Joint modeling: an application in behavioural scoring

Abstract

Survival analysis has become an appealing approach in credit scoring. It is able to readily incorporate time-dependent covariates and dynamically predict the survival probability. However, the difference between endogenous and exogenous covariates is ignored in the existing extended Cox models in behavioural scoring. In this paper, we apply joint modelling framework, which can be seen as an extension of survival analysis, to overcome such deficiency of survival models. We carefully design experiments on two datasets and verify the superiority of joint modelling over the extend Cox model through cross validation on dynamic discrimination and calibration performance measures. The experimental results indicate that the joint model performance is better, especially in the calibration measure. The key reason for the better performance is discussed and illustrated.

Keywords:

• Behavioral scoring
• survival analysis
• joint model
• longitudinal data
• credit risk

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 http://www.freddiemac.com/research/datasets/sf_loanlevel_data set.html

Additional information

Funding

This work was supported by the Humanity and Social Science Youth foundation of Ministry of Education of China [grant number 16YJCZH031].