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Avoiding the scam: Tactics for combatting AI fraud

The bank HSBC, for example, partnered with Google in 2021 to develop an AI system for detecting financial crime.

HSBC on Wednesday named chief financial officer Georges Elhedery as the bank's next chief executive
HSBC on Wednesday named chief financial officer Georges Elhedery as the bank's next chief executive - Copyright AFP Roslan RAHMAN
HSBC on Wednesday named chief financial officer Georges Elhedery as the bank's next chief executive - Copyright AFP Roslan RAHMAN

Both before and after the introduction of ChatGPT, the world’s most popular AI chatbot, in late 2022, the use of AI in financial fraud tactics has been on the increase. A 2022 report from Cifas found an 84 percent increase in the number of cases where AI was used to try and attack banks’ security systems.

Digital Journal has learnt how to combat AI related fraud with input from Stuart Wilkie, Head of Commercial Finance at Anglo Scottish Finance. This solution is embedded in AI itself.

Just as fraudsters are using AI to commit fraud, banking and finance institutions are using machine learning to detect fraudulent activity – and getting progressively better at doing so.

Risk assessments are essential for every organisation; however, the traditional risk assessment often provides a static picture. This means new solutions are required to cope with the trajectory being taken by cybercriminals. The bank HSBC, for example, partnered with Google in 2021 to develop an AI system for detecting financial crime.

Here the Dynamic Risk Assessment system is becoming increasingly accurate; initially, false positives were common, but these reduced by 60 percent between 2021 and 2024. The more accurate these systems become, the better chance we have of eliminating financial fraud altogether.

Dynamic Risk Assessment is a cloud-native system that runs in Google Cloud leveraging its risk detection product, AML AI. With the system, models are trained on the bank’s production data and validated through a testing process.

“Generally, banks are doing a good job of shoring up their biometric systems against deepfaking – the more scammers they detect via their own machine learning algorithms, the quicker they’ll be able to identify them,” Wilkie explains.

He continues: “It’s not just about combatting fraud at an institutional level, however,” he continues. “Part of ensuring that fraud doesn’t take place in the first place is about education – teaching banks’ customers to spot new and developing scams in order to avoid being caught out.”

Wilkie finds that the system is dynamic, requiring vigilance and new technological solutions. Here he notes: “With AI and other technological advances changing the fraud landscape on an almost daily basis, however, this can be challenging.”

As an example, Wilkie says: “If you receive communications from your bank via email, phone call or any other method, always be sure to interrogate what they’re actually asking you to do. Most banks will never ask you for specific details, so make sure you’re clued up at all times.”

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Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, business, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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