摘要
如何识别财务报表舞弊成为国内外学者普遍关注的问题。基于传统识别技术的诸多固有缺陷,近年来数据挖掘技术应用到识别财务报表舞弊领域成为发展趋势。数据挖掘技术包括统计方法、人工神经网络和其他数据挖掘技术。文章不仅对各种识别模型和技术进行了归纳,而且比较分析了各种模型和方法的优缺点、判别正确率以及适用条件,为下一步实施实证研究提供支持。
Identifying fraudulent financial statements becomes a common problem concerned by scholars from both domestic and abroad.As a preferable means to overcome the intrinsic weakness brought by the traditional approaches,the recent application of Data Mining is regarded as development trend in this area.Models and Methods to identify the Fraudulent Financial Statements include： Methods of Statistic Analysis,Neural Network Models and other Data Mining Methods.The article not only concludes all kinds of methods and models,but also compares and analyzes the advantages and disadvantages,rates of correct identification and conditions of application of each technology,supporting for the empirical research to be conducted.
出处
《财务与金融》
北大核心
2010年第3期39-43,共5页
Accounting and Finance
基金
南京审计学院校级课题<公司治理和内部控制信息在识别财务报告舞弊中的有效性研究>(NSK2009/C07)的阶段性研究成果)
关键词
财务报表舞弊
数据挖掘
统计方法
神经网络
Fraudulent Financial Statements
Data Mining
Methods of Statistic Analysis
Neural Network
