| dc.description.abstract | In the present century, modelling of mortality risk has become a prerequisite consideration
in the insurance industry, especially in product pricing and claims reserving. Actuaries
and statisticians have developed various methods for modelling mortality risks for use in
insurance product pricing and claim reserving. However, there is room for more improved
methods in mortality risk modelling. The current paper was designed to model mortality
rates using a ine stochastic process, namely the Feller process. The Feller model was
derived from first principle by a simply modification of the CIR process in order to eliminate
the mean-reversion element.
The Kenyan 2010 mortality rates for both male and female population were used to fit the
derived Feller process by fi ing the data to the model. The process provided parameters
estimates of the fi ed Feller model. The models were then tested for their goodness of
fit and parameters profiled. The empirical analysis provided good and stable parameter
estimates for both the female and male model models. The goodness of fit test also
confirmed that the models perfectly fi ed the observed mortality rates data.
The results of the empirical analysis confirmed that the Feller process provides a good
avenue for modelling mortality rates for both female and male populations. The model is
easy to implement in the calculation of the mortality rates since only the time element
is needed – the parameters have been estimated. The model can be used in actuarial
practice for insurance product pricing and claim reserving processes. | en_US |
