Research on BP Neural Network Prediction of Financial Transformation and Upgrading Potential of Enterprises in the Digital and Intelligent Era

In order to reduce the operational risks of enterprises and help enterprises improve their core competitiveness, this paper studies the BP neural network prediction method for the financial transformation and upgrading potential of enterprises in the age of digital intelligence. Select the sample data of enterprises from Shanghai and Shenzhen Stock Exchanges, use the financial data of these enterprises to build an indicator of the potential for financial transformation and upgrading of enterprises, and use the nonparametric test method to eliminate the duplicate content in the indicator, and provide the tested indicators as input to the BP neural network model. Under the prediction of the model, obtain the potential for financial transformation and upgrading of different enterprises. The model test results show that the prediction method has a high fitting effect, which can divide the company’s financial transformation and upgrading potential into three states: poor, ordinary, and high, while maintaining accurate prediction ability.