Abstract

http://ssrn.com/abstract=1215302
 


 



Self-Organizing Fuzzy and MLP Approaches to Detecting Fraudulent Financial Reporting


Ehsan H. Feroz


University of Washington, Tacoma-Milgard School of Business; Vernon Zimmerman Center, University of Illinois; US Government Accountability Office

Taek M. Kwon


University of Minnesota - Twin Cities - Electrical and Computer Engineering

August 10, 2008

SOFT COMPUTING IN FINANCIAL ENGINEERING, R.A. Riberio, H.J. Zimmerman, R.R. Yager, & J. Kacpryzk, eds., New York, 1999

Abstract:     
The purpose of this study is to compare a class of neural networks and fuzzy controller approaches, more specifically, a multi-layered perceptron (MLP) and a self-organizing fuzzy approach, in determining the efficacy of selected Statement of Auditing Standard No. 53 red flags in predicting the targets of the Securities and Exchange Commission's (SEC) investigations. The motivation for studying these two approaches is provided in part by our earlier work with conventional tools such as logit which generally leads to inferior prediction accuracy for such classification problems.

In direct comparison of the performance on the present SEC investigation problem, the MLP network outperformed both logit and fuzzy approaches. We believe that the performance of the fuzzy approach can be significantly improved if the center vectors are fine tuned using some adaptive algorithms. Our empirical results demonstrate that both MLP and fuzzy approaches can be powerful tools, especially in the pattern classification or detection problems, such as those related to fraudulent financial reporting.

Number of Pages in PDF File: 6

Keywords: Fraudulent financial reporting, SEC, GAAP, SAS, Red flags, Neural Networks, Fuzzy controller, Financial engineering, Soft Computing

JEL Classification: C45, D57, G18, G38, K22, L81, M41

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Date posted: August 12, 2008 ; Last revised: July 26, 2014

Suggested Citation

Feroz, Ehsan H. and Kwon, Taek M., Self-Organizing Fuzzy and MLP Approaches to Detecting Fraudulent Financial Reporting (August 10, 2008). SOFT COMPUTING IN FINANCIAL ENGINEERING, R.A. Riberio, H.J. Zimmerman, R.R. Yager, & J. Kacpryzk, eds., New York, 1999. Available at SSRN: http://ssrn.com/abstract=1215302

Contact Information

Ehsan H. Feroz (Contact Author)
University of Washington, Tacoma-Milgard School of Business ( email )
1900 Commerce Street, Campus Box 358420
Tacoma, WA 98402-3100
United States
(253) 692 4728 (Phone)
253 692 4523 (Fax)
HOME PAGE: http://www.tacoma.washington.edu/business
Vernon Zimmerman Center, University of Illinois ( email )
515 East Gregory Drive# 2307
Champaign, IL 61820
United States
US Government Accountability Office ( email )
441 G Street NW
Washington, DC 20548-0001
United States
Taek M. Kwon
University of Minnesota - Twin Cities - Electrical and Computer Engineering ( email )
Duluth, MN 55812
United States
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