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Digital financial services are becoming part of everyday life. We use mobile banking to transfer money, digital wallets to pay for food and transport, remittance apps to support families across borders, and QR payments for everyday purchases.
Artificial intelligence (AI) is now opening another chapter in this transformation. But as the financial industry moves towards AI, automation and increasingly sophisticated digital experiences, I believe there is a simple question every product team should keep asking: Who are we actually designing these products for?
A digitally confident professional and a factory worker may use the same digital wallet. A university student and a domestic worker may use the same banking app. A business owner and a construction worker may use the same payment service.
They may use the same product, but their levels of digital literacy, financial knowledge, language preferences and confidence with technology can be very different.
Good FinTech cannot be designed only for the easiest users to digitise. It has to work for everyone.
During digital transformation, it is easy to design around people who are already comfortable with technology.
We add more features, more menus and more automation. From a technology perspective, the product becomes more advanced. But does it become easier?
In remittance, for example, I have seen how different customer journeys can be. One customer may be comfortable completing everything through an app, while another may still prefer visiting a counter because speaking to someone gives them confidence.
We should not automatically assume that the second customer does not want digital services. Perhaps the digital service has simply not been designed around their needs. That distinction is important.
What If Technology Could Adapt to the User? This is where I see one of the most practical opportunities for AI.
Instead of expecting every customer to learn how our product works, what if the product could learn how to serve different customers better?
A digitally confident customer may prefer biometric login, quick transfers, saved beneficiaries and minimal interaction.
Another customer may benefit from fewer steps, simpler language, voice assistance and clearer explanations.
Imagine a migrant worker opening a remittance app and saying in their native language: “I want to send RM500 to my mother’s bank account.”
AI could understand the request, guide the customer through the necessary steps, explain the exchange rate and fees, and ask for confirmation before completing the transaction.
The same idea can extend beyond remittance. A digital-wallet user could ask, “How do I pay this QR?” and receive voice guidance in their preferred language.
A mobile-banking customer whose transfer failed could ask, “Why didn’t my payment go through?” Instead of displaying a technical error code, the app could explain the problem in simple language and suggest what to do next.
This is where AI becomes more than a chatbot. It becomes part of the user experience.
Making an app available in several languages is useful, but localisation should go much further.
How do people in different communities describe financial transactions? Which parts of a digital journey confuse them? Why do they abandon transactions? Why do some customers continue visiting branches or agents even when digital alternatives exist?
Not every answer can be found in a dashboard. Sometimes companies need to go closer to their users and listen. Some of the world’s most successful technology products have been built around a simple discipline: observe how people actually use technology, listen to them and continuously improve the product around their needs.
Google is one example of a company known for putting significant emphasis on user experience and understanding how products work for people across different markets. FinTech needs the same user obsession.
Customer feedback should not remain only with customer-service teams. Insights from customers, agents, branches and frontline employees need to reach the people designing the product.
AI can also help FinTech companies understand their users better. Customer-support conversations, complaints, failed transactions, search behaviour and abandoned digital journeys contain valuable product information.
If thousands of customers struggle at the same e-KYC step, perhaps it is not simply a customer problem. It may be a product problem.
If users repeatedly ask what a transaction status means, perhaps the wording needs to change. If a particular group prefers voice assistance, perhaps the interface needs to evolve.
AI can help identify these patterns much faster. So the role of AI should not only be to automate more processes. AI can also help companies listen better.
Not everyone will move from physical to digital financial services at the same speed. Branches, agents and customer-service teams can therefore remain important parts of digital transformation.
The objective should not simply be to push customers from counters to apps because digital transactions may cost less.
The objective should be to build enough trust and confidence that customers want to use digital services.
The future of FinTech will bring more AI, digital wallets, embedded finance, instant payments and automation.
But having the most features or using the most AI will not automatically create the best financial product. The winners will be companies that understand their users best.
White-collar or blue-collar. Digitally confident or less confident. English-speaking or more comfortable in another language.
Different users should not be considered after a product has been built. They should be part of the design from the beginning.
The next stage of FinTech transformation should not simply make finance more digital. It should make it more adaptive, more local, more accessible and more human.
We should not keep asking millions of people to adapt to financial technology. It is time to build financial technology that can adapt to millions of different people.
The views expressed in this article are the author’s own and do not necessarily reflect Sarabangla English Edition’s editorial stance.