Quantification of operational risk in U.S. property and casualty insurance companies

Abstract

Over the years, financial institutions have experienced operational risk of increasing complexity. These operational risks can be extremely detrimental to the market value of a financial institution and hard to foresee. Research in this area is more matured for the insurering sector due to the introduction of Advanced Measurement Approach model by Basel II. On the other hand, Solvency II did not enforce the compulsory usage of a specific model for quantification of operational risks. There is limited study for insurance sector. This paper uses several firm attributes and economic information that might affect firm risk-taking and estimate the effect of those variables. Based on the results, a normalized formula is developed for quantifying operational risks. Algo OpData and National Association of Insurance Commissioners (NAIC) financial databases are utilized in aiding the analysis of this paper. Results of this paper show that the one of the recent and robust scaling regression equations used for calculating the severity of operational losses in the insurering sector is not applicable to the insurers. Therefore, modifications have been implemented to better explain the variability of losses in the Property and Casualty insurance companies domiciled in United States.