文章基本信息

标题：Detecting Fraudulent Financial Information of a Company Using Hidden Markov Model
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作者：Ruicheng Yang ; Ailing Zuo ; Qing Shen 等
期刊名称：International Journal of Security and Its Applications
印刷版ISSN：1738-9976
出版年度：2016
卷号：10
期号：9
页码：19-28
出版社：SERSC
摘要：Using Hidden Markov Model (HMM), this paper detects some fraudulent financial information of a company. The research index MBSPM (Main Business Service Profit Margin) ratio of company is used to test the effectiveness of HMM. Due to the shortage of the fraudulent data, based on the MBSPM index data we generate the artificial fraudulent financial information data by Poisson process and Uniform distribution, that is, we use the Poisson process to simulate the arrival times of the fraudulent financial information and the Uniform distribution to simulate their fraudulent sizes. By embedding the artificial fraudulent financial information data into the non-fraudulent MBSPM data, we form the sample data series. Applying Henderson filter method, we derive the research sample data by getting rid of the sample data series trends. We do some experiments to test the validity of HMM for detecting the fraudulent financial information, and further make some comparisons with other detecting techniques: logistic regression and ANNs. The detected results show that the HMM approach can significantly improve the identification accuracy.
关键词：Fraudulent information detection; Hidden Markov Model; MBSPM ratio