Direction of using machine learning in the financial industry

In the modern world of information technology and artificial intelligence, the financial market has become one of the areas where the use of machine learning can have a significant impact. In a rapidly changing technology and financial landscape, traditional financial institutions have to compete with tech giants, which are often more flexible and innovative in using the latest artificial intelligence. The need for operational research and the use of innovations in the financial market increases the relevance of the topic of scientific research. The purpose of this article is to study the analysis of existing forecasting models based on artificial intelligence, as well as the directions and specifics of the application of these models in the financial sector. The article highlights the importance of applying machine learning methods in the financial sector, and suggests an integrated approach to analyzing technologies represented on the global financial market. The models of the machine learning model are considered for solving such tasks as risk management, including credit, fraud detection, cybercrime, consulting, algorithmic trading, investment portfolio optimization, automation of routine tasks, personalized marketing and others. It is noted that the general realized advantages of using machine learning in business processes are to increase the speed of processes, their efficiency, product functionality and the creation of new ones.