Research on Corporate Financial Risk Prediction and Early Warning System Based on Big Data Analysis

This study centers on creating an enterprise financial risk early warning system utilizing big data analysis to predict and manage potential risks through advanced data processing and machine learning technologies. The system incorporates data collection, preprocessing, feature selection, model training, evaluation, and risk warning notifications to provide a comprehensive solution, enabling enterprises to identify and respond promptly to financial risks. The performance evaluation metrics used in the study, including accuracy, precision, recall and F1 score, all show that the system has a high degree of predictive accuracy and reliability. Despite the limitations of data acquisition and the adaptability of the model to rapid changes in the market, future research will be dedicated to further optimization by introducing more real-time data sources, exploring more advanced analysis techniques, and conducting more extensive field testing. System performance. This study not only provides enterprises with a practical financial risk early warning tool, but also provides new directions and ideas for future research in the field of financial risk management.