This article focuses on the research of intelligent financial risk identification and early warning models driven by big data platforms. By integrating multiple sources of data and using machine learning algorithms, an intelligent identification and early warning model for financial risks is established. The big data platforms is used to collect, clean, and process various types of financial data, including financial statements, transaction data, and market indicators. Secondly, combined with data mining and model building techniques, a supervised learning based intelligent financial risk identification model is constructed to achieve timely identification of abnormal changes and potential risks. Finally, the effectiveness and practicality of the model are verified through empirical case analysis, providing reliable early warning support for enterprise financial risk management. This study has important theoretical and practical significance in the field of financial risk management, providing new ideas and methods for building an intelligent financial risk warning system.