数据与计算发展前沿2023，Vol.5Issue(6)：20-30,11.DOI:10.11871/jfdc.issn.2096-742X.2023.06.003
基于RFM模型的上市公司违规行为画像研究
Research on The Violation Portrait of Listed Companies Based on RFM Model
摘要
Abstract
[Objective]Based on the concept of classified supervision,this paper depicts the multidimen-sional characteristics of illegal listed companies so as to assist the regulatory authorities in iden-tifying signs of risk and discovering clues of illegal activities.[Methods]Taking China's listed manufacturing companies punished for violations as the research object,the RFM model is in-troduced to evaluate the violation risk index to reflect their violation severity and regulatory concern.On this basis,a hierarchical cluster analysis is performed in six dimensions:profitabili-ty,solvency,operation ability,dividend ability,capital structure,and corporate governance,and the violation portrait of listed companies is drawn.[Results]According to the RFM score,the illegal listed companies are divided into four categories:low risk,medium risk,sub high risk,and high risk.The listed companies with different violation risk levels have different character-istics.Weak operating capacity,solvency and corporate governance capacity,and high capital structure often mean high violation risk,which is consistent with the internal logic of violations.[Conclusions]The regulatory authorities should take differentiated measures according to the violation risks and characteristics of listed compa-nies so as to further improve the regulatory accuracy.关键词
RFM模型/违规行为/分类监管/系统聚类/企业画像Key words
RFM model/violation/classified supervision/hierarchical clustering/enterprise portrait引用本文复制引用
徐静,袁慧..基于RFM模型的上市公司违规行为画像研究[J].数据与计算发展前沿,2023,5(6):20-30,11.基金项目
北京市社会科学基金规划项目"大数据审计模式下财务报表审计线索发现研究"(21GLB015) （21GLB015）
