Arzhenovskii S.V. Rostov State University of Economics (RSUE), Rostov-on-Don, Russian Federation firstname.lastname@example.org
Bakhteev A.V. Rostov State University of Economics (RSUE), Rostov-on-Don, Russian Federation email@example.com
Slobodyan A.S. Southern Federal University, Rostov-on-Don, Russian Federation firstname.lastname@example.org
Importance 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. Objectives 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. Methods 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. Results 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. Conclusions and Relevance 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.
Keywords: auditing, fraud, risk of material misstatement, regression model, discrete choice
Beneish M. Detecting GAAP Violations: Implications for Assessing Earnings Management among Firms with Extreme Financial Performance. Journal of Accounting and Public Policy, 1997, vol. 16, iss. 3, pp. 271–309. doi: 10.1016/S0278-4254(97)00023-9
Beneish M.D. The Detection of Earnings Manipulation. Financial Analysts Journal, 1999, vol. 55, no. 5, pp. 24–36.
Roxas M.L. Financial Statement Fraud Detection Using Ratio and Digital Analysis. Journal of Leadership, Accountability and Ethics, 2011, vol. 8(4), pp. 56–66.
Jones K.L. Improving Fraud Risk Assessments through Analytical Procedures. The University of Arizona, 2004.
Jones J.J. Earnings management during import relief investigations. Journal of Accounting Research, 1991, vol. 29, no. 2, pp. 193–228. doi: 10.2307/2491047
Spathis C.T. Detecting false financial statements using published data: Some evidence from Greece. Managerial Auditing Journal, 2002, vol. 17, no. 4, pp. 179–191.
Mohamed Yusof K., Ahmad Khair A.H., Jon Simon. Fraudulent Financial Reporting: An Application of Fraud Models to Malaysian Public Listed Companies. The Macrotheme Review, 2015, vol. 4, no. 3, pp. 126–145.
Oshinsky R., Olin V. Troubled banks: Why don't they all fail? FDIC Banking Review, 2006, vol. 18(1), pp. 23–44.
Egorova O.Yu. [Classification of approaches, models and diagnostic methods of bank bankruptcy]. Global'nye rynki i finansovyi inzhiniring = Global Markets and Financial Engineering, 2015, vol. 2, no. 3, pp. 229–244. (In Russ.) doi: 10.18334/grfi.2.3.1916
Peresetskii A.A. Modeli prichin otzyva litsenzii u rossiiskikh bankov [Modeling the reasons for Russian bank license withdrawal]. Moscow, Rossiiskaya Ekonomicheskaya Shkola Publ., 2010, 26 p.
Peresetskii A.A. [Modeling reasons for Russian bank license withdrawal: Unaccounted factors]. Prikladnaya ekonometrika = Applied Econometrics, 2013, vol. 30, no. 2, pp. 49–64. (In Russ.)
Peresetskii A.A. Ekonometricheskie metody v distantsionnom analize deyatel'nosti rossiiskikh bankov [Econometric methods in the remote analysis of Russian banks]. Moscow, NRU HSE Publ., 2012, 235 p.
Fetisov G.G. Ustoichivost' kommercheskogo banka i reitingovye sistemy ee otsenki [Sustainability of a commercial bank and rating systems for its evaluation]. Moscow, Finansy i statistika Publ., 1999, 168 p.
Afanas'eva O.N. [Methodology for determining the stability of the banking system]. Bankovskoe delo = Banking, 2016, no. 1, pp. 11–16. (In Russ.)
Lanine G., Vennet R. Failure Prediction in the Russian Bank Sector with Logit and Trait Recognition Models. Expert Systems with Applications, 2006, vol. 30, iss. 3, pp. 463–478. doi: 10.1016/j.eswa.2005.10.014
Emel'yanov A.M., Bryukhova O.O. [Drivers of banks license withdrawal: The after crisis (2010–2011) study]. Ekonomika i matematicheskie metody = Economics and Mathematical Methods, 2015, vol. 51, no. 3, pp. 41–53. (In Russ.)
Maddala G.S. Limited-dependent and Qualitative Variables in Econometrics. Cambridge University Press, 1983.