基于自适应熵投影聚类算法财务欺诈预测工具研究

Research on financial fraud prediction tool based on adaptive entropy projection clustering algorithm

我国上市企业财务欺诈问题时有发生,严重损害了财务报告信息需求方的利益,扰乱了资本市场的正常运行。上市企业财务报告的有效监管是实现财务欺诈控制的有效手段,由于企业财务报告数据量巨大,急需开发适用于财务报告文本数据挖掘的财务欺诈应用工具。因此,通过构建自适应熵投影聚类模型,并采用自适应熵投影聚类算法进行了财务报告文本数据挖掘预测财务欺诈应用工具开发设计,以期能在较大程度上识别财务欺诈企业,使财务信息的使用者能更好利用上市企业披露的财务信息,做出正确决策,促进资本市场的良性发展。

Financial fraud occurs frequently in listed enterprises in China,which seriously damages the interests of the demander of financial report information and disturbs the normal operation of the capital market.The effective supervision of financial reports of listed enterprises is an effective means to realize financial fraud control.However,due to the huge amount of data in financial reports,it is urgent to develop financial fraud application tools suitable for text data mining of financial reports.Therefore,this article constructed the adaptive projection entropy clustering model,and the adaptive projection entropy clustering algorithm is used for application to predict financial fraud financial reporting text data mining tools development and design,in order to identify financial fraud companies in a large extent,make the financial information users can make better use of the listed companies to disclose financial information,to make the right decisions,Promote the sound development ofthe capital market.