Modelling credit risk of portfolios of consumer loans
Modelling credit risk of portfolios of consumer loans
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.
finance, credit risk, survival analysis, credit scoring
411-420
Malik, Madhur
fcf77f80-dc6b-42aa-9287-949b27f49a3f
Thomas, Lyn C.
a3ce3068-328b-4bce-889f-965b0b9d2362
March 2010
Malik, Madhur
fcf77f80-dc6b-42aa-9287-949b27f49a3f
Thomas, Lyn C.
a3ce3068-328b-4bce-889f-965b0b9d2362
Malik, Madhur and Thomas, Lyn C.
(2010)
Modelling credit risk of portfolios of consumer loans.
[in special issue: Consumer Credit Risk Modelling]
Journal of the Operational Research Society, 61 (3), part 1, .
(doi:10.1057/jors.2009.123).
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.
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Published date: March 2010
Keywords:
finance, credit risk, survival analysis, credit scoring
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Local EPrints ID: 155033
URI: http://eprints.soton.ac.uk/id/eprint/155033
ISSN: 0160-5682
PURE UUID: 61872277-733c-48f1-8ae3-9dce9f400030
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Date deposited: 02 Jun 2010 13:47
Last modified: 14 Mar 2024 01:36
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Author:
Madhur Malik
Author:
Lyn C. Thomas
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