Fraudulent financial reporting and related party transactions
Evidence from a mining industry in a developing country
DOI:
https://doi.org/10.20525/ijrbs.v12i2.2365Keywords:
Related Party Transactions, Fraudulent Financial Reporting, Accounting Fraud, Forensic Accounting Tools, Fraud Detection, M-score, Z-scoreAbstract
The study assessed the possibility of accounting fraud among Zambian listed companies with a focus on the mining sector and the relationship between related party transactions (RPTs) and financial statement manipulation (FSM). The financial statements (2012 to 2020) of listed companies were analysed to detect accounting fraud using the M-score and the Z-score. Descriptive statistics were used to explain the extent of FSM. The Chi-Square test of independence was employed to test the relationship between FSM and RPTs. Both the Z-Score and M-Score indicate that the mining companies were possibly involved in FSM. There is a relationship between the FSM and RPTs. The Total Accruals to Total Assets, Days in Sales in Receivables Index and Sales Growth Index show that revenue and profits were the most manipulated. The RPTs disclosures were the lowest for mining companies. Relevant authorities should not neglect FSM as a form of fraud despite the routine external audit of financial statements. There is the potential loss of tax revenue through accounting fraud.
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References
ACFE. (2018). Report to the nation’s 2018 global study on occupational fraud and abuse. Government Edition, Association of Certified Fraud Examiners, New York, NY.
AICPA. (2001). Accounting and Auditing for Related Party Transactions: A Toolkit for Accountants and Auditors. AICPA, New York, NY.
Akoglu, H. (2018). User’s guide to correlation coefficients. Turkish Journal of Emergency Medicine, 18, 91–93. https://doi.org/10.1016/j.tjem.2018.08.001 DOI: https://doi.org/10.1016/j.tjem.2018.08.001
Alhadab. M., Abdullatif, M., & Mansour, I. (2020). Related party transactions and earnings management in Jordan: the role of ownership structure. Journal of Financial Reporting and Accounting, 18(3), 505-531. https://doi.org/10.1108/JFRA-01-2019-0014 DOI: https://doi.org/10.1108/JFRA-01-2019-0014
Altman, E.I. (1968). Financial ratios, 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
Amidu, M., Coffie., W., & Acquah, P. (2019). Transfer pricing, earnings management and tax avoidance of firms in Ghana. Journal of Financial Crime, 26 (1), 235-259. https://doi.org/10.1108/JFC-10-2017-0091 DOI: https://doi.org/10.1108/JFC-10-2017-0091
Aviantara, R. (2020). Scoring the financial distress and the financial statement fraud of Garuda Indonesia with «DDCC» as the financial solutions. Journal of Modelling in Management, pp.1-16. https://doi.org/10.1108/JM2-01-2020-0017 DOI: https://doi.org/10.1108/JM2-01-2020-0017
Beerbaum, D.O. & Piechocki, M. (2017). Related Party Transactions – Empirical Study based on IFRS and SEC Disclosures. Available at SSRN: https://ssrn.com/abstract=2665015 or http://dx.doi.org/10.2139/ssrn.2665015 DOI: https://doi.org/10.2139/ssrn.2665015
Beneish, M.D. (1999). The detection of earnings manipulation. Financial Analysts Journal, 55(5), 24-36. DOI: https://doi.org/10.2469/faj.v55.n5.2296
Bhavani, G., & Amponsah, C.T. (2017). M score and Z score for detection of accounting fraud. Accountancy Business and the Public Interest, 16, 68-86.
Bhuiyan, U.B., & Roudaki, J. (2018). Related party transactions and finance company failure: New Zealand evidence. Pacific Accounting Review, 30(2), 199-221. https://doi.org/ 10.1108/PAR-11-2016-0098 DOI: https://doi.org/10.1108/PAR-11-2016-0098
Cahan, F.S. (1992). The Effect of Antitrust Investigations on Discretionary Accruals: A Refined Test of the Political-Cost Hypothesis. The Accounting Review, 67(1), pp. 77-95.
Caprio, G. (2012). The Evidence and Impact of Financial Globalization. Academic Press. Crumbley, L.D., Lester, E.H., Stevenson, S., & Smith, S.G. (2017). Forensic and Investigative Accounting, (8th ed), Wolters Kluwer, Riverwoods.
Cynthia, H. (2005). Analysis ratios for detecting Financial Statement fraud. ACFE Fraud Magazine.
Djankov, S., La Porta, R., Lopez-De-Silanes, F., & Shleifer, A. (2008). The law and economics of self-dealing. Journal of Financial Economics, 88(3), 430-465. DOI: https://doi.org/10.1016/j.jfineco.2007.02.007
El-Helaly, M. (2016). Related party transactions and accounting quality in Greece. International Journal of Accounting and Information Management, 24(4), 375-390. DOI: https://doi.org/10.1108/IJAIM-04-2016-0044
El-Helaly, M. (2018). Related-party transactions: a review of the regulation, governance and auditing literature. Managerial Auditing Journal, 33(8/9), 779-806. https://doi.org/10.1108/MAJ-07-2017-1602 DOI: https://doi.org/10.1108/MAJ-07-2017-1602
Ericsson, M., & Löf, O. (2019). Mining’s contribution to national economies between 1996 and 2016. Mineral Economics, 32, 223–250. https://doi.org/10.1007/s13563-019-00191-6 DOI: https://doi.org/10.1007/s13563-019-00191-6
Fang, J., Lobo, G., Zhang, Y., & Zhao, Y. (2018). Auditing related party transactions: evidence from audit opinions and restatements. Auditing: A Journal of Practice and Theory, 37(2), 73-106. DOI: https://doi.org/10.2308/ajpt-51768
Fanning, K.M. (1998). Neural network detection of management fraud using published financial data. International Journal of Intelligent Systems in Accounting, Finance &Management, 7(1), 21-41. DOI: https://doi.org/10.1002/(SICI)1099-1174(199803)7:1<21::AID-ISAF138>3.0.CO;2-K
Fisman, R., & Wang, X.Y. (2010). Trading favors within Chinese business groups. American Economic Review,100 (2), 429-433. DOI: https://doi.org/10.1257/aer.100.2.429
Ge, W., Drury, D.H., Fortin, S., Liu, F., & Tsang, D. (2010). Value relevance of disclosed related party transactions. Advances in Accounting, 26(1), 134-141. DOI: https://doi.org/10.1016/j.adiac.2010.02.004
Godfrey, J., Hodgson, A., Tarca, A., Hamilton, J., & Holmes, S. (2010). Accounting Theory 7th Edition. New York: McGraw Hill.
Hakami, A.T., Rahmat, M.M., Yaacob, H.M., & Saleh, M.N. (2020). Fraud Detection Gap between Auditor and Fraud Detection Models: Evidence from Gulf Cooperation Council. Asian Journal of Accounting and Governance, 13, 1–13. http://dx.doi.org/10.17576/AJAG-2020-13-01 DOI: https://doi.org/10.17576/AJAG-2020-13-01
Hasan, S.M., Omar, N., Barnes, P., & Handley-Schachler, M. (2017). A cross-country study on manipulations in financial statements of listed companies: Evidence from Asia. Journal of Financial Crime, 24(4), 656-677. https://doi.org/10.1108/JFC-07-2016-0047 DOI: https://doi.org/10.1108/JFC-07-2016-0047
Hasan, S.M., Omar. N., & Hassan, R.A., (2018). Financial health and management practices: a multi-year cross country analysis of PLCs. Journal of Financial Crime, 25(3), 646 657. https://doi.org/10.1108/JFC-01-2017-0002 DOI: https://doi.org/10.1108/JFC-01-2017-0002
Henry, E., Gordon, E., Reed, B., & Louwers, T. (2012). The role of related party transactions in fraudulent financial reporting. Journal of Forensic and Investigative Accounting, 4(2), 186-213.
Ho?da, A. (2020). Using the Beneish M-score model: Evidence from non-financial companies listed on the Warsaw Stock Exchange. Investment Management and Financial Innovations,17(4),389-401. http://dx.doi.org/10.21511/imfi.17 (4).2020.33 DOI: https://doi.org/10.21511/imfi.17(4).2020.33
Holtzblatt, A.M., Foltin, C., & Tschakert, N. (2020). Learning from Ethical Violations in Public Accounting: A South African Audit Scandal and a Firm's Transformation. Issues in Accounting Education, 35 (2), 37–63. https://doi.org/10.2308/issues-19-062 DOI: https://doi.org/10.2308/issues-19-062
Ibadin, O.P., & Ehigie, H.A. (2019). Beneish Model, Corporate Governance and Financial Statements Manipulation. Asian Journal of Accounting and Governance, 12, 51–64. http://dx.doi.org/10.17576/AJAG-2019-12-05 DOI: https://doi.org/10.17576/AJAG-2019-12-05
IFRS Foundation. (2018). Mission Statement. [Online] Available from: https://www.ifrs.org/ [Accessed: 01.02.2022].
Kabwe, M., Mwanaumo, E. & Chalu, H. (2021a). Effect of corporate governance attributes on IFRS compliance: evidence from a developing country. Corporate Governance, 21(1), 1-22. https://doi.org/10.1108/CG-03-2020-0103 DOI: https://doi.org/10.1108/CG-03-2020-0103
Kabwe, M., Mwanaumo, E., & Chalu, H. (2020). Extent of compliance with international financial reporting standards (IFRSS) disclosures in a developing country: evidence from Zambian listed companies. International Journal of Commerce and Management Research, 6(3), 37-46.
Kabwe, M., Mwanaumo, E., & Chalu, H.(2021b). Antecedents of IFRS Compliance: The Moderating Effect of Audit Quality. Journal of Finance and Accounting, 9(6), 216-229. https://doi.org/10.11648/j.jfa.20210906.12 DOI: https://doi.org/10.11648/j.jfa.20210906.12
Kahnna, T., & Palepu, K. (2000). Is group affiliation profitable in emerging markets? An analysis of diversified Indian business groups. Journal of Finance, 55(2), 867-891. DOI: https://doi.org/10.1111/0022-1082.00229
Kukreja, G., Gupta, M.S., Sarea, M.A., & 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. ISSN 1528-5812. https://doi.org/10.1108/JOIC-09-2020-0022 DOI: https://doi.org/10.1108/JOIC-09-2020-0022
Lenard, M.J., & Alam, P. (2009). An historical perspective on fraud detection: from bankruptcy models to most effective indicators of fraud in recent incidents. Journal of Forensic and Investigative Accounting, 1(1), 1-27.
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.
Maniatis, A. (2022). Detecting the probability of financial fraud due to earnings manipulation in companies listed in Athens Stock Exchange Market. Journal of Financial Crime, 29(2), 603-619. https://doi.org/10.1108/JFC-04-2021-008 DOI: https://doi.org/10.1108/JFC-04-2021-0083
Marchini, P.L., Mazza, T., & Medioli, A. (2018). Related party transactions, corporate governance and earnings management. Corporate Governance: The International Journal of Business in Society, 18(6), 1124-1146. DOI: https://doi.org/10.1108/CG-11-2017-0271
Mehta, A., & Bhavani, G. (2017). Application of Forensic Tools to Detect Fraud: The Case of Toshiba. Journal of Forensic and Investigative Accounting, 9 (1), 692-710.
Omar, N., Koya, R.K., Sanusi, Z.M., & Shafie, N.A. (2014). Financial statement fraud: a case examination using beneish model and ratio analysis. International Journal of Trade, Economics and Finance, 5(2), 184-186. DOI: https://doi.org/10.7763/IJTEF.2014.V5.367
Panel on Audit Effectiveness. (2000). The Panel on Audit Effectiveness Report and Recommendations. Public Oversight Board.
Pereira, C. and Cerqueira, A. (2020). The Effect of Economic Conditions on Accounting Conservatism under IFRS in Europe. Review of Economic Perspectives – Národohospodá?ský obzor, Vol. 20(2), pp.137–169, https://doi.org/10.2478/revecp-2020-0007 DOI: https://doi.org/10.2478/revecp-2020-0007
Persons, O.S. (2011). Using financial statement data to identify factors associated with fraudulent financial reporting. Journal of Applied Business Research, 11(3), 38-46. DOI: https://doi.org/10.19030/jabr.v11i3.5858
Pustylnick, E.I. (2015). Use of Z-Score in detection of earnings manipulation. SSRN Electronic Journal, 1-18, available at: http://ssrn.com/abstract=2577473 DOI: https://doi.org/10.2139/ssrn.2577473
Rafay, A. (2022). Related party disclosures in financial reporting for Islamic banks. Journal of Islamic Accounting and Business Research, 1-21. https://doi.org/10.1108/JIABR-03-2020-0066 DOI: https://doi.org/10.1108/JIABR-03-2020-0066
Rahmat, M.M., Muniandy. B., & Ahmed, K. (2019). Do related party transactions affect earnings quality? Evidence from East Asia. International Journal of Accounting & Information Management, 28(1), 147-166. https://doi.org/ 10.1108/IJAIM-12-2018-0146 DOI: https://doi.org/10.1108/IJAIM-12-2018-0146
Ratmono, D., Darsono, D., & Cahyonowat, N. (2020). Financial Statement Fraud Detection with Beneish M-Score and Dechow F-Score Model: An Empirical Analysis of Fraud Pentagon Theory in Indonesia. International Journal of Financial Research, 11(6), 154-164. https://doi.org/10.5430/ijfr. v11n6p154 DOI: https://doi.org/10.5430/ijfr.v11n6p154
Readhead, A. (2016). Transfer Pricing in the Mining Sector in Zambia. Natural Resource Governance Institute, 1-28.
Repousis, S. (2016). Using Beneish model to detect corporate financial statement fraud in Greece, Journal of Financial Crime, 23(4), 1063-1073. https://doi.org/ 10.1108/JFC-11- 2014-0055 DOI: https://doi.org/10.1108/JFC-11-2014-0055
Rittenberg, L., Johnstone, K., and Gramling, A. (2011). Auditing: A Business Risk Approach. Cengage Learning.
Schilit, H. (2002). Financial Shenanigans, (2nd ed.), McGraw-Hill, New York, NY.
SEC. (2003). Report Pursuant to Section 704 of the Sarbanes-Oxley Act of 2002. Washington D.C.
Sellami, M.Y., & Fendri, B.H. (2017). The effect of audit committee characteristics oncompliance with IFRS for related party disclosures Evidence from South Africa. Managerial Auditing Journal, 32(6), 603-626. https://doi.org/ 10.1108/MAJ-06-2016-1395 DOI: https://doi.org/10.1108/MAJ-06-2016-1395
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. DOI: https://doi.org/10.1016/j.sbspro.2015.11.122
World Bank. (2017). Report on the observance of standards and codes (ROSC)-Accounting and Auditing. World Bank, Zambia.
Zang, A.Y. (2012). Evidence on the trade-off between real activities manipulation and accrual based earnings management. The Accounting Review, 87(2), 675-703. DOI: https://doi.org/10.2308/accr-10196
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