AI poised to transform banking with fraud prevention focus

SAS experts have predicted that 2025 will be a transformative year for artificial intelligence (AI) in the banking sector. They highlight advancements in fraud prevention, risk management, and customer experience as key areas of impact.

A recent SAS report suggests that generative AI already provides substantial benefits to banks in areas such as employee experience, risk and compliance processes, and significant time and cost savings. This reflects a broader trend towards AI integration in the financial industry.

Thomas French, Senior Financial Industry Consultant for Fraud at SAS, remarked on the growing prevalence of digital fraud driven by the intersection of social, economic, and technological factors. "The Digital Industrial Age of Fraud has dawned, fueled by a perfect storm of social, economic and technological factors that have made fraud more common – and easier to commit – than ever. In one recent survey, 42% of Zoomers (Gen Z) admitted to disputing legitimate transactions," he said. He warned that the rise of "fraud as a service" leverages inexpensive generative AI tools, urging banking leaders to adapt swiftly to meet customer expectations for fraud protection.

Ian Holmes, Director and Global Lead for Enterprise Fraud Solutions at SAS addressed the energy demands of AI technologies. "As industry clamours for AI to drive greater speed, automation and productivity, AI demands GPUs to satisfy the higher levels of processing," he explained, emphasising the paradox faced by banks striving to enhance environmental sustainability amidst increased energy consumption.

Naeem Siddiqi, Senior Risk Advisor at SAS, predicted the rise of robot assistants in the banking sector. "Watch for robot assistants to begin replacing branch staff and customer service desks," he noted, indicating a shift towards AI-driven customer service that necessitates enhanced governance at financial institutions.

Stu Bradley, Senior Vice President of Risk, Fraud and Compliance Solutions at SAS, highlighted an impending "Great IT Rationalisation" driven by cloud and AI acceleration. He suggested that banks embracing AI platforms capable of multiple functions will gain the most from integrated data and decision-making capabilities.

Julie Muckleroy, Global Banking Strategic Advisor at SAS, discussed the dual nature of big data as an opportunity and a challenge for banks. She underscored the importance of effective data governance in turning vast amounts of data into valuable assets.

David Stewart, Director of Financial Crimes and Compliance at SAS, observed a cautious approach to AI in anti-money laundering (AML) due to regulatory uncertainty. He noted a preference for optimising existing monitoring strategies over adopting pure AI-based detection strategies.

Terisa Roberts, Global Lead for Risk Modeling and Decisioning at SAS, detailed how AI is being integrated into risk and compliance operations. She stressed the need for human oversight and effective governance frameworks as AI models mature.

Stephen Greer, Banking Industry Consultant at SAS, indicated decreased banking investments in environmental, social, and governance (ESG) initiatives. He suggested that, without clear financial returns, ESG is seen more as a cost burden than a growth strategy.

Dan Barta, Principal Industry Consultant for Enterprise Fraud and Risk Strategy at SAS, forecasted an increase in liveness tests in response to the rising use of generative AI for creating deepfakes. This technology will become more integral to banks' authentication processes.

Cornelia Reitinger, Head of Advertising Business Development at SAS, noted the expansion of consumer banks into retail media, leveraging first-party data to offer personalised promotions. This, she argued, will enhance customer engagement and create new revenue avenues.

Finally, Martim Rocha, Global Head of Risk Banking Solutions at SAS, highlighted ongoing market volatility, prompting banks to invest in risk management and leverage advancements in cloud and AI. He predicted a focus on asset and liability management due to sustained interest rates and liquidity risks.