IDEAS home Printed from https://ideas.repec.org/a/rjr/romjef/vy2011i3p162-177.html
   My bibliography  Save this article

Consumer Credit Scoring

Author

Listed:
  • Costangioara, Alexandru

    (Oradea University, Faculty of Economic Studies)

Abstract

After presenting the main issues in consumer credit market and introducing the issue of credit scorecards, I have used statistical modeling to predict the default probabilities of applicants in a dataset of consumer loans. I have found evidence for the superior accuracy of complex non-linear estimations. In particular, the bagging model offers better results than the traditional tree and logit estimations. The proposed statistical scorecard offers a 60 percent improvement over the baseline model. Lastly, this paper argues that the management must establish a decisional probability threshold in accordance with its propensity for risk. A higher threshold requires a greater promotional effort, although the increased costs may be compensated by a more efficient communication with clients and by more flexible contractual clauses.

Suggested Citation

  • Costangioara, Alexandru, 2011. "Consumer Credit Scoring," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 162-177, September.
    • Handle: RePEc:rjr:romjef:v::y:2011:i:3:p:162-177
    as

    Download full text from publisher

    File URL: http://www.ipe.ro/rjef/rjef3_11/rjef3_2011p162-177.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Adrian Blundell-Wignall & Paul Atkinson, 2010. "Thinking beyond Basel III: Necessary Solutions for Capital and Liquidity," OECD Journal: Financial Market Trends, OECD Publishing, vol. 2010(1), pages 9-33.
    3. David Durand, 1941. "Risk Elements in Consumer Instalment Financing," NBER Books, National Bureau of Economic Research, Inc, number dura41-1, May.
    4. Rinaldi, Laura & Sanchis-Arellano, Alicia, 2006. "Household debt sustainability: what explains household non-performing loans? An empirical analysis," Working Paper Series 570, European Central Bank.
    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. Thomas Wainwright, 2011. "Elite Knowledges: Framing Risk and the Geographies of Credit," Environment and Planning A, , vol. 43(3), pages 650-665, March.
    2. Agustin Pérez-Martín & Agustin Pérez-Torregrosa & Alejandro Rabasa & Marta Vaca, 2020. "Feature Selection to Optimize Credit Banking Risk Evaluation Decisions for the Example of Home Equity Loans," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    3. Doruk Şen & Cem Çağrı Dönmez & Umman Mahir Yıldırım, 2020. "A Hybrid Bi-level Metaheuristic for Credit Scoring," Information Systems Frontiers, Springer, vol. 22(5), pages 1009-1019, October.
    4. Fernandes, Guilherme Barreto & Artes, Rinaldo, 2016. "Spatial dependence in credit risk and its improvement in credit scoring," European Journal of Operational Research, Elsevier, vol. 249(2), pages 517-524.
    5. 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.
    6. Przemys{l}aw Biecek & Marcin Chlebus & Janusz Gajda & Alicja Gosiewska & Anna Kozak & Dominik Ogonowski & Jakub Sztachelski & Piotr Wojewnik, 2021. "Enabling Machine Learning Algorithms for Credit Scoring -- Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models," Papers 2104.06735, arXiv.org.
    7. Crook, Jonathan N. & Edelman, David B. & Thomas, Lyn C., 2007. "Recent developments in consumer credit risk assessment," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1447-1465, December.
    8. Petr Jakubík & Petr Teplý, 2011. "The JT Index as an Indicator of Financial Stability of Corporate Sector," Prague Economic Papers, Prague University of Economics and Business, vol. 2011(2), pages 157-176.
    9. Büşra Alma Çallı & Erman Coşkun, 2021. "A Longitudinal Systematic Review of Credit Risk Assessment and Credit Default Predictors," SAGE Open, , vol. 11(4), pages 21582440211, November.
    10. Sanela Pasic & Adisa Omerbegovic Arapovic, 2016. "What Triggers Loan Repayment Failure of Consumer Loans – Evidence from Bosnia and Herzegovina," Eurasian Journal of Business and Management, Eurasian Publications, vol. 4(1), pages 11-22.
    11. Dimitrios Nikolaidis & Michalis Doumpos, 2022. "Credit Scoring with Drift Adaptation Using Local Regions of Competence," SN Operations Research Forum, Springer, vol. 3(4), pages 1-28, December.
    12. 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.
    13. Neuberg Richard & Hannah Lauren, 2017. "Loan pricing under estimation risk," Statistics & Risk Modeling, De Gruyter, vol. 34(1-2), pages 69-87, June.
    14. Doruk Şen & Cem Çağrı Dönmez & Umman Mahir Yıldırım, 0. "A Hybrid Bi-level Metaheuristic for Credit Scoring," Information Systems Frontiers, Springer, vol. 0, pages 1-11.
    15. Fernandes, Guilherme Barreto & Artes , Rinaldo, 2013. "Spatial correlation in credit risk and its improvement in credit scoring," Insper Working Papers wpe_321, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    16. Finlay, Steven, 2011. "Multiple classifier architectures and their application to credit risk assessment," European Journal of Operational Research, Elsevier, vol. 210(2), pages 368-378, April.
    17. Yang, Yingxu, 2007. "Adaptive credit scoring with kernel learning methods," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1521-1536, December.
    18. Dangxing Chen & Weicheng Ye & Jiahui Ye, 2022. "Interpretable Selective Learning in Credit Risk," Papers 2209.10127, arXiv.org.
    19. Alessandra Canepa & Fawaz Khaled, 2018. "Housing, Housing Finance and Credit Risk," IJFS, MDPI, vol. 6(2), pages 1-23, May.
    20. Jonathan K. Budd & Peter G. Taylor, 2015. "Calculating optimal limits for transacting credit card customers," Papers 1506.05376, arXiv.org, revised Aug 2015.

    More about this item

    Keywords

    credit market; prudential regulation; statistical scorecards; logit; bagging estimations;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    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:rjr:romjef:v::y:2011:i:3:p:162-177. 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: Corina Saman (email available below). General contact details of provider: https://edirc.repec.org/data/ipacaro.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.