Insurance companies have sold lots of deferred annuities to insurance customers for their retirement life. However, insurance companies are recently facing mortality risk due to lower mortality trend. Actuaries usually calculate premiums based on expe...
Insurance companies have sold lots of deferred annuities to insurance customers for their retirement life. However, insurance companies are recently facing mortality risk due to lower mortality trend. Actuaries usually calculate premiums based on experience life table. If realized future mortality rates are lower than the estimated mortality rates, the insurance companies may get financially distressed. Therefore, this study discusses Lee-Carter model for mortality trend and calculates premiums based on life table using the model. In order to assess the impact of mortality risk on life insurance products, the study examines two different approaches that are adopting the current mortality table and using projected mortality applying Lee-Carter model. In conclusion, we emphasize that insurance companies set up the pricing process using the projected mortality which includes a forecast of the future trends in mortality against the mortality risks.
Multiple life models are useful in multiple life insurance and multiple life annuities when the payment times of benefits in these insurance products are contingent on the future life times of at least two people. A reverse mortgage is an annuity whose monthly payments terminate at the death time of the last survivor; however, actuaries have used female life table to calculate monthly payments of a reverse mortgage. This approach may overestimate monthly payments. This paper suggests a last-survivor life table rather than a female life table to avoid the overestimation of monthly payments. Next, this paper derives the distribution of the future life time of last survivor, and calculates the expected life times of male, female and last survivor. This study calculates principal limits and monthly payments in cases of male life table, female life table and last-survivor life table, respectively.
Life times of couple insureds can be thought as correlated random variables. To calculate the premiums of these insurance products, joint survival function is needed because the probability of the time of benefit plays a important role in determining insurance premiums. Although there exists a correlation between insured people, actuaries calculate the premium assuming that the insured people's lifetimes are independent. In this study, Gaussian copula is used to reflect the correlation of the future life times. Using a Gaussian copula, this study calculates the premiums of the multiple life insurance products under the dependency assumption. Premiums based on assumption of dependent lifetimes are quite different from those based on independence assumption as its correlation is high. In this study, we shows that it is more rational to consider the dependency of life times so as to calculate the premiums of multiple life products.
Keywords : Lee-Carter model, mortality risk, multiple life insurance, copula, correlation.