The Age of Hyper-Personalised Banking: Why the Next Decade Belongs to the Banks That Dare

As banking start-ups quickly transition through growth-stage and begin entering the mainstream, what challenges does this present to “Big Banks”, where trust is less dependable as the reason ‘why’, and increasingly it is friction-free, hyper-personalised banking that is the main competitive landscape.

In an age where customers expect personalised experiences in every aspect of their lives, from streaming to shopping, banks have a unique opportunity to redefine their role. No longer just custodians of money, the winners will be those who can become partners in helping customers achieve life goals – but only if they embrace the next wave of AI: autonomous, context-aware, and agentic.

An era of banking innovation

Across Europe, the banking sector is entering a new phase—one shaped by the evolution of data capabilities, AI tools, and increasingly refined approaches to digital customer engagement. As fintech maintain their share gains, and mature their propositions, more customers are more used to increasingly frictionless, immediate, tailored banking solutions.

Setting up accounts for my kids – with my fintech it is done in seconds.

Making FX transfers whilst travelling on business – available anytime, anywhere.

As new banks push the envelope of customer expectation, I find it valuable to reflect on how these developments shift the pressure on established banks, and open the door to new opportunities to impact the everyday financial lives of their customers.

And it triggers, at its heart, a more profound question which goes to the core of the purpose of banking: What should the role of a retail bank be: To manage money, or to help build wealth?

The difference is subtle but significant. Money, in day-to-day terms, is about cash, payments, short-term balances and liquidity. It is the core of what banks do, and why they exist. Big Banks do this particularly well.

But ‘Wealth’ implies something broader and more enduring – the ability to accumulate financial stability, absorb life’s shocks, and take control of one’s goals and choices. Banking today is transactional. But every transaction, in retail banking at least, is in pursuit of something else – it is enabling a life moment. And strung together, it is these micro moments that determine whether someone spends, saves, invests, or borrows… and over time this pattern determines whether they pay off their loan early, buy their first house, or get the retirement of their dreams.

Across Europe—particularly in markets such as the Netherlands, UK, Germany, and the Nordics—we’re seeing challenger banks operating in this in-between space. Firms like Bunk, Revolut, and more recently BUUT (developed in collaboration with ABN AMRO) are experimenting with propositions that aim to offer more than functional tools. They support planning, education, feedback, and behavioural guidance – positioning themselves less as processors of transactions and more as quiet enablers of financial wellbeing.

If we recognise that many customers struggle with managing their money, and that we now have the tools to help them better than ever before, then this becomes an interesting area for thoughtful exploration. Not in critique, but in curiosity: what role can banks play going beyond enabling transactions in this transformational technology time?

The Youth Banking Lens: Signals From the Next Generation

The BUUT initiative in the Netherlands offers an insightful case study into what modern financial services could become. Designed specifically for young people, this neo-bank addresses key pain points identified in research by the Dutch National Institute for Family Finance Information. Their findings show that many young people have limited visibility into their spending, lack a structured understanding of budgeting, and often only begin to consider financial consequences after making a mistake.

BUUT has aimed to intervene earlier, providing features like real-time balance updates, spending insights, financial nudges, and even co-management tools that allow parents to support without intruding. It recognises different behavioural personas – from planners to spenders to chaos-prone – and creates a user experience that caters to each, while embedding light-touch education throughout.

The key here is proactivity. Rather than reacting to financial stress after the fact, BUUT’s proposition anticipates behavioural patterns and nudges users gently toward better decisions. And while this innovation is geared toward youth, it holds implications far beyond its target audience.

The Adult Parallel: Same Challenges, Greater Stakes

It would be a mistake to assume that these youth-specific features solve problems unique to young people. In fact, the gaps that BUUT seeks to close—lack of financial overview, disconnection between spending and consequence, and low levels of functional literacy—are present at scale among adults.

Consider that across the EU, over 40% of adults report low confidence in understanding interest, credit products, or investment risk. Studies from the OECD and NFEC highlight widespread deficiencies in core financial literacy, with millions struggling to manage subscriptions, track irregular income, or consolidate views across multiple bank accounts.

Tools like Buy Now Pay Later have amplified this problem – offering convenience at the expense of transparency. When repayments are distributed over weeks or months, and split across apps, banks, and retailers, it becomes increasingly difficult for individuals to track what’s truly theirs to spend.

In that context, the solutions aimed at helping youth gain a structured financial view are equally vital for adults. A truly useful bank, then, is one that helps all customers – regardless of age or financial position – construct a coherent, real-time, actionable picture of their money.

The Promise of Hyper-Personalised Banking

The evolution of technology – especially in data modelling, behavioural analytics, and AI – has unlocked an unprecedented ability to personalise the banking experience. From subtle nudges to contextual offers, banks are increasingly able to tailor services based not just on static profiles, but on real-time behavioural signals.

Imagine a customer who typically gets paid on the 25th of each month. Their bank knows this pattern. If a recurring payment is scheduled for the 23rd, the bank could provide a gentle notification with an option to reschedule, avoiding overdraft fees. Or it could anticipate end-of-month financial pressure and offer relevant credit or budgeting tools. These are simple, intuitive interventions – but ones that only become possible when data is structured, timely, and intelligently actioned.

Hyper-personalisation at its best is not just about product pushing. It’s about relevance. It can:

• Be as simple as modifying the hierarchy of content on the app to better reflect my user behaviour
• Subtly warning on spending anomalies or trends in activity
• Suggest micro-saving behaviours – Integrate educational tips in moments of decision-making
• Propose context-aware financial products at life milestones

In this way, personalisation isn’t just messaging – it can be a quiet mechanism for building trust and promoting better financial outcomes. Done right, it’s a win-win.

5. Institutional Realities and Constraints

Yet, for many incumbent banks, these promises run into hard realities. Banking is – of course – a serious and highly regulated business.  And our experience with banks talks to many of the common structural and cultural hurdles:

• Data Structure & Quality Issues: Transactional data is messy and inconsistent. Merchant names are often cryptic or unstructured (“STRIPE*SPOTIFY”). Categorisation engines misclassify (e.g. AH TO GO = groceries or travel?). And splitting out joint accounts or shared payments is not a trivial exercise. It means in reality it is difficult to reliably build user-level financial narratives (e.g., what you spend on food, how often, and where you overspend).
• Legacy Tech + Fragmented Data Systems: Many banks’ core systems are built around product silos (current account, savings, credit), not customer journeys or unified views. Transaction data sits in different systems or is stored in formats that don’t easily support modern analytics (e.g., real-time stream processing or ML). Even if a bank wants to deliver insights, it may lack the tech infrastructure to scale this across millions of customers in real-time.
• Risk Aversion and Compliance Caution: Banks fear being seen as providing “financial advice” under regulatory definitions (which brings fiduciary responsibility). Any nudges that relate to saving/spending may trigger compliance reviews, especially in the EU under MiFID II or in the US under SEC/FINRA rules. The impact is it’s safer to show raw data or generic messages than to say: “You’re overspending on takeout – cut back.”
• Fear of Misfire and Erosion of Trust: Misguided or poorly timed advice can undermine trust, e.g., telling someone to save more when they just lost a job, or flagging a “problem” when it was a one-off or necessary expense (e.g., medical bills). Banks are right to hesitate to “get personal” unless they’re sure. And as such, many default to generic advice to avoid backlash or embarrassment.
• Monetisation Misalignment: The truth in plain sight is banks don’t always profit from helping you save. Many still generate revenue from overdrafts, BNPL, credit cards etc. and encouraging savings over spending may be good for the user but not for quarterly earnings. Unless the bank has a fee-for-service model or a “customer lifetime value” play, there’s limited financial incentive to nudge better behaviour.
• Product-Centric vs. Customer-Centric Culture: Most banks still operate as product delivery platforms (sell account, sell loan, sell insurance). Few have truly shifted to a platform mindset where value is generated by supporting broader life goals (financial wellness, not just transactions). Personalised, insight-led engagement doesn’t get prioritised because it’s not seen as a core product or revenue engine.
• UX and Delivery Constraints: Delivering financial insights requires more than good data—it needs contextual, bite-sized, emotionally resonant UX. Few banking apps have cracked the tone, timing, and interface to make advice feel helpful rather than invasive. As a result, insights either get buried in dashboards, come off as cold or robotic, or overwhelm the user – if they even appear in the first place.

Whilst these constraints are real, they are not insurmountable.

Mapping Risk, Reward, and Feasibility

One useful tool is to map use cases not just by value, but by feasibility and risk. In our experience, banks benefit from creating a matrix across three axes:

1. Customer value potential: How meaningful is this to a customer’s financial wellbeing?
2. Business alignment: Does this contribute to core KPIs or strategic goals?
3. Operational and compliance feasibility: Can it be delivered within existing constraints?

By plotting ideas across this grid, a bank can begin to prioritise use cases that offer quick wins (e.g., subscription alerts or cash flow forecasting) as well as identify longer-term transformation areas (e.g., embedded financial coaching).

Interestingly, this is where challenger banks may currently have an advantage. Their smaller scale, modern infrastructure, and more flexible compliance models allow them to move faster. But larger banks still hold something even more valuable: trust, reach, and institutional memory.

A Process, Not a Challenge: What Leaders Might Do

Rather than frame this as a challenge to be met with urgency, it is more constructive to think in terms of long-term internal capability building. For leaders in traditional banks, the key question is not whether to build personalised experiences, but how to do so responsibly, incrementally, and sustainably.

This means moving away from isolated pilots or channel-based campaigns, and instead, establishing a durable internal model that can continuously evolve—anchored in strategy, governed by the right metrics, and enabled by the right technology, people and processes.

At our firm, we use a Target Setup Framework to guide how organisations can structure for scalable, AI-enabled personalisation. It sets out the key components of a modern personalisation engine, aligned to both business outcomes and customer value.

The Personalisation Strategy Framework

At the centre of this framework is a clearly articulated personalisation strategy—defining the vision, operating model, roadmap, and business case. This strategy then translates into five interdependent building blocks:

• D&A Foundation
  Establishing robust data collection, privacy and governance frameworks, identity resolution, and predictive modelling to enable meaningful, real-time insights.
• NBA (Next Best Action) Engine
  Orchestrating signals and rules to dynamically serve the most relevant next action – whether advice, product offer, or educational content – across channels.
• AI Campaign Creation & Execution Engine
  Designing and delivering tailored experiences across customer segments, ensuring creative relevance and timing aligned with the NBA layer.
• Value Realisation
  Embedding continuous measurement of ROI and customer impact to feed learnings back into the system, strengthening the business case over time.
• Feedback Loop
  A cross-cutting mechanism that connects insight to action and back again, supporting the iteration of journeys and messages based on observed impact.

Supporting this engine are two critical enablers:

• MarTech and AdTech Infrastructure
  Technology capabilities—such as CDPs and real-time orchestration platforms—that enable activation across channels and use cases.
• Organisational Enablement and Execution
  Change management, cross-functional governance, and operational model design that ensures insights are not just generated but acted on consistently and compliantly.

What Banks Should Do Next

Bringing this to life requires a step-by-step approach grounded in the real constraints of the institution. Our recommended actions include:

• Create a cross-functional personalisation team that includes data, marketing, product, and compliance
• Audit existing infrastructure and capabilities against each layer of the target setup framework
• Map and prioritise use cases across customer value, business alignment, and operational feasibility
• Design modular MVPs that allow for safe experimentation, with clear measurement from the start
• Invest in test-and-learn culture by empowering teams with insights and the autonomy to act on them
• Embed feedback loops that ensure learning is captured, shared, and built into the roadmap
• Align KPIs and incentives to long-term customer outcomes, not just short-term revenue gains

While this work is complex, it is also increasingly necessary. Banks don’t need to solve for everything at once. But they do need to be intentional – designing a model that builds toward personalisation maturity, not just campaign delivery.

The Rise of Agentic Framing

This evolution sits now within a broader technological shift. As AI capabilities mature, we’re moving into the era of goal-oriented, autonomous agents. These agentic systems don’t just respond to user behaviour – they act proactively, driven by predefined goals, context, and feedback loops.

In highly regulated sectors, the design of such systems must prioritise explainability and emotional intelligence. For example, agentic systems must distinguish between transient financial shocks and persistent overspending patterns, ensuring interventions are nuanced and well-timed.

For example, if nudges sent on Friday evenings yield low engagement, but Monday morning prompts drive action, the agent can recalibrate its outreach strategy autonomously. The value loop is closed not by human insight, but by machine learning embedded in the system itself.

Increasingly, these building blocks resemble the layered architecture of agentic systems.

This is the promise of agentic technology in banking: augmenting human decision-making with intelligence that is quiet, contextual, and confidently proactive.

Examples of Banking Agents

Mortgage Agent – Proactively monitors interest rate changes and customer affordability, suggesting refinance options at the optimal time.
Investment Agent – Continuously reviews portfolio performance, risk exposure, and market movements, recommending timely rebalancing actions.
Retail Banking Agent – Tracks day-to-day spending patterns, identifies anomalies, and initiates micro-savings or budget adjustments.

These specialised agents would feed into a central decision-making layer – a ‘Judge’ – that prioritises across them based on customer goals, compliance rules, and overall value impact.

Imagine a digital co-pilot that sees your income drop temporarily due to health leave, and adjusts budget categories to prioritise essentials while preserving savings. These aren’t static rules – they are intelligent, adaptive actions taken in real time, grounded in an understanding of what matters most to the user.

Looking ahead, admittedly a long way ahead, this offers the most sophisticated banks the potential to evolve from service providers into orchestration platforms – where intelligent agents coordinate across domains (e.g., income, health, calendar, family needs) to align financial behaviour with life goals. But first things first, and one step in front of another…

Redefining Relevance

The most compelling reason to explore this space is not technology, nor competition, but relevance. In a market where consumers are used to Spotify recommending a playlist and Amazon anticipating a repeat purchase, banks have an opportunity to quietly reassert their role – not just as custodians of money, but as enablers of financial confidence.

The concept of wealth, when viewed through this lens, becomes less about accumulation and more about alignment – of habits, tools, understanding, and decisions. A personalised banking experience can help customers make better choices. But even more importantly, it can help them feel in control.

And that, perhaps, is the future of banking. Not just a product catalogue or a payment engine, but a trusted partner in navigating the economic rhythms of life—whatever form they take.