Exclusive insights from 1,000 senior banking executives
The Global Banking Benchmark Study is a survey of more than 1,000 senior banking executives around the world. It is part of our ongoing research program focused on digital transformation trends in financial services. To access more reports, articles and case studies, visit www.publicissapient.com/fs.
When generative AI (Gen AI) burst onto the scene in late 2022 with the launch of OpenAI’s ChatGPT, it captivated the world’s imagination. The banking industry was no exception.
AI is not new to banking. Banks have used it for years to automate insight generation, augment employee skills, eliminate repetitive tasks and more. But Gen AI is different. It creates original content, understands natural language and adapts to contextual nuances. Banks have begun to explore what Gen AI can do. They have experimented, weighed the risks and rewards, and have worked to understand the value that Gen AI can bring to the business, customers and employees.
While some banks are using Gen AI tools for everything from streamlining credit scoring to delivering personalized financial alerts, the industry has been cautious about it, largely due to regulatory constraints and fears about financial and reputational risk. Many banks are still in the process of establishing Gen AI policies and governance, and 30 percent of U.S. banks don’t allow employees to use Gen AI tools at work.
This year’s Global Banking Benchmark Study reveals that AI dominates banks’ digital transformation plans, signaling that banks’ adoption of AI is on the brink of change. The launch of Gen AI not only captured the attention of banks, but it also boosted their interest in AI and machine learning overall. This momentum around AI is kickstarting the next wave of digital transformation in banking—and Transformation Leaders are approaching Gen AI differently.
On average, banks are spending nearly one-third of their customer experience digital transformation investment on machine learning, AI and generative AI. Banks leading in digital transformation (Transformation Leaders) are the most likely to identify AI and emerging technologies as their most important business priority. At the same time, banking executives find digital transformation more challenging than they did when we conducted this survey two years ago. They are looking to digital to improve the bottom line. Budgets are tight, so executives are shifting their digital transformation priorities from “doing more” to “doing better.”
The good news? Investment in AI, machine learning and Gen AI can supercharge how banks meet their operational and customer experience goals in a spending squeeze. As our Financial Services Leader for North America David Donovan sees it, “When banks put these advanced tools in the hands of highly skilled people, it’s like having a SEAL team attack a business problem.”
Banks that make the most of Gen AI with the right foundation can connect, innovate and compete in ways they never have before, all while preserving consumer trust. That’s the power of digital transformation in the Gen AI era.
This year, only 11 percent of banks are Transformation Leaders, compared to 22 percent in 2022. That’s an 11 percent drop in just two years. In contrast, there was a 9 percent increase in Slow Starters, from 57 percent in 2022 to 66 percent today.
Banks fall into one of four digital transformation segments based on how they answer specific questions related to customer and operational leadership.
These shifts confirm that digital transformation has become more difficult for banks. Banking executives say that regulatory challenges, lack of operational agility and legacy technology are the top barriers to their organization’s digital transformation in the past 12 months. There’s also the issue of budget constraints coming from a period of retrenchment.
Given this, it’s not so surprising that executives more commonly cite lack of budget as a barrier (32 percent) than they did in 2022 (19 percent). The budget environment is more than a mere influence on banks’ digital transformation; it’s dictating it. Two years ago, executives’ top goals were improving customer experience, revenue growth from new products and services and revenue growth from existing products. The focus was on doing more.
Fast forward to today and improving customer experience, especially for current customers, remains a top goal. However, bottom-line improvements like higher margins and more efficiency have rocketed up banking executives’ list of digital transformation priorities. They say that cost reduction from improved efficiency and greater agility are among their top goals. Now, the focus is on doing better.
“Regulatory compliance is the biggest challenge we see for banks adopting Gen AI. But with the right guardrails and threat modeling, banks can take advantage of massive productivity improvements that drive downstream cost savings. Beyond that, the ability to get granular insights fast from all the customer data that banks have will be a game changer.”
— DAVID DONOVAN, Financial Services Leader, North America, Publicis Sapient
This study ranks banks’ digital transformation maturity by assessing traits and behaviors in two areas: customer leadership and operational leadership.
Create unique and beloved experiences which solve for customer needs and turn customers into advocates
LEADER Top 5 Traits:
NEW BANKING LEADERS Top 5 Traits:
TRADITIONAL BANKS
Drive significantly lower cost to serve through highly automated, highly efficient processing
How has your investment in Gen AI changed over the past year? Why is your Gen AI investment an important part of your digital transformation journey?
The emergence of generative AI couldn’t have come at a better time. Gen AI is a turbo boost for the AI-powered capabilities that banks already have and can be used to drive efficiency and cost savings while also supporting operational and customer-focused innovation. It’s the best of both worlds.
Banking executives are spending nearly one-third (29 percent) of their customer experience digital transformation investment on AI, machine learning and Gen AI. Also, AI is their biggest focus for digital transformation over the next three years. Executives most commonly cite data and AI as the top functional area for digital transformation during this period, followed by Gen AI for internal use.
Interestingly, developing existing talent is executives’ third most common functional focus for digital transformation. This emphasis signals that they are equally focused on the human side of the human-machine equation. Executives recognize the need to prepare employees to work with Gen AI. What’s more, despite regulatory worries, banks are pursuing internal and customer-facing use cases.
Focus areas for Gen AI deployment:
With investments being made and use cases implemented, the banking industry is clearly embracing AI broadly. Transformation Leaders are doubling down on AI in ways that Laggards aren’t. Leaders spend 34 percent of their customer experience digital transformation budget on AI, machine learning and Gen AI, which is 6 percent more than Laggards spend.
Mean budget allocated:
Transformation Leaders set themselves apart from Laggards in their approach to Gen AI:
Transformation Leaders aren’t just spending more on AI, machine learning and generative AI—they are spending differently. Forty-four percent prioritize AI tools for internal use, while just 25 percent of Laggards do. And 84 percent of Transformation Leaders agree that it’s better to take time to develop custom-made AI tools rather than save time by using third-party solutions, compared to just 70 percent of Laggards.
The most compelling difference between Transformation Leaders and Laggards is that they are building the foundation to get more value from AI.
Executives in these banks know that they can’t just plug in this breakthrough technology, stand back and watch the transformation happen on its own. They are building operational scaffolding to fuel their success with AI. A look at the top operational areas that Transformation Leaders want to transform over the next three years reveals how they are doing it:
Whether they are Transformation Leaders or not, most traditional banks struggle with agility. Think of agility in this instance as continually anticipating customer, market and competitive dynamics and rethinking and reinventing—fast. The reality for banks? Agility is next to impossible to have when running on legacy systems in a highly regulated environment. It’s like swimming upstream.
Even so, banking executives report that they are making good progress on being agile. Seventy-six percent agree that their bank has made significant progress embracing an agile operating model. What’s more, 35 percent, up from 20 percent in 2022, say that their bank has a fully agile operating model that supports cross-functional collaboration, decentralized structures, real-time access to data and an adaptive culture. There is variability based on bank type and size. Retail banks are more likely than commercial banks to say they are fully agile. Banks with more than $1 billion in assets and those that serve a global customer base are also more likely to see themselves as fully agile.
Despite progress in this area, banking executives still point to a lack of operational agility as a top barrier to digital transformation. The lack of operational agility is tied to regulatory challenges as the biggest barrier to banks’ digital transformation efforts over the past 12 months. Becoming more agile is also one of their top digital transformation goals, more so than it was in 2022. After all, banking executives still view an agile culture as one of the most important traits of digitally innovative banks. As banks continue to chase agility, Gen AI can help them leapfrog progress if it’s implemented in a systematic way.
Do you have a focus on using AI to improve agility? Why is this important for your bank?
The lack of operational agility is tied to regulatory challenges as the biggest barrier to banks’ digital transformation efforts over the past 12 months.
Customer experience excellence, like agility, is the ultimate goal for banks. It’s the second most common reason they pursue digital transformation. When asked about the importance of digital transformation in enhancing customer experience, 52 percent of banking executives said it’s because of changing customer expectations. This suggests that agility fuels customer experience excellence, and customer experience excellence fuels agility.
Banks’ assessment of their customer experience capabilities has improved since 2022. Banks, especially Transformation Leaders, are very confident that their institution offers a better customer experience than the competition. The majority of banking leaders see their bank as ahead of peers in key aspects of customer experience, including personalization, innovation, distribution, servicing and customer experience optimization.
The perception gap that existed in this area between the C-suite and their direct reports in 2022 has closed. Across the board, both groups now agree that they outshine their peers in customer experience.
Banking executives are leaning into the “do better” spirit of their digital transformation efforts around customer experience. Yet their focus is different today. The top three priorities for executives are personalizing customer journeys, combining customer data across systems to better understand customers and enabling seamless customer journeys with omnichannel servicing. These priorities indicate that banks are pursuing personalization, with an increased sense of urgency compared to 2022. Their focus is on keeping existing customers happy rather than winning new ones. Forty-two percent of banking executives say they are implementing personalized customer journeys, making it the leading method of improving customer experience. At the same time, they are getting their data house in order, with data and analytics as a main focus for digital transformation over the next three years to develop a richer understanding of customers and their relationships with them. That’s up two spots from 2022. Banks pioneering customer-facing Gen AI tools are quickly realizing the significant impact they have in driving a new level of personalization.
“In this era, our commitment to effectively leveraging data is not just about staying competitive; it’s about reimagining the customer experience—transforming every touchpoint into an opportunity for connection and every service into a testament of understanding needs. Our ability to harness the power of data and analytics is not just an operational advantage but a cornerstone of customer trust and delight. They guide beyond mere transactions to create meaningful, tailored interactions that resonate with each customer. This is not merely an enhancement of the customer experience; it is its complete redefinition.”
— GOLDY SAMRA, Technology Platform Director - Digital, Lloyds Banking Group
Whether the focus is on traditional AI or generative AI, banks’ success stories have one thing in common: the right data. The challenge for banks isn’t a lack of customer data. They have plenty of it. The challenge is that banks’ data is typically siloed across lines of business.
“Gen AI and AI will ultimately reinvent banking across the business in everything from processes and tooling to ways of working and skills,” explains our Financial Services Lead for International David Murphy. “All of these dimensions are critically important. But building the foundation starts with having the data and APIs to feed the models.”
Banks that have migrated to a modern, cloud-based coreless architecture have a clear advantage. Having a cloud-based data and analytics environment makes it possible to crunch through data quickly and at scale and flex capacity and computing power as needed. The challenge is not coming up with use cases and proofs of concept. It’s developing the underlying capabilities to enable all that AI can do for them.
In addition to accessing the right data, banks need to implement responsible practices to secure and protect it. When it comes to the models themselves, ethical and responsible AI practices are non-negotiable. Explainability and transparency are also paramount, as they are critical for complying with regulations, protecting customer trust and avoiding reputational risk. Zack Scott, Managing Director, Strategy, expects banks to double down on ensuring responsible use. “Banks’ data is their most precious currency,” he says. “I expect to see heavy focus on Gen AI oversight mechanisms around how language models and algorithms operate. Banks will put ethical AI implementation principles first. The controls matter as much as the outcomes do.”
“AI, machine learning and Gen AI are both the focus and the fuel of banks’ digital transformation efforts. The biggest question for executives isn’t about the potential of these technologies. It’s how best to move from experimenting with use cases in pockets of the business to implementing at scale across the enterprise. The right data is key. It’s what powers the models.”
— DAVE MURPHY, Financial Services Lead, International, Publicis Sapient
Deutsche Bank is well known as a digital business pioneer in banking. The global leader worked with us to implement its generative AI agenda, building the core AI and machine learning platform.
Thanks to investments in data and cloud, and a focus on positioning the bank to solve tomorrow’s business problems with AI, Deutsche Bank had a strong foundation to build from. We helped the bank develop an AI platform and infrastructure, use cases and proofs of concept, as well as operating models and adoption plans. Over the next several years, the plan is to scale these solutions across the business to save costs and support new revenue sources. Deutsche Bank is already using Gen AI to augment software code development, support compliance activities and serve as productivity assistants to advisors.
As Murphy explains, “It was important to get the basics right to take full advantage of Gen AI. This type of foundational approach is key to get value from both internal and customer-facing applications of Gen AI. Every decision was in the context of the bigger picture of employees, customers and culture.”
By 2026, more than 80 percent of banks will have adopted Gen AI, according to Gartner. To reach this point, banks will have to boost their investment in AI and intelligent technologies. The results of this year’s study overwhelmingly show their intention to do this. The shift has already begun for some banks.
There are complex technological, organizational and cultural changes that must happen with this shift, and the importance of bringing the workforce along with the change should not be underestimated. Even Transformation Leaders could find themselves chasing the pace of change because there’s always a new horizon to conquer.
Gen AI brings nuance, breakthrough capabilities and exciting potential to banks’ AI journey. It can help banks drive operational efficiencies and create cost savings. That’s just what’s needed in an environment where belts are tight and business cases are scrutinized. At the same time, Gen AI can help banks transform employee and customer experiences and innovate every aspect of how they do business. The goal is to go beyond implementing the technology itself to thoughtfully incorporate Gen AI into the underlying business model, existing workflows and enterprise-wide digital business transformation.
Banks that go all in on AI with responsible approaches that preserve trust and security can stand apart in the new digital era in banking. It’s already here.
“Banks never really use Gen AI in isolation. Think of it as a component within a service that links to other systems. How banks integrate Gen AI into other solutions—how it’s fed by them and feeds back to them—is the difference between experimenting with Gen AI and harnessing it with purpose to deliver value at scale.”
— ZACK SCOTT, Managing Director, Strategy, Publicis Sapient
Recognized as a 2023 Market Leader in Generative Enterprise Services by HFS Research, Publicis Sapient helps organizations prepare for AI and generative AI implementation, evaluate and prioritize use cases and execute the right strategy. Together, we can unleash AI with an ethical and sustainable strategy with the following AI solutions:
The findings in this report are based on a survey of more than 1,000 senior retail and commercial banking leaders conducted between February 19 and April 14, 2024. Every participating bank had more than $1 billion in global assets, and most had between $25 billion and $100 billion. Respondents were based in 13 countries.
Firms were scored on their digital transformation leadership in two core areas: customer experience and operational leadership. Survey questions were designed to ascertain organizations’ digital transformation maturity in relation to their peers across a number of indicators within these two areas. Each survey response was assigned an index score on a scale of 1 to 10, where 10 indicates a high level of maturity and 1 indicates a low level of maturity. These scores were then used to create the four groups outlined in this report: Transformation Leaders (11 percent), Customer Champions (13 percent), Operational Evangelists (11 percent) and Slow Starters (66 percent).
DAVID DONOVAN
Financial Services Leader, North America
david.donovan@publicissapient.com
DAVID MURPHY
Financial Services Leader, International
david.murphy@publicissapient.com
ZACK SCOTT
Managing Director, Strategy
zachary.scott@publicissapient.com
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