Development and Application of Enterprise Financial Risk Analysis System Based on Data Mining Technology

Abstract

With the rapid rise of the digital economy, the overall informatization level of enterprises is getting higher and higher, and massive data information is transformed into productivity, which gives enterprises opportunities for development and brings new challenges to internal financial management. Faced with numerous financial risk problems, traditional risk management tools and technologies have obvious shortcomings in application scope, identification efficiency and control ability. In this regard, this paper puts forward a set of construction scheme of enterprise financial risk analysis system based on data mining technology, aiming at making use of the practical advantages of digital information technologies such as big data and machine learning, and putting forward new solutions for enterprise financial risk management. The system takes Hadoop cluster as the data management and processing server, MapReduce as the data mining engine, and combines Javaweb technology to form a comprehensive application service platform integrating online application, intelligent processing, visual analysis and other functions. Practice has proved that the system constructs the corresponding enterprise financial risk identification and measurement model through data mining algorithms such as Logistic, which meets the enterprise's demand for financial risk management and improves the enterprise's ability to resist risks.