Development of a random forest ai based robo-advisor as a factor of increasing the investment activity of the population

The article discusses current trends in the use of artificial intelligence in the financial market. The relevance of the study is based on active use of exchange trading robots when conducting transactions on the exchange. However, despite some “splash” in 2021, the low investment activity of the population remains an acute problem. The purpose of the work is to solve a major national economic problem: increasing the investment activity of the population of the Russian Federation, strengthening the stability of the financial sector through the active use of private investors’ funds thanks to the introduction of a reliable robo-advisor. In the course of the study, the following tasks were solved: 1) theoretical basis for increasing the investment activity of the population was investigated; 2) an analysis of the current state of financial markets was carried out and trends in the use of artificial intelligence were identified; 3) a reliable highly efficient neural-network robo-advisor was developed. The scientific novelty lies in the fact that the proposed algorithm is based on the use of the machine learning algorithm of Random Forest, which allows you to get a reliable forecast for each next hour during the exchange trading of the SiH3 futures contract. The practical significance and value is that the developed recommendations can be implemented in practice, as they are confirmed by certificates of state registration for PC software. As a result of the study, conclusions were drawn: firstly, increasing the investment activity of the population contributing to the strengthening of the stability of the financial sector is important; secondly, the use of AI systems to support decision-making by private investors plays an important role in modern conditions; thirdly, the developed algorithm based on Random Forest machine learning is proposed, which allows you to get a reliable forecast of the price of the SiH3 futures contract for each next hour, providing a yield of 17,1 % during the exchange trading day. Among the directions for further scientific research, the use of Industry 5.0 technologies should be noted.