A zero-inflated non default rate regression model for credit scoring data

摘要

The aim of this paper is to propose a survival credit risk model that jointly accommodates three types of time-to-default found in bank loan portfolios. It leads to a new framework that extends the standard cure rate model introduced by Berkson and Gage (1952) regarding the accommodation of zero-inflations. In other words, we propose a new survival model that takes into account three different types of individuals which have so far not been jointly accounted for: (i) an individual with an event at the starting time (zero time); (ii) non susceptible for the event, or (iii) susceptible for the event. Considering this, the zero-inflated Weibull non default rate regression models, which include a multinomial logistic link for the three classes, are presented using an application for credit scoring data. The parameter estimation is reached by the maximum-likelihood estimation procedure and Monte Carlo simulations are carried out to assess its finite sample performance.