Fintech
IBM: Exploring the Impact and Challenges of Generative AI in Financial Services
The implementation, opportunities, and challenges of generative AI in the financial services industry are hot topics across industries. With rapid progress and growing interest, it is essential to stay ahead of the curve in AI adoption.
IBM, world leader in technology and consulting services, shared their insights into generative AI with FinTech Magazine, discussing the strategic priorities, regulatory compliance, and talent acquisition challenges the industry faces today.
In this exclusive interview, we spoke with John Duigenan, Global CTO of Financial Services, and Shanker Ramamurthy, Global Managing Partner of Banking and Finance at IBM, about the findings of their recent survey on GenAI implementation.
A recent survey of 2,500 CEOs, including more than 300 from the banking industry, by IBM revealed some particularly noteworthy findings.
Shanker Ramamurthy comments: “The survey produced some pretty interesting results. 60% of CEOs cited generative AI as a strategic priority for them at the company level.”
He adds: “The reason this statistic is particularly interesting is that we recently published another study showing that 80% of banks are implementing generative AI at enterprise scale, while another 80% are only running pilots and proof-of-concept projects.
“From our most recent survey, we found that at least 60% of banks plan to tackle generative AI at an enterprise scale for the remainder of the year and into 2025. This is significant and closely aligns with what we and IBMC see as the potential of generative AI.”
Persistent challenges with tech talent acquisition
“About 50% of CEOs talked about talent and their inability to attract the right tech talent specifically to address the opportunities arising from generative AI,” Ramamurthy says. This highlights a critical challenge in the industry: finding and retaining qualified professionals who can drive AI initiatives forward.
“In fact, when we talk to our clients about generative AI, we focus not only on the technology aspects, but also on talent acquisition. It is critical to ensure that the entire company can leverage the potential of generative AI. For CEOs, attracting and retaining the right talent to take advantage of these opportunities is a significant challenge.”
In the survey, over 75% of CEOs stressed the importance of ecosystemspartnerships and collaboration to achieve positive outcomes with generative AI.
Ramamurthy is a firm believer in the importance of partnerships and ecosystems, which are key focus areas for IBM: “Our CEO and chairman have always pushed partnerships and ecosystems, and it’s important to bring that to the forefront as CEOs look to unlock the economic value of generative AI.”
A focus on customer experience and employee productivity
IBM is also placing a strong emphasis on removing friction from the customer experience. John Duigenan comments, “Every financial services company on the planet, regardless of what type of business they are in and who their customers are, is improving the customer experience, hyper-personalized, hyper-contextual, instantly relevant recommendations, instant decisions, instant fulfillment on any available channel,” Duigenan says.
Additionally, applying generative AI to automate manual back-office processes and integrate multiple back-end systems can significantly improve employee productivity,
“Employee productivity is dramatically improved through digital work, which is transforming and automating the extensive manual back-office processes that currently occupy thousands of employees in financial services firms. By applying generative AI, these processes can be orchestrated and conversationally integrated across multiple back-end systems,” says John.
“Modernizing application development and IT operations, especially with older code bases, is critical. Creating developer productivity improvements of at least 60% is a huge thing for any company,” concludes John
Regulatory impact on AI: EU AI Act
“The EU has moved quickly,” says John Duigenan, “and it’s important that it has done so because the need for transparent and trustworthy AI used by businesses is huge.”
It continues, “The EU AI Act introduces a risk classification framework that bans certain uses of AI, such as facial recognition for commercial purposes, due to its potential for discrimination. It also includes a comprehensive assessment framework on how companies measure their AI, and non-compliance can lead to fines of up to 7% of global turnover or €35 million.”
“At IBM, we have worked tirelessly to build AI within a framework of trust and regulation. We foster an open community around AI development, ensuring our clients can trust the AI solutions they deploy.”
A 12 month forecast
Shanker Ramamurthy believes that customers are entering a multi-model world where the speed and pace of change will be extraordinary.
“Balancing business and technology will be critical, requiring a flexible and adaptable approach. While business strategy will continue to drive our technology efforts, technology capabilities will increasingly shape the possibilities for business models. Over the next three years, we expect to see dramatic changes in banking business models. Harnessing the power of hybrid cloud AI and generative AI, combined with ecosystems and platforms, will be critical to unlocking potential and converting it into tangible outcomes for our clients.”
John Duigenan says: “To build on this, we have two sides to the coin. On the one hand, we will see valuable insights and KPIs provided by enterprise AI platforms. On the other hand, there will be challenging times when AI may not perform as expected.
“Therefore, anyone considering an AI solution should ask their AI vendor critical questions: How were the models created? What Data origin have they been used? They can be trustworthy? Look for clear answers to these questions, and if your AI vendor is unwilling or unable to provide them, that’s a red flag. Look for alternatives.”