Unlock smarter banking with the power of personalisation

A key insight from our survey is that 66 percent of users are open to switching to a provider that offers tailored tools and insights. The connection between integrated services and personalisation is clear. Banks that provide seamless, intuitive experiences will win user trust.

So, how can banks rise to the challenge? By leveraging technology, particularly AI, to create solutions that simplify financial management and align with individual goals.

For more insights, explore our seven key takeaways from the UK Banking Survey.

The shift toward personalisation is reshaping how customers engage with banks. The one-size-fits-all approach no longer works, users expect experiences that adapt to their unique needs. With AI and user-centric design, banks can redefine value in a digital-first world.

From hyper-personalised financial advice to AI-driven virtual assistants, personalisation is no longer a luxury. It’s an expectation. Here’s how it can take shape in practice:

1. Context-aware financial guidance

By leveraging user data and behavioral insights, banks can offer real-time, context-aware financial advice. Understanding spending patterns, seasonal fluctuations, and personal goals allows for tailored recommendations that drive better financial decisions.

For example, a banking app detecting a winter spike in energy costs might suggest reallocating discretionary spending, recommend lower-cost energy providers, and even propose a savings plan to prepare for next year’s expenses. This shifts banking apps from passive tools to proactive financial partners, helping users stay in control.

2. AI-powered financial assistants

AI-powered financial assistants are transforming the way customers interact with their banks, making financial management more intuitive and accessible. These AI agent tools combine advanced analytics and natural language processing to deliver tailored recommendations, service suggestions, and real-time insights.

A user might ask their banking app, “What’s the best way to save for my child’s education?” The AI assistant can analyse their financial profile, suggest tailored savings or investment plans, and estimate the necessary monthly contributions. It could also highlight relevant services, such as insurance or financial safety nets.

By acting as intelligent financial agents, these systems can go beyond reactive support, proactively identifying risks, opportunities, and smarter ways to manage money. For customers, this removes financial guesswork. For banks, it enhances customer engagement and opens opportunities for cross-selling, positioning them as trusted financial advisors.

AI-driven personalisation is already deeply embedded in our daily lives. Platforms like Netflix, Spotify, and Google Maps use advanced algorithms to curate recommendations and anticipate user needs. Netflix predicts what you want to watch based on past behaviour, Spotify builds personalised playlists, and Google Maps suggests routes based on your routines. These services demonstrate how AI can transform raw data into valuable, personalised experiences.

Banks, however, have been slow to adopt similar strategies. Despite having access to extensive customer data, most financial institutions still operate with legacy systems designed for transactions rather than dynamic, personalised engagement. Regulatory caution, risk aversion, and outdated infrastructure further limit their ability to implement AI-driven personalisation at scale.

However, the demand is clear. Banks have the ability to see months in advance when a customer might run out of money, but most do little proactively to prevent financial distress. Meanwhile, retailers and media companies have built business models around AI-powered personalisation, offering tailored discounts, promotions, and recommendations. If banks were to apply similar approaches, helping customers set financial goals, adjust spending, and plan for the future, they could fundamentally reshape the customer experience.

While most traditional banks have been slow to adopt AI-driven personalisation, fintech companies and digital-first players are setting the pace. A growing number of financial apps are using AI to offer intelligent, personalised services that go beyond basic account management. Here are three standout examples of AI in banking today:

1. Cleo – The conversational financial assistant

Cleo is a chatbot-driven AI financial assistant that helps users manage their money through an engaging conversational interface. From tracking spending and setting savings goals to offering personalised financial advice, Cleo makes money management more accessible, particularly for younger users.

2. Origin – A unified AI-powered financial hub

Origin consolidates tax filing, estate planning, budgeting, and investment management into a single platform. Its AI-powered assistant acts as a holistic financial advisor, offering tailored insights for retirement planning, emergency savings, and investments. With its “Couples” feature, Origin also helps partners manage joint finances transparently, reducing money-related stress.

3. Erica – Bank of America's virtual financial assistant

Erica leverages AI and natural language processing to provide personalised financial insights and streamline customer support. While not based on generative AI, Erica uses machine learning to analyse user behaviour and proactively assist with budgeting, cash flow management, and account security.

AI-driven personalisation is no longer optional. It is the key to staying competitive in an evolving financial landscape. Banks that leverage AI to automate customer interactions, predict user needs, and create seamless, tailored experiences will build trust, loyalty, and long-term growth.

The financial industry has reached a turning point. Customers expect more, and the technology to deliver it is already here. The question is not if banks should adopt AI-powered personalisation, but how they can integrate it in ways that truly benefit their customers and business.

At Futurice, we help bridge the gap between innovation and execution. By combining creative strategy and technical expertise, we turn AI-driven personalisation from vision to reality. Together, we can explore how AI-driven personalisation can create more meaningful financial experiences for both banks and their customers.