By Ademola Adepoju

Scenes like this play out every day across Nigeria: a customer attempts to pay at a supermarket by transfer, but instead of a clear confirmation, the app only shows “transfer pending.” The sender is left uncertain, the queue grows tense, and trust in digital payments takes another small hit. This is not because our banking systems are weak or unreliable. More often, the problem is that the language on our screens does not reflect the reality that behind every transaction is a student paying school fees, a worker sending money home, a parent covering medical bills, or in this case, a customer shopping in a long queue.

Now imagine if that same app said, “your transfer is being processed and should reflect within 10 minutes.” Suddenly the situation feels different. The customer can breathe, plan, and carry on. What changed was not the algorithm or the network. It was the language, the bridge between technology and trust. Every automated decision, whether made by a simple rule or a complex algorithm, reaches people through words. If those words are clear, the decision becomes transparent. If they are vague or technical, even a fair algorithm can feel biased or hostile.

Banks and fintech teams work under enormous pressure. They juggle new regulations and multiple market challenges. It is no surprise that teams sometimes use phrases from legal or technical documents. But those phrases rarely land well with everyday users. When someone sees “preauthorisation” without explanation, or when a form simply says “Enter BVN/NIN,” many are left guessing which number to provide. The algorithm behind the scenes may have worked perfectly, but the experience still feels broken.

Fairness and transparency in AI is often described in technical terms: algorithms that do not discriminate, models that score customers accurately. But fairness is also about communication. People need to know why a decision affecting their money has happened. A vague message like “Transaction declined” leaves a person in the dark. By contrast, “We could not process your transfer because it exceeds your daily limit. You can try again tomorrow or adjust your limit now” gives an explanation and a choice.

The same principle applies to loan applications. Instead of “Application under review,” a message that says “We are checking your documents to keep your account safe. We will update within 24 hours” does more than inform. It shows care, offers a timeframe, and reassures the customer that progress is underway. The underlying model is assessing credit risk, but the writing is what turns a technical evaluation into a process people can understand and trust.

Few experiences rattle people like fraud alerts. A cold technical notification can heighten fear. But a carefully crafted message can protect the customer while easing their worry. For example, “We stopped a ₦20,000 debit from an unknown device. Your money is safe. If this was you, enter the OTP we just sent to continue. If not, you don’t need to do anything — we’ve blocked the attempt and will keep you updated.” Here, the tone is protective, not punitive. It treats the user as a partner, not a suspect.

Elsewhere, Nigerians are rightly concerned about how their personal information is used. Privacy policies written in dense legal English do little to reassure. But a simple, direct note can. “We need your location to confirm this transaction. You can turn this off anytime in settings.” That single sentence explains the purpose, sets a limit, and offers a choice. It treats customers as owners of their data, not passive subjects. The algorithm requires data to function, but UX writing frames that data request in a way that feels respectful rather than extractive.

When words misfire, the consequences are bigger than a moment of confusion. People complain to friends, vent online, and sometimes abandon digital services altogether. Many revert to cash, despite the risks of carrying it. For banks and fintechs, that erosion of trust is costly. For the wider economy, it slows down the shift toward safer, more efficient digital payments. Headlines often capture this dynamic. When system upgrades or account holds delay salaries, the rhetoric is not about new technology. It is about teachers or nurses unable to access their money. When explanations are vague or contradictory, frustration spreads. But when people get straight answers the first time, even difficult situations become more manageable.

The encouraging news is that improving financial language does not require a massive budget. It can start with a simple exercise: take five of the most stressful screens—a failed payment, a fraud alert, an account hold, a verification step, and a loan decision—and rewrite them as if you were explaining to a neighbour. Then test those screens with real customers, especially those new to digital banking. If they hesitate or misinterpret, that is a sign to refine the wording. Consistency is another critical step. A transfer that says “completed” on the app should not say “pending” by SMS or “failed” by email. Aligning language across channels reduces confusion and support calls. If questions persist, it is the copy that needs work, not the customer.

At its core, UX writing is not decoration. It is infrastructure for fairness. Every algorithmic decision must cross the bridge of language before it reaches the person it affects. If that bridge is weak, fairness collapses. If it is strong, people can see the decision, understand it, and act on it. When banks and fintechs invest in words that clarify rather than confuse, they build trust that is more durable than any marketing campaign. Customers who feel respected and understood are more likely to stay, recommend, and explore new services.

Fair finance in Nigeria’s future will depend on many things: stable networks, smart regulation, secure algorithms. But just as important are the words that explain those systems. If we want financial technology to work for everyone — from the market trader in Aba to the software developer in Abuja — we must treat language as part of the system itself. When words ooze care and carry clarity, algorithms stop feeling like black boxes. They become understandable and trustworthy. And in that trust lies the promise of financial inclusion that is transparent and fair for all.

Vanguard News