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What Makes Banking Products Stand Out When AI Becomes the Baseline?

00 / THE CHALLENGE

AI features become increasingly accessible in banking products and digital experiences. What sets a product apart won’t come from who has AI, but from how thoughtful it’s integrated into customer experiences and how it makes us feel.

The real challenge is not access to AI, but knowing where it creates meaningful value for customers.

01 / OUR PERSPECTIVE

Banking experiences should adapt to the moments that matter.

Our financial needs change with our lives. A trip abroad, saving for a home, starting a family, or changing jobs can each bring different priorities, questions, and anxieties.

Yet most banking apps continue to give us the same experience regardless of what we’re trying to achieve. A fixed home screen can’t serve all of that at once, so it serves none of it particularly well. It shows everyone the same overview and requires each person to dig for relevance on their own.

This is where hyper-personalization can become more than a recommendation engine. It can help banking experiences respond to what matters to a customer in a particular moment, making the product feel more relevant, rather than simply more intelligent.

What if your banking experience knew your needs in the moment, and proactively brought it to you?

02 / THE AI AUTONOMY SPECTRUM

Choosing the right level of AI autonomy

AI can operate across a spectrum, from supporting a decision to taking action on a customer’s behalf. The challenge isn’t choosing the most advanced capability, but determining which level of autonomy creates the most value in a given context.

In banking, that means balancing convenience with trust, transparency, and customer control, knowing when AI should assist, when it can act, and when it should step back.

LEVEL 0

Assistive agents

Drafts a suggestion, recommendation, or a first pass, but a person makes the final call.

Example: The “recommended for you” section on a shopping app, a streaming service, even a maps app suggesting a route.

In banking, this shows up as a spending insight or a savings suggestion, offered but never acted on without consent.

LEVEL 1

Semi-autonomous agents

Handles the routine cases on its own within clear limits, but hands anything unusual to human judgement.

Example: A spam filter quietly sorting the obvious cases but leaving anything uncertain in the inbox to be assessed.

In banking, this is fraud monitoring where everyday transactions clear automatically, and anything unusual gets flagged for a person to check.

LEVEL 2

Autonomous agents

Plans and acts toward a goal with little daily check-in with pre-programmed boundaries someone already agreed to.

Example: A robo-advisor rebalancing a portfolio on autopilot, or a thermostat holding a pre-set temperature range.

In banking, a treasury system does the same thing with cash positions, adjusting continuously within limits that were already approved.

LEVEL 3

Tool-using agents

Reaches outside its own reasoning to actually do something, calling other systems or data sources to complete the task.

Example: Asking a voice assistant for today’s weather, it does not know, so it checks.

In banking, this looks like an agent pulling a live exchange rate and completing a currency conversion on your behalf.

LEVEL 4

Multi-agent or orchestrator

Several specialized agents, each responsible for a sub-task, coordinating to get the whole task done.

Example: Ordering food through a delivery app; one system finds the restaurant, another calculates the route, another handles payment, all invisible to you as separate steps.

In banking, opening a new account works the same way: identity check, risk assessment, compliance review, running together as one process instead of three.

03 / CONCEPT: THE SPACE

A familiar foundation, with an experience that adapts to you.

We designed the experience as two layers, each serving a different purpose. The first is the home screen people already know and trust: balance, quick actions, recent activity. It provides a familiar starting point for everyday banking.

The second is an intelligent layer we call Spaces: a contextual experience that adapts to what you’re moving through right now. It uses signals from your situation to surface relevant information, actions, and support when they’re most useful.

So how does this work in practice?

We put the AI-powered banking experience concept into a real-life scenario: a trip abroad. The journey shows how Spaces can understand context, surface relevant support, and apply different levels of AI autonomy as the customer’s needs change.

Follow the journey

04 / JOURNEY

Putting contextual banking into practice

Travel is a useful test case for an adaptive banking experience. It combines anticipation, uncertainty, changing context, and financial decisions, with different levels of trust required along the way.

The journey below shows the experience can adapt to each moment, using context to offer guidance before the trip, preparing things in advance, and coordinating action in response to when something goes wrong.

Assistive agents

Anticipating intent before departure

A flight purchase signals an upcoming trip. By recognizing this transaction pattern, the system proactively prepares a ‘Travel Space’ with relevant guidance before travellers seek for help.

IMPLEMENTATION EXAMPLES

  • Budget architect
  • Contextual currency guide
  • Smart card selector

05 / REFLECTION

In a market where any feature can be copied, the relationship is what holds.

AI is quickly becoming the baseline across digital banking. As technology matures, competitive advantage shifts away from simply deploying AI and toward designing experiences that use it thoughtfully.

We don’t believe every interaction should be automated. Banking is built on trust, and trust requires knowing when to lead with intelligence and when to hold it back. Deciding what AI autonomy means in a regulated industry (where every action must be explainable, every decision defensible, and every customer protected) is where the real design challenge lies. When system intelligence and human judgment align, that is where real value emerges.

Every organization faces different questions when balancing system intelligence with customer trust. We help teams explore those questions through research, product strategy, concept development, and AI-enabled product design.

If you’re planning your next AI initiative or building AI features customers trust, let us help you shape what’s next.

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