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How Banks and Fintechs Can Beat Fraudsters in the AI Arms Race

5 de abril de 2024

Fraudsters increasingly are leveraging artificial intelligence to commit crimes, with AI-powered fraud projected to reach $10.5 trillion by 2025. But the good news is that AI also is arming banks and fintechs with powerful new tools to combat fraud, reducing risk and minimizing losses, while also maintaining streamlined, user-friendly experiences for customers.  

In a recent Payments Journal webinar, Galileo Senior Director of Global Payments Risk Management Max Spivakovsky likened the dynamic to a “digital arms race, [with] the criminals and the cybersecurity and fraud professionals trying to stay one step ahead of each other all the way.” 

Why a proactive anti-fraud strategy is key 

Recent advances in the power of AI are causing the speed of that arms race to pick up considerably, Spivakovsky said during the webinar.

“The difference between what we’ve seen [in the past] and what we’re going to see in the near future is that, given natural language models, the pace of trying to outdo one another is going to increase...”
Max Spivakovsky
Galileo Senior Director of Global Payments Risk Management

In the high-velocity competition between fraudsters and the good guys, it’s imperative to adopt an anti-fraud strategy that emphasizes proactive risk analysis, detecting and preventing fraud before it can occur, according to the Galileo payments risk head.

How Banks Are Leveraging Anti-Fraud Tech to Fight Fraud

“The link analysis and accuracy of the models make the proactive approach so much more accurate,” Spivakovsky said. He went on to cite examples of proactive anti-fraud measures, including tools that automatically notify financial institutions or customers that they might be the target of potential fraudulent activity and cancel or restrict spending on the card when there’s an indication it may have been accessed by fraudsters.  

AI-powered detection, customer service  

 The evolution of AI and machine learning also have opened the doors for advanced pattern recognition, behavior analysis and adaptive learning about customer activity–all of which banks and fintechs can use to help detect instances of possible fraud more effectively and efficiently than humans could, noted Spivakovsky. 

“Model creation is automated and recursively learned from previous experiences, such that exceptions requiring manual review become less and less common over time,” Spivakovsky said. “That’s a huge win for commercial enterprises and for financial institutions, in that it frees up human capital that would otherwise be tied up with those manual reviews. That, in turn, allows them to utilize their workforce more efficiently and to stretch departmental resources a bit further than they otherwise could.”

How AI Is Helping Banks Improve Customer Service, Security

Meanwhile, providers also increasingly are leveraging AI-powered chatbots with intelligent digital assistants that interact with customers in real-time to address emerging fraud risks, further reducing the need for human capital, Spivakovsky added.

Breaking down data silos 

Data silos in which different systems have different sets of data and don’t “talk” to one another traditionally have been among the biggest challenges in protecting multi-channel systems from fraud–especially as the amount of customer data banks have on hand has grown significantly with the rise of digital banking. 

Applying AI has helped banks and fintechs gain a more holistic view of the data across various channels–visibility and interoperability that improves fraud detection capabilities, said Spivakovsky. 

Learn more about how Galileo can help you proactively protect your customers - and your business - from fraud.

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