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The modern insurance market operates in conditions of high uncertainty, exacerbated by macroeconomic fluctuations, technological changes, and the growing interdependence of risks. In such conditions, it is particularly important to accurately assess the probability of insured events and set reasonable insurance rates. Traditional approaches based on the assumption of risk independence are increasingly demonstrating their limitations and insufficient accuracy, especially when analyzing complex portfolios in which insurance events are highly interdependent. For this reason, there is growing interest in mathematical modeling of correlated risks and its application in tariff setting. The aim of this research is to develop and analyze approaches to mathematical modeling of the probability of insurance events and the formation of insurance tariffs, taking into account correlated risks. The methodological basis is provided by methods of probability theory, mathematical statistics, elements of actuarial mathematics, as well as models of correlation analysis and multidimensional distributions of random variables. The paper uses analytical and comparative methods to assess the impact of risk dependencies on tariff calculations. As a result of the study, a modernized approach to assessing the probability of insured events is proposed, taking into account the dependence between insurance risks based on the introduction of a systemic correlation coefficient. It has been established that taking into account the dependence between insurance events leads to an increase in the calculated probability of aggregate losses and requires an adjustment of insurance tariffs to ensure the financial stability of the insurance portfolio.
insurance, insurance risks, economic and mathematical modeling, probability of insured events, correlated risks, insurance pricing, risk hedging, reinsurance
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