The change in mortality trends experienced over the last decades leads to the use of projected mortality tables in order to avoid underestimation of the future liabilities and costs in long term insurance products such as life annuities and pension funds. Although the projected mortality tables aim to capture the dynamic structure of mortality in the future, the future mortality trend itself is random and systematic deviations from the projected mortality might take place. Being a non-pooling risk, the impact of this ``uncertainty risk'' on the insurance portfolios can be dramatic due to the fact that the severity resulting from it increases as the size of the portfolio. For this reason, a proper modelling of uncertainty risk in mortality trends is required.
In this work the uncertainty risk modelling in mortality trends has been studied. In this aspect, the two stochastic models in the literature, scenario based and dynamic models have been adopted and assessed their level of capturing the uncertainty in mortality trends. One of the models, the static model, has been extended to the continuous case with the allowance of the multiple cohorts in the portfolio. As defining the model, two approximation methods has been adopted to define the distribution of total number of deaths in the portfolio. Bayesian inferential procedure has been used in updating the random variables representing the uncertainty risk to the experience in the portfolio.
