Real-time Early-warning Model of Enterprise Financial Risk Based on Dynamic Association Rule Maintenance Algorithm

In order to improve the efficiency and accuracy of enterprise financial risk management, this study combined with dynamic association rule maintenance algorithm on the basis of in-depth analysis of enterprise financial data to build a real-time monitoring and early warning financial risk model. This model can not only effectively identify potential financial risk factors, but also dynamically adjust association rules according to the actual situation of enterprises to ensure the timeliness and accuracy of early warning. Through experimental verification, the accuracy, recall rate and F1 value of the enterprise financial risk real-time early warning model built in this study based on the dynamic association rules maintenance algorithm are higher than the traditional Z-Score model on the test set, and it has higher accuracy and reliability in predicting enterprise financial risk.