2023 Australasian Actuarial Education and Research Symposium

Francesco Ungolo

University of New South Wales

An augmented variable Dirichlet Process Mixture model for the analysis of dependent lifetimes

Insurance and annuity products issued on multiple lives require the use of statistical models which account for lifetime dependence. This work presents a Dirichlet Process Mixture-based approach which allows to model dependent lifetimes within a group, such as married couples, accounting for individual as well as group-specific covariates. The approach allows to account for right censoring and left truncation as typical of survival analysis. The model is analysed in a fully Bayesian setting and illustrated to jointly model the lifetime of male-female couples in a portfolio of joint and last survivor annuities of a Canadian life insurer. The model shows an improved in-sample and out-of-sample performance compared to traditional approaches assuming independent lifetimes, and offers additional insights on determinants of the dependence between lifetimes and on their impact on joint and last survivor annuity prices.