Research on the Risk Evaluation of Enterprise Industry and Finance Integration Based on Big Data Information Empowerment
This study aims to explore the challenges of integrating corporate finance and risk within the context of big data information empowerment,and establishes a risk assessment system.Through indicator selection,and model overview,the study designed a neural network discriminant model to address the classification problem.For data acquisition,researchers collected 1,469 valid questionnaires through surveys for reliability and validity tests.The results and analysis section describes the sample characteristics,linear regression results,and neural network model analysis.Descriptive statistics show the influence of various internal and external risk factors,while linear regression indicates that factors such as technological innovation and social responsibility significantly affect industry-finance integration risk.The neural network model analysis demonstrates good performance on the training and validation sets,but the test set suffers from underfitting.The confusion matrix and ROC curves illustrate the model's classification capabilities and performance.Based on the findings of this analysis,organizations should focus on data integration and analysis,risk assessment and management,and intelligent decision support to effectively tackle financial and risk convergence.These initiatives will help enterprises better understanding market trends,customer needs,and potential risk factors,enabling timely decisions to maintain competitive advantages.
big Datainformation empowermentbusiness-finance integrationrisk assessment