Predicting and Reducing Exposure to Non-Performing Loans in Emerging Markets


One of the key differentiators of good governance performance in the banking sector is effective credit risk management and customer service.


Growth in the value of the loan portfolio with better diversification


Reduction in the delinquency rates driven by better customer credit profiles


Reduction in default rates driven by better credit risk scoring


Our client is one of the largest commercial banks in Nigeria with over 3 million customers, 161 branch offices, NGN ₦1 trillion in total assets and a loan book worth over NGN ₦619 million. Over the past year they have delivered 15% growth in profit after tax through a concerted effort in improving the quality of their funding base. They wanted to find a way to proactively strengthen credit quality controls and risk management within their commercial loan portfolio given the negative economic outlook for the global economy.


Our client wanted to focus on a solution for one of their digital lending platforms which offers individuals and businesses loans of up to NGN ₦5 million in 5 minutes. One of the key objectives in the credit portfolio management is to diversify exposure to risks to the extent that the interest rate premiums collected on all loans must always be greater than loss given defaults. What is more, default rates, delinquency rates and the probability of default must be kept low at all times in order to protect the underlying liquidity and credit quality of the entire loan portfolio.

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Our principal data scientist for this project had extensive experience in credit risk insurance, quantitative risk management and microfinance. After exploring the performance of the existing loan portfolio and credit risk controls we identified a way to grow a profitable loan portfolio that not only minimises exposure to fraud and credit risks but also provides a deeper insight into consumer behaviours and business spending patterns. This analysis involved an assessment of income, spending patterns, the validation of mobile phone data and typographical discipline in filling out the loan applications.


Our solution provided an innovative and evidence based solution to reduce exposure to loan defaults by 8% and reduced delinquency rates by 5%. This provided even greater value to the senior leadership team since the model could be scaled and implemented across other loan portfolios in order to enrich their understanding of customer behaviours.

Note: Delivered in partnership with Pivigo Limited.