Financial fraud is an issue with far reaching consequences in the finance industry,
government, corporate sectors, and for ordinary consumers. Increasing dependence on new …

Interest in using artificial neural networks (ANNs) for forecasting has led to a tremendous
surge in research activities in the past decade. While ANNs provide a great deal of promise …

Recently, high profile cases of financial statement fraud have been dominating the news.
This paper uses data mining techniques such as Multilayer Feed Forward Neural Network …

This paper explores the effectiveness of Data Mining (DM) classification techniques in
detecting firms that issue fraudulent financial statements (FFS) and deals with the …

Purpose The Chinese housing market has witnessed rapid growth during the past decade
and the significance of housing price forecasting has undoubtedly elevated, becoming an …

Social scientists find neural networks attractive because of their rel evance to commonly
encountered types of problems. Neural networks can be used for classification problems …

A survey of journal articles on neural network business applications published between
1988 and 1995 indicates that an increasing amount of neural network research is being …

The purpose of this paper is to present a comprehensive bibliography of neural network
application research in business during the period of 1994–1998. Our extensive literature …

This article gives an overview of artificial neural network (ANN) studies conducted in the
auditing field. The review pays attention to application domains, data and sample sets, ANN …

Financial fraud is an issue with far reaching consequences in the finance industry,
government, corporate sectors, and for ordinary consumers. Increasing dependence on new …