Banks can unlock Nigeria’s informal credit market with AI – Mathesis Analytics

The Founder and Chief Executive Officer of Mathesis Analytics, Winston Osuchukwu, has urged Nigerian banks to rethink the long-held assumption that millions of unbanked and informal sector borrowers are inherently high-risk, arguing that the real challenge is limited access to reliable data rather than poor creditworthiness.

Osuchukwu said advances in artificial intelligence (AI) and alternative data analytics now offer financial institutions the opportunity to safely expand lending, improve risk pricing and deepen financial inclusion without compromising portfolio quality.

According to him, many Nigerians operating outside the formal banking ecosystem are excluded from access to credit because conventional underwriting models rely heavily on collateral, formal documentation and traditional banking records.

He explained that while these approaches were appropriate when little data was available, they no longer reflect the realities of today’s digital economy, where millions of Nigerians generate verifiable financial footprints through mobile money platforms, fintech wallets and other digital payment channels.

“The average Nigerian borrower is often labelled high-risk, but that assessment is frequently based on data limitations rather than actual repayment behaviour,” Osuchukwu said.

He noted that informal traders, gig workers and remote employees earning through digital platforms often maintain consistent cash flows that remain invisible to conventional credit assessment systems despite demonstrating responsible financial behaviour.

According to him, AI-powered credit decisioning can analyse alternative datasets to provide lenders with a more comprehensive understanding of borrowers’ repayment capacity, enabling banks to extend credit to previously underserved segments with greater confidence.

He argued that Nigeria’s banking sector has sufficient liquidity to support increased lending, but the inability to accurately assess borrowers outside traditional banking records has constrained credit expansion.

“The challenge has never been a shortage of lendable customers but incomplete visibility into their financial behaviour,” he said.

Osuchukwu maintained that adopting AI-driven credit assessment would not replace the judgment of financial institutions but strengthen existing risk management frameworks by incorporating a broader range of financial data.

He said this would enable banks to grow their loan portfolios while providing much-needed capital to small businesses, informal entrepreneurs and other economically active Nigerians currently excluded from formal credit.

Highlighting the role of Mathesis Analytics, Osuchukwu said the company develops AI-powered credit scoring and decisioning solutions that combine multiple data sources to generate bank-grade risk scores for borrowers lacking traditional credit histories.

According to him, the platform has processed more than 40 million credit scores and facilitated over $272 million in credit disbursements across Nigeria.

He added that stronger collaboration between technology firms and financial institutions would be critical to closing Nigeria’s credit gap and unlocking new growth opportunities within the financial services sector.