Abstract
Starting from the theory of probabilities, which represents an attempt to investigate uncertainty, insurance companies must calculate their insurance premiums in such a way as to cover all their operational expenses and obtain the expected benefit, preserving the principle of equity and solidarity. In commercial insurance, statistical research plays a special role in estimating the level of insurance activity and its prospects. For this purpose, the events that take place in insurance are measured, ordered, systematized and aggregated through observation (collection), processing and analysis. Estimating the risk and the insurer’s obligations based on inadequate or incorrect data is an extremely dangerous situation. Therefore, it is extremely important for the insurer to establish the best possibility of observing and using the data. Basing premium rates and reserves is an important activity for insurance companies. If insurers do not accurately set premium rates that reflect the size of the risk, they may suffer losses due to the financial imbalance created between premiums and indemnities or due to adverse selection. The actuary deals with this within the insurance company, using various actuarial statistical methods. The Chain-Ladder method is one of the most popular claims reserving techniques. The aim of this study is to back-test the chain-ladder method. We use a stochastic scenario generator that allows us to simulate arbitrarily many upper claims reserving triangles of similar characteristics for which we also know the corresponding lower triangles. Based on these simulated triangles, we analyse the performance of the chain-ladder claims reserving method. The substantiation of technical reserves must be based on specific methods because there is a possibility that two insurers may use different calculation techniques for similar obligations and obtain totally different results, thus disrupting profitability and financial soundness.
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