Tech Explained: The AI-ready bank: building smarter customer journeys in Simple Terms

AI is changing the way we search for information, discover different perspectives and ultimately make decisions. While these behaviours are not universal and vary by generation, many consumers are tapping less text into search boxes and instead engaging with generative AI chatbots or conversational AI like Siri and Alexa, looking for clearer, more plain-English responses.

This shift could radically alter customer journeys in the financial sector, with AI leading to more self-directed and personalised interactions. Banks, building societies, consumer lenders and providers of consumer payments and wallets are well aware they need to respond to this shift. In fact, when Raconteur and Capco recently surveyed 100 financial services leaders, 62% said they were planning major customer journey redesigns within the next 12 months, rising to 90% within five years.

Payments firms and wallet providers are moving fastest on redesigns, with over three-quarters (76%) expecting to make major customer journey redesigns within the next year. They’re also ahead of the pack when it comes to experimenting with fully self-directed journeys (44%), which reflects their digitally-led nature and relatively narrow and transactional customer proposition.

“The payments or wallet proposition is infinitely simpler and a bit more transactional than retail banking,” says Sam Riordan, executive director, UK banking and payments at Capco. “If you think about those interactions and touchpoints – paying for something online, paying for something in store, app-to-app experiences – they’re typically short, sharp, emotionless journeys. But if you think about the products that a bank offers – mortgages, for example – they’re deeply emotive, quite complex and therefore inherently more challenging in terms of embracing emerging technologies.”

Although there are clearly profound differences in how fintechs and traditional banks operate, and the constraints they face, most respondents highlighted omnichannel experiences (83%) and personalised financial guidance (70%) as the key drivers of their approach. Emerging innovations like fully self-directed journeys (38%) and voice-led interfaces (35%) are also steadily gaining traction, hinting at where firms may focus next.

“Conversational banking and voice-led interfaces are the next frontiers,” says Riordan. “If you start to look at the way we currently engage with AI interfaces, with technologies like Siri, Alexa, Google Home and our smart watches as quick intuitive, ways to seek out information, it’s clear that consumer behaviour is starting to shift towards prioritising short, sharp interactions to solve basic queries through voice or instant messaging.”

As these new interfaces reshape customer expectations, organisations face the challenge of responding in ways that are both seamless and intelligent. This is where AI becomes a key enabler, helping businesses interpret vast amounts of data and deliver personalised, real-time interactions. 

Chris Probert, partner and global head of data, analytics and AI at Capco, explains that well-implemented technologies from the past, such as semantic layers – which convert complex, raw data into business-friendly terms – can play a key role in making AI more effective in customer journeys. “The one thing that enables agents and AI to work together across these journeys is understanding, and that comes from a shared language,” he says.

Trusted innovation

While ambition is high when it comes to redesigning customer journeys, less than one in ten leaders feel very confident in their ability to build long-term trust through AI. Furthermore, just 5% are very confident about aligning with regulatory expectations.

It is vital leaders take steps to address these issues. “It’s about building trust in the use cases – understanding what AI can do, what it can’t do and making sure the right frameworks are in place,” says Riordan. “Because what you’d hate to see is huge investment in AI tooling to help customers that isn’t adopted because customers don’t trust it.” 

Leaders across all financial firms also see a stark generational gap emerging around AI, with 81% believing that generation z customers expect very high transparency, versus just 22% of older customers. In addition, respondents from firms with physical branches perceive customers as more cautious and preferring human interaction.

While almost all leaders believe that customers expect transparency around AI, those at retail banks believe they face the highest bar, with 75% reporting that consumers expect very high disclosure around how AI is used. Given the deeply personal and highly sensitive nature of retail banking relationships, this perhaps isn’t surprising. But it also indicates that retail banks, which typically form long-lasting relationships with their customers, could have more to lose if they deploy AI in ways that alienate people.

“The single biggest consideration is not misleading people,” says Riordan. “If someone starts a conversation with a customer service representative and they later realise it was AI – some customers won’t care, but some will and that can really damage trust.” 

Despite these challenges, large retail banks have one significant advantage over newer wallet and payment firms: decades of rich customer data. However, it’s an opportunity that many banks are not leveraging properly today. “If you look at some of the large retail banks, the percentage of payments that they process is astronomical, so they have a lot of data. They’re just not maximising it,” says Probert.

When it comes to the barriers that hold back AI projects, data fragmentation, legacy technology, compliance and difficulty integrating AI were all highlighted by survey respondents. Leadership buy-in and employee resistance were less commonly flagged, suggesting that implementation issues lie more on the technical side than the cultural.

Human and AI interactions

Almost all respondents (99%) also expect human advisors to remain integral to customer journeys – particularly for complex financial planning, oversight of AI-generated advice and providing emotional support and empathy in high-stress moments. However, when it comes to striking the right balance between human and AI interactions, Probert doesn’t believe there is a single optimal pathway.

“The organisation that gets it right is the one that can help customers between AI and human interaction in a way that doesn’t feel awkward or clunky,” he says. “Some journeys will be extremely AI-heavy. But if you’re guiding customers through a bereavement journey, which is very emotive, you will likely want that to be more human-led.”

In the near term, firms are likely to realise the most value from connecting customers to the right expertise faster. “I don’t think anyone is looking to AI to actually give someone advice at the moment,” says Probert. “Firms aren’t quite at a stage where that feature is ready to be launched. It’s more about introducing AI to help advisors get the right advice to the right people quicker.” 

Many firms are currently focusing more on AI’s impact on internal cost-efficiency and productivity than on fundamental transformations of customer journeys. “There’s much higher risk with the latter. There can be biased decision-making, there’s ethics issues – pieces that are really important to get right,” says Probert. “So firms are mainly playing around with those internal use cases right now and dipping their feet into external ones.”

One of the key characteristics of firms that manage to enhance customer journeys with AI could be their ability to avoid the kind of siloed approaches that lead to competing internal solutions. “At the back-end, they need to look at the things which should only be done once – data cleanups, data provisions, data controls and so on,” says Probert. “If they can’t build uniform patterns for those, which are re-deployable at speed across the whole organisation, agnostic of its hierarchy, that is what will stop them from progressing.”

Rather than pushing customers toward a particular channel simply for efficiency’s sake, firms that focus more on how AI can help to orchestrate customer journeys across them are also more likely to see strong results. As Riordan puts it: “Customers want you to remember them across the different digital, in-person and remote channels they engage with you on, and they want that experience to feel personalised and seamless.”

Firms that tackle AI challenges in the short term will gain a temporary competitive edge, but as Capco and Raconteur’s research shows, the true winners will be those who use AI to enhance customer experiences in a genuinely transformative manner. That means creating meaningful interactions and building trust in ways that align with their brand and propositional strengths – not simply adopting AI for its own sake.

For more information please visit capco.com

AI is changing the way we search for information, discover different perspectives and ultimately make decisions. While these behaviours are not universal and vary by generation, many consumers are tapping less text into search boxes and instead engaging with generative AI chatbots or conversational AI like Siri and Alexa, looking for clearer, more plain-English responses.

This shift could radically alter customer journeys in the financial sector, with AI leading to more self-directed and personalised interactions. Banks, building societies, consumer lenders and providers of consumer payments and wallets are well aware they need to respond to this shift. In fact, when Raconteur and Capco recently surveyed 100 financial services leaders, 62% said they were planning major customer journey redesigns within the next 12 months, rising to 90% within five years.

Payments firms and wallet providers are moving fastest on redesigns, with over three-quarters (76%) expecting to make major customer journey redesigns within the next year. They’re also ahead of the pack when it comes to experimenting with fully self-directed journeys (44%), which reflects their digitally-led nature and relatively narrow and transactional customer proposition.