Abstract
Fraud is becoming more prevalent in recent years as the number of frauds and their costs escalate. At the same time, the detection of fraud has been badly lagging. Several recent studies have evaluated the use of computer technologies such as expert systems and neural networks in management fraud detection. The purpose of this paper is to extend this line of research by investigating the utility of neural fuzzy systems in management fraud detection. Recent hybrid systems that integrate fuzzy logic, neural networks and other techniques are reviewed. A hybrid neural fuzzy system is then proposed to predict the likelihood of management fraud based on a set of five financial ratios.
Recommended Citation
Hwang, Mark I. and Lin, Jerry W., "A Neural Fuzzy System Approach to Management Fraud Detection" (2000). AMCIS 2000 Proceedings. 9.
https://aisel.aisnet.org/amcis2000/9