IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v33y2009i4p701-708.html
   My bibliography  Save this article

A practical approach to validating a PD model

Author

Listed:
  • Medema, Lydian
  • Koning, Ruud H.
  • Lensink, Robert

Abstract

The capital adequacy framework Basel II aims to promote the adoption of stronger risk management practices by the banking industry. The implementation makes validation of credit risk models more important. Lenders therefore need a validation methodology to convince their supervisors that their credit scoring models are performing well. In this paper we take up the challenge to propose and implement a simple validation methodology that can be used by banks to validate their credit risk modelling exercise. We will contextualise the proposed methodology by applying it to a default model of mortgage loans of a commercial bank in the Netherlands.

Suggested Citation

  • Medema, Lydian & Koning, Ruud H. & Lensink, Robert, 2009. "A practical approach to validating a PD model," Journal of Banking & Finance, Elsevier, vol. 33(4), pages 701-708, April.
  • Handle: RePEc:eee:jbfina:v:33:y:2009:i:4:p:701-708
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378-4266(08)00278-1
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Diebold, Francis X. & Chen, Celia, 1996. "Testing structural stability with endogenous breakpoint A size comparison of analytic and bootstrap procedures," Journal of Econometrics, Elsevier, vol. 70(1), pages 221-241, January.
    2. Carling, Kenneth & Jacobson, Tor & Linde, Jesper & Roszbach, Kasper, 2007. "Corporate credit risk modeling and the macroeconomy," Journal of Banking & Finance, Elsevier, vol. 31(3), pages 845-868, March.
    3. J. S. Cramer, 2004. "Scoring bank loans that may go wrong: a case study," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(3), pages 365-380.
    4. Dewald, William G & Thursby, Jerry G & Anderson, Richard G, 1986. "Replication in Empirical Economics: The Journal of Money, Credit and Banking Project," American Economic Review, American Economic Association, vol. 76(4), pages 587-603, September.
    5. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    6. McCullough, B. D. & McGeary, Kerry Anne & Harrison, Teresa D., 2006. "Lessons from the JMCB Archive," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(4), pages 1093-1107, June.
    7. Stein, Roger M., 2005. "The relationship between default prediction and lending profits: Integrating ROC analysis and loan pricing," Journal of Banking & Finance, Elsevier, vol. 29(5), pages 1213-1236, May.
    8. Dwyer, Douglas W. & Stein, Roger M., 2006. "Inferring the default rate in a population by comparing two incomplete default databases," Journal of Banking & Finance, Elsevier, vol. 30(3), pages 797-810, March.
    9. Blochlinger, Andreas & Leippold, Markus, 2006. "Economic benefit of powerful credit scoring," Journal of Banking & Finance, Elsevier, vol. 30(3), pages 851-873, March.
    10. Jürg M. Blum, 2007. "Why 'Basel II' May Need a Leverage Ratio Restriction," Working Papers 2007-04, Swiss National Bank.
    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. Tsukahara, Fábio Yasuhiro & Kimura, Herbert & Sobreiro, Vinicius Amorim & Zambrano, Juan Carlos Arismendi, 2016. "Validation of default probability models: A stress testing approach," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 70-85.
    2. Rosen, Dan & Saunders, David, 2010. "Risk factor contributions in portfolio credit risk models," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 336-349, February.
    3. Aussenegg, Wolfgang & Resch, Florian & Winkler, Gerhard, 2011. "Pitfalls and remedies in testing the calibration quality of rating systems," Journal of Banking & Finance, Elsevier, vol. 35(3), pages 698-708, March.
    4. Christopoulos, Andreas D., 2017. "The composition of CMBS risk," Journal of Banking & Finance, Elsevier, vol. 76(C), pages 215-239.
    5. Clara Cardone-Riportella & Antonio Trujillo-Ponce & Anahí Briozzo, 2013. "Analyzing the role of mutual guarantee societies on bank capital requirements for small and medium-sized enterprises," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 16(2), pages 142-159, June.
    6. Kroot, Jan & Giouvris, Evangelos, 2016. "Dutch mortgages: Impact of the crisis on probability of default," Finance Research Letters, Elsevier, vol. 18(C), pages 205-217.
    7. Floros, Ioannis & White, Joshua T., 2016. "Qualified residential mortgages and default risk," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 86-104.
    8. Dragoş Bolocan & Cristian Litan, 2011. "Estimating the Probability of Default with Applications in Provisioning the Portfolio of Clients of a Credit Institution," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 18(2), pages 271-285, December.
    9. Kavussanos, Manolis G. & Tsouknidis, Dimitris A., 2016. "Default risk drivers in shipping bank loans," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 71-94.
    10. Christopoulos, Andreas D. & Barratt, Joshua G., 2016. "Credit risk findings for commercial real estate loans using the reduced form," Finance Research Letters, Elsevier, vol. 19(C), pages 228-234.
    11. Fitzpatrick, Trevor & Mues, Christophe, 2016. "An empirical comparison of classification algorithms for mortgage default prediction: evidence from a distressed mortgage market," European Journal of Operational Research, Elsevier, vol. 249(2), pages 427-439.

    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:eee:jbfina:v:33:y:2009:i:4:p:701-708. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/jbf .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.