Failure prediction of insurance companies in kenya
Shareholders, policyholders and other stakeholders invest their capital for a return, guarantee of compensation when disaster falls or a policy matures among other objectives. The ability to sustain positive returns and promise to honor claims obligations as they fall due is critical for the insurance industry and other investment ventures. However, business failure is unavoidable, but what is important is the ability to detect such failures well in advance and avoid unnecessary economic losses. In this paper, the aim was to expose and explore possible indicators of impending failure and develop a failure prediction model for insurance companies in Kenya. Investigation reports of various Kenyan insurance companies and other scholarly research studies were reviewed and at least possible indicators of business failure were identified. These included high labor turnover, CEQs resignations, negative earnings, heavy debts, weak corporate governance practices and financial mismanagement. A failure prediction model was derived for both composite and general insurance businesses. The data used to develop the model was derived from financial statements submitted to the Commissioner of Insurance (Kenya) annually. The MDA technique was used to come with the coefficients using the SPSS program. The model was at least able to classify failing and non-failing companies in at least the period of the study (1989- 2004) for the companies in the study. The model indicated a 100% correct classification of the initial failed companies and at least 80% of the non-failed. The model was at least able to detect failure two years before closure of the affected companies commenced. The results were slightly different between the models for composite insurance companies basis and general insurance companies. The results show that business failure indicators can be identified and failure prediction for insurance companies can be developed.