MATHEMATICAL-STATISTICAL MODELS IN INSURANCE

Abstract

The insurance companies use many different models especially when they look for the optimal solutions of problems in pricing and development of product, complete risk profile of the company, risk quantification, cession of risks, capital adequacy, the location of assets, administration and management of capital and in many other areas. The big world-wide insurance companies invest huge amounts to development of models focused on right pricing insured risks and also risks which are very difficult quantified and non-insurable nowadays, but probably they will influence the insurance and reinsurance market markedly in future. Mentioned risks are risk of global ecological disasters, risk of global climatic conditions, energetic risks, risk of information and communication technologies, etc. The climatic changes bring new and statistic uncharted risks. The insurance companies have to give up reliance only upon risks models strictly based on historical data. The models are simplified images of complicated real systems and modeling is often sole instrument for their understanding. The key to successful modeling is also accession to right information. The insurance companies have to develop database of information and also technologies for specialists responsible for decision making. The problem is not sufficient data of loss experience in some countries. The modeling, if it should be exact, has to work with sufficient data. Because of decrease of costs connected to records archive and database making, it will be not problems in future.