AI models have the potential to significantly increase the effectiveness of AML systems, according to senior bank executives. Robert Edwards, former Global Head of Transaction Monitoring at Credit Suisse, stated that the new technology can supplant the rules-based systems that dominate the financial sector. “I was brought into Credit Suisse to implement a rules-based transaction monitoring system. [But] it hasn’t really evolved over the past 20 years. That is not the case with AI,” he remarked during a webinar organized by Hawk and AML Intelligence.
Edwards emphasized the rapid evolution of AI, noting, “AI is changing month to month; the speed with which it’s changing is really quite impressive.” He criticized the traditional rules-based engines, which he called ineffective due to their 99% false positive rate. “AI gives us an opportunity to become much more effective in our transaction monitoring and alert resolutions,” he added.
The webinar precedes an in-depth report featuring interviews with senior banking leaders about the governance and implementation of AI models. The report aims to analyze how these leaders create and maintain their AI systems, with insights from the webinar also shared with attendees. Interested parties can sign up for the AML Intelligence newsletter to receive more details on the forthcoming e-book.
Adrianna Fabijanska, Global Head of Financial Crime Compliance Investment Banking at ING, provided additional context during the discussion, emphasizing the importance of “clarity of purpose” when deploying AI models. “Our biggest learning curve throughout the years that we’ve been experimenting with various models, including the most recent AI models, is actually understanding that AI is just another tool,” she stated.
Fabijanska highlighted that while AI can amplify strategies, it can also exacerbate issues if the underlying strategy lacks clarity. She explained that financial institutions must first identify the specific use case for an AI model prior to its implementation. “We start with defining, okay, what is exactly the problem we’re trying to solve? And therefore, what is the risk that we’re trying to mitigate through the implementation of the solution?”
She further elaborated that clarity in objectives allows institutions to focus on desired outcomes such as reducing false positives, uncovering hidden patterns, and improving overall consistency. “Everything else flows from that clarity. If that clarity is not there, we’re going to have a [negative] ripple effect,” Fabijanska warned.
The full e-book, which will encompass insights from Edwards, Fabijanska, and other banking leaders, is slated for publication next week. Both AML Intelligence and Hawk plan to share additional details, underscoring the ongoing importance of effective governance in AI technology as it continues to reshape the financial landscape.
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