Construction of Enterprise Financial Risk Pre-alarm System Based on Big Data

Big data has brought new opportunities for enterprise development, and the work efficiency of the financial department has been greatly improved. However, the current combination of big data and enterprise financial risk pre-alarm has some problems, such as unreasonable and irregular data processing. Based on this, this paper puts forward an innovative idea to improve the financial risk pre-alarm model, constructs a new enterprise financial risk pre-alarm model based on big data, and makes a qualitative analysis of the enterprise financial crisis, so as to predict the enterprise financial risk. The test results show that this method can further improve the prediction accuracy of the model, and the accuracy of the algorithm can reach 95.74%, which is about 12% higher than that of the traditional neural network method. This shows that it is effective to use big data method in financial risk pre-alarm. This model enhances the robustness of the algorithm and the rationality of initial weight threshold setting, and effectively improves the prediction performance of the pre-alarm model. Using this model to analyze and predict the capital situation of enterprises can provide reference for enterprises to scientifically formulate development decisions and financial strategies and effectively avoid financial risks, thus ensuring the stable growth of enterprises under big data.