Accounting frauds – review of advanced technologies to detect and prevent frauds

Abstract

In past decades, accounting fraud has adversely affected economies worldwide. Therefore, effective measures and methods ought to be employed in order to efficiently prevent and detect accounting fraud in a rapidly changing and technologybased business environment. Data mining methods can assist in prevention and detection of fraudulent transactions as it enables the use of past cases of fraud to build models that can recognize and spot the risk of fraud and can design new techniques for preventing fraudulent financial reporting. This article reviews the concept of accounting fraud, and focuses on some of the available data mining tools and methodologies , as well as other commuter-based techniques and tools that are available to order to assist in preventing accounting fraud and detecting if fraudulent acts have been committed. The article asserts the importance of using the available computer-based and data mining techniques as a prevention mechanism by detecting financial statement fraud, concluding that data mining software propose a good supporting procedure which offers an effective solution to the problem of detecting fraudulent transactions and accounting frauds.