Skip to main content
Log in

Modelling credit risk of portfolio of consumer loans

  • Part 1: Consumer Credit Risk Modelling
  • Published:
Journal of the Operational Research Society

Abstract

One of the issues that the Basel Accord highlighted was that, though techniques for estimating the probability of default and hence the credit risk of loans to individual consumers are well established, there were no models for the credit risk of portfolios of such loans. Motivated by the reduced form models for credit risk in corporate lending, we seek to exploit the obvious parallels between behavioural scores and the ratings ascribed to corporate bonds to build consumer-lending equivalents. We incorporate both consumer-specific ratings and macroeconomic factors in the framework of Cox Proportional Hazard models. Our results show that default intensities of consumers are significantly influenced by macro factors. Such models then can be used as the basis for simulation approaches to estimate the credit risk of portfolios of consumer loans.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4

References

  • Basel Committee on Banking Supervision (BCBS) (2004). International Convergence of Capital Measurement and Capital of Capital Standards: A revised framework. Bank of International Settlements: Basel.

  • Breslow NE (1974). Covariance analysis of censored survival data. Biometrics 30: 89–99.

    Article  Google Scholar 

  • Campbell J, Hilscher J and Szilagyi J (2008). In search of distress risk. J Financ 63: 2899–2939.

    Article  Google Scholar 

  • Cox DR (1972). Regression models and life-tables (with discussion). J Roy Stat Soc B 74: 187–220.

    Google Scholar 

  • Duffie D, Saita L and Wang K (2007). Multi-period corporate default prediction with stochastic covariates. J Financ Econ 83: 635–665.

    Article  Google Scholar 

  • Efron B (1977). The efficiency of Cox's likelihood function for censored data. J Am Stat Ass 72: 557–565.

    Article  Google Scholar 

  • Figlewski S, Frydman H, Liang W (2007). Modelling the effect of macroeconomic factors on corporate default and credit rating transitions. Working Paper no. FIN-06-007. NYU Stern School of Business.

  • Jarrow R, Lando D and Turnbull S (1997). Pricing derivatives on financial securities subject to credit risk. J Financ 50: 53–86.

    Article  Google Scholar 

  • Kalbfleisch JD and Prentice RL (1980). The Statistical Analysis of Failure Time Data. Wiley: New York.

    Google Scholar 

  • Lando D (1994). Three essays on contingent claims pricing. PhD thesis, Cornell University, Ithaca, NY.

  • Narain B (1992). Survival analysis and the credit granting decision. In: Thomas LC, Crook JN and Edelman DB (eds). Credit Scoring and Credit Control. OUP: Oxford, pp. 109–121.

    Google Scholar 

  • Shumway T (2001). Forecasting bankruptcy more accurately: A simple hazard model. J Bus 74(1): 101–124.

    Article  Google Scholar 

  • Stepanova M and Thomas LC (2002). Survival analysis methods for personal loan data. Oper Res 50: 277–289.

    Article  Google Scholar 

  • Tang L, Thomas LC, Thomas S and Bozzetto J-F (2007). It's the economy stupid: Modelling financial product purchases. Int J Bank Market 25: 22–38.

    Article  Google Scholar 

  • Thomas LC (2009). Consumer Credit Models: Pricing, Profit and Portfolios. Oxford University Press: Oxford.

    Book  Google Scholar 

  • Thomas LC, Banasik J and Crook JN (1999). Not if but when will borrowers default. J Opl Res Soc 50: 1185–1190.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by an EPSRC grant that pump primed the Quantitative Financial Risk Management Centre. We are grateful to the referees for their useful suggestions on an earlier version of this paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to L C Thomas.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Malik, M., Thomas, L. Modelling credit risk of portfolio of consumer loans. J Oper Res Soc 61, 411–420 (2010). https://doi.org/10.1057/jors.2009.123

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/jors.2009.123

Keywords

Navigation