Predicting and analyzing the arrival of financial risks using artificial intelligence neural networks

Risk analysis and its management is very important in the financial field and is considered as one of the most fundamental principles of investment management. Due to the developments of financial liberalization and banking innovation, the nature of banking risks has changed, which leads to the use of new financial instruments. So banks are increasingly adopting risk assessment to avoid it. The purpose of this research is to predict and analyze the arrival of financial risks using artificial networks. The type of research method is descriptive and analytical and the method of collecting information is based on library studies and the tool of collecting data. The results showed that the use of artificial intelligence in the private sector is increasing rapidly. This puts pressure on financial managers to use artificial intelligence to maintain their efficiency. Although AI has significant benefits, it also poses challenges, particularly for financial stability. CFOs are rapidly expanding their use of artificial intelligence in financial regulation. Competitive pressures are driving the rapid expansion of AI in the private sector, and authorities must keep up if they are to remain effective. According to research findings, artificial intelligence can be useful in financial and accounting risk management. By using artificial intelligence algorithms and models, risks can be identified, analyzed and improved. Also, by using artificial intelligence in financial management based on artificial intelligence, it is possible to analyze and predict market trends and various investments, and based on that, better decisions can be made in the field of investments.