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Essential that firms ensure good data and step-by-step migration when adopting automated AML systems, ‘otherwise, it won’t work,’ industry experts claim

By Dan Byrne for AMLi

THE DEBATE OVER AI in anti-money laundering should be less about the technology and more about the data it processes, according to one industry expert.

Markus Schulz, Global Head in Change Management and Financial Crime Compliance at ING stressed that while AI was a welcome addition the world of AML, it was not the ‘silver bullet’ that some are making it out to be.

“It’s all about data, data, data,” he told a British-Irish Virtual AML & KYC Summit. “It doesn’t matter if your machine is better or cheaper, if it doesn’t feed on the right information, it won’t work.”

He harked back to the ‘garbage-in-garbage-out’ mantra reiterated by so many of his colleagues and said that instead of firms trying to replace their old systems with brand new automated ones, they should instead build on what they currently have.

“People should not be thinking about where they can jump to, they should be thinking about a migration path – one step at a time.”

He expressed a dislike for the term ‘AI’ meaning ‘artificial Intelligence’ and said that there was more realism in the alternate ‘augmented intelligence’

“We’re in transition like that from the petrol engine to the electric vehicle,” he explained. “And right now, we’re in the hybrid phase where we need to augment everything into one package.”

Colleagues at the KYC summit echoed Schulz’s claims that AI was not about jumping into a brand-new way of working. The process required a ‘theory of change’, step by step approach rather than an overhaul, they said.

“AI is here to stay,” said Head of surveillance and financial crime at Nomura Nitzan Solomon. “It’s a wonderful tool. In ten years, people will laugh at us for questioning this technology.”

“But people need to be mindful and lift the hood when looking at solutions,” she cautioned.

Meanwhile, Head of Transaction Monitoring at Santander Bank Caroline Kennedy stressed that attention was needed on how different AI solutions would win out for different lines of business.

“AI is not something that we can just throw at all our problems,” she said. “We need to focus on what the questions are and be open with vendors and other banks about how these solutions can help.”

She also called for any AI solution to be applied across various banks, acting as a single collaborative unit, rather than it being used to solve one problem at one institution, with little outside input. 

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