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Credit risk estimation using payment history data: a comparative study of Turkish retail stores

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  • Mehmet Karan
  • Aydın Ulucan
  • Mustafa Kaya

Abstract

Our paper presents a comparative study applying logistic regression and multiple criteria decision analysis tools to the operations of wholesalers to assess the credit risk of their retailers using payment history data and to cluster the risky customers by ranking their risk levels. Our sample comprises approximately 6,000 retailer customers and 600.000 transactions of one of the major wholesalers of Turkey. Our findings emphasize the importance of using payment history and some non-financial factors data for predicting the creditworthiness of a firm. Copyright Springer-Verlag 2013

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  • Mehmet Karan & Aydın Ulucan & Mustafa Kaya, 2013. "Credit risk estimation using payment history data: a comparative study of Turkish retail stores," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(2), pages 479-494, March.
    • Handle: RePEc:spr:cejnor:v:21:y:2013:i:2:p:479-494
    DOI: 10.1007/s10100-012-0242-y
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    1. Levy, Daniel & Bergen, Mark & Dutta, Shantanu & Venable, Robert, 1997. "The Magnitude of Menu Costs: Direct Evidence from Large U.S. Supermarket Chains," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 112(3), pages 791-824.
    2. Jones,Stewart & Hensher,David A. (ed.), 2008. "Advances in Credit Risk Modelling and Corporate Bankruptcy Prediction," Cambridge Books, Cambridge University Press, number 9780521689540.
    3. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    4. Paul Asquith & Robert Gertner & David Scharfstein, 1994. "Anatomy of Financial Distress: An Examination of Junk-Bond Issuers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(3), pages 625-658.
    5. Pendaraki, K. & Zopounidis, C. & Doumpos, M., 2005. "On the construction of mutual fund portfolios: A multicriteria methodology and an application to the Greek market of equity mutual funds," European Journal of Operational Research, Elsevier, vol. 163(2), pages 462-481, June.
    6. Michael Doumpos & Fotios Pasiouras, 2005. "Developing and Testing Models for Replicating Credit Ratings: A Multicriteria Approach," Computational Economics, Springer;Society for Computational Economics, vol. 25(4), pages 327-341, June.
    7. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    8. Wilbur G. Lewellen & John J. McConnell & Jonathan A. Scott, 1980. "Capital Market Influences On Trade Credit Policies," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 3(2), pages 105-113, June.
    9. G. Baourakis & M. Conisescu & G. Dijk & P. Pardalos & C. Zopounidis, 2009. "A multicriteria approach for rating the credit risk of financial institutions," Computational Management Science, Springer, vol. 6(3), pages 347-356, August.
    10. Park, Sangkyun & Peristiani, Stavros, 1998. "Market Discipline by Thrift Depositors," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 30(3), pages 347-364, August.
    11. J. Stephen Ferris, 1981. "A Transactions Theory of Trade Credit Use," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 96(2), pages 243-270.
    12. Zopounidis, Constantin & Doumpos, Michael, 1999. "A Multicriteria Decision Aid Methodology for Sorting Decision Problems: The Case of Financial Distress," Computational Economics, Springer;Society for Computational Economics, vol. 14(3), pages 197-218, December.
    13. Özgür Arslan & Mehmet Baha Karan, 2009. "Credit risks and internationalization of SMEs," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 10(4), pages 361-368, September.
    14. Paloma López-García & Sergio Puente, 2006. "Business demography in Spain: determinants of firm survival," Working Papers 0608, Banco de España.
    15. Ann Gaeremynck & Marleen Willekens, 2003. "The endogenous relationship between audit-report type and business termination: evidence on private firms in a non-litigious environment," Accounting and Business Research, Taylor & Francis Journals, vol. 33(1), pages 65-79.
    16. Blum, M, 1974. "Failing Company Discriminant-Analysis," Journal of Accounting Research, Wiley Blackwell, vol. 12(1), pages 1-25.
    17. Nam Sang Cheng & Richard Pike, 2003. "The trade credit decision: evidence of UK firms," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 24(6-7), pages 419-438.
    18. Sunti Tirapat & Aekkachai Nittayagasetwat, 1999. "An Investigation of Thai Listed Firms' Financial Distress Using Macro and Micro Variables," Multinational Finance Journal, Multinational Finance Journal, vol. 3(2), pages 103-125, June.
    19. Andrew W. Lo, "undated". "Logit Versus Discriminant Analysis: A Specification Test," Rodney L. White Center for Financial Research Working Papers 11-85, Wharton School Rodney L. White Center for Financial Research.
    20. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    21. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    22. Edward I. Altman & Gabriele Sabato, 2013. "MODELING CREDIT RISK FOR SMEs: EVIDENCE FROM THE US MARKET," World Scientific Book Chapters, in: Oliviero Roggi & Edward I Altman (ed.), Managing and Measuring Risk Emerging Global Standards and Regulations After the Financial Crisis, chapter 9, pages 251-279, World Scientific Publishing Co. Pte. Ltd..
    23. Männasoo, Kadri & Mayes, David G., 2009. "Explaining bank distress in Eastern European transition economies," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 244-253, February.
    24. Santomero, Anthony M. & Vinso, Joseph D., 1977. "Estimating the probability of failure for commercial banks and the banking system," Journal of Banking & Finance, Elsevier, vol. 1(2), pages 185-205, October.
    25. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    26. Wilcox, Jw, 1973. "Prediction Of Business Failure Using Accounting Data," Journal of Accounting Research, Wiley Blackwell, vol. 11, pages 163-179.
    27. Doumpos, Michael & Zopounidis, Constantin, 2001. "Assessing financial risks using a multicriteria sorting procedure: the case of country risk assessment," Omega, Elsevier, vol. 29(1), pages 97-109, February.
    28. Peter Back, 2005. "Explaining financial difficulties based on previous payment behavior, management background variables and financial ratios," European Accounting Review, Taylor & Francis Journals, vol. 14(4), pages 839-868.
    29. Jones,Stewart & Hensher,David A. (ed.), 2008. "Advances in Credit Risk Modelling and Corporate Bankruptcy Prediction," Cambridge Books, Cambridge University Press, number 9780521869287.
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    Cited by:

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    2. Salihu, Armend & Shehu, Visar, 2020. "A Review of Algorithms for Credit Risk Analysis," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020, pages 134-146, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    3. Vahid Baradaran & Maryam Keshavarz, 2017. "System dynamics modelling of retailers' credit risk," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 26(3), pages 380-396.
    4. Oliver Lukason & Germo Valgenberg, 2021. "Failure Prediction in the Condition of Information Asymmetry: Tax Arrears as a Substitute When Financial Ratios Are Outdated," JRFM, MDPI, vol. 14(10), pages 1-13, October.
    5. Ao Yu & Zhuoqiang Jia & Weike Zhang & Ke Deng & Francisco Herrera, 2020. "A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods," Sustainability, MDPI, vol. 12(5), pages 1-21, February.

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