Models for assessing the financial stability of insurance companies
The efficient functioning of the insurance market requires financially reliable insurers, able to fulfil their obligations to policyholders on time and in full. The financial stability of insurers is the starting point for the continued implementation of the insurance function. The frequency and variety of risk manifestation models necessitate thorough risk analysis to justify the adoption of financial strategies by insurance companies. The application of economicmathematical models provides a reliable basis for assessing the financial stability of insurers. To achieve financial stability, insurance companies engage in mathematical modelling of key indicators such as the probability of bankruptcy and the solvency margin. Modelling the probability of bankruptcy in insurance companies serves as a tool for preventing insolvency. Accordingly, determining an adequate insurance premium is based on a previously estimated probability of bankruptcy. Differences between models arise from assumptions regarding the distribution, amount, and timing of insurance claim payments, which form the basis for their construction. Insurance claim payments are modelled using an appropriate probability distribution. The time intervals between claim payments are typically modelled using exponential distributions, while the sequence of claim events is defined by a Poisson process. Assessing the financial stability of an insurance company is a complex process due to the multifaceted nature of the issue. The use of economic-mathematical models provides a foundation for generating valuable insights in the management decision-making process. From a market perspective, insurance companies aim to achieve the most reliable assessments of financial stability. However, this assessment is highly complex, and existing mathematical models often fail to incorporate all external factors that affect the financial soundness of insurance companies. Including a large number of variables results in a highly complex model that requires sophisticated solutions but yields more precise results. Conversely, simplifying the model by excluding certain factors facilitates easier computation but reduces the accuracy of the outcome.
engleski
2025
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Key words: financial stability, insurance companies, insurance market