Financial statement manipulation in failing Small and Medium-Sized Enterprises in Bosnia and Herzegovina

Elvisa Buljubasic Musanovic; Sanel Halilbegovic

doi:10.15549/jeecar.v8i4.692

Authors

Elvisa Buljubasic Musanovic International Burch University, Sarajevo https://orcid.org/0000-0002-9141-7973
Sanel Halilbegovic International Burch University, Sarajevo

DOI:

https://doi.org/10.15549/jeecar.v8i4.692

Keywords:

financial distress, accounting manipulations, earnings management, wholesale and retail industry,, Beneish M-score, Altman Z-score model

Abstract

The overall objective of this research is to analyze the financial condition of failing companies prior to bankruptcy, in comparison with non-failing companies, which are matched on the industry, size, and time-period. The sample consists of 168 SMEs from the wholesale and retail industry, whose financial statements were analyzed for the 2011-2015 period. The analysis is primarily based on the ratio analysis and the models developed for bankruptcy prediction and financial statement manipulation. Mann-Whitney U test is used to compare differences between failing and non-failing SMEs for a set of twenty variables. Research findings indicate that there is a significant difference between failing and non-failing SMEs, especially in accruals, asset quality, leverage, profitability, and liquidity. For the very first time in the transition economy of CEE Bosnia and Herzegovina, the pre-bankruptcy behavior of failing SMEs is analyzed, providing insights into potentially manipulated areas, which represent the main contribution of the research.

References

Abu Bakar, D. B., & bin Yahya, M. H. (2021). Impact of Financial Information Fraudulence to Financial Distress in Malaysia. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(6), 896–914. https://doi.org/10.17762/turcomat.v12i6.2367 DOI: https://doi.org/10.17762/turcomat.v12i6.2367

Altman, E. I. (1968). Financial Distress, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, 23(4), 589–609. DOI: https://doi.org/10.1111/j.1540-6261.1968.tb00843.x

Altman, E., I. (1983). Corporate Financial Distress: A Complete Guide to Predicting, Avoiding, and Dealing with Bankruptcy (Frontiers in Finance Series) (1st ed.). Wiley.

Association of Certified Fraud Examiners. (2020). Report to the Nations 2020 Global Study on Occupational Fraud and Abuse. https://acfepublic.s3-us-west-2.amazonaws.com/2020-Report-to-the-Nations.pdf

Beneish, M. D. (1999). The Detection of Earnings Manipulation. Financial Analysts Journal, 55(5), 24–36. https://doi.org/10.2469/faj.v55.n5.2296 DOI: https://doi.org/10.2469/faj.v55.n5.2296

Bisogno, M., & De Luca, R. (2015). Financial Distress and Earnings Manipulation: Evidence from Italian SMEs. Journal of Accounting and Finance, 4(1), 42–51. DOI: https://doi.org/10.24102/ijbrd.v5i1.594

Bisogno, M., Restaino, M., & Di Carlo, A. (2018). Forecasting and preventing bankruptcy: A conceptual review. African Journal of Business Management, 12(9), 231–242. https://doi.org/10.5897/ajbm2018.8503 DOI: https://doi.org/10.5897/AJBM2018.8503

Boda, M., & Úradní?ek, V. (2016). The Portability of Altman’s Z-score Model to Predicting Corporate Financial Distress of Slovak Companies. Technological and Economic Development of Economy, 22(4), 532–553. https://doi.org/10.3846/20294913.2016.1197165 DOI: https://doi.org/10.3846/20294913.2016.1197165

Campa, D., & Camacho-Miñano, M. D. M. (2014). Earnings management among bankrupt non-listed firms: evidence from Spain. Spanish Journal of Finance and Accounting / Revista Española de Financiación y Contabilidad, 43(1), 3–20. https://doi.org/10.1080/02102412.2014.890820 DOI: https://doi.org/10.1080/02102412.2014.890820

Chen, Y., Chen, C., & Huang, S. (2010). An Appraisal of Financially Distressed Companies’ Earnings Management. Pacific Accounting Review, 22(1), 22–41. https://doi.org/10.1108/01140581011034209 DOI: https://doi.org/10.1108/01140581011034209

Csikosova, A., Janoskova, M., & Culkova, K. (2019). Limitation of Financial Health Prediction in Companies from Post-Communist Countries. Journal of Risk and Financial Management, 12(1), 15. https://doi.org/10.3390/jrfm12010015 DOI: https://doi.org/10.3390/jrfm12010015

Dalnial, H., Kamaluddin, A., Sanusi, Z. M., & Khairuddin, K. S. (2014). Accountability in Financial Reporting: Detecting Fraudulent Firms. Procedia - Social and Behavioral Sciences, 145, 61–69. https://doi.org/10.1016/j.sbspro.2014.06.011 DOI: https://doi.org/10.1016/j.sbspro.2014.06.011

Dani, R. M., Ismail, W. A. W., & Kamarudin, K. A. (2013). Can Financial Ratios Explain the Occurrence of Fraudulent Financial Statements? The 5th International Conference on Financial Criminology (ICFC), N/A(N/A), 345–354.

Dechow, P. M., Ge, W., Larson, C. R., & Sloan, R. G. (2011). Predicting Material Accounting Misstatements. Contemporary Accounting Research, 28(1), 17–82. https://doi.org/10.1111/j.1911-3846.2010.01041.x DOI: https://doi.org/10.1111/j.1911-3846.2010.01041.x

Dechow, P. M., Sloan, R. G., & Sweeney, A. P. (1995). Detecting Earnings Management. American Accounting Association, 70(2), 193–225. https://www.jstor.org/stable/248303?seq=1

Dichev, I. D., & Dechow, P. M. (2002). The Quality of Accruals and Earnings: The Role of Accrual Estimation Errors. The Accounting Review, 77, 35–59. https://doi.org/10.2139/ssrn.277231 DOI: https://doi.org/10.2308/accr.2002.77.s-1.35

Djuric, D., & Jovanovic, V. (2019). “Too big to fail”? The Agrokor case and its impact on West Balkan economies. International Insolvency Review, 28(1), 22–43. https://doi.org/10.1002/iir.1327 DOI: https://doi.org/10.1002/iir.1327

European Commission. (2019, May). Analytical Report - Commission Opinion on Bosnia and Herzegovina’s application for membership of the European Union (COM(2019) 261 final).

Gerantonis, N., Vergos, K., & Christopoulos, A. G. (2009). Can Altman Z-score Models Predict Business Failures in Greece. Research Journal of International Studies, 12(N/A), 21–28.

Grove, H., Cook, T., Streeper, E., & Throckmorton, G. (2010). Bankruptcy and Fraud Analysis: Shorting and Selling Stocks. Journal of Forensic & Investigative Accounting, 2(2), 276–293.

Harrington, C. (2005). Detecting Financial Statement Fraud. New Perspectives - Association of Healthcare Internal Auditors, 26–27.

Jones, J. J. (1991). Earnings Management During Import Relief Investigations. Journal of Accounting Research, 29(2), 193. https://doi.org/10.2307/2491047 DOI: https://doi.org/10.2307/2491047

Kiaupaite-Grushniene, V. (2016, December). Altman Z-score Model for Bankruptcy Forecasting of the Listed Lithuanian Agricultural Companies. In J. Alver (Ed.), 5th International Conference on Accounting, Auditing, and Taxation: Advances in Economics, Business and Management Research (pp. 222–234). Atlantis Press. https://doi.org/10.2991/icaat-16.2016.23 DOI: https://doi.org/10.2991/icaat-16.2016.23

Kothari, S., Leone, A. J., & Wasley, C. E. (2005). Performance matched discretionary accrual measures. Journal of Accounting and Economics, 39(1), 163–197. https://doi.org/10.1016/j.jacceco.2004.11.002 DOI: https://doi.org/10.1016/j.jacceco.2004.11.002

Kubí?ková, D., & Nulí?ek, V. (2019). The Prediction Ability of New Bankruptcy Models in National Environment. Proceedings of the International Scientific Conference Hradec Economic Days 2019 Part I. Published. https://doi.org/10.36689/uhk/hed/2019-01-050 DOI: https://doi.org/10.36689/uhk/hed/2019-01-050

Lesáková, U., Gundová, P., & Vinczeová, M. (2020). The practice of use of models predicting financial distress in Slovak companies. Journal of Eastern European and Central Asian Research (JEECAR), 7(1), 122–136. https://doi.org/10.15549/jeecar.v7i1.369 DOI: https://doi.org/10.15549/jeecar.v7i1.369

Liou, F., & Yang, C. (2008). Predicting Business Failure Under the Existence of Fraudulent Financial Reporting. International Journal of Accounting & Information Management, 16(1), 74–86. https://doi.org/10.1108/18347640810887771 DOI: https://doi.org/10.1108/18347640810887771

MacCarthy, J. (2017). Using Altman Z-score and Beneish M-score Models to Detect Financial Fraud and Corporate Failure: A Case Study of Enron Corporation. International Journal of Finance and Accounting, 6(6), 159–166. https://doi.org/10.5923/j.ijfa.20170606.01

Mahama, M. (2015). Detecting Corporate Fraud and Financial Distress Using the Altman and Beneish Models. International Journal of Economics, Commerce and Management, 3(1), 1–18.

Ofori, E. (2016). Detecting Corporate Financial Fraud Using Modified Altman Z-Score and Beneish M-Score. The Case of Enron Corp. Research Journal of Finance and Accounting, 7(4), 59–65.

Ogachi, D., Ndege, R., Gaturu, P., & Zoltan, Z. (2020). Corporate Bankruptcy Prediction Model, a Special Focus on Listed Companies in Kenya. Journal of Risk and Financial Management, 13(3), 47–61. https://doi.org/10.3390/jrfm13030047 DOI: https://doi.org/10.3390/jrfm13030047

Perols, J. L., & Lougee, B. A. (2011). The Relation Between Earnings Management and Financial Statement Fraud. Advances in Accounting, 27(1), 39–53. https://doi.org/10.1016/j.adiac.2010.10.004 DOI: https://doi.org/10.1016/j.adiac.2010.10.004

Sloan, R. G. (1996). Do Stock Prices Fully Reflect Information in Accruals and Cash Flows about Future Earnings? The Accounting Review, 71(3), 289–315.

Svabova, L., Kramarova, K., Chutka, J., & Strakova, L. (2020). Detecting Earnings Manipulation and Fraudulent Financial Reporting in Slovakia. Oeconomia Copernicana, 11(3), 485–508. https://doi.org/10.24136/oc.2020.020 DOI: https://doi.org/10.24136/oc.2020.020

Tarjo, & Herawati, N. (2015). Application of Beneish M-Score Models and Data Mining to Detect Financial Fraud. Procedia - Social and Behavioral Sciences, 211, 924–930. https://doi.org/10.1016/j.sbspro.2015.11.122 DOI: https://doi.org/10.1016/j.sbspro.2015.11.122

Warshavsky, M. (2012). Analyzing Earnings Quality as a Financial Forensic Tool. Financial Valuation and Litigation Expert Journal, N/A(39), 16–20.