中国科学院自动化研究所机构知识库

With the explosion of the Internet Finance Platforms, identifying the risks of these platforms is of growing significance, which can help discover problematic platforms in time and ensure the healthy development of the Internet finance industry. In this paper, we design a risk index system to measure the quantitative risk of the Internet finance platforms, and propose a deep neural network based model, CBiGRU-RI, to identify the risks of the platforms using multisource text data. We conducted comparative experiments with various baseline models on real-world data. The experimental results show that our proposed model can identify the risks of platforms more effectively than the baseline methods.