Abstract
Risk management requires the use of a number of mathematical models for calculation. To use these models, it is necessary to form large databases on the quantitative characteristics of both the studied objects/processes/systems and the surrounding environment and conditions of the task. Implementation of this program requires the use of modern information technologies. The article analyzes the methodology for the formation of quantitative risk values, which allows for the formation of approaches to a certain standard for performing risk analysis for complex situations. A system of mathematical models and methods is proposed that allow building a system of quantitative modeling of risk situations for a wide class of objects/processes/systems. The article provides a comparative analysis of deterministic and stochastic risk management models, analyzes the riskiness model of risk stratification and the model for detecting differences from white noise. For the latter, a comparison of the experimental and theoretical concepts of the models was made. Information technologies that help organizations effectively identify, analyze and manage various types of risks, while providing a reliable protection mechanism against possible threats, such as ERM Systems, GRC Platforms, IRM Solutions, Cybersecurity Risk Management, Project Risk Management and Data Risk, are highlighted and analyzed Management.
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