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By Chinenye Anuforo
Nigerian lenders must address three major infrastructure gaps if they are to effectively manage credit risk and expand lending to retail customers and small businesses, financial technology expert Winston Osuchukwu has said.
In a commentary titled “3 Infrastructure Gaps Nigerian Lenders Can’t Afford to Ignore,” Osuchukwu argued that while digital transformation has improved customer-facing credit processes, the core infrastructure supporting lending decisions remains largely outdated.
According to him, the weakness has become more apparent following the withdrawal of the Central Bank of Nigeria’s forbearance measures, which saw the banking sector’s non-performing loan (NPL) ratio rise to 8.03 per cent, significantly above the regulatory threshold of five per cent.
Osuchukwu identified fragmented borrower data as the first major challenge confronting lenders.
He explained that most institutions rely on internal transaction records and periodic credit bureau reports, both of which provide incomplete insights into borrowers’ financial behaviour.
“Neither source effectively captures how a borrower actually earns, spends and repays,” he noted.
To address the challenge, he urged financial institutions to combine internal behavioural data with external information sources such as payroll records, utility payment histories and alternative financial data to create a more comprehensive and real-time picture of borrowers’ repayment capacity.
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The second infrastructure gap, according to him, is the use of static risk acceptance criteria.
Osuchukwu observed that many lenders continue to assess borrowers using fixed benchmarks despite rapidly changing economic realities characterised by inflationary pressures and fluctuating interest rates.
He noted that such rigid frameworks often result in the rejection of potentially creditworthy borrowers, particularly first-time applicants and individuals with limited credit histories.
He advocated the adoption of predictive risk models capable of analysing high-frequency behavioural data and dynamically adjusting lending decisions in real time.
According to him, this would enable institutions to optimise pricing, improve portfolio quality and take preventive action before loans become distressed.
The third challenge, he said, is the disconnect between credit underwriting and collections operations.
Osuchukwu explained that collections teams often function independently from credit departments, limiting the ability of lenders to use repayment and recovery outcomes to improve future lending decisions.
As a result, underwriting systems fail to learn from actual borrower behaviour, leading to recurring pricing and risk assessment inefficiencies.
He recommended the establishment of integrated feedback systems that channel recovery performance data directly into lending platforms, allowing risk models to continuously evolve based on real-world outcomes.
Osuchukwu stressed that addressing these gaps requires lenders to move beyond traditional risk management approaches and embrace systems capable of continuously monitoring, learning from and responding to borrower behaviour.
“The lenders that lead over the next year will be those that treat credit not as an isolated transaction, but as a continuous, dynamic process,” he said.
