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

Francisco Louzada, Fernando F. Moreira and Mauro Ribeiro de Oliveira

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 12, 3002-3021

Abstract: 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.

Date: 2018
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DOI: 10.1080/03610926.2017.1346803

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