By Juliet Umeh

As Nigerian banks battle rising bad loans amid economic uncertainty, industry stakeholders are urging lenders to look beyond digital loan applications and address deeper weaknesses in their credit infrastructure.

The call comes as the country’s non-performing loan, NPL, ratio climbed to 8.03 percent, above the Central Bank of Nigeria’s regulatory threshold of five percent, raising concerns about the sustainability of credit growth, particularly in the retail and SME segments.

According to Chief Executive Officer of Mathesis, Winston Osuchukwu, while digital transformation has improved customer onboarding and loan disbursement processes, the systems underpinning credit risk management remain largely outdated.

He identified three critical infrastructure gaps that lenders must address to reduce defaults and expand access to credit safely.

The first challenge, he noted, is fragmented borrower data. Many lenders rely on internal transaction records and credit bureau reports, which often provide only a limited picture of a customer’s financial behaviour. Osuchukwu argued that integrating additional data sources, including payroll records, utility payments and alternative financial data, would help institutions build a more accurate and real-time view of borrowers’ repayment capacity.

A second gap lies in the use of static risk assessment criteria. According to him, many banks continue to apply fixed lending benchmarks despite inflation, changing interest rates and shifting economic realities. This often results in unnecessary loan rejections, especially for first-time borrowers and individuals with limited credit histories.

“Risk management should be dynamic rather than based on a single point-in-time assessment,” he said, advocating predictive models that analyse behavioural data continuously and identify potential risks before defaults occur.

The third challenge is disconnect between lending and debt recovery operations. Osuchukwu observed that collections teams often operate separately from credit departments, preventing valuable repayment data from informing future lending decisions.

He maintained that integrating collections and underwriting systems would create a self-learning credit framework capable of refining risk models and reducing future losses.

According to him, lenders that embrace data-driven and predictive credit infrastructure will be better positioned to improve financial inclusion, strengthen asset quality and drive sustainable growth in Nigeria’s evolving financial sector.