Forecasting mortality rates is crucial for insurance companies to accurately pricing policies and manage risks. accurate forecasted mortality rates enable insurance companies to minimize losses, set reasonable premiums, introduce new policies,.and manage longevity risks effectively. Improved forecasting accuracy not only benefits insurance companies but also impacts pension funds, life insurers, and social securities, making it a vital aspect of actuarial science and demographic statistics. based on this, this research provides the two factor Cairns-Blake-Dowd (CBD) model to forecasting Egyptian mortality rates using R package StMoMo. Estimated of CBD parameters model by maximizing the model log-
likelihood,and the multivariate random walk with drift will be used to forecast the CBD model's parameters. The model applied on both males and females data for the period (1960-2023). The forecast is for period (2024-2043). The main finding is that CBD model is useful for specific age ranges (elderly ages) and time periods. And there is an increasing in life expectancy for both males and females in Egypt.
and manage longevity risks effectively. Improved forecasting accuracy not only benefits insurance companies but also impacts pension funds, life insurers, and social securities, making it a vital aspect of actuarial science and demographic statistics. based on this, this research provides the two factor Cairns-Blake-Dowd (CBD) model to forecasting Egyptian mortality rates using R package StMoMo. Estimated of CBD parameters model by maximizing the model log-
likelihood,and the multivariate random walk with drift will be used to forecast the CBD model's parameters.