured transactions , the focus will shift to more intricate issues that need human expertise . So rather than reducing jobs , AI is likely to transform them , necessitating advanced skills and deeper analysis .” 8
Reduction in silos
AI will compel financial services firms to become less siloed and more inclined to making sure information is shared uniformly and consistently across departments . AI only works if there is continuous data to feed it . More importantly , that information needs to be accurate , solid and consistent . Remember , firms are using AI across all departments , not just in FCC . Banks , for example , use AIpowered financial advisors to provide personalized banking experiences and products . 9 Broker / dealers and trading firms optimize their trading strategies using machine learning algorithms . Many firms , from Klarna to Capital One , are engaging AI bots to provide customer service . 10 Each department collects specific data based on its vertical and purpose ― and data is everything . How do you harness all that data collectively ? Phillips answers this question perfectly , noting , “ As institutions become more integrated and technologically complex , AML teams will need to liaise with other parts of the bank to ensure that information is being shared across teams . In addition , there will be a need for AML professionals to speak with the data people building and maintaining the models or looking for new risks . This could very much be a full-time position as these models grow and teams become more dependent on them for identifying suspect activity .” 11
AI is expected to become increasingly sophisticated in the broader fight against financial crime
AI ’ s role in the fight against financial crime will become increasingly crucial because of its ability to detect patterns , continuously monitor and quickly generate alerts . The moral of the story is that FCC programs will depend more on AI technology for more rote , administrative and time-intensive tasks . Many of the human jobs that focus on doing that type of work will transform . The line between the investigator and the QA analyst will become less evident . And business analysts and liaisons between FCC teams and data scientists will become vital . Tay sums it up succinctly : “ I don ’ t believe organizational charts will undergo dramatic changes in the next 10 years . However , I do foresee shifts in job titles and roles . Traditional AML and financial crimes investigators will likely evolve into operators of AI tools . Their responsibilities will include informing and guiding AI to identify , understand and detect emerging risks .” 12
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