Hitting the Books: How Southeast Asia's largest bank uses AI to fight financial fraud | Engadget

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Hitting the Books: How Southeast Asia's largest bank uses AI to fight financial fraud

by Thomas H. Davenport and Steven M. Miller. Reprinted with permission from The MIT Press. Copyright 2022.Since the passage of the Bank Secrecy Act, also known as the Currency and Foreign Transactions Reporting Act, in the US in 1970, banks around the world have been held accountable by governments for preventing money laundering, suspicious cross-border flows of large amounts of money, and other types of financial crime.

If the analyst confirms that a transaction is justifiably suspicious or verified as fraud, the bank has a legal obligation to issue a Suspicious Activity Report to the appropriate authorities. This is a high-stakes decision, so it is important for the analyst to get it right: if incorrect, law-abiding bank customers could be incorrectly notified that they are being investigated for financial crimes.

In parallel, DBS has also replaced a labor-intensive approach to investigation workflow with a new platform that automates for the analyst much of the support for surveillance-related investigation and case management. Called CRUISE, it integrates the outputs of the rule-based engine, the ML filter model, and the Network Link Analytics system.

Commenting on how this differs from traditional surveillance approaches, the DBS head of transaction surveillance shared the following: DBS invested in a skill set “uplift” across the staff who were involved in creating and using these new surveillance systems. Among the staff benefiting from the upskilling were the transaction surveillance analysts, who had expertise in detecting financial crimes and were trained in using the new technology platform and in relevant data analytics skills. The teams helped design the new systems, beginning with the front-end work to identify risk typologies.

It is important to note that money launderers and sanctions evaders are always finding new ways of doing things. Our people need to work with our technology and data analytics capabilities to stay ahead of these emerging threats. We want to free up the time our people have been spending on the tedious, manual aspects of reviewing alerts, and use that time to keep pace with the emerging threats.

 

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