Research on the Construction of Intelligent System for Risk Management and Decision Making in Green Financial Markets

Abstract

The evolution process of green financial risk includes three links: risk shock, contagion and diffusion. This paper constructs a green financial development level indicator system to evaluate the development effectiveness of green finance. Through intelligent engine design, artificial intelligence modeling, automatic identification of suspicious risks, dynamic one-click reporting, etc., the design decision-making intelligent system combines principal component analysis and BP neural network algorithm to establish a BPNN green financial risk early warning model, learn and train historical financial data information, and warn of risks in the green financial market, accurately capturing the changes in green financial market risks. The results show that the BPNN green financial risk early warning model established in this paper has a high accuracy rate at all warning moments, with an average accuracy of 0.9952 and a shortest decision time of 530ms. The system in this paper performs very well in short-term prediction, which helps to promote the advancement and development of the green financial system.