Survival Analysis in LGL Modelling for Retail Mortgage Portfolios

Loss given default (LGD) is one of the key parameters banks need in order to estimate expected and unexpected losses. These losses are necessary for credit pricing and for the calculation of the regulatory requirements regarding Basel III. Loss given cure (LGC) and loss given liquidation (LGL) are the components used in the LGD model for retail mortgage portfolios of Rabobank. In particular, this study focuses on the modelling of the LGL component. LGL depends on the recovery cash flow data of defaulted loans. The main difficulty in modelling LGL is incorporating the incomplete recovery cash flow data. This study makes use of the statistical technique of survival analysis (SA) in order to solve this main difficulty. It uses the modelling and validation choices from earlier studies that satisfy regulatory requirements. The two used SA methods, the Cox Proportional Hazards model and the Extended Cox model, examine the effects of risk drivers on the length of repayment of a monetary unit. With the models, Rabobank can estimate LGL for newly defaulted loans. At the same time, Rabobank gets insight into what drives high LGL estimations and what drives low LGL estimations. The models scored high on discriminatory power and calibration. Therefore, our results show high potential of applying SA in the modelling of the LGL component, used in the LGD model for retail mortgage portfolios.