ABSTRACT
The administrative punishment announcements of financial fraud issued by the China Securities Regulatory Commission (CSRC) are unstructured texts, and it is difficult for them to effectively play their role of reference and decision-assisting without pre-processing and resorting. This paper uses quantitative analysis method to analyze the administrative punishment announcements texts of financial fraud issued by the CSRC. It counts the number of the administrative punishment announcements issued from 2011 to 2019, analyzes the trends, and summarizes the categories of financial fraud and punishment methods. This paper analyzes the content of the administrative punishment announcements and designs the conceptual model for the administrative punishment case, which is conducive to the construction of a case analysis knowledge graph of administrative punishment for financial fraud and realizing the text analysis and case reasoning based on artificial intelligence.
