Preventing the unpleasant: fraudulent financial statement detection using financial ratios

Michail Pazarskis, Grigorios Lazos, Andreas G. Koutoupis and George Drogalas

Abstract

The aim of this study is to investigate financial fraud in companies listed on the Athens Stock Exchange during the period 2008–18, in which a major economic crisis took place in Greece. Based on 30 financial indicators resulting from the analysis of financial statements, several statistical tests are applied to the primary sample and the control sample in order to create a model that uses the indicators as “forecasts” to detect possible fraud. The data used in the research were obtained from the financial statements of the listed companies, the reviews in the auditors’ reports and the available data and information from the reports of the Athens Stock Exchange. The proposed model is able to correctly classify the total sample with an accuracy of 78.4%. The results of the research show that the model works effectively in detecting fraudulent financial statements when the economy is operating in crisis conditions. By using financial ratios, this model signals red flags for the audit process, and it could be used as an effective tool by the banking system, internal and external auditors, tax authorities and other government authorities.