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Bank Credit Risk Analysis with K-Nearest-Neighbor Classifier: Case of Tunisian Banks

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  • Aida Krichene Abdelmoula

    (Institut des Hautes Etudes Commerciales de Carthage, University of Carthage, Tunisia)

Abstract

Credit risk is defined as the risk that borrowers will fail to pay its loan obligations. In recent years, a large number of banks have developed sophisticated systems and models to help bankers in quantifying, aggregating and managing risk. The outputs of these models also play increasingly important roles in banks’ risk management and performance measurement processes. In this study we try to tackle the question of default prediction of short term loans for a Tunisian commercial bank. We use a database of 924 credit records of Tunisian firms granted by a Tunisian commercial bank from 2003 to 2006. The K-Nearest Neighbor classifier algorithm was conducted and the results indicate that the best information set is relating to accrual and cash-flow and the good classification rate is in order of 88.63 % (for k=3). A curve ROC is plotted to assess the performance of the model. The result shows that the AUC (Area Under Curve) criterion is in order of 87.4% (for the first model), 95% (third model) and 95.6% for the best model with cash flow information.

Suggested Citation

  • Aida Krichene Abdelmoula, 2015. "Bank Credit Risk Analysis with K-Nearest-Neighbor Classifier: Case of Tunisian Banks," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 14(1), pages 79-106, March.
    • Handle: RePEc:ami:journl:v:14:y:2015:i:1:p:79-106
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    References listed on IDEAS

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    1. Steenackers, A. & Goovaerts, M. J., 1989. "A credit scoring model for personal loans," Insurance: Mathematics and Economics, Elsevier, vol. 8(1), pages 31-34, March.
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    Cited by:

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    2. Lin Li, 2023. "Investigating risk assessment in post-pandemic household cryptocurrency investments: an explainable machine learning approach," Journal of Asset Management, Palgrave Macmillan, vol. 24(4), pages 255-267, July.
    3. Ionuț Nica & Daniela Blană Alexandru & Simona Liliana Paramon Crăciunescu & Ștefan Ionescu, 2021. "Automated Valuation Modelling: Analysing Mortgage Behavioural Life Profile Models Using Machine Learning Techniques," Sustainability, MDPI, vol. 13(9), pages 1-27, May.

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    More about this item

    Keywords

    banking sector; risk assessment; default risk; k-Nearest-Neighbor classifier; ROC curve;
    All these keywords.

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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