Influence of competitive strategy on performance of insurance industry in Kenya
The study set out to deal with three objectives. The first objective was to determine performance of the insurance industry in Kenya as presented by return on assets; the second objective was to determine relationship between performance and capital adequacy, reinsurance risk, expenses, claims, investment income, underwriting profit and leverage. The third objective was to determine insurance penetration for general business, life business and total penetration. All insurance company results were included in the study over a ten year period starting in 2004 to 2013. Financial performance was determined by calculating return on assets. Insurance penetration was computed by dividing gross premiums written for the entire industry over the ten year period to gross domestic product. Relationship between financial performance and the determinant variables was determined using regression analysis while relationship between variables was measured using the Pearson’s correlation coefficients. It was found that financial performance of the insurance industry averaged 4% over the ten year period with a minimum of 3% and a maximum of 5%. Insurance penetration for general business averaged 1.92% with a minimum of 1.75% and a maximum of 2.28%. Life insurance penetration showed an average of 0.92% with a minimum of 0.77% and a maximum of 1.16%. The results showed that general insurance penetration is twice that of life. It was found that a relationship exists between financial performance and the determinant variables. Capital adequacy had a medium relationship with performance with a correlation factor of 0.492. Reinsurance risk had a small and negative relationship with performance as shown by the correlation factor of -0.141. Investment income had a correlation factor of 0.856 implying a very strong relationship with performance. This was statistically significant at 0.05 level two tailed (95%); while leverage had a medium negative relationship with performance with a correlation factor of -.0387. Claims had a strong positive relationship with performance with a correlation factor of 0.746. This was statistically significant at 0.01 (90%); while combined expenses had a small positive relationship with performance with a factor of 0.298. Underwriting profits had a medium relationship with performance with a factor of 0.410. The results also showed a good linear relationship between performance and the determinant variables with an adjusted R-squared of 0.615 meaning that the variables explain 61.5% of the variations on performance while 38.5% is explained by other factors not in the model. Although performance averaged 4% there is room for improvement given the low penetration ratio established during the study. It was also found that claims ratio averaged 73% which is high. Efforts need to be made to reduce this ratio by strictly adhering to good underwriting practices and the use of actuaries to properly cost insurance products. Combined ratio was also high averaging over 100%. This means management expenses are too high in the industry and efforts have to be made to control these expenses.