In order to solve the problems of poor connection between business data and financial data, lag in risk identification and insufficient collaborative decision-making support in the intelligent transformation of financial data, an intelligent analysis model of industry and finance data fusion was constructed, and the application effect was evaluated with case enterprises. The research established an analysis link around data access, feature fusion, risk identification, decision support and effect feedback, and jointly identified order execution, inventory turnover, payment collection cycle, revenue cost and gross profit change. The results show that after the application of the model, the accuracy of risk identification increases from 83.6% to 92.4%, the average response time of early warning decreases from 26.5 hours to 9.8 hours, the completion rate of collaborative processing of industry and finance increases from 71.2% to 88.7%, and the gross profit rate increases from 22.34% to 23.41%. The research shows that the model can enhance the ability of business risk perception, improve the efficiency of collaborative decision-making, and provide method support and application reference for the intelligent transformation of enterprise financial data.
