ИСПОЛЬЗОВАНИЕ МАШИННОГО ОБУЧЕНИЕ В ПРОЦЕССЕ РИСК-МЕНЕДЖМЕНТА ПРЕДМЕТНЫХ РИСКОВ

Abstract

Background. 
 Currently, artificial intelligence (AI) and machine learning are frequently implemented into the corporate structure and are aimed to transform the risk management system. Not only AI is useful for detection the interconnections between business processes, but also allows to accurately predict financial indicators and the reasons for possible deviations from standard values. Thus, the implementations of artificial intelligence and machine learning mechanisms makes it possible to increase the efficiency of operational activities and detect hidden risks.
 Method. 
 The article discusses the main types of risks, identidication and minimization of which can be carried out using machine learning and also reveals key difficulties that arise while introducing innovative mechanisms into the structure of risk-management. The scientific novelty of the work lies in the relevance of using artificial intelligence mechanisms while minimizing the risks of an economic entity, as well as in identifying the main incentives for the efficient usage of machine learning in risk management. 
 Result. 
 As a result, the potential of introducing innovative methods into the structure of risk management to improve the efficiency of operating activities was revealed. 
 Conclusion.
 In the process of the methodological study, the features of the application of machine learning methods in the risk management process were identified, moreover the article main limitations and possibilities of using artificial intelligence in order to minimize risks were revealed.