Risk Management Practices and Performance of Insurance Companies in Kenya

Abstract

Risk management is at the core of all insurance firms, both locally and globally. To a great extent, threats posed by poor risk management have led to massive insurance claims towards insurers leading to a reduced performance by such firms. The study's objective was to establish the influence of risk management practices on the performance of insurance firms in Kenya. The study is anchored on the Contingency theory of enterprise risk management, open systems theory, and institutional theory. A descriptive survey design was embraced. All the fifty-six (56) registered insurers for the period ended 2019 were contacted for the study. The research adopted primary besides secondary data. Preliminary data were obtained through structured questionnaires filled by underwriting managers or the equivalent in each firm. Secondary data was sourced from IRA industry annual reports designed for the last five years, 2015-2019. Data analysis was performed through descriptive and inferential statistics, correlation analysis alongside multiple regression. The findings established a statistically significant correlation between Risk Monitoring/Control and Performance (r=0.755, p-value=0.000). Risk mitigation was also found to significantly influence the performance of Kenyan registered insurers (r=0.435, p-value=0.001). A significant positive relationship was also established between Risk Identification and the performance of insurance companies in Kenya (r=0.355, pvalue= 0.010). However, Risk Assessment was established to have an inconsequential influence on Kenyan registered insurers' performance (r=0.207, p-value=0.140). The collective influence of Risk Management techniques on the insurers' performance was established to be positively significant. The study has contributed towards theory by researchers, policy alongside management gaining a vibrant picture of the effect of Peril Supervision techniques on Processes. Therefore, the study recommends underwriting firms implement risk management practices through good data mining techniques and enhanced artificial intelligence systems to help capture real-life information on risk management practices. The research also recommends the implementation of risk management practices since they have been established to influence performance. The study was limited due to its adoption of a cross-sectional survey design and was conducted in the insurance subsector, not the entire financial sector. Hence, the study recommends that future research adopt a longitudinal study design on other financial sectors.