And 2025 looks set to be just as much of a financial firecracker. Already this year, rising bond yields may have the effect of pushing interest rates back in the wrong direction – threatening to derail the UK government’s spending plans. Santander, meanwhile, has floated the idea of quitting the UK.
And then there is the Donald Trump factor. As the mercurial US entrepreneur re-enters the White House for his second term as President, the smart money is on banking deregulation – quickly followed by a new wave of consolidation in the sector.
But what about the technological tectonic plates that underpin the sector? How will digital and AI innovation impact the frontline relationship between consumers and their banks? Here are my key predictions for high street banks, neobanks and fintech startups.
The digital experience gap between legacy banks and neobanks will narrow
In 2025, incumbents will continue to close the gap with the neobanks in terms of the quality of digital experiences and features they offer. In part this is because they have learned the importance of doing the simple yet essential things well: ensuring the customer’s journey is smooth, and that their apps can handle peak demand without compromising speed or user experience. In addition, however, they have the muscle to take the fight to their nascent rivals. With deeper pockets and the ability to provide a wider suite of banking products and services, they are well-placed to challenge neobanks for younger demographics.
This narrowing digital experience gap is a problem for the neobanks, which have sought to grow market share by positioning themselves to experimental early adopters as digitally native and therefore cooler than their legacy rivals. And it’s exacerbated by the fact that most fintech early adopters have now been snapped up by Monzo, Revolut, Starling and co. For emerging generations of banking customers the neobanks are arguably no newer or cooler than the incumbents.
In 2025, the neobanks need to widen the experience gap with incumbents by going all in on innovative personalisation in order to help customers meet their unique banking needs and goals. In a recent survey we conducted, 66% of respondents said they would consider switching to a provider that offered more innovative app features. In practice this means neobanks leveraging AI and user-centric design, to redefine what it means to deliver value and support in a digital-first world. From offering hyper-relevant and personalised financial advice, to providing virtual assistants that simplify complex decisions, personalisation is moving from a nice-to-have, to an essential part of modern banking.
2. To capitalise on AI, legacy banks will need to exploit their customer interaction and transaction flow data
When it comes to harnessing the power of AI and LLMs, the vast amount of data flowing through incumbent banks gives them a head start over neobanks. This pool of data is a critical point of differentiation and a potential source of value they will be looking to exploit in 2025.But to do so they will need to increase their investment in next-gen IT.
Historically, banks haven’t made the most of their data. With data points stored in different locations and aligned to different products, they haven’t had the unified view of their customers necessary to exploit AI’s strengths in terms of predictive modelling, and helping to boost productivity and innovate new customer experiences. It doesn't matter how smart AI is, if it hasn't got access to all the data it needs, it can’t fulfil its game-changing potential. Citi and JP Morgan are leaders in terms of updating data and infrastructure, but most major legacy banks are aware that increased IT investment is needed in order to bring data and AI closer together within their organisations, and unlock AI’s full potential.
3. Predicting customer transitions will be the new market share battleground
This year, the ability to proactively identify when a customer’s banking needs are changing will be a key battleground.Currently, data silos within banks mean these transitions become real friction points for customers, which may encourage them to look elsewhere.
Banks looking to get ahead will need to combine user data, situational insights and AI’s predictive capabilities to develop proactive,context-aware guidance around changing customer needs. For example, an effective AI-powered bank will be able to predict when a small business banking customer is ready to transition to a commercial banking customer, or when a young person wants more products and services than a junior account allows. This predictive capability equips banks to offer a highly proactive and personalised approach to their customers. For the small business banking customer, this could include tailored advice on the best way to scale, signposting to appropriate business loans and grants, as well as advice on the best bank account options. For the young person, a proactive approach to their changing needs could include a personalised quiz helping to work out their individual money management style, guidance on budgeting, as well as advice on the best account features to opt for.
4. In 2025 embracing AI will be about closing the cultural gap not the tech gap
Going into 2025, the maturing capabilities of AI tools means banks will find it easier to build AI products and services.Already, sophisticated tools like ChatGPT and Microsoft Copilot are accessible and easy to adopt. However, the momentous task of melding legacy culture with AI’s potential, remains.
This challenge manifests in various ways. Firstly, how do you get staff to embrace new tech when it is expected to result in the loss of 200,000 jobs in the next 3-5 years? Persuading employees that AI can augment their roles and improve their working experience is key. The general view is that, as AI advances in the workplace, the role of the human workforce will naturally shift to a higher level, with more bandwidth for the relationship-based, customer-facing roles where human emotional intelligence is vital. If this is the case, banks need to prepare the way with targeted training.
Secondly, how do you ensure staff know how to use the tech safely and effectively? Worried about unforeseen pitfalls, some banks end up being risk averse - restricting staff access to GenAI tools because they haven’t been trained and don’t know how to use them. Banks are right to recognise that AI misuse by employees could create problems everywhere from regulatory compliance to brand trust to cybersecurity. But they don’t want to become so cautious they fail to seize the new tech’s potential. Banks need to create an AI innovation culture that has the necessary compliance and security guardrails but which also allows staff to experiment with these new tools so they can deploy them to the best of their ability.