The applicability of credit scoring models in emerging economies: an evidence from Jordan
Maher Ala’raj,
Maysam Abbod and
Mohammed Radi
International Journal of Islamic and Middle Eastern Finance and Management, 2018, vol. 11, issue 4, 608-630
Abstract:
Purpose - The purpose of this study is to propose an objective and efficient method for assessing credit risk by introducing and investigating to a greater extent the applicability of credit scoring models in the Jordanian banks and to what range they can be used to achieve their strategic and business objectives. Design/methodology/approach - The research methodology comprises two phases. The first phase is the model development. Three modeling techniques are used to build the scoring models, namely, logistic regression (LR), artificial neural network (NN) and support vector machine (SVM), and the best performing model is selected for next stage. The second phase is two-fold: linking the credit expert knowledge in a way that can enhance the outcomes of the scoring model and a profitability test to explore if the selected model is efficient in meeting banks’ strategic and business objectives. Findings - The findings showed that LR model outperformed both ANN and SVM across various performance indicators. The LR model also fits best with achieving the bank’s strategic and business objectives. Originality/value - To the best of the authors’ knowledge, this study is the first that applied several modeling and classification techniques for Jordanian banks and calibrated the best model in terms of its strategic and business objectives. Furthermore, credit experts’ knowledge was engaged with the scoring model to determine its efficiency and reliability against the sole use of an automated scoring model in the hope to encourage the application of credit scoring models as an advisory tool for credit decisions.
Keywords: Credit scoring techniques; Emerging market countries; Classification techniques; Jordanian banks (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)
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Persistent link: https://EconPapers.repec.org/RePEc:eme:imefmp:imefm-02-2017-0048
DOI: 10.1108/IMEFM-02-2017-0048
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