Money20/20 Europe Exclusive Video: IBM on Gen AI in Finserv

The implementation, opportunities, and challenges of generative AI in the financial services industry are hot topics across all industries. With rapid advancements and growing interest, staying ahead of the curve in AI adoption is essential.

IBM, a global leader in technology and consulting services, have shared their insights on generative AI with FinTech Magazine, discussing strategic priorities, regulatory compliance and talent acquisition challenges facing the industry 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.

IBM's recent survey involves 2,500 CEOs, with over 300 from the banking sector and has some particularly noteworthy findings.

Shanker Ramamurthy comments: "The survey has had some pretty interesting findings. 60% of the CEOs talked about generative AI as a strategic priority for them at an enterprise level."

He adds: "The reason this statistic is particularly interesting is that we recently released another study showing that 80% of banks are implementing generative AI on an enterprise scale, while another 80% are only conducting pilots and proof-of-concept projects.

"From our most recent survey, we found that at least 60% of banks plan to address generative AI on an enterprise scale through the rest of this year and into 2025. This is significant and aligns closely with what we and IBMC see as the potential for generative AI."

Persistent Challenges with Tech Talent Acquisition

"About 50% of the CEOs talked about talent and their inability to attract the right technology talent in particular to address the opportunities coming out of generative AI," says Ramamurthy. This highlights a critical challenge in the sector: finding and retaining skilled professionals who can drive AI initiatives forward.

"In fact, when we discuss generative AI with our clients, we focus not only on the technological aspects but also on talent acquisition. It's crucial to ensure the entire enterprise can leverage the potential of generative AI. For CEOs, attracting and retaining the right talent to harness these opportunities is a significant challenge."

In the survey, over 75% of CEOs emphasised the importance of ecosystems, partnerships, and collaboration in achieving successful outcomes with generative AI.

Ramamurthy believes strongly in the importance of partnerships and ecosystems, which are key areas of focus for IBM: "Our CEO and chairman have been all about partnership and ecosystems, and it's important to bring that dimension to the fore as CEOs try 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 firm on the planet, no matter what business they're in and no matter who their customers or clients are, improving customer experience, hyper-personalised, hyper contextual, instant relevant recommendations, instant decisions, instant fulfilment across any available channel," says Duigenan.

Additionally, applying generative AI to automate manual back-office processes and integrate multiple backend systems can massively enhance employee productivity,

"Employee productivity is being significantly enhanced through digital labour, 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 conversationally orchestrated and integrated across multiple backend systems," says John.

"Modernising application development and IT operations, particularly with old codebases, is crucial. Creating developer productivity improvements of at least 60% is huge for any firm," concludes John

Regulatory Impact on AI: EU AI Act 

"The EU has moved swiftly," says John Duigenan, "And it's important that they did because the need for transparent, trusted AI used by enterprises is vast."

He continues, "The EU AI Act introduces a risk classification framework that bans certain AI uses, such as facial recognition for commercial purposes due to its potential to discriminate. It also includes a comprehensive assessment framework for how firms measure their AI, and non-compliance can result in penalties up to 7% of global turnover or 35 million euros."

"At IBM, we've been relentlessly working on building AI within the framework of trust and regulation. We foster an open community around AI development, ensuring that our clients can trust the AI solutions they implement."

A 12-month forecast 

Shanker Ramamurthy believes that clients are entering a multi-model world where the rate and pace of change will be extraordinary.

"Balancing business and technology will be crucial, requiring a flexible and adaptable approach. While business strategy will continue to guide our technological efforts, the capabilities of technology will increasingly shape the possibilities for business models. Over the next three years, we anticipate massive changes in banking business models. Leveraging the power of hybrid cloud AI and generative AI, combined with ecosystems and platforms, will be key to unlocking potential and converting it into tangible outcomes for our clients."

John Duigenan says: "To build on that, we have two sides of the coin. On one hand, we'll see valuable insights and key performance indicators (KPIs) delivered by enterprise AI platforms. On the other hand, there will be challenging moments where the AI may not perform as expected.

"Therefore, anyone considering an AI solution should ask their AI provider critical questions: How were the models created? What data sources were used? Can they be trusted? Seek clear answers to these questions, and if your AI provider is unwilling or unable to provide them, it's a red flag. Look for alternatives."

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