With the development of Internet finance, the risk prevention and control of online P2P lending are always the difficult points. Based on multi-dimensional data analysis of online P2P lending user profile model may become an effective opportunity to avoid risks. User profile model is based on multi-dimensional data analysis by integrating and analyzing data from different sources, storage types or descriptions, so as to fully and deeply depict the characteristics of online P2P lending users. This paper proposes a profile model of online P2P lending users with the four dimensions of basic attributes, ability attributes, social attributes and psychological attributes, mainly through the analysis of users’ basic information, lending data from online P2P lending platform, social data from micro-blog and multi-source heterogeneous data, for completing the construction of the model. Then, specific data analysis methods are given for different dimensions, and the social attribute dimension is taken as an example for empirical analysis. Reasonable and reliable user profile results were obtained, which shows that the multi-dimensional data analysis method proposed in this paper is effective.
