Optimising a bank's credit portfolio Online publication date: Wed, 23-Mar-2016
by Annshirley Aba Afful; Michael Kofi Asare; Raymond Benjamin Afful
International Journal of Applied Management Science (IJAMS), Vol. 8, No. 1, 2016
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.
Online publication date: Wed, 23-Mar-2016
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