LAUSR

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.