Research on Data-Driven Financial Risk Prediction Model Based on Cloud Computing

This article aims to explore a data-driven financial risk prediction model based on cloud computing technology. This model achieves accurate identification and prediction of corporate financial risks by integrating advanced algorithms and knowledge graph technology. This article proposes a new risk prediction algorithm model that combines multiple methods such as machine learning, deep learning, and statistical analysis to learn patterns from historical data and predict future financial risks. In addition, the application of knowledge graph enables the model to better understand the internal connections of financial data and improve the accuracy of predictions. Finally, through system simulation experiments, this paper verifies the effectiveness and stability of the proposed model in practical applications. Experimental results show that this model can significantly improve the accuracy of financial risk prediction and provide powerful decision support for enterprises. This research not only enriches the theoretical system in the field of financial risk management, but also provides new ideas and technical means for the practice of financial risk management and control of enterprises.