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Optimising a bank's credit portfolio

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  • Annshirley Aba Afful
  • Michael Kofi Asare
  • Raymond Benjamin Afful

Abstract

The purpose of this paper is to show the practical application of linear programming and logistic regression models in the formulation of an optimal bank credit policy. Firstly, we formulate a linear programming model and develop a solution (using the simplex algorithm) that optimally allocates funds, where a financial institution is facing the problem of allocation of limited funds among different types of loans/advances at different markup/interest rates with varying degree of risk (bad debts). We go further, after optimal allocation of funds, to propose a binary logistic regression model (BLRM) to discriminate loan defaulters from non-defaulters. The study revealed that the available funds of GH¢166 million for credit facilities will yield a return of GH¢35.25 million after allocation. Four important influences were identified and the LR proposed predicts that about 80% of prospective customers are likely not to default.

Suggested Citation

  • Annshirley Aba Afful & Michael Kofi Asare & Raymond Benjamin Afful, 2016. "Optimising a bank's credit portfolio," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 8(1), pages 68-82.
    • Handle: RePEc:ids:injams:v:8:y:2016:i:1:p:68-82
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    References listed on IDEAS

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    1. Ann Tarca & Richard D. Morris & Melissa Moy, 2013. "An Investigation of the Relationship between Use of International Accounting Standards and Source of Company Finance in G ermany," Abacus, Accounting Foundation, University of Sydney, vol. 49(1), pages 74-98, March.
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