Internal Bank-Specific Determinants of Non-Performing Loans in Zambian Commercial Banks: A Time-Series Analysis, 2018–2024

Authors

DOI:

https://doi.org/10.59413/eafj/v5.i2.10

Keywords:

Non-Performing Loans, Credit Risk, Return On Assets, Capital Adequacy, Loan-To-Deposit Ratio, Commercial Banks, Zambia

Abstract

Non-performing loans (NPLs) pose a serious threat to the soundness of the banking sector in developing countries where credit markets are shallow and borrowers are informationally opaque. This study investigates the determinants of NPLs in Zambian commercial banks at the internal bank-specific level: profitability, lending practices, efficiency, and capitalisation-proxied by the return on assets (ROA), the loan-to-deposit ratio (LDR), the efficiency ratio and the capital adequacy ratio (CAR) respectively. Using a panel of secondary data derived from annual banking sector-wide reports of the Bank of Zambia over the period 2018-2024, an Ordinary Least Squares (OLS) regression is fitted after rigorous pre- and post-estimation diagnostic testing. The regression explains 85.8 per cent of the variation in the net NPL ratio and is fully compliant with classical linear regression assumptions. The evidence suggests a significant, strong negative relation between the ROA and NPLs; also negatively and significantly related to default are the LDR and efficiency ratio. The CAR is instead significantly positively related to NPLs, thus validating the risk-shifting hypothesis where well-capitalised banks take greater credit risk. Neither the net foreign-exchange exposure nor liquidity variable is significant. The findings corroborate the significance of internal management quality in restraining credit risk and underscore that strengthening profitability, lending, and efficiency should underpin credit risk management strategy within Zambia's banking sector.

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Published

2026-06-10

How to Cite

Kalenga, D., & Chisenga, D. (2026). Internal Bank-Specific Determinants of Non-Performing Loans in Zambian Commercial Banks: A Time-Series Analysis, 2018–2024. East African Finance Journal, 5(2), 109-115. https://doi.org/10.59413/eafj/v5.i2.10

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