IDEAS home Printed from https://ideas.repec.org/a/ers/journl/vvy2002i1-2p53-68.html
   My bibliography  Save this article

A Multicriteria Hierarchical Discrimination Approach for Credit Risk Problems

Author

Listed:
  • Kosmidou K.
  • Doumpos M.
  • Zopounidis C.

Abstract

Recently, banks and credit institutions have shown an increased interest in developing and implementing credit-scoring systems for taking corporate and consumer credit granting decisions. The objective of such systems is to analyze the characteristics of each applicant (firm or individual) and support the decision making process regarding the acceptance or the rejection of the credit application. This paper addresses this problem through the use of a multicriteria classification technique, the M.H.DIS method (Multi-group Hierarchical Discrimination). M.H.DIS is applied to real-world case studies regarding the assessment of corporate credit risk and the evaluation of credit card applications. The results obtained through the M.H.DIS method are compared to the results of three well-known statistical techniques, namely linear and quadratic discriminant analysis, as well as logit analysis.

Suggested Citation

  • Kosmidou K. & Doumpos M. & Zopounidis C., 2002. "A Multicriteria Hierarchical Discrimination Approach for Credit Risk Problems," European Research Studies Journal, European Research Studies Journal, vol. 0(1-2), pages 53-68, January -.
  • Handle: RePEc:ers:journl:v:v:y:2002:i:1-2:p:53-68
    as

    Download full text from publisher

    File URL: http://www.ersj.eu/repec/ers/papers/02_12_p5.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. R. Slowinski & C. Zopounidis, 1995. "Application of the Rough Set Approach to Evaluation of Bankruptcy Risk," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 4(1), pages 27-41, March.
    2. Srinivasan, Venkat & Ruparel, Bharat, 1990. "CGX: An expert support system for credit granting," European Journal of Operational Research, Elsevier, vol. 45(2-3), pages 293-308, April.
    3. Srinivasan, Venkat & Kim, Yong H, 1987. "Credit Granting: A Comparative Analysis of Classification Procedures," Journal of Finance, American Finance Association, vol. 42(3), pages 665-681, July.
    4. 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.
    5. Kahya, Emel & Theodossiou, Panayiotis, 1999. "Predicting Corporate Financial Distress: A Time-Series CUSUM Methodology," Review of Quantitative Finance and Accounting, Springer, vol. 13(4), pages 323-345, December.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Burcu Dikmen & Güray Küçükkocaoğlu, 2010. "The detection of earnings manipulation: the three-phase cutting plane algorithm using mathematical programming," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 442-466.
    2. Tangian, Andranik, 2008. "Predicting DAX trends from Dow Jones data by methods of the mathematical theory of democracy," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1632-1662, March.
    3. Tsionas, Mike G., 2019. "Multi-objective optimization using statistical models," European Journal of Operational Research, Elsevier, vol. 276(1), pages 364-378.
    4. 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.
    5. Şaban Çelik & Bora Aktan & Bruce Burton, 2022. "Firm dynamics and bankruptcy processes: A new theoretical model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 567-591, April.
    6. Dimova, L. & Sevastianov, P. & Sevastianov, D., 2006. "MCDM in a fuzzy setting: Investment projects assessment application," International Journal of Production Economics, Elsevier, vol. 100(1), pages 10-29, March.
    7. Fernando A. F. Ferreira & Ieva Meidutė-Kavaliauskienė & Edmundas K. Zavadskas & Marjan S. Jalali & Sandra M. J. Catarino, 2019. "A Judgment-Based Risk Assessment Framework for Consumer Loans," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 7-33, January.
    8. Marco Corazza & Stefania Funari & Federico Siviero, 2008. "An MCDA-based Approach for Creditworthiness Assessment," Working Papers 177, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    9. Ioannis Tsolas, 2015. "Firm credit risk evaluation: a series two-stage DEA modeling framework," Annals of Operations Research, Springer, vol. 233(1), pages 483-500, October.
    10. Şaban Çelik, 2013. "Micro Credit Risk Metrics: A Comprehensive Review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(4), pages 233-272, October.
    11. Silvia Angilella & Maria Rosaria Pappalardo, 2021. "Assessment of a failure prediction model in the energy sector: a multicriteria discrimination approach with Promethee based classification," Papers 2102.07656, arXiv.org.
    12. Perko, Igor, 2017. "Behaviour-based short-term invoice probability of default evaluation," European Journal of Operational Research, Elsevier, vol. 257(3), pages 1045-1054.
    13. Angeliki Papana & Anastasia Spyridou, 2020. "Bankruptcy Prediction: The Case of the Greek Market," Forecasting, MDPI, vol. 2(4), pages 1-21, December.
    14. Corazza, Marco & Funari, Stefania & Gusso, Riccardo, 2016. "Creditworthiness evaluation of Italian SMEs at the beginning of the 2007–2008 crisis: An MCDA approach," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 1-26.
    15. Eduardo Fernandez & Jorge Navarro & Rafael Olmedo, 2018. "Characterization of the Effectiveness of Several Outranking-Based Multi-Criteria Sorting Methods," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1047-1084, July.
    16. Wang, Jing & Wang, Kai & Li, Xiang & Zhao, Ruiqing, 2022. "Suppliers’ trade credit strategies with transparent credit ratings: Null, exclusive, and nonchalant provision," European Journal of Operational Research, Elsevier, vol. 297(1), pages 153-163.
    17. Evangelos C. Charalambakis, 2015. "On the Prediction of Corporate Financial Distress in the Light of the Financial Crisis: Empirical Evidence from Greek Listed Firms," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 22(3), pages 407-428, November.
    18. Marco Corazza & Giovanni Fasano & Stefania Funari & Riccardo Gusso, 2021. "MURAME parameter setting for creditworthiness evaluation: data-driven optimization," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 295-339, June.
    19. Fernando A. F. Ferreira & Ronald W. Spahr & Irina F. M. D. Gavancha & Amali Çipi, 2013. "Readjusting trade-offs among criteria in internal ratings of credit-scoring: an empirical essay of risk analysis in mortgage loans," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 14(4), pages 715-740, September.
    20. Silvia Angilella & Sebastiano Mazz`u, 2013. "The Financing of Innovative SMEs: a multicriteria credit rating model," Papers 1308.0889, arXiv.org, revised Jun 2014.
    21. Angilella, Silvia & Mazzù, Sebastiano, 2015. "The financing of innovative SMEs: A multicriteria credit rating model," European Journal of Operational Research, Elsevier, vol. 244(2), pages 540-554.
    22. Marco Corazza & Giovanni Fasano & Stefania Funari & Riccardo Gusso, 2017. "PSO-based tuning of MURAME parameters for creditworthiness evaluation of Italian SMEs," Working Papers 04, Department of Management, Università Ca' Foscari Venezia.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zopounidis, Constantin & Doumpos, Michael, 2001. "A preference disaggregation decision support system for financial classification problems," European Journal of Operational Research, Elsevier, vol. 130(2), pages 402-413, April.
    2. S. Balcaen & H. Ooghe, 2004. "Alternative methodologies in studies on business failure: do they produce better results than the classical statistical methods?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/249, Ghent University, Faculty of Economics and Business Administration.
    3. Burcu Dikmen & Güray Küçükkocaoğlu, 2010. "The detection of earnings manipulation: the three-phase cutting plane algorithm using mathematical programming," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 442-466.
    4. Doumpos, M. & Kosmidou, K. & Baourakis, G. & Zopounidis, C., 2002. "Credit risk assessment using a multicriteria hierarchical discrimination approach: A comparative analysis," European Journal of Operational Research, Elsevier, vol. 138(2), pages 392-412, April.
    5. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    6. Zopounidis, Constantin & Doumpos, Michael, 2002. "Multicriteria classification and sorting methods: A literature review," European Journal of Operational Research, Elsevier, vol. 138(2), pages 229-246, April.
    7. Zopounidis, C., 1999. "Multicriteria decision aid in financial management," European Journal of Operational Research, Elsevier, vol. 119(2), pages 404-415, December.
    8. Aaro Hazak & Kadri Männasoo, 2007. "Indicators of corporate default : an EU based empirical study," Bank of Estonia Working Papers 2007-10, Bank of Estonia, revised 04 Sep 2007.
    9. McKee, Thomas E. & Lensberg, Terje, 2002. "Genetic programming and rough sets: A hybrid approach to bankruptcy classification," European Journal of Operational Research, Elsevier, vol. 138(2), pages 436-451, April.
    10. Ch. Spathis & M. Doumpos & C. Zopounidis, 2002. "Detecting falsified financial statements: a comparative study using multicriteria analysis and multivariate statistical techniques," European Accounting Review, Taylor & Francis Journals, vol. 11(3), pages 509-535.
    11. Thomas E. Mckee, 2000. "Developing a bankruptcy prediction model via rough sets theory," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 9(3), pages 159-173, September.
    12. Siskos, Yannis & Grigoroudis, Evangelos & Krassadaki, Evangelia & Matsatsinis, Nikolaos, 2007. "A multicriteria accreditation system for information technology skills and qualifications," European Journal of Operational Research, Elsevier, vol. 182(2), pages 867-885, October.
    13. Siskos, Y. & Spyridakos, A., 1999. "Intelligent multicriteria decision support: Overview and perspectives," European Journal of Operational Research, Elsevier, vol. 113(2), pages 236-246, March.
    14. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    15. 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.
    16. Fedya Telmoudi & Mohamed El Ghourabi & Mohamed Limam, 2011. "Rst–Gcbr‐Clustering‐Based Rga–Svm Model For Corporate Failure Prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(2-3), pages 105-120, April.
    17. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
    18. Michael Doumpos & Constantin Zopounidis, 1999. "A Multicriteria Discrimination Method for the Prediction of Financial Distress: The Case of Greece," Multinational Finance Journal, Multinational Finance Journal, vol. 3(2), pages 71-101, June.
    19. 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.
    20. Sancho Salcedo‐Sanz & Mario DePrado‐Cumplido & María Jesús Segovia‐Vargas & Fernando Pérez‐Cruz & Carlos Bousoño‐Calzón, 2004. "Feature selection methods involving support vector machines for prediction of insolvency in non‐life insurance companies," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 12(4), pages 261-281, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ers:journl:v:v:y:2002:i:1-2:p:53-68. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Marios Agiomavritis (email available below). General contact details of provider: https://ersj.eu/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.