Detecting false financial statements: evidence from Greece in the period of economic crisis

Abstract

The purpose of this study is the examination of the financial fraud in Greek companies, listed on the Athens Exchange for the period of 2008-2015 during the economic crisis in Greece. The data of all the listed companies that were used comprise financial statements, reviews in the reports by the auditors and the figures and information based on the reports of the Athens Exchange. A total of twelve companies were found and they comprise the primary research sample with fraud in their financial statements (FFS), while another twelve companies were employed as a control sample (non-FFS) for various comparisons. From thirty financial ratios, several statistical tests to the sample and the control sample are applied in order to create a model that will use ratios as “predictors” in the analysis of financial statements for fraud. The model is accurate in classifying the total sample correctly with accuracy rates exceeding 90 percent. The results demonstrate that the model functions effectively in detecting FFS in a period of economic crisis and could be used as a tool to the banking system, from internal and external auditors and taxation or other state authorities.

Feature Selection for Dimension Reduction of Financial Data for Detection of Financial Statement Frauds in Context to Indian Companies

“…Mean ratio analysis was performed to find out the individual ratio's ability to clearly distinguish a behavioural pattern of fraudulent companies in comparison with non-fraudulent companies. Pazarskis et al (2017) indicated that the ratios with high difference between the fraudulent and non-fraudulent sample have high probability of being related to the falsification of the financial statements of the company. Through mean ratio analysis the significance of each selected ratio and possible motivations behind the fraud committed by the fraudulent companies was established.…”

“…The possible reason for this may be that current liabilities include provisions and the provision have scope of manipulations. Pazarskis et al (2017) compared and classified the fraudulent sample on the basis on manipulations done by the companies and found that the maximum companies (24.67%) had manipulated 'Provisions'. Feroz et al (1991) stated that three-fourth cases of SEC enforcement had overstated the inventories and accounts receivables.…”

“…Nia (2015); Zainuddin and Hashim (2016) indicated the existence of strong possibility of manipulations of inventory and accounts receivables in the case of fraudulent companies. Pazarskis et al (2017) found through their research that 12.33 per cent of the fraudulent companies had manipulated inventories and 10.96 per cent of the fraudulent companies had manipulated accounts receivables in their books. The same can be observed in the present study too, that the mean values of IATA (Table 7) in case of fraudulent companies are greater than non-fraudulent companies.…”

Using a hybrid model to detect earnings management for Polish public companies

“…The research on earnings management prediction contributes to understanding factors that can be used to predict fraud. In prior research studies, authors most often used nonlinear regression such as logit and probit models to detect earnings management (Dechow et al, 1996;Beasley, 1996;Beneish, 1999;Spathis et al, 2002;Skounsen et al, 2008;Johnson et al, 2009;Dechow et al, 2011;Amara et al, 2013;Kanapickiene & Grundiene, 2015;Ozcan, 2016;Ozdagoglu et al, 2017;Pazarskis et al, 2017;Nindito, 2018;Mohammadi et al, 2020). In the logit and probit regressions, the coefficients of the explanatory variables do not influence the different values of the indices in the fraudulent and control companies.…”

The international fraud triangle

“…The literature on the pressure to commit fraud is mainly focused on financial pressures (Drogalas et al , 2017; Krambia-Kapardis and Papastergiou, 2016), these pressures comprise the main etiology for fraud as companies “in their effort to survive resorted to falsification of the financial statements, accounting tricks and various methods incompatible with the principles methods” (Pazarskis et al , 2017). In Greece, falsified financial statements have been associated with attempts by companies to reduce the level of taxation on profits (Zopounidis et al , 2000).…”