Zero-inflated cure rate regression models for time-to-default with applications

In this paper, we introduce a methodology based on zero-inflated long-term survival data in order to deal with fraud rate estimation in bank loan portfolios. Our approach enables us to accommodate three different types of loan borrowers, i.e., fraudsters, those who are susceptible to default and finally, those who are not susceptible to default. Regarding to the survival analysis framework, an advantage of our approach is to accommodate zero-inflated times, which is not possible in the standard cure rate model introduced by Berkson & Gage. To illustrate the proposed method, a real dataset of loan survival times is fitted by the zero-inflated Weibull cure rate model. The parameter estimation is reached by maximum likelihood estimation procedure and Monte Carlo simulations are carried out to check its finite sample performance