Predicting Mortality Rates and Longevity Using Cains -Blake-Dowd Model

Pension schemes and annuity providers frequently guarantee their retirement payouts until the retirees' deaths. As a result of longer life expectancies and declining rates of death in old age, trends in mortality and longevity have become evident. Academicians and actuaries have been forced to concentrate their research on mortality and longevity concerns in particular as a result of this. Instead of a provident fund, the new National Social Security Fund Act Number 45 of 2013 established a pension fund that is a requirement for every employee. Annuity service providers are exposed to the longevity risk when the scheme's participants retire. For pricing and reserving, appropriate modeling tools or projected life tables are required. In comparison to deterministic models, which were based on projected present values, stochastic models allow a variety of risk causes and components as well as pertinent effect on portfolio performance. The long term mean level of Longevity has become more uncertain exposing the annuity service providers such as assurance companies and states to the risk of uncertainty after retirement. Most industrialized countries' national security systems, pension plans, and annuity providers have revised their mortality tables to account for longevity risks due to decline mortality rates and rising life expectancy. Kenya is one of the developing nations that has seen a drop-in death rates and a rise in life expectancy recently. Since developing nations choose to take the longevity risk into account when pricing and reserving annuities because such long term mean level in mortality rates declines and increases life expectancy, particularly at retirement age, pose risks to annuity service providers and pension plans that has been pricing annuities based on mortality tables that do not take these trends into account. The stochastic aspect of mortality was ignored by earlier actuarial models used to estimate trends. The actuary will therefore likely be interested in knowing how the future mortality trend utilizing stochastic models affects annuity pricing and reserve. Demographers and actuaries have since employed a variety of stochastic methods to forecast mortality while examining a variety of stochastic model ranges. The CBD stochastic model, which was the first to take longer life expectancies into account, is now extensively used, and a number of expansions and adjustments have been suggested to stop the major characteristics of mortality intensity. The CBD model, developed by Andrew Cairn, David Blake, and Kevin Dowd, is being used in this study to fit mortality rates, forecast mortality trends, using least square method and then calculate projections for life expectancy. Regarding the longevity risk, we take into account the possibilities of computing annuity benefits by connecting the benefits to actual mortality and calculating the present value on annuities. The results of the study showed that, the CBD model can be used to forecast mortality rates where parameters estimating the CBD model are performed using the bivariate random walk (drift).

Human Mortality database, defined Benefits, age-period-cohort, Defined contribution, Root Mean Square Error

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