Quantitative investment can be roughly divided into five stages, each of which cannot be separated from big data intelligent analysis. Through big data intelligent analysis, investors can be assisted in discovering and exploring profitable opportunities, making investment decisions, implementing trading operations, predicting and warning of trading risks, and helping to control risks. Financial big data intelligent analysis is the expansion of information theory. Intelligent analysis methods based on reliable big data and reliable artificial intelligence can enable people to better achieve financial and economic prosperity, prevent financial risks, warn of financial crises, and safeguard financial security. In quantitative investment, intelligent analyses can better perform their functions and better exert their value. It is based on this that this paper constructs a financial intelligence analysis model based on the random forest algorithm, constructs a mathematical model by training historical data through the algorithm, and finally realises financial intelligence analysis. The experimental results show that the prediction accuracy of the algorithm is between 90 and 98%, and the random forest algorithm has achieved significant research results in financial intelligence analysis.