IDEAS home Printed from https://ideas.repec.org/p/wdi/papers/2011-1015.html
   My bibliography  Save this paper

Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data

Author

Listed:
  • Evzen Kocenda
  • Martin Vojtek

Abstract

Credit to the private sector has risen rapidly in European emerging markets but its risk evaluation has been largely neglected. Using retail-loan banking data from the Czech Republic we construct two credit risk models based on logistic regression and Classification and Regression Trees. Both methods are comparably efficient and detect similar financial and socio-economic variables as the key determinants of default behavior. We also construct a model without the most important financial variable (amount of resources) that performs very well. This way we confirm significance of socio-demographic variables and link our results with specific issues characteristic to new EU members.

Suggested Citation

  • Evzen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," William Davidson Institute Working Papers Series wp1015, William Davidson Institute at the University of Michigan.
    • Handle: RePEc:wdi:papers:2011-1015
    as

    Download full text from publisher

    File URL: http://deepblue.lib.umich.edu/bitstream/2027.42/133030/1/wp1015.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. David A Grigorian & Vlad Manole, 2006. "Determinants of Commercial Bank Performance in Transition: An Application of Data Envelopment Analysis," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 48(3), pages 497-522, September.
    2. Avery, Robert B. & Calem, Paul S. & Canner, Glenn B., 2004. "Consumer credit scoring: Do situational circumstances matter?," Journal of Banking & Finance, Elsevier, vol. 28(4), pages 835-856, April.
    3. Reint Gropp & John Karl Scholz & Michelle J. White, 1997. "Personal Bankruptcy and Credit Supply and Demand," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(1), pages 217-251.
    4. 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, Decembrie.
    5. Özgür Arslan & Mehmet Baha Karan, 2010. "Consumer Credit Risk Characteristics: Understanding Income and Expense Differentials," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(2), pages 20-37, March.
    6. Lee, Tian-Shyug & Chiu, Chih-Chou & Chou, Yu-Chao & Lu, Chi-Jie, 2006. "Mining the customer credit using classification and regression tree and multivariate adaptive regression splines," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 1113-1130, February.
    7. Tor Jacobson & Jesper Lindé & Kasper Roszbach, 2005. "Credit Risk Versus Capital Requirements under Basel II: Are SME Loans and Retail Credit Really Different?," Journal of Financial Services Research, Springer;Western Finance Association, vol. 28(1), pages 43-75, October.
    8. Sexton, Donald E, Jr, 1977. "Determining Good and Bad Credit Risks among High- and Low-Income Families," The Journal of Business, University of Chicago Press, vol. 50(2), pages 236-239, April.
    9. Jacobson, Tor & Roszbach, Kasper, 2003. "Bank lending policy, credit scoring and value-at-risk," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 615-633, April.
    10. Long, Michael S., 1976. "Credit Screening System Selection," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 11(2), pages 313-328, June.
    11. Apilado, Vincent P. & Warner, Don C. & Dauten, Joel J., 1974. "Evaluative Techniques in Consumer Finance—Experimental Results and Policy Implications for Financial Institutions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 9(2), pages 275-283, March.
    12. Altman, Edward I., 1980. "Commercial Bank Lending: Process, Credit Scoring, and Costs of Errors in Lending," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 15(4), pages 813-832, November.
    13. Régis Blazy & Laurent Weill, 2006. "Why Do Banks Ask for Collateral and Which Ones ?," Working Papers of LaRGE Research Center 2006-03, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.
    14. Desai, Vijay S. & Crook, Jonathan N. & Overstreet, George A., 1996. "A comparison of neural networks and linear scoring models in the credit union environment," European Journal of Operational Research, Elsevier, vol. 95(1), pages 24-37, November.
    15. D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541, September.
    16. José Luis Gallizo & Ramon Saladrigues & Manuel Salvador, 2010. "Financial Convergence in Transition Economies: EU Enlargement," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(3), pages 95-114, May.
    17. Jesús Saurina & Carlos Trucharte, 2007. "An Assessment of Basel II Procyclicality in Mortgage Portfolios," Journal of Financial Services Research, Springer;Western Finance Association, vol. 32(1), pages 81-101, October.
    18. Andreas Charitou & Evi Neophytou & Chris Charalambous, 2004. "Predicting corporate failure: empirical evidence for the UK," European Accounting Review, Taylor & Francis Journals, vol. 13(3), pages 465-497.
    19. J Banasik & J Crook & L Thomas, 2003. "Sample selection bias in credit scoring models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 822-832, August.
    20. Alberto F. Alesina & Francesca Lotti & Paolo Emilio Mistrulli, 2013. "Do Women Pay More For Credit? Evidence From Italy," Journal of the European Economic Association, European Economic Association, vol. 11, pages 45-66, January.
    21. Lawrence, Edward C & Arshadi, Nasser, 1995. "A Multinomial Logit Analysis of Problem Loan Resolution Choices in Banking," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(1), pages 202-216, February.
    22. Alexis Derviz & JiÅí Podpiera, 2008. "Predicting Bank CAMELS and S&P Ratings: The Case of the Czech Republic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 44(1), pages 117-130, January.
    23. Marcello Bofondi & Francesca Lotti, 2006. "Innovation in the Retail Banking Industry: The Diffusion of Credit Scoring," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 28(4), pages 343-358, June.
    24. Robert B. Avery & Paul S. Calem & Glenn B. Canner, 2004. "Consumer credit scoring: do situational circumstances matter?," BIS Working Papers 146, Bank for International Settlements.
    25. Nanny Wermuth & D.R. Cox, 1998. "On the Application of Conditional Independence to Ordinal Data," International Statistical Review, International Statistical Institute, vol. 66(2), pages 181-199, August.
    26. Hubert Gabrisch & Lucjan T. Orlowski, 2010. "Interest Rate Convergence in Euro-Candidate Countries: Volatility Dynamics of Sovereign Bond Yields," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(6), pages 69-85, November.
    27. Evžen Koèenda & Jan Hanousek & Peter Ondko, 2007. "The Banking Sector in New EU Member Countries: A Sectoral Financial Flows Analysis (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 57(5-6), pages 200-224, August.
    28. Blochlinger, Andreas & Leippold, Markus, 2006. "Economic benefit of powerful credit scoring," Journal of Banking & Finance, Elsevier, vol. 30(3), pages 851-873, March.
    29. Dinh, Thi Huyen Thanh & Kleimeier, Stefanie, 2007. "A credit scoring model for Vietnam's retail banking market," International Review of Financial Analysis, Elsevier, vol. 16(5), pages 471-495.
    30. David Feldman & Shulamith Gross, 2005. "Mortgage Default: Classification Trees Analysis," The Journal of Real Estate Finance and Economics, Springer, vol. 30(4), pages 369-396, June.
    31. Stefano Caselli & Stefano Gatti & Francesca Querci, 2008. "The Sensitivity of the Loss Given Default Rate to Systematic Risk: New Empirical Evidence on Bank Loans," Journal of Financial Services Research, Springer;Western Finance Association, vol. 34(1), pages 1-34, August.
    32. Ceyla Pazarbasioglu & Miss Gudrun Johnsen & Mr. Paul Louis Ceriel Hilbers & Ms. Inci Ötker, 2005. "Assessing and Managing Rapid Credit Growth and the Role of Supervisory and Prudential Policies," IMF Working Papers 2005/151, International Monetary Fund.
    33. Ranjula Bali Swain, 2007. "The demand and supply of credit for households," Applied Economics, Taylor & Francis Journals, vol. 39(21), pages 2681-2692.
    Full references (including those not matched with items on IDEAS)

    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. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
    2. Hussein A. Abdou & John Pointon, 2011. "Credit Scoring, Statistical Techniques And Evaluation Criteria: A Review Of The Literature," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(2-3), pages 59-88, April.
    3. Ha Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," Working Papers hal-04133309, HAL.
    4. Timotej Jagric & Vita Jagric & Davorin Kracun, 2011. "Does Non-linearity Matter in Retail Credit Risk Modeling?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(4), pages 384-402, August.
    5. Fabián Enrique Salazar Villano, 2013. "Cuantificación del riesgo de incumplimiento en créditos de libre inversión: un ejercicio econométrico para una entidad bancaria del municipio de Popayán, Colombia," Estudios Gerenciales, Universidad Icesi.
    6. Dorfleitner, G. & Just-Marx, S. & Priberny, C., 2017. "What drives the repayment of agricultural micro loans? Evidence from Nicaragua," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 89-100.
    7. Ha Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," Working Papers hal-04141336, HAL.
    8. Zhiyong Li & Xinyi Hu & Ke Li & Fanyin Zhou & Feng Shen, 2020. "Inferring the outcomes of rejected loans: an application of semisupervised clustering," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 631-654, February.
    9. K Rajaratnam & P Beling & G Overstreet, 2010. "Scoring decisions in the context of economic uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 421-429, March.
    10. Huseyin Ince & Bora Aktan, 2009. "A comparison of data mining techniques for credit scoring in banking: A managerial perspective," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 10(3), pages 233-240, March.
    11. Singh, Ramendra Pratap & Singh, Ramendra & Mishra, Prashant, 2021. "Does managing customer accounts receivable impact customer relationships, and sales performance? An empirical investigation," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    12. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
    13. Chomsisengphet, Souphala & Elul, Ronel, 2006. "Bankruptcy exemptions, credit history, and the mortgage market," Journal of Urban Economics, Elsevier, vol. 59(1), pages 171-188, January.
    14. Azam, Rehan & Muhammad, Danish & Syed Akbar, Suleman, 2012. "The significance of socioeconomic factors on personal loan decision a study of consumer banking local private banks in Pakistan," MPRA Paper 42322, University Library of Munich, Germany.
    15. Rais Ahmad Itoo & A. Selvarasu & José António Filipe, 2015. "Loan Products and Credit Scoring by Commercial Banks (India)," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 5(1), pages 851-851.
    16. 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.
    17. Lobna Abid & Afif Masmoudi & Sonia Zouari-Ghorbel, 2018. "The Consumer Loan’s Payment Default Predictive Model: an Application of the Logistic Regression and the Discriminant Analysis in a Tunisian Commercial Bank," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(3), pages 948-962, September.
    18. Thi Thu Tra Pham & Robert Lensink, 2008. "Household Borrowing in Vietnam," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 7(3), pages 237-261, December.
    19. Dawn Burton, 2012. "Credit Scoring, Risk, and Consumer Lendingscapes in Emerging Markets," Environment and Planning A, , vol. 44(1), pages 111-124, January.
    20. Maria Rocha Sousa & João Gama & Elísio Brandão, 2013. "Introducing time-changing economics into credit scoring," FEP Working Papers 513, Universidade do Porto, Faculdade de Economia do Porto.

    More about this item

    Keywords

    credit scoring; discrimination analysis; banking sector; pattern recognition; retail loans; CART; European Union;
    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
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • P43 - Political Economy and Comparative Economic Systems - - Other Economic Systems - - - Finance; Public Finance

    Statistics

    Access and download statistics

    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:wdi:papers:2011-1015. 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: WDI (email available below). General contact details of provider: https://edirc.repec.org/data/wdumius.html .

    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.