Nigeria’s banking sector is facing renewed pressure as rising bad loans continue to strain balance sheets, prompting experts to call for a deeper rethink of how credit is assessed and managed across the industry.
Recent figures show that the country’s non performing loan ratio has climbed to 8.03 percent, moving above the Central Bank of Nigeria’s recommended threshold of 5 percent. The development has raised fresh concerns about the quality of loan portfolios, especially within retail and small and medium scale lending.
Amid these challenges, industry observers are urging banks to move beyond surface level digital lending processes and confront long standing weaknesses in their credit systems.
The Chief Executive Officer of Mathesis, Winston Osuchukwu, noted that while financial institutions have made progress in digitising loan applications and improving customer onboarding, many of the core systems used for evaluating risk remain outdated and fragmented.
He outlined three key areas that require urgent attention if lenders are to reduce defaults and strengthen credit performance.
One of the major concerns is the lack of unified borrower data. Many institutions still depend heavily on internal records and credit bureau reports, which often fail to capture a full picture of a customer’s financial behaviour. He suggested that integrating broader data sources such as salary records, utility payments, and other alternative financial indicators would allow lenders to better understand repayment capacity in real time.
Another issue is the reliance on fixed risk assessment models. According to him, many banks continue to use static benchmarks even in a volatile economic environment shaped by inflation and fluctuating interest rates. This approach, he argued, can lead to unfair loan rejections, particularly for new borrowers and individuals with limited credit history.
He explained that risk evaluation should be continuous and adaptive, supported by predictive tools that monitor behaviour over time and flag potential defaults before they occur.
The third challenge, he said, lies in the separation between loan issuance and debt recovery functions. In many cases, collections teams operate independently from credit departments, limiting the flow of repayment insights that could improve future lending decisions.
Osuchukwu suggested that linking these systems would create a more intelligent credit structure, where repayment patterns directly inform future risk assessments and help reduce losses over time.
He added that lenders who invest in data driven and predictive credit systems are more likely to improve financial inclusion, strengthen loan quality, and achieve more stable growth within Nigeria’s evolving financial landscape.
