| dc.description.abstract | 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. | en |
