1013 Chapter 2.44 The Use of Fuzzy Logic and Expert Reasoning for Knowledge Management and Discovery of Financial Reporting Fraud Mary Jane Lenard University of North Carolina – Greensboro, USA Pervaiz Alam Kent State University, USA Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI is prohibited. ABSTRACT This chapter examines the use of fuzzy cluster- ing and expert reasoning for the identifcation of frms whose fnancial statements are affected by fraudulent fnancial reporting. For this purpose, we developed a database consisting of fnancial and nonfnancial 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 informa- tion 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 fnancial reporting. INTRODUCTION In the light of recent reporting of the alleged fnancial reporting abuses in some of the major publicly-held companies in the U.S. (e.g., Enron and WorldCom), it has become increasingly im- portant that management, auditors, analysts and regulators be able to assess and identify fraudulent