Logit models to assess the risk of fraudulent misstatements in financial statements of Russian banks
<b>Importance</b> The article investigates the possibilities to apply regression models when performing the audit procedures to assess the risk of material misstatement in financial statement due to fraud. <br></br> <b>Objectives</b> The aim is to develop mathematical models enabling to assess the risk of material misstatement arising from fraud during the financial audit of Russian banks. <br></br> <b>Methods</b> We overview current studies dedicated to model-building to assess the risk of fraud in financial statements, perform a praxeological analysis of information on reasons for financial organizations’ license revocation published by the Bank of Russia. The paper employs econometric modeling using panel data in Stata. <br></br> <b>Results</b> We reviewed the existing regression models that help identify and assess the risk of material misstatement in financial statements, prepared a list of reasons for license withdrawal of Russian banks associated with financial statement fraud, offered a five-factor logit model to assess the said risk in financial statements of Russian commercial banks. <br></br> <b>Conclusions and Relevance</b> If used, the model will increase the efficiency of audit procedures for assessing the risk of material misstatement due to fraud in the course of financial audit of Russian banks.