DocumentCode
2288699
Title
Research on detecting technique of financial statement fraud based on Fuzzy Genetic Algorithms BPN
Author
Liang, Jie ; Lv, Wei
Author_Institution
Sch. of Manage., Shenyang Univ. of Technol., Shenyang, China
fYear
2009
fDate
14-16 Sept. 2009
Firstpage
1462
Lastpage
1468
Abstract
In recent years, the phenomenon of financial statement fraud what happened in listed companies becomes a global focus, which seriously affects economic development. To avoid the huge harm brought by financial statement fraud, to reduce the heavy work of the auditors, to increase the efficiency and precision of auditing and detecting,it is extremely urgent to research detecting technique, which is efficient, convenient and practical. This paper studies on the financial statements of fraud companies and paired companies. It explores the two aspects characteristic signals both from finance and corporate governance, and establishes a set of more perfect feature indicators for detecting the fraud. Then it designs the Fuzzy Genetic Algorithms BPN (FGABPN) model to detecting fraudulent financial reporting for the first time. It is found by test that discrimination of the model is higher.
Keywords
auditing; backpropagation; financial data processing; fraud; fuzzy neural nets; genetic algorithms; backpropagation neural net; corporate governance; economic development; financial statement fraud; fuzzy genetic algorithm BPN; Conference management; Engineering management; Environmental economics; Finance; Financial management; Genetic algorithms; Manufacturing industries; Research and development management; Stock markets; Technology management; detecting technology; financial statement fraud; fuzzy genetic algorithm BPN;
fLanguage
English
Publisher
ieee
Conference_Titel
Management Science and Engineering, 2009. ICMSE 2009. International Conference on
Conference_Location
Moscow
Print_ISBN
978-1-4244-3970-6
Electronic_ISBN
978-1-4244-3971-3
Type
conf
DOI
10.1109/ICMSE.2009.5317990
Filename
5317990
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