The zero-inflated promotion cure rate model applied to financial data on time-to-default

In this paper, we extend the promotion cure rate model studied in Yakovlev & Tsodikov [20] and Chen et al. [5] by incorporating an excess of zeros in the modeling. Despite relating covariates to the cure fraction, the current approach does not enable us to relate covariates to the fraction of zeros. The presence of excess of zeros in credit risk survival data stems from a group of loans that became defaulted shortly after the granting process. Through our proposal, all survival data available of customers is modeled with a multinomial logistic link for the three classes of banking customers: (i) individual with an event at the starting time (zero time); (ii) non-susceptible for the event, or (iii) susceptible for the event. The model parameter estimation is reached by the maximum likelihood estimation procedure and Monte Carlo simulations are carried out to assess its finite sample performance.