The Ability of Financial Ratios in Detecting Fradulent Financial Reporting: Logit Analysis

Using logit analysis in cross section data, this paper examine the role of accounting data to develop a model for detecting factors associated with fraudulent financial reporting. The sample is comprised of 178 firms (66 with fraudulent financial reporting and 112 with non-fraudulent financial reporting) listed in Tehran Stock Exchange (TSE) during the period of 1383-1386. Firms with fraudulent financial reports selected on the basis of 1) Inclution of company in TSE lists for reasons associated with falsification of financial data and 2) doing insider trading and the existence of court proceedings pending with respect to fraudulent financial reporting. After doing analysis ten financial ratios introduced for examination as potential predictors of fraudulent financial reporting. The results indicate that the model is accurate in classifying the total sample correctly with accuracy rate exceeding 82.98 percent. Also, results demonstrate that the models function effectively in detecting fraudulent financial reporting and can be of assistance to various users such as auditors, taxation and other state authorities, the banking system, and so on.