A Comparison of the use of risk measures and the application of the adjustment coefficient in calculating optimal reinsurance.

Abstract

Reinsurance is a mechanism by which an insurance company can protect itself against the risk of losses by transferring the risk to other companies. A reinsurance arrangement could be considered optimal if it minimizes the probability of ruin. When an insurer effects reinsurance, they are required to pay a reinsurance premium. Therefore, the total cost to the insurer in the presence of reinsurance is the cost of meeting the retained loss in the event of a claim and paying the reinsurance premium. The purchase of reinsurance is therefore a compromise between expected gain and security. Reinsurance reduces the cedant’s risk; on the other hand, it will reduce the expected gain of the cedant. Claims experience is assumed to follow a particular loss distribution. i.e. the exponential, pareto, gamma, lognormal, Weibull and burr distributions. This paper determines optimal reinsurance by use of risk measures such as VaR and CTE. The results are compared with the use of the adjustment coefficient in determining the optimal reinsurance strategy. Claims experience data is simulated through the Monte Carlo simulation techniques