Abstract
This paper discusses the use of dynamic modelling in consumer credit risk assessment. It surveys the approaches and objectives of behavioural scoring, customer scoring and profit scoring. It then investigates how Markov chain stochastic processes can be used to model the dynamics of the delinquency status and behavioural scores of consumers. It discusses the use of segmentation, mover–stayer models and the use of second‐ and third‐order models to improve the fit of such models. The alternative survival analysis proportional hazards approach to estimating when default occurs is considered. Comparisons are made between the ways credit risk is modelled in consumer lending and corporate lending.
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