Operational risk modeling for general insurance companies in Kenya

Date
2018
Authors
Mwangi, Michael Maina
Journal Title
Journal ISSN
Volume Title
Publisher
Strathmore University
Abstract
This study looked at the quantification of operational risk based capital for general insurance companies in Kenya. It is important to note that the regulator requires all insurance companies to compute risk based capital annually. The study pointed out the various operational risk categories and analyzed the operational risk modeling approaches that have been developed in the insurance sector globally. In Kenya, the model used by the regulator to quantify operational risk capital is that recommended by the actuarial profession in the United Kingdom (Solvency II). The main shortcomings of the model used by the regulator were cited as lack of prudence in the estimation of capital requirements and the failure to truly indicate how insurance company operations interact leading to operational losses. The study then illustrated how a proxy-a hybrid modeling approach, could be used to quantify operational risk. The hybrid model was shown to be more prudent than the standardized approach used by the regulator. The methodology involved modeling a general insurance company and creating a hybrid simulations model for operational risk losses. Further, operational risk capital estimates were computed using the model by the regulator and the hybrid simulations model. The operational risk capital estimates were compared and tested for adequacy. The results led to the conclusion that the hybrid model yielded a more prudent operational risk capital estimate than the model used by the regulator. Based on the overall conclusion that the standardized method may not be fully adequate in computing operational risk capital, it is hoped that this study will encourage best practice in computing operational risk capital. It is also hoped that the study increases interest in Kenya's actuarial profession in the emerging field of operational risk
Description
A Research project submitted in partial fulfillment of the requirements for the degree of Bachelor of Business Science in Actuarial Science at Strathmore University
Keywords
operational risk management, Insurance, risk modeling
Citation