ANALYSIS OF LONGEVITY RISK USING STOCHASTIC MORTALITY MODEL - Fayyadh Rifqi, Muhammad
Mortality refers to the rate of death in a population during a certain period. Mortality information is collected in life tables. A decreasing trend in mortality or an increase in life expectancy results in improved health indicators. However, this leads to a risk for insurance companies providing annuities or pension funding, known as longevity risk. The transition of deterministic life tables to stochastic life tables is an option offered to minimize this risk. The stochastic life table is obtained after modeling stochastic mortality. The Lee-Carter model is an age-specific stochastic mortality model that can forecast the log mortality rate in the future. This model has parameters that need to be estimated and there are time-dependent parameters. The ARIMA process as a stochastic process and time series model are required to forecast the mortality rate in the Lee-Carter model through its parameters. The forecasted mortality rate will be predicted using the assumption of constant force of mortality. The predicted probability of death is used to valuing the life annuity. In analyzing the longevity risk, the VaR and TVaR as the risk measures are predicted based on the distribution of life annuity valuation losses between the stochastic life table and the deterministic life table. At 90%, 95%, and 99% confidence levels, a certain range of values is obtained to predict the risk incurred due to the expectation of mortality rates decreasing more than the expected.