APPLICATION OF ARTIFICIAL INTELLIGENCE IN FINANCE BASED ON INTERNATIONAL EXPERIENCE

The introduction of artificial intelligence systems in the financial industry is introducing revolutionary changes in the way information is analyzed, presented and managed. Machine learning is a type of artificial intelligence that allows it to learn and improve autonomously. Unlike traditional hard programming techniques, machine learning uses neural networks and deep learning to work with large amounts of data to identify patterns and anomalies. The hypothesis of the study is that the financial sphere is characterized by its own methods of applying AI, relying on the most common ones, but differing from them. The purpose of the work is to systematize the ways of using artificial intelligence models in financial institutions in the context of structural divisions. The use of artificial intelligence allows financial institutions to create models aimed at solving specific issues in a constantly updated information environment. In accordance with the objective, the paper addresses the following tasks: a general description of the tasks solved by AI and the advantages and disadvantages of AI application; characterization of the prevalence of artificial intelligence systems in the financial sphere; characterization of the areas of application of artificial intelligence in the financial sphere. To complete the work, the author used methods of information synthesis, source analysis, classification, and comparative analysis methods.