How Nigerian Banks Can Use AI to Reduce Loan Default Rates

Nigeria’s banking sector is the backbone of Africa’s largest economy, serving more than 100 million active accounts and supporting businesses across every industry. Yet one persistent challenge threatens stability and growth: high loan default rates. From large commercial banks to emerging fintech lenders in Lagos, defaults reduce profitability, increase risk aversion, and limit access to affordable credit for individuals and small businesses.

Traditional methods of credit assessment, often based on static demographic data or incomplete credit bureau reports, are struggling to keep pace with Nigeria’s fast-changing economy. Many borrowers operate in the informal sector and lack formal credit histories, leaving banks with little insight into their repayment capacity. The result is a lending environment where risk is misjudged: strong borrowers are sometimes denied credit, while high-risk borrowers are approved, leading to unsustainable default rates.

Against this backdrop, artificial intelligence (AI) offers a new path forward. By analyzing large, diverse datasets and identifying patterns invisible to traditional models, AI can help Nigerian banks predict defaults more accurately, reduce losses, and extend credit to more people with confidence.

Building AI Models for Lending

One researcher advancing this work is Emmanuel Adefila, a software engineer and AI specialist with an MSc in Artificial Intelligence from the University of Bradford, UK. In a project inspired by peer-to-peer lending data, Adefila developed a cloud-based AI system for predicting loan defaults.

Using thousands of borrower records, the system applied algorithms such as Logistic Regression, Decision Trees, Random Forests, and Gradient Boosting. His experiments showed that ensemble methods like Random Forests performed best, achieving accuracy levels above 88% in identifying likely defaulters. The models highlighted key predictors, such as income-to-loan ratios, repayment histories, and debt-to-income levels.

To demonstrate practical use, Adefila deployed the trained model as a Flask API on Heroku, a cloud platform. This meant the AI service could be accessed by any application or digital lending platform in real time — a model that Nigerian banks and Lagos fintechs could easily adopt without heavy infrastructure investments.

Why It Matters for Nigerian Banks

The relevance to Nigeria’s financial ecosystem is clear. Banks already collect vast data: mobile transactions, BVN-linked account histories, SME POS activity, and even utility bill payments. By training AI systems on this local data, lenders can move beyond static scoring to dynamic, data-driven risk assessments.

Imagine a bank assessing a loan application not only by looking at past credit bureau records but also by analyzing:

• Patterns in mobile money transfers.
  
  

• Consistency of electricity or water bill payments.
  
  

• Cash flow data from POS terminals for small businesses.
  
  

• Savings and withdrawal behaviors across accounts.
  
  

By combining these signals, an AI system could produce a far more accurate risk score in seconds. For fintechs in Lagos handling large volumes of microloans, this would cut fraud and improve recovery rates. For traditional banks, it would mean safer lending to previously underserved segments — expanding financial inclusion without fueling default rates.

Lagos as the Fintech Testbed

While Nigerian banks provide nationwide reach, Lagos remains the heart of innovation. Startups like Carbon, Renmoney, and FairMoney already use machine learning in some form for borrower scoring. These companies can act as testbeds, refining models and workflows that can later be scaled across the banking sector.

In this way, fintechs and banks form a symbiotic relationship. Fintechs bring agility, experimentation, and digital-first platforms. Banks contribute capital, regulatory compliance, and trust. AI is the bridge, enabling both sides to manage risk more effectively while opening doors to new lending opportunities.

Challenges to Overcome

Adopting AI in Nigerian banking won’t be without hurdles:

1. Data quality and integration – Many institutions still operate with siloed or incomplete datasets, limiting AI effectiveness.
   
   

2. Regulation and trust – The Central Bank of Nigeria (CBN) enforces strict lending rules, and AI systems must remain transparent and explainable.
   
   

3. Infrastructure – While cloud hosting reduces costs, banks must still invest in secure, reliable connectivity and cybersecurity.
   
   

4. Skills gap – Financial institutions need more trained AI engineers and data scientists who understand both technology and local context.
   
   

Despite these challenges, gradual adoption is possible. Banks can begin by piloting AI-driven scoring in select product lines and expanding as confidence grows.

Broader Economic Benefits

If implemented well, AI could reshape Nigeria’s credit landscape:

• Banks would enjoy healthier balance sheets and fewer non-performing loans.
  
  

• Borrowers would benefit from fairer access to credit and potentially lower interest rates.
  
  

• SMEs, which form the backbone of Nigeria’s economy, would find it easier to access working capital, fueling growth and job creation.
  
  

• Regulators would gain a more stable financial system, less prone to shocks from widespread defaults.
  
  

For a country where access to affordable credit is a major barrier to entrepreneurship, the ripple effects of reducing defaults could be transformative.

Looking Ahead

As Emmanuel Adefila’s project demonstrates, the building blocks for AI-driven lending are already here: accurate models, cloud deployment, and API integration. What remains is scaling these solutions within Nigerian institutions.

The future of banking in Nigeria will depend not just on adopting AI, but on doing so responsibly — ensuring fairness, transparency, and inclusivity. Institutions that move first will gain a competitive advantage, reduce losses, and build trust with a new generation of digital-first customers.

With Lagos as the fintech testbed and Nigerian banks as the nationwide backbone, the country is uniquely positioned to lead Africa in AI-driven financial innovation. By applying lessons from projects like Adefila’s, Nigeria can move toward a financial system where loans are not just safer for banks, but also fairer and more accessible for its citizens.

By Emmanuel Adefila