AI Reshapes Banking: Promises and Pitfalls as Industry Grapples With Transformation

As artificial intelligence revolutionizes the banking sector, industry leaders from UBS and McKinsey highlighted the potential and challenges facing financial institutions. Concerns range from return on tech investments to the future role of human bankers in an AI-driven landscape. McKinsey: AI Promises Banking Revolution, but ROI Challenges Persist AI is poised to transform the banking […]

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As artificial intelligence revolutionizes the banking sector, industry leaders from UBS and McKinsey highlighted the potential and challenges facing financial institutions.

Concerns range from return on tech investments to the future role of human bankers in an AI-driven landscape.

McKinsey: AI Promises Banking Revolution, but ROI Challenges Persist

AI is poised to transform the banking sector, yet new commentary from McKinsey Monday (July 1) highlighted challenges financial institutions face in realizing AI’s potential.

The banking industry’s track record with technology investments has been mixed, according to the firm. McKinsey’s research indicated that only 30% of digital transformation initiatives have succeeded. This statistic underscores banks’ difficulty demonstrating a return on investment for their tech spending, particularly in AI.

Several factors compound these challenges, McKinsey said. Banks must show ROI on past technology investments, differentiate themselves from competitors, and achieve success in ongoing transformation efforts. McKinsey’s data showed that higher revenue in banking “remains very strongly correlated with more manual work,” suggesting that technology still needs to deliver the expected automation benefits.

The consulting firm emphasized that capturing value from AI requires actions beyond the technology domain. McKinsey surveys revealed that 60% of executives cited skill gaps as an obstacle in digital transformations, while 70% reported facing fundamental resistance to change.

To address these challenges, McKinsey advocated for a comprehensive approach. For every dollar invested in technology, an equal amount should be allocated to strategic organizational, cultural and change management initiatives. This approach ensures that AI implementations yield tangible benefits in revenue generation, cost reduction or risk management, providing a sense of reassurance.

As banks navigate the AI landscape, McKinsey outlined three questions for leaders. First, they must identify areas where AI can generate the most business value. Second, banks need to reallocate spending toward these high-potential areas. Finally, institutions should implement change management strategies that extend beyond the IT department.

While AI’s transformative potential in banking is clear, McKinsey’s insights suggested that success will depend on technological advancements and banks’ ability to reshape their organizations to use AI effectively and fundamentally. As financial institutions grapple with these challenges, turning AI’s promise into measurable results looms large on the horizon.

UBS Exec: AI Revolutionizing Banking

UBS is seeing a shift in the way clients interact with their bankers, powered by AI, according to Sabine Keller-Busse, the head of the Swiss bank’s domestic business, Reuters reported.

Speaking at the Point Zero Forum in Zurich Tuesday (July 2), Keller-Busse compared the change to how patients now approach doctors with preconceived ideas about their conditions, noting that clients increasingly use AI to generate ideas before presenting them to the bank.

“In our industry, this will happen as well because with ChatGPT, there is more data available,” Keller-Busse said, per the report. “We have to be aware that our clients are using it.”

UBS has been integrating AI into its client services and products. Last year, the bank launched a pilot program for instant credit aimed at small- to medium-sized businesses (SMBs), which often need quick access to liquidity. The service allows for bypassing credit officers, speeding up the process for this relatively standard product, the report said.

Keller-Busse emphasized that these developments are the start of a broader trend, saying in the report, “It’s just the beginning of what we will see.”

The shift reflects a broader trend in the financial services industry, where AI and machine learning transform traditional banking practices. As clients become more tech-savvy and access sophisticated AI tools, banks must adapt their services and client engagement strategies. The change affects how banks interact with their customers and how they develop and offer products and services.

The integration of AI in banking also raises questions about the future role of human bankers. While AI can streamline processes and provide quick data analysis, human judgment remains crucial, especially in complex financial decisions. Banks like UBS will likely face the challenge of balancing AI capabilities and maintaining the personal touch that many clients still value in their banking relationships.

In a June report, Citigroup warned that the banking industry faces the most significant impact from AI deployment, with 54% of roles at risk of AI-driven job displacement. Furthermore, an additional 12% of banking jobs could be enhanced by AI integration.

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