Al, Fintech Data identified as key to unlocking SMEs credit access 

Nigeria’s small and medium-sized enterprises (SMEs) continue to struggle with access to credit despite contributing significantly to national output and employment. Analysts say the country’s lending system still relies heavily on collateral, manual assessments, and outdated credit-history requirements that exclude thousands of viable businesses. A new study by U.S.-based financial analytics specialist Elizabeth Umah suggests […]

Nigeria’s small and medium-sized enterprises (SMEs) continue to struggle with access to credit despite contributing significantly to national output and employment. Analysts say the country’s lending system still relies heavily on collateral, manual assessments, and outdated credit-history requirements that exclude thousands of viable businesses.

A new study by U.S.-based financial analytics specialist Elizabeth Umah suggests that the situation could change if Nigeria adopts Al-driven credit modelling and integrates fintech transaction data into lending decisions. According to the research, the bulk of Nigerian SMEs are deemed “high risk” not because of poor performance but because lenders lack reliable data to assess their true financial health. With millions of daily transactions processed by OPay, Moniepoint, Flutterwave and other fintechs, Umah argues that Nigeria already has the raw data needed to build more accurate credit profiles.

Her study outlines how Al models can analyse thousands of alternative data points, such as POS activity, mobile money flows, savings patterns, utility payments, supplier invoices and digital purchase history, to determine the creditworthiness of SMEs that traditional systems overlook.Drawing from her experience in the U.S. digital-lending industry, Umah explained that automated underwriting systems using Al have improved loan decisions, reduced default rates, and expanded credit access for small businesses. “Collateral is no longer the only or even the best, indicator of an SME’s ability to repay,” she said. “Al allows lenders to evaluate real business activity using transactional evidence, not guesswork. Nigeria already generates enough digital data to make this shift possible.”

The study calls for stronger collaboration between banks and fintech companies to integrate merchant-level transactional data into credit scoring models. It also highlights the Central Bank of Nigeria’s role in implementing open-banking standards, regulatory sandboxes and data-sharing frameworks needed to support responsible Al adoption.

Umah concludes that modernising Nigeria’s credit-evaluation system will unlock financing for millions of SMEs, boost productivity and stimulate long-term economic growth.

“If Nigeria aligns policy, data and technology, SME lending can be transformed at a national scale,” she added.