How Artificial Intelligence Is Quietly Reshaping Nigerian Fintech

Nigeria’s financial technology sector did not slow down to wait for artificial intelligence. It absorbed it quickly, unevenly, and with growing consequence.

Over the past two years, the country’s fintech companies have moved from casual experimentation with machine learning tools to deploying them at the core of fraud detection, credit assessment, and customer operations. The shift is structural and reshaping how millions of Nigerians access and use financial services.

A Sector Already Under Pressure to Perform

Context matters here. Nigeria processed close to 11 billion real-time payment transactions in 2024, more than double the volume recorded in 2022, placing the country among the world’s most active instant payment markets. That velocity brings its own strain: rising compliance costs, fraud exposure, and the pressure to serve a largely underbanked population without proportionally expanding headcount. That is precisely where machine learning tools have found their entry point.

Fraud Detection Leads Adoption

The most authoritative measure of where the sector currently stands comes from the CBN Fintech Report 2025, published by the Central Bank of Nigeria as part of its Policy Insight Series. The report shows that fraud detection is the dominant AI use case among Nigerian fintechs, far outpacing other applications — with 87.5% of surveyed companies deploying it primarily to detect fraudulent transactions.

Digital payment fraud losses dropped 51% in recent years as a result, according to industry data. But the cost of that vigilance is high: 87.5% of fintech executives say compliance costs significantly impact their capacity to innovate. As Nairametrics reported, the CBN itself has acknowledged that this pattern reflects both the scale of digital fraud challenges confronting Nigeria’s financial system and the growing reliance on data-driven tools as fintech services become more embedded in payments, lending, and remittances.

For platforms processing millions of daily transactions, this is less a competitive advantage than an operational necessity.

Credit Scoring Without a Credit Bureau

Perhaps the more consequential application, and the one with the longest-term implications for financial inclusion, is AI-driven credit assessment.

About 37.5% of surveyed fintechs deploy AI for credit scoring and risk modelling, while the same proportion applies it to customer onboarding and know-your-customer processes. This matters in a market where a significant share of potential borrowers carry no formal credit history.

Fintechs like Carbon and FairMoney are deploying AI to assess creditworthiness and deliver instant loans to mobile users, improving financial access and empowering individuals to manage their finances and invest in businesses. As the OECD’s Africa Capital Markets Report 2025 notes, retail investors in Nigeria have developed a preference for AI-based recommendation engines, with personalised machine learning risk models facilitating greater inclusivity by expanding access to capital markets.

In Nigeria, digital lenders are providing working capital to traders by analysing transaction histories from mobile wallets — a model that turns behavioural data into credit decisions where conventional systems see nothing.

The result is a lending market that has quietly expanded access beyond what the traditional banking system ever managed.

Customer Service Automation Fills the Gap

Beyond fraud and credit, about 62.5% of Nigerian fintechs now use AI-powered chatbots for customer service handling user complaints, transaction issues, and basic enquiries as platforms scale to millions of users.

This is not simply a cost-cutting exercise. In a sector where trust is still being built, where users have experienced fraud, sudden account restrictions, and abrupt service changes, the responsiveness of customer support directly shapes retention. Automation, when implemented well, can narrow that gap.

The Regulatory Question

Nigeria’s regulators have not ignored these developments. The CBN’s regulatory sandbox, launched in 2023 and expanded through 2024 and 2025, now evaluates model explainability, fairness, and consumer transparency before granting approvals for AI-powered fintech tools.

Yet the broader governance picture is fragmented. As TechCabal has reported, overlapping jurisdictions among NITDA, the NDPC, the NCC, and the CBN have raised concerns about regulatory duplication and conflict as the country attempts to develop a coherent AI oversight framework.

The Nigeria Data Protection Act of 2023 made important progress on data rights, but between 2019 and 2023, only 27 regulatory investigations were conducted under the NDPR and NDPA, none specifically targeting AI-related violations, pointing to a significant enforcement gap.

The CBN survey asked fintechs what would help them scale responsible AI. The answers were consistent: infrastructure, regulatory clarity, and collaboration, not less oversight. That framing reflects an industry that understands the stakes, even if the frameworks to match are still being assembled.

What the Data Signals

AI is projected to add $15 billion to Nigeria’s GDP by 2030, and 72% of Nigerian CEOs expect it to transform workforce and skills strategies, according to PwC Nigeria data. Meanwhile, BusinessDay’s analysis of Nigeria’s tech outlook suggests that AI will become invisible but indispensable in fintech, primarily powering fraud detection, credit underwriting for SMEs, and automated regulatory reporting through 2026 and beyond.

The CBN report identifies AI, cross-border payments, and financial inclusion as the main drivers of Nigeria’s next fintech growth wave, with 26% of Nigerian adults still outside the formal financial system, rising to 37% in rural areas.

The Unfinished Work

None of this means the transition is smooth or complete. Talent gaps are real. The pool of engineers who can build and maintain production-grade machine learning systems in Nigeria remains thin relative to demand. Concerns about data privacy, algorithmic bias, and the digital divide raise practical questions about the deployment of AI in financial services that have received less public scrutiny in Nigeria than they deserve.

What is clear is that Nigeria’s fintech sector has moved past treating AI as an optional upgrade. For fraud teams, credit analysts, and customer operations functions, it has become embedded infrastructure. The remaining questions are not whether these tools will be used, but how responsibly they are built, and whether regulation will keep pace with deployment, or continue to follow at a distance.