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基于舞弊三角理论的财务舞弊识别模型研究——支持向量机与Logistic回归的耦合实证分析
引用本文:金花妍,刘永泽.基于舞弊三角理论的财务舞弊识别模型研究——支持向量机与Logistic回归的耦合实证分析[J].大连理工大学学报(社会科学版),2014(1):92-97.
作者姓名:金花妍  刘永泽
作者单位:[1]辽宁师范大学数学学院,辽宁大连116029 [2]东北财经大学会计学院,辽宁大连116023
基金项目:辽宁省教育厅项目:“连锁董事对公司战略与绩效的影响”(W2011126)
摘    要:文章基于舞弊三角理论,对舞弊风险因素进行T检验,选取显著特征运用支持向量机算法和Logistic回归分析方法构建了舞弊识别模型,并进行比较。研究结果表明,财务稳定性越差、监督部门的监督积极性越低、曾经获得非标准审计意见次数越多,公司发生财务舞弊可能性越高。应制定合理的报酬激励机制,降低报酬契约冲突带来的舞弊压力;建立健全内部控制和风险管理评价,减少舞弊的机会;加强内外监督机制,杜绝舞弊的借口。

关 键 词:财务舞弊  三角理论  支持向量机  Logistic回归

Study of Identification and Countermeasure of Financial Frauds Based on Triangle Theory of Frauds-Empirical Analysis of the Coupling of Machine Learning and Logistic Regression
JIN Hua-yan,LIU Yong-ze.Study of Identification and Countermeasure of Financial Frauds Based on Triangle Theory of Frauds-Empirical Analysis of the Coupling of Machine Learning and Logistic Regression[J].Journal of Dalian University of Technology(Social Sciences),2014(1):92-97.
Authors:JIN Hua-yan  LIU Yong-ze
Institution:1. School of Mathematics, Liaoning Normal University, Dalian 116029, China 2. School of Accounting, Dongbei University of Finance and Economics, Dalian 116023, China )
Abstract:This paper analyzed fraud risk factors with T-test based on triangle theory of frauds and selected re-markable factors to model the identification of frauds by support vector machine and logistic regression .The re-sults showed that frauds’ increased with the number of the non-standard audit opinions ,but decreased with the financial stability and the positivity of the supervision .In order to prevent and find frauds ,some measures should be taken as follow s .Firstly ,the pressure caused by the conflict of compensation contracts can be re-duced by making reasonable incentive mechanism .Secondly ,the opportunities of frauds can be reduced by im-proving internal controls and evaluation system of risk management .Finally ,the internal and external supervi-sion mechanism can be strengthened to eliminate the excuses of frauds .
Keywords:financial frauds  triangle theory  support vector machine  logistic regression
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