| Reflecting various mortality risk factors in actuarial calculations is becoming an increasingly important issue within the life insurance market. Doing this enables insurers to provide more equitable life insurance and annuity benefits for individuals in different risk classes and allows them to manage mortality/longevity risk more efficiently. In order to include determinants of mortality in a mathematical model, it is crucial to identify risk factors and to gain an understanding of their nature and relationships among them.;After reviewing numerous articles regarding mortality, the longitudinal survey data from the Canadian National Population Health Survey was used for analysis and parametrization of the model, focusing on basic determinants of adult mortality. Based on statistically significant risk factors, risk classes were generated and mortality differentials among these classes were quantified.;The impact of mortality differentials on actuarial calculations in life insurance and annuities was investigated. In addition to this, the variance of present values for term insurance policies in the Markov framework was considered. Also, other applications for selective lapsation and reentry term insurance products were explored by extending the mortality model.;Keywords: Annuities, generalized linear model, life insurance, Markov chain, mortality, multi-state model, reentry term, risk classification, risk factors, selective lapsation.;This thesis explores a method of considering risk variables in a statistical mortality model. The model uses the Markov process, which is a widely used model in actuarial science, combined with generalized linear models, so that the model can reflect the nature of the determinants of mortality. |
