The Use of Fuzzy Logic and Expert Reasoning for Knowledge Management and Discovery of Financial Reporting Fraud

The Use of Fuzzy Logic and Expert Reasoning for Knowledge Management and Discovery of Financial Reporting Fraud

Mary Jane Lenard (University of North Carolina at Greensboro, USA) and Pervaiz Alam (Kent State University, USA)
DOI: 10.4018/978-1-59140-134-6.ch016
OnDemand PDF Download:
$30.00
List Price: $37.50

Abstract

This chapter examines the use of fuzzy clustering and expert reasoning for the identification of firms whose financial statements are affected by fraudulent financial reporting. For this purpose, we developed a database consisting of financial and nonfinancial variables that evaluated the risk of fraud. The variables were developed using fuzzy logic, which clusters the information into various risk areas. Expert reasoning, implemented in an Excel spreadsheet model, is then used as a form of knowledge management to access the information and develop the variables continuously over the life of the company. At the conclusion of the chapter, the authors discuss emerging trends and future research opportunities. The combination of fuzzy logic, expert reasoning and a statistical tool is an innovative method to evaluate the risk of fraudulent financial reporting.

Complete Chapter List

Search this Book:
Reset