The implementation, opportunities, and challenges of generative AI in the financial services industry are hot topics across industries. Rapid advancements and growing interest make it essential to stay ahead of the curve in AI adoption.
IBM, a global leader in technology and consulting services, shared insights on generative AI with FinTech Magazine and discussed the strategic priorities, regulatory compliance and talent acquisition challenges facing the industry today.
In this exclusive interview, we spoke with John Duigenan, global CTO, financial services, IBM, and Shanker Ramamurthy, global managing partner, banking and finance, about recent survey findings on GenAI implementations.
A recent IBM survey of 2,500 CEOs, including over 300 from the banking industry, produced some particularly noteworthy findings.
Shanker Ramamurthy commented: “The survey yielded some very interesting results: 60% of CEOs are talking about generative AI as a strategic priority at the enterprise level.”
He added: “This statistic is particularly interesting because another recently published study revealed that while 80% of banks have implemented generative AI at enterprise scale, the other 80% are only conducting pilots or proof-of-concept projects.”
“Our latest research finds that at least 60% of banks plan to engage with generative AI at enterprise scale between the remainder of this year and 2025. This is significant and aligns closely with what we and IBMC see as the potential for generative AI.”
Persistent challenges in attracting technical talent
“Nearly 50% of CEOs spoke about talent, specifically the inability to attract the right technical talent to address the opportunities arising from generative AI,” Ramamurthy says, highlighting a significant challenge in the field: finding and retaining skilled professionals who can drive AI initiatives.
“In fact, when we discuss generative AI with our clients, we don't just focus on the technical aspects, but also on talent acquisition. It's important to enable the entire enterprise to harness the potential of generative AI. For CEOs, attracting and retaining the right talent to take advantage of these opportunities is a big challenge.”
In the survey, over 75% of CEOs emphasized the importance of ecosystems, partnerships and collaboration to achieve results with generative AI.
Ramamurthy is a strong believer in the importance of partnerships and ecosystems, which are key areas of focus for IBM: “Our CEO and Chairman have been very big on partnerships and ecosystems, and it's important that CEOs bring that aspect to the forefront as they look to unlock the economic value of generative AI.”
Focus on customer experience and employee productivity
IBM is also focused on removing friction from the customer experience. John Duygenin commented: “Every financial services company on the planet, regardless of industry or who their customers or clients are, needs improved customer experience and highly personalized, highly contextualized and relevant instant recommendations, instant decisions, instant fulfillment on every available channel.”
Additionally, generative AI can be applied to automate manual back-office processes and integrate multiple back-end systems, significantly improving employee productivity.
“Employee productivity is being significantly improved by digital workforce, which is transforming and automating the massive manual back-office processes that currently engage thousands of employees at financial services firms. By applying generative AI, these processes can be conversationally orchestrated and integrated with multiple back-end systems,” said John.
“Modernizing application development and IT operations is critical, especially for older code bases. Increasing developer productivity by at least 60% is a big deal for any company,” John concludes.
Regulatory Impact on AI: EU AI Law
“The EU acted swiftly,” said John Duygenin, “and this is important because there is a huge need for transparent, trustworthy AI for use by businesses.”
He added: “EU AI law introduces a risk classification framework that bans certain uses of AI, such as facial recognition for commercial purposes, due to their potential for discrimination. It also includes a comprehensive assessment framework on how companies should measure their AI, with fines of up to 7% of global turnover or €35 million for non-compliance.”
“At IBM, we have been relentlessly committed to building AI within a framework of trust and regulation. We foster an open community around AI development so our clients can have confidence in the AI solutions they implement.”
12-Month Forecast
Shankar Ramamurthy believes that clients are entering a multi-model world where the speed and pace of change is extraordinary.
“Striking a balance between business and technology is crucial and requires a flexible and adaptable approach. While business strategy will continue to guide our technology efforts, technology capabilities will increasingly shape business model possibilities. Over the next three years, we expect banking business models to change significantly. Leveraging the power of hybrid cloud AI and generative AI, combined with ecosystems and platforms, will be key to unlocking potential and translating it into tangible outcomes for our clients.”
“With this in mind, there are two sides to the coin: on the one hand, you will see the valuable insights and key performance indicators (KPIs) provided by an enterprise AI platform. On the other hand, there will be challenging moments where the AI doesn't work as expected,” said John Duygenin.
“So anyone considering an AI solution should ask their AI provider key questions: How were the models created? What data sources were used? Can they be trusted? Demand clear answers to these questions. If the AI provider is unwilling or unable to answer, that's a red flag. Look for alternatives.”
