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Credit scoring for the supermarket and retailing industry: analysis and application proposal

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Abstract

This paper develops and tests a credit scoring model focused on the supermarket and retailing industry which can help financial institutions in assessing credit requests coming from customers belonging to these industries category. The empirical study has the objective of answering two questions: (1) Which ratios better discriminate the companies based on their being solvent or insolvent? (2) What is the relative importance of these ratios? To do this, several statistical techniques with a multifactorial focus have been applied. The overall approach is the same as the one in Altman (1968), but the application of the design as well as the purpose of it are different. Through the application of several statistical techniques, the credit scoring model has been proved to be effective in assessing credit scoring applications within the super-market and retailing industry under certain conditions.

Suggested Citation

  • Raffaele Manini & Oriol Amat, 2018. "Credit scoring for the supermarket and retailing industry: analysis and application proposal," Economics Working Papers 1614, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:1614
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    References listed on IDEAS

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    1. Ligang Zhou & Kin Keung Lai & Jerome Yen, 2009. "Credit Scoring Models With Auc Maximization Based On Weighted Svm," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 8(04), pages 677-696.
    2. Sebnem Kalemli-Ozcan & Bent Sorensen & Carolina Villegas-Sanchez & Vadym Volosovych & Sevcan Yesiltas, 2015. "How to Construct Nationally Representative Firm Level Data from the Orbis Global Database: New Facts and Aggregate Implications," NBER Working Papers 21558, National Bureau of Economic Research, Inc.
    3. Anderson, Raymond, 2007. "The Credit Scoring Toolkit: Theory and Practice for Retail Credit Risk Management and Decision Automation," OUP Catalogue, Oxford University Press, number 9780199226405.
    4. Hu, Yu-Chiang & Ansell, Jake, 2007. "Measuring retail company performance using credit scoring techniques," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1595-1606, December.
    5. Sørensen, Bent E & Kalemli-Özcan, Sebnem & Volosovych, Vadym & Villegas-Sanchez, Carolina & Yesiltas, Sevcan, 2015. "How to construct nationally representative firm level data from the ORBIS global database," CEPR Discussion Papers 10829, C.E.P.R. Discussion Papers.
    6. Paleologo, Giuseppe & Elisseeff, André & Antonini, Gianluca, 2010. "Subagging for credit scoring models," European Journal of Operational Research, Elsevier, vol. 201(2), pages 490-499, March.
    7. Ochoa P., Juan Camilo & Galeano M., Wilinton & Agudelo V., Luis Gabriel, 2010. "Construcción de un modelo de scoring para el otorgamiento de crédito en una entidad financiera," Perfil de Coyuntura Económica, Universidad de Antioquia, CIE, November.
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    More about this item

    Keywords

    Credit scoring; supermarket industry; retail industry; bank analysis.;
    All these keywords.

    JEL classification:

    • M1 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration

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