To model factors affecting life assurance penetration in Kenya A Case study of Narok County.

Abstract

Statistical models have for a long time been installed in numerous organizational operations and key sectors of government.Life assurance penetration is still below par in Kenya and much has to be done to correct the situation. As such a statistical model GLM was developed based on current data that help the insurance companies to address the issue better and test the real-case scenario. The GLM brings out the true picture of how different factors affecting life assurance relate to one another and their general contribution to life assurance penetration in Kenya. A logistic regression model has been used find probabilities of having a life assurance cover.n this research project, Ms excel was used to enter, explore and Graph the data. R statistical software was used to model the generalized linear models specifically the logit models for the data. This gave the statistical summary measures and relationship of predictor and explanatory variables.The research work relied on secondary data obtained from insurance firms in Narok Town. Narok Town is metropolitan town capturing all members of Narok county hence data ontained from the insurance firm gave a true picture of the whole county.The developed numerical model will enable insurance companies understand contribution of each factor of life assurance to life assurance penetration. This will also help insurance companies in making statistically informed policies and strategies to meet their consumer's expectation leading to increase in the number of their clients. In return, this will encourage future investments and country's economic growth at large.