UPOTREBA NEFINANSIJSKIH MERA U UNAPREĐENJU PROCENE RIZIKA OD PREVARA: MOGUĆNOSTI I OGRANIČENJA

  • Marko Špiler Novi Sad School of Business
  • Vesna Bogojević Arsić Fakultet organizacionih nauka, Univerzitet u Beogradu
  • Snežana Knežević Fakultet organizacionih nauka, Univerzitet u Beogradu
Ključne reči: nefinansijske mere, finansijske mere, rizik, prevarne radnje, kompanije

Sažetak


Prethodna istraživanja ukazuju na rastuću potrebu za bavljenje problematikom prevarnog finansijskog istraživanja. Pored finansijskih mera, i nefinansijske mere su te koje treba uzimati u obzir u procesu merenja ekonomskog učinka preduzeća. Ovo istraživanje ukazuje na značaj integrisanog načina u merenju finansijskih performansi komanije u proceni rizika od nastanka prevarnih radnji, što podrazumeva primenu nefinansijskih mera učinka zajedno sa finansijskim. Ukoliko postoji razlika između nefinansijskih mera i finansijskih performansi, to može da bude znak upozorenja da je moguće postojanje rizika od prevarne radnje. Istraživanja o primeni nefinansijskih mera u poboljšanju procene rizika od prevarnih radnji su oskudna kada se posmatra srpski kontekst. Stoga će ovo istraživanje dodati vrednost postojećoj literaturi za upravljanje rizikom od prevarnih radnji u finansijskim izveštajima.

Reference

Ames, D., Brazel, J. F., Jones, K. L., Rich, J. S., & Zimbelman, M. F. (2012). Using Nonfinancial Measures to Improve Fraud Risk Assessments. Current Issues in Auditing, 6(1), 28–34. doi:10.2308/ciia50168.

Amiram, D., Bozanic, Z., Cox, J. D., Dupont, Q., Karpoff, J., & Sloan, R. (2018). Financial reporting fraud and other forms of misconduct: A multidisciplinary review of the literature. Review of Accounting Studies, 23(2), 732-783.

Bhasin, M. L. (2013). Corporate Accounting Fraud: A Case Study of Satyam Computers Limited. Open Journal of Accounting, 2(2), 26-38. doi:10.4236/ojacct.2013.22006.

Brazel, J. F., Jones, K. L., & Zimbelman, M. F. (2009). Using nonfinancial measures to assess fraud risk. Journal of Accounting Research, 47(5), 1135–1166.

Brown, A., Milašinović, M., Mitrović, A., & Knežević, S. (2020). Are audit opinions related to bancruptcy forecasting of companies listed on the Sector A-Agriculture, forestry and fisheries? Fresenius Environmental Bulletin, 29(11), 9899-9905.

Christopher D. I. & Larcker, D. F. (1998). Are Nonfinancial Measures Leading Indicators of Financial Performance? An Analysis of Customer Satisfaction Reviewed work(s): Journal of Accounting Research, 36, 1-35.

Dechow, P. M., Ge, W., Larson, C. R. and Sloan, R. G. (2011). Predicting material accounting misstatements. Contemporary Accounting Research, 28(1), 17–82.

Dong, W., Liao, S. S., Fang, B., Cheng, X., Chen, Z., & Wenjie, F. (2014). The detection of fraudulent financial statements: an integrated language model. PACIS 2014 Proceedings. 383. Available at: http://aisel.aisnet.org/pacis2014/383.

Erdoğan, M., & Erdoğan, E. O. (2020). Financial Statement Manipulation: A Beneish Model Application. In Contemporary Issues in Audit Management and Forensic Accounting (pp.173-188), doi:10.1108/s1569-

Ilter, C. (2014), Misrepresentation of financial statements: An accounting fraud case from Turkey. Journal of Financial Crime, 21(2), 215-225. https://doi.org/10.1108/ JFC-04-2013-0028.

Kaminski, K. A., Sterling Wetzel, T., & Guan, L. (2004). Can financial ratios detect fraudulent financial reporting? Managerial Auditing Journal, 19(1), 15- 28. Available at: https://doi.org/10.1108/02686900410509802.

Кnežević, S., Cvetković, D., Mićović, M., Mitrović, A., & Milojević, S. (2021). Analysis of the Presence of Criminal Offenses in the Field of the Shadow Economy in Serbia. Lex localis - Journal of Local Self-Government, 19(1), 131-147.

Kochinev, Y., Antysheva, E., & Putintseva, N. (2020). Formalization of Analytical Procedures for Assessing the Risks of Material Misstatement in Financial Statements due to Fraud. In Proceedings from International Scientific Conference on Innovations in Digital Economy (pp. 1-5). Available at: https://doi.org/10.1145/3444465.3444532.

Kukreja, G., Gupta, S. M., Sarea, A. M., & Kumaraswamy, S. (2020). Beneish M-score and Altman Z-score as a catalyst for corporate fraud detection. Journal of Investment Compliance, 21(4), 231- 241. https://doi.org/10.1108/JOIC-09-2020-0022.

Low, J., & Siesfeld, T. (1997). Measures that matter: Non-Financial Performances. Strategy & Leadership. Emerald Backfilles.

Meyer, C. (2015). Pay attention to nonfinancial measures when performing audits. Journal of Accountancy, 14. Available at: https://www.journalofaccountancy.com/newsletters/2015/sep/nonfinancial-measures-when-performing-audits.html.

Milojević, S., Đurić, O., Maksimović, D., & Rađenović, I. (2021). Monitoring of expenditure and revenue and fraudulent financial reporting. In Education and Social Sciences Business and Economics (p. 3). International Academic Institute, Skopje, Republic of N. Macedonia.

Noviarty, H., Puspitasari, A., & Heniwati, E. (2021). Do Internal Auditor and Audit Committee Have Impact on Audit Report Lag for Mining Industry? Journal Akuntansi dan Keuangan, 23(1), 15-23. doi: 10.9744/jak.23.1.15- 23.

Obradović, V., Milašinović, M., & Bogićević, J. (2021). Segment disclosures in the financial statements of stock companies in the Republic of Serbia and the Republic of Croatia. Ekonomski horizonti, 23(1), 55-70. https://doi.org/10.5937/ ekonhor2101055O.

Omar, N., Johari, Z., & Smith, M. (2017). Predicting fraudulent financial reporting using artificial neural network. Journal of Financial Crime, 24(2), 362-387. https://doi.org/10.1108/JFC-11-2015-0061.

Pallant, J. (2007). SPSS Survival Manual: A step by step guide to data analysis using SPSS for Windows. Open University Press.

Persons, O. S. (1995). Using Financial Statement Data to Identify Factors Associated with Fraudulent Financial Reporting. Journal of Applied Business Research (JABR), 11(3), 38-46. https://doi.org/10.19030/jabr.v11i3.5858.

Repousis, S. (2016). Using Beneish model to detect corporate financial statement fraud in Greece. Journal of Financial Crime, 23(4), 1063–1073. doi:10.1108/jfc-11-2014-0055.

Rezaee, Z., Ha, M., & Lo, D. (2014). China Needs Forensic Accounting Education. Open Journal of Social Sciences, 2, 59-65.doi:10.4236/jss. 2014.25013.

Skousen, C. J., Smith, K. R., & Wright, C. J. (2009). Detecting and predicting financial statement fraud: The effectiveness of the fraud triangle and SAS No. 99. In M. Hirschey, K. John, & A. K. Makhija (Eds.) Corporate Governance and Firm Performance (pp. 53-81). Emerald Group Publishing Limited. https://doi.org/10.1108/S15693732(2009)0000013005.

Stuart, T., & Wang, Y. (2016). Who cooks the books in China, and does it pay? Evidence from private, high-technology firms. Strategic Management Journal, 37(13), 2658–2676. doi:10.1002/smj.2466.

Teeratansirikool, L., Siengthai, S., Badir, Y., & Charoenngam, C. (2013). Competitive strategies and firm performance: the mediating role of performance measurement. International Journal of Productivity and Performance Management, 62(2), 168–184. doi:10.1108/17410401311295722.

Zhou, W. & Kapoor, G. (2011). Detecting evolutionary financial statement fraud. Decision Support Systems, 50(3), 570-575, https://doi.org/10.1016/j.dss.2010.08.007.

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2024/01/31
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