Abstract

The article examines the definition of the category "risk" in the works by domestic scientists. Financial risk management in the company management system is considered. Its basic principles and postulates are established. Risk management is defined as the process of identifying, analysing, and making or reducing uncertainty in making investment decisions. Approaches to the formation of modern strategies and tactics of risk management are generalized. The sequence of stages, which most fully reflects the essence of the risk management process, is presented. The main stages of financial risk management are characterized and their functional significance is determined. It is established that the main direction for improving the management system is the deve-lopment and implementation of active management based on systemic and situational approaches. To choose the optimal tactics for managing financial risks, it is advisable to classify them into industry and quality. The strategies for financial risk management of modern business are generalized in two categories: passive and active response. The use of integrated approaches and new business concepts for efficient financial risk management is substantiated. The main means of reducing financial risk are identified, namely insurance and sale of financial instruments (forward contracts, futures contracts, swaps and options). The main elements of using business analytics tools are considered and analysed. It is noted that most business analytics tools are used to improve risk management; therefore, risk management tools benefit from business analytics approaches. The use of artificial intelligence models, such as neural networks and the method of reference vectors, agent-oriented theory, cognitive computation, is characterized. The proposed approach is aimed at combining several expert solutions, achieving the highest return on investment and reducing losses by working with difficult situations in a dynamic market environment. It is proved that researching business analytics tools in the field of risk management is useful for both practitioners and academic researchers.

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