Author(s)

Yu Yang

Corresponding Author

Yu Yang

ABSTRACT

Some problems have gradually emerged in the process of enterprise operation with the rapid development of the economy, which causes the financial sector of modern enterprises to face greater risks. To actively respond to financial risks and further improve enterprises' risk response and prevention capabilities, enterprises should establish a forecasting mechanism that can the enterprises' financial risks based on the actual financial operation. This paper discusses the application of BP neural network in financial risk forecasting, starts with selecting financial risk information indicators, studies the theory of risk identification, and designs and optimizes the risk assessment model by constructing BP neural network and using the idea of combined forecasting. Finally, to eliminate the negative influence of the local optimum, the particle swarm algorithm is used to improve the convergence ability of the model, thereby improving the algorithm's robustness.

KEYWORDS

Artificial intelligence; BP neural network; Financial risk prediction; Combined forecasting model