Let’s be honest — we’ve been talking about open banking in Nigeria like it’s a distant relative who promised to visit but keeps rescheduling.
Back in 2021, the conversation was electric. Banks and fintechs would finally share data securely. Lending decisions would get smarter. Customers would get personalized financial services tailored to their actual lives. Innovation would move faster once the walls around financial data came down. It was going to be the thing.
Five years later, we’re still mostly talking about the potential of the thing.
Sure, progress has happened. Infrastructure conversations have matured. Regulatory frameworks and standards exist. API standards have been defined, but the vibe is still oddly “waiting for the future to show up” — which is a strange place to be in 2026.
What nobody really wants to say out loud is that: open banking is not the silver bullet. If anything, it will expose just how fragmented and inconsistent Nigeria’s financial system already is. The real question was never whether institutions could connect systems. The real question is whether they can make any sense of what flows through those systems once everything is plugged in.
That distinction matters more than the industry is currently admitting.
More Data Is Not the Same as Better Decisions
Open banking sounds irresistible in theory. A connected financial ecosystem where banks, fintechs, payment providers, and third-party platforms securely share financial data — with customer consent — to build smarter products, make better lending decisions, and finally treat customers like the intelligent adults they are.
In the UK and parts of Europe, this is actually working, however those markets spent years quietly standardizing operations before open banking arrived at scale. Consistent transaction formats, clean metadata, predictable data structures and institutions that largely speak the same language when recording financial activity. Open banking there was the final layer on top of an already-mature foundation.
Nigeria said: hold my Agege bread.
Our reality is a beautiful, complicated, deeply human mess. Inconsistent transaction histories and cryptic bank statement narrations that only the sender fully understands, salary payments that look indistinguishable from a random transfer from your cousin. Two different banks record the exact same transaction in completely different ways. Customer names that shift depending on which platform you’re using.
This isn’t a criticism of anyone — it’s the natural result of a fast-moving, partially informal economy that financial infrastructure was never quite designed to handle.
The uncomfortable truth is that more data doesn’t automatically mean better decisions. More messy data, moving faster across more connected systems, mostly just creates more noise. Human teams cannot process that level of complexity across millions of records. You would need an army of analysts working around the clock just to keep up — and you’d still be losing ground.
Which is exactly where AI walks into the room and sits down uninvited.
AI Is the Real Infrastructure Layer — and Connectivity Is Just the Beginning
APIs create connectivity, they move data from one place to another, however, connectivity alone doesn’t create intelligence — it just means information travels faster. If connected systems are simply exchanging poorly structured, inconsistent financial records at higher speed, congratulations: you’ve successfully scaled confusion.
AI changes that equation entirely.
Modern machine learning can identify transaction patterns across inconsistent records, classify spending behavior, reconcile fragmented account activity across wallets and bank accounts, detect irregular income flows that don’t look like income, map merchant identities, and extract meaning from financial data that would make a human analyst reach for a strong drink. What used to require large operations teams manually reviewing bank statements can increasingly happen at scale and in near real-time.
This matters especially in Nigeria because so much of the economy is — by design or by necessity — informal or semi-formal. Income is irregular, people move money across multiple wallets and accounts constantly, businesses operate with one foot in formal systems and one foot out. Narration conventions range from beautifully descriptive to completely useless. Traditional financial models hate this environment because they were built around clean assumptions that don’t survive contact with real Nigerian economic life.
AI can interpret financial behavior contextually — not just against rigid rules, but against patterns that actually reflect how people live and move money. That unlocks smarter credit decisions for people traditional scoring models would simply reject. It also enables more adaptive fraud detection in a world where fraud doesn’t politely follow predictable patterns.
And on the fraud point — this is important because it’s often treated as a separate conversation when it’s really the same one. Open banking won’t just create opportunities for legitimate financial services to move faster. It will create opportunities for bad actors to move faster too. Once banks, fintechs, wallets, and payment platforms are all connected through APIs, fraudsters gain multiple entry points and the ability to exploit all of them quickly. Legacy rule-based fraud systems — flag the large transaction, raise an alert on the unusual location — are genuinely inadequate in that environment. By the time a manual review team decides something looks suspicious, funds have already moved across three platforms. Nobody wants to explain that to their board.
AI-powered fraud detection matters here because context catches what rules miss, behavioral patterns, device activity, transaction velocity and the full picture around multiple transactions, not just the transaction itself.
The more complex and connected the ecosystem becomes, the more an intelligent interpretation layer becomes the real infrastructure — not a nice-to-have sitting on top of it.
The Strategic Stakes: Who Actually Wins This Era
Traditional banks have a specific reason to be anxious about open banking, and it’s not regulatory complexity. It’s existential.
For decades, banks controlled the customer relationship because they controlled access to financial information. You needed them to understand what you had, what you owed, and what you could do with your money. That exclusivity was the foundation of their relevance, regardless of whether the product experience was actually any good.
Open banking dismantles that advantage quietly and completely.
Once customers can aggregate balances, payments, savings, lending products, and transactions across multiple institutions in a single interface — probably a fintech app they actually enjoy using — the bank risks becoming background infrastructure, useful but invisible – the pipes behind the wall. And if another platform delivers sharper insights, smarter recommendations, clearer cash flow visibility, and genuinely helpful financial automation, customers will simply spend their time there. It doesn’t matter where the money is technically stored.
This is why AI becomes strategically critical, not just operationally useful. In a world where exclusive ownership of customer data disappears, institutions can no longer compete on information asymmetry. They have to compete on intelligence — on how well they understand customer behavior and translate that understanding into experiences people actually value.
The institutions that win the next decade may not be the largest ones. They may simply be the ones that understand their customers best and build around that understanding relentlessly.
Trust and Governance Are Not Optional Extras
Open banking asks customers to do something psychologically significant: grant visibility into their full financial life, across institutions, in a system they already approach with caution. That’s a big ask — and trust like that cannot be demanded. It has to be earned, slowly, through consistent behavior over time.
AI makes this conversation harder, not easier.
Once customers realize that institutions are not just sharing data but using AI systems to make real decisions — about their loan applications, their fraud flags, their creditworthiness, their spending categories — transparency stops being a nice-to-have and becomes the price of entry. People will ask questions, and they deserve clear answers:
Why was my loan rejected?
Why was that transaction flagged?
Who has access to my financial data?
Can I revoke that access?
What exactly is this system deciding about me?
Institutions that cannot answer these questions clearly will lose people — regardless of how technically impressive their systems are underneath. And the stakes are higher here than in most markets because being unfairly locked out of financial services in Nigeria isn’t abstract. For millions of people, access to credit or payment infrastructure is the difference between a business surviving or not.
Poorly trained models will discriminate without intending to. Overly aggressive fraud systems will exclude legitimate users at scale. Bad data fed into AI produces bad decisions — consistently, at speed, without anyone necessarily noticing until real damage is done. These aren’t hypothetical risks, they’re the predictable consequences of deploying powerful systems without adequate governance.
The institutions that build genuine trust — through transparency about how AI is used, clear explanations when systems make consequential decisions, and real accountability when things go wrong — will have a durable advantage that technology alone cannot replicate.
The Real Work
Open banking in Nigeria will not be defined by who connects systems the fastest. It will be defined by who can make the most sense of the complexity flowing through those systems, who builds the intelligence layer that turns fragmented financial behavior into genuine insight, and who earns enough trust from customers to be given the visibility that makes all of it possible.
The infrastructure is necessary but not sufficient. AI is necessary but not sufficient. Trust is necessary but not sufficient. The institutions that understand all three as parts of the same challenge — not separate workstreams to be handled by different teams — are the ones most likely to actually build something that matters.
Written by:
Chigozie Madubuko is a fintech and API infrastructure specialist with deep experience at the intersection of open banking, lending systems, and financial technology in Africa.
He has contributed to Nigeria’s Open Banking movement, working on initiatives focused on API standardisation and ecosystem alignment across banks and fintechs. Professionally, he has played a key role in building and scaling lending infrastructure, designing systems that leverage APIs to enable credit access and financial inclusion.
His work sits at the intersection of product, engineering, and policy, giving him a unique perspective on how APIs move from specifications to real-world impact. Chigozie is passionate about unlocking financial systems through interoperable infrastructure and believes the next wave of innovation in emerging markets will be API-driven.