An Enterprise Risk Prediction Model Combined Financial Data and News Based on Memory Network

Abstract

Enterprise risk management is very important for enterprise development. It can help enterprises effectively manage risks and avoid heavy losses. Traditional enterprise risk prediction methods can’t meet the current requirements for accuracy and timeliness. Artificial intelligence technology represented by deep learning has brought new ideas and methods to enterprise management. We propose an enterprise risk prediction model based on memory network by combining the financial data and news as the input data. The model can not only solve the problem of low performance of traditional methods, but also solve the problem of long-term dependence of traditional machine learning methods. The result of this research shows that the model can greatly improve the timeliness and accuracy, which can help promote the management level of enterprises.