The Fintech Retention Crisis: When Better Is No Longer Enough
For much of the past decade, consumer fintech followed a relatively straightforward formula. Take a financial product that was complicated, expensive, or unpleasant. Make it digital. Remove friction. Improve the user interface. Add transparency. Make onboarding faster. Put everything into an app. This formula created an entire generation of successful fintech companies.
But what happens when almost everyone can build a good digital product? And what happens when artificial intelligence dramatically reduces the cost and time required to build the next one?
That is where the next phase of consumer fintech becomes much more interesting. This is what we’ll discuss today.
In his recent essay, “The Coming Product Retention Crisis,” investor Andrew Chen makes an intriguing argument about artificial intelligence and consumer technology. AI has been remarkably successful in professional environments because work contains enormous amounts of repetitive activity. Consumer products operate differently. They compete for human attention, and humans continuously seek novelty.
As Chen puts it, consumer technology increasingly operates in an environment of “adversarial creativity”: once something becomes familiar, competitors imitate it, consumers become accustomed to it and attention moves somewhere else.
For fintech companies, this has consequences that go well beyond adding an AI assistant to a banking app. The AI transformation of consumer finance may ultimately change what we mean by a financial product.
AI makes products easier to build. It does not make attention easier to win.
Generative AI is already compressing product development cycles. Research, coding, UX prototyping, content production, customer segmentation, testing and marketing can increasingly be accelerated with AI. Small teams can produce what previously required significantly larger product and marketing organisations.
This sounds like an obvious advantage, and it possibly is.
But there is another side to the equation. If your company can build faster, so can everyone else.
The result is an enormous increase in the supply of products, features, campaigns and content competing for roughly the same finite amount of human attention.
Chen describes a future in which applications themselves begin behaving more like internet content. Products can be created, launched, shared, copied and replaced at much greater speed. The traditional assumption that companies build a product and then optimise retention around it becomes less reliable.
Consumer fintech will not be immune. The barriers to building a beautiful savings interface, investment dashboard, budgeting tool or AI financial coach are falling rapidly.
The difficult part will increasingly be convincing somebody to care.
Fintechs: from product economy to attention economy
This situation represents an important change in fintech product strategy. Historically, consumer financial services were unusually protected from the attention economy.
People rarely changed banks. Switching was inconvenient. Financial relationships lasted for years. Products such as current accounts, savings accounts and credit cards benefited from inertia. Fintech already weakened some of these advantages. AI could weaken them much further.
McKinsey estimates that 23 percent of consumers already use generative AI for financial tasks at least monthly. Among the most common uses are understanding financial products, receiving investment advice and comparing alternatives.
The next step is agentic AI.
Instead of asking:
“Which savings account has the best interest rate?”
a consumer might tell an AI:
“Keep my emergency fund accessible, but make sure the rest of my cash always earns a competitive return.”
The agent could continuously compare alternatives and eventually execute the necessary actions.
At that point, loyalty changes fundamentally.
The customer may no longer be loyal to a financial institution.
They may be loyal to the intelligence layer managing their financial life.
McKinsey describes a scenario in which AI agents become the primary interface between consumers and financial institutions, potentially reducing the need to open a bank's own app at all.
That is a much bigger strategic challenge than building a better chatbot.
The paradox of AI personalisation
There is another paradox emerging.
AI enables financial products to become extraordinarily personalised.
A traditional banking application essentially shows the same product to millions of people, with relatively minor variations.
An AI-native financial application can theoretically behave differently for every customer.
One person might receive a savings challenge.
Another might see an investment opportunity.
Someone else might receive a warning that their subscriptions have increased.
A customer preparing to buy a house might see a completely different experience from someone planning a six-month sabbatical.
McKinsey argues that AI-powered personalisation could allow banks to move from generic digital experiences toward contextual and “always on” customer relationships.
That sounds like the ultimate answer to engagement.
But personalisation alone may not be enough.
Because once every financial application becomes personalised, personalisation itself stops being distinctive.
The question becomes:
What happens when everyone has a personalised financial app?
The answer is likely the same thing that happened to many other digital experiences.
Consumers start looking for something new.
Financial products may need to become less static
Traditional financial products are remarkably static.
You open an account.
You receive a card.
You download the application.
The interface changes occasionally.
Perhaps a new feature appears every few months.
For a regulated financial product, this stability has historically been considered an advantage. Customers want reliability, security and predictability.
Those expectations will not disappear.
But the experience surrounding the financial infrastructure may need to become considerably more dynamic.
This creates an interesting distinction between two layers of the future fintech product.
The financial infrastructure layer needs to be stable, secure and predictable.
The experience layer may need to be almost the opposite: personalised, adaptive, surprising and continuously evolving.
The account itself should not surprise you.
The experience around it probably should.
The rise of the living financial product
This could create what we might call the living financial product.
Instead of launching a product and occasionally adding features, fintech companies continuously reinterpret the product around the customer.
Imagine opening your banking app in January and receiving a personalised “financial reset.”
In February, the experience changes into a savings challenge.
Before your summer holiday, the app automatically creates a travel budget, analyses previous holiday spending and recommends the cheapest way to pay abroad.
After returning home, it identifies recurring expenses you might want to reconsider.
When markets fall significantly, your investment app changes its educational content and explains what the movement means for your portfolio rather than simply displaying a red percentage.
When you receive a salary increase, your financial assistant asks whether you would like to allocate part of it automatically toward a house deposit, investment portfolio or pension.
None of these features is revolutionary individually.
The important difference is the rhythm.
The product changes with the customer.
And occasionally, it surprises them.
Surprise may become a product feature
This is something financial services companies have historically been uncomfortable with.
Banks love consistency.
Marketers love campaigns.
Product teams love roadmaps.
Compliance teams understandably love predictability.
Consumers, however, also love discovery.
Look at the products that dominate the attention economy.
TikTok does not tell you exactly what you will see next.
Spotify does not simply give you access to music. It continuously creates new ways to rediscover your own taste.
Duolingo does not simply provide language exercises. It creates streaks, competitions, characters, rewards and changing challenges around an otherwise repetitive activity.
The underlying service remains relatively stable.
The experience continuously changes.
Consumer fintech may increasingly need to learn from this logic without blindly importing gamification into financial decision-making.
There is a major difference between encouraging someone to practise Spanish and encouraging someone to trade financial assets.
But the broader design principle remains useful:
Predictability creates trust. Controlled unpredictability creates attention.
The strongest consumer fintech products may need both.
More is not the same as more features
There is an obvious danger here.vWhen companies hear that consumers want novelty, the instinctive response is often to add features.
This is how applications become cluttered.
Savings. Investing. Crypto. Insurance. Cashback. Travel. Shopping. Rewards. Budgeting. AI assistant. News. Community.
Everything eventually ends up on the home screen.
That is not what “more” should mean.
The AI-native opportunity is almost the opposite.
Instead of showing customers more features simultaneously, companies can show them more relevant experiences over time.
The product can become simpler at any given moment while becoming richer across the lifetime of the customer.
AI makes this possible because the interface no longer needs to treat every customer identically.
The future banking application may therefore contain fewer permanent menus but considerably more contextual experiences.
The fintech home screen could eventually disappear
Taken further, this raises another question. Do we actually need the traditional fintech dashboard?
Most financial applications still resemble digital filing cabinets.
Accounts.
Cards.
Payments.
Investments.
Documents.
Settings.
These structures reflect the organisation of the financial institution more than the life of the customer. AI creates an opportunity to reverse that relationship.
Instead of asking customers to navigate financial products, the interface could begin with intentions:
“I want to save €10,000.”
“Can I afford this apartment?”
“Help me reduce my monthly expenses.”
“I want to invest €500.”
“Am I financially prepared for retirement?”
The financial products then operate behind the conversation.
The interface becomes less about banking and more about decision-making.
Deloitte has described a similar evolution in which banking assistants move beyond today's frequently frustrating chatbots toward systems that advise, anticipate and eventually act. The implications for product design are significant.
The winning financial application may eventually look less like a bank and more like a personalised operating system for money.
This also changes fintech marketing
If products become more dynamic, marketing must change with them.
The traditional fintech GTM model often separates product and marketing.
Product builds > Marketing launches > Performance marketing acquires > CRM retains
That separation becomes increasingly artificial when products can change continuously.
In the attention economy, the product itself becomes part of the content engine. A new financial insight can become a shareable experience. A personalised annual financial review can become a social moment. A savings challenge can become a campaign. A new AI capability can become a product launch. A temporary experience around the World Cup, summer holidays, Black Friday or tax season can create another reason to open the application.
This is where Chen's concept of adversarial creativity becomes particularly relevant.
Companies will increasingly need to observe culture, consumer behaviour and competitors and respond faster than the traditional annual marketing calendar allows.
Product, marketing, data and customer experience will need much tighter feedback loops.
Launch. Learn. Change. Relaunch.
This could also change how fintech companies think about launches.
Historically, a product launch represented the end of a long development process.
In an AI-driven consumer market, launch may increasingly become a continuous activity.
Launch a feature > Observe behaviour > Change it > Package it differently > Launch another experience > Remove something that did not work > Bring something back when the context changes
This resembles the content economy much more than traditional banking product development.
And that is precisely the uncomfortable point.
Consumer fintech may be moving into the attention business.
Retention itself may need to be reconsidered
Chen goes even further and questions whether traditional retention metrics will remain as meaningful when products become easier to create and consumer attention moves faster.
Fintech cannot abandon retention. Financial relationships are fundamentally different from entertainment content.
But the way we measure engagement may still need to evolve.
Opening an investment application every day is not necessarily a sign of a healthy customer relationship.
A pension product that quietly works for twenty years might be extremely successful despite very low application engagement.
The better questions may therefore become:
Does the customer return when there is a financial decision to make?
Does the product own an increasing share of the customer's financial decisions?
Does the customer trust the platform enough to connect more of their financial life?
Does the customer act on recommendations?
Does the product help the customer achieve measurable financial outcomes?
And perhaps most importantly:
When the customer has a financial question, which interface do they open first?
That may become one of the defining metrics of consumer finance.
Trust becomes even more valuable when everything else accelerates
There is, however, an important constraint.
Finance is not entertainment.
Consumers might tolerate a strange recommendation from Spotify.
They will be considerably less forgiving when an AI makes a strange recommendation about their mortgage, pension or investment portfolio.
Recent Deloitte research illustrates this tension. Consumers are increasingly using generative AI to research financial products, but concerns about privacy, accuracy and bias remain significant.
This creates an interesting competitive dynamic.
Fintech companies need to become faster, more adaptive and more creative while simultaneously demonstrating stronger governance.
The product experience can change rapidly.
The underlying controls cannot.
This makes trust one of the few durable competitive advantages in an increasingly fluid product environment.
The new competitive advantage is the system behind the product
If AI reduces the cost of building features, individual features become easier to copy.
If interfaces can be generated quickly, beautiful interfaces become less defensible.
If personalised content can be created automatically, personalisation itself becomes less differentiated.
Competitive advantage therefore moves elsewhere. It moves toward proprietary data. Distribution. Brand. Trust. Community. Regulatory capabilities. Customer understanding.
And, perhaps most importantly, the organisational ability to repeatedly create experiences that customers find useful, relevant and fresh.
The moat is no longer necessarily the product.
It may be the system that keeps producing the next version of the product.
What this means for fintech leaders
For consumer fintech companies, the strategic question is therefore no longer simply:
“How can we use AI in our product?” Almost everyone will use AI.
The more interesting questions are:
How frequently can our product meaningfully change?
How quickly can we identify changing consumer needs?
Can our product respond to cultural and financial moments in real time?
Can we personalise the experience without making it feel artificial?
Can we surprise customers without undermining trust?
Can marketing insights influence the product quickly enough?
Can compliance and governance support faster experimentation rather than becoming involved only at the end?
And do customers have a reason to come back when another application can offer essentially the same financial functionality?
These questions move AI strategy beyond technology.
They turn it into product strategy, organisational design and go-to-market strategy.
The next fintech battle is not about features
The first generation of fintech competed against banks by making finance easier.
The next generation may compete by making finance more intelligent, but intelligence will eventually become abundant too.
When every banking app can explain spending, optimise savings, compare financial products, generate personalised advice and deploy an AI assistant, those capabilities will stop feeling remarkable.
Consumers will simply expect them.
At that point, differentiation moves again.
Towards relevance.
Towards personality.
Towards trust.
Towards timing.
Towards experiences that continuously evolve.
And towards the ability to occasionally make someone open a financial application and think:
I didn't expect that.
AI therefore creates a strange new equation for consumer fintech.
Companies will be able to build more than ever before. Consumers will simultaneously become harder to impress.
Winning that equation will require more than adding AI to existing products. It will require fintech companies to become considerably better at understanding attention, behaviour and culture and considerably faster at turning those insights into new product experiences.
The future of consumer fintech may therefore be less about building the perfect financial product.
It may be about building an organisation capable of continuously creating the next reason to care.
But novelty alone does not create retention. Habit does.
There is another side to this argument. If consumer fintech increasingly competes for attention, the answer cannot simply be to produce an endless stream of new experiences. A product that constantly changes but never becomes part of someone's life may attract attention without creating loyalty.
This is where an interesting lesson is emerging from China.
A recent Harvard Business Review article by Yuanyuan Gina Cui, Patrick van Esch and Jan Kietzmann contrasts the AI strategies pursued by many American and Chinese technology companies.
While much of the Western AI race has focused on better models, bigger benchmarks and more sophisticated capabilities, the authors argue that Chinese companies are pursuing another competitive advantage: embedding AI into existing customer habits.
Alibaba, for example, can integrate AI into activities consumers already perform across shopping, payments, food delivery and travel. Instead of asking consumers to consciously decide to “use AI,” intelligence becomes part of an existing behaviour.
The authors describe the resulting competitive advantage as a “habit moat,” and this distinction is particularly relevant for fintech.
The best AI may be the AI customers stop noticing
Many financial institutions currently approach AI as a feature.
>Open the banking app > Click on the AI assistant > Ask a question > Receive an answer.
That may be useful, but it still requires the customer to consciously decide to use AI. A more interesting model emerges when AI disappears into the financial experience itself.
You receive your salary and the application automatically recognises that your income has changed.
You book a flight and your financial service anticipates the foreign exchange, insurance and spending implications.
Your electricity bill increases and your financial assistant identifies the change before you do.
You regularly have excess liquidity at the end of the month, and the application begins helping you decide whether it should go towards savings, investments or debt repayment.
The customer does not necessarily think: “I am using AI.” They simply start expecting their financial product to understand what is happening.
That difference matters because technical advantages are becoming increasingly difficult to defend.
If several fintechs can access comparable models and build comparable AI capabilities, having a slightly better model may provide only a temporary advantage. Owning a customer habit is considerably harder to replicate.
From owning transactions to owning financial moments
This also changes how we should think about customer relationships. Financial institutions traditionally compete to own transactions.
Who holds the current account?
Who issues the card?
Where is the investment portfolio?
Who provides the mortgage?
AI creates another competitive layer: who owns the moment before the transaction?
The moment when somebody wonders whether they can afford something.
The moment they receive their salary.
The moment they start thinking about retirement.
The moment they consider buying a home.
The moment they realise they are spending too much.
The moment they decide what to do with €5,000 sitting in their account.
Whoever becomes the default interface for those moments may have considerably more influence over the eventual financial decision. And that player does not necessarily have to be the institution providing the underlying financial product.
This may become one of the most important strategic threats for incumbent banks and fintechs alike.
If consumers begin asking an external AI agent what to do with their money before they open their banking application, the bank risks becoming infrastructure behind somebody else's customer relationship.
The real opportunity is habit plus surprise
At first glance, this seems to contradict the attention-economy argument. If habit creates retention, why do products need constant change and surprise? Because the two solve different problems.
Habit gives customers a reason not to leave. Novelty gives them a reason to pay attention.
The strongest consumer fintech products may therefore need both.
The core behaviour should become remarkably consistent. When I need to understand my finances, I go here. When I receive money, this product helps me decide what to do with it. When something important changes financially, this product notices. When I need to make a financial decision, this is the first interface I open.
Around that habit, however, the experience can continuously evolve.
New insights.
New challenges.
New recommendations.
New interfaces.
New ways of visualising progress.
New experiences triggered by changes in the customer's life.
This creates a very different product philosophy from simply adding features. The objective is not to keep changing what the product is for. It is to keep changing how valuable, relevant and interesting that recurring relationship feels.
The fintech moat may therefore be behavioural
This has significant implications for product and GTM strategy. Fintech companies frequently analyse feature gaps:
What does our competitor offer that we don't?
The HBR authors suggest that companies should pay greater attention to behavioural cues instead.
For consumer fintech, that means asking different questions.
What recurring financial behaviour can we become part of?
What event should trigger interaction with our product?
Where is there still friction in that behaviour?
What would make our product the automatic choice rather than one of several alternatives?
And which customer moments are we currently allowing another platform to own?
This also changes how acquisition incentives might be designed.
Instead of spending heavily to subsidise initial acquisition, fintechs could increasingly incentivise the behaviours they want customers to repeat. The objective is not merely:
> Download our app.
It becomes: Build this financial habit with us.
Once that habit exists, AI can make the relationship progressively richer, and that may be a much stronger moat than any individual AI feature.
In an environment where technology can increasingly be copied, the ultimate competitive advantage may not be owning the smartest model, but instead may be owning the customer's financial habit while continuously giving them new reasons to value it.
At Contextual Solutions, we help fintech companies, banks and technology providers translate changing consumer behaviour and emerging technologies into product, positioning and go-to-market strategies. If you are developing a new financial product, reconsidering your customer proposition or exploring how AI should change your product strategy, contact us at info@contextuals.de to discuss your approach.