Detecting Fraudulent Financial Data Using Multicriteria Decision Aid Method

被引：1

作者：

Yang Ruicheng ^{[1
]}

Guo Rongrong ^{[1
]}

Shen Qing ^{[1
]}

机构：

[1] Inner Mongolia Univ Finance & Econ, Sch Finance, Hohhot, Peoples R China

来源：

2016 3RD INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE) | 2016年

关键词：

UTADIS; linear programming theory; financial fraud;

D O I：

10.1109/ICISCE.2016.78

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The fraudulent financial statement of a company is becoming serious over the last few years, so, finding a valid forecasting fraudulent financial statement model is an urgent work for academic research and financial practice. The UTilities Additives DIScriminants (UTADIS) classification method is an effective approach to classify some data into different groups. Therefore, based on UTADIS method, this paper uses the utility function theory and linear programming theory to classifying the financial data of a company as fraudulent or non fraudulent class, in which the research dataset of the company consists of 10 financial ratios. The empirical results show that UTADIS method can effectively detect the fraudulent financial data.

引用

页码：321 / 324

页数：4

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