Detecting fraudulent financial reporting: Teaching the ‘Watchdog’ new tricks

Abstract

The purpose of this study is to identify those approaches and techniques from the literature which auditors could usefully employ to detect fraudulently complied financial statements. The classification which results includes a brief analysis of a number of studies classified within the following categories: prediction models, expert systems, neural networks, Benford’s law, computer technology assistance, simple analytical procedure, ‘red flag’ grouping and broad strategies. We conclude on how this analysis could be useful to future researchers and to auditors in the field who are seeking to improve their approach to detecting material fraud in the financial statements.