FINANCIAL STATEMENT FRAUD AND FIRM PERFORMANCE: EMPIRICAL EVIDENCE FROM INDONESIA
Main Article Content
Abstract
Fraudulent financial reporting is an intentional misstatement of the financial
statements, which is the incorrect representation intentionally used to manipulate
the decision of stakeholders by ensuring that they make their decision based on
incorrect information. This study examines factors affecting the likelihood of
financial statement fraud occurrences and differences between fraudulent and nonfraudulent companies listed in Indonesia Stock Exchange with respect to the
company’s profitability over the period 2010 to 2018. Empirical results indicate
that the ratio of current assets to total assets, long-term debt to total equity, total
sales to total equity, and the cost of goods sold to sales have significant impact on
affecting the likelihood of financial statement fraud. Based on the propensity score
matching using cross-sectional data, the study finds that profitability has no
significant difference between fraudulent and non-fraudulent companies
Article Details
References
Albrecht, W. S., Albrecht C.O., Albrecht, C.C. and Zimbelman, M. 2012. Fraud
examination. South-Western Cengage Learning, USA
Association of Certified Fraud Examiner (ACFE). 2017. Cooking the books: What every
accountant should know about fraud. USA
Association of Certified Fraud Examiner (ACFE). 2018. Report to the nations: 2018
Global study on occupational fraud and abuse. Austin, USA.
Association of Certified Fraud Examiner (ACFE) Indonesia Chapter. 2017. Survai fraud
Indonesia 2016. Indonesia: ACFE Indonesia Chapter
Attah, M.I. and Jindal, P. 2017. Impact of misstatement in financial statements on
investment decision making. International Journal of Scientific and Research
Publications. 7(5): 145-150
Brennan, N. M. and McGrath, M. 2007. Financial statement fraud: Some lessons from
US and European case studies. Australian Accounting Review. 17(2): 49-61
CNN Indonesia. 2019. Kronologi kisruh laporan keuangan garuda Indonesia. Retrieved
from https://www.cnnindonesia.com/ekonomi/20190430174733-92-
/kronologi-kisruh-laporan-keuangan-garuda-indonesia
Cressey, D.R. 1953. Other People’s Money: A study in the social psychology of
embezzlement. The Free Press, Glencoe, US.
Dalnial, H., Kamaluddin, A., Sanusi, Z. A. and Khairuddin, K. S. 2014. Detecting
fraudulent financial reporting through financial statement analysis. Journal of
Advanced Management Science. 2(1): 17-22
Indonesia Stock Exchange Website. 2021. Laporan Keuangan Perusahaan Tercatat.
Retrieved from https://www.idx.co.id/perusahaan-tercatat/laporan-keuangandan-tahunan/
Jakarta and Indonesia Stock Exchange Website, 2021. Financial Data. Retrieved from
Jofre, M, and Gerlach, R. 2018. Fighting accounting fraud through forensic data analytics.
Doctoral Dissertation. The University of Sydney Business School, Australia.
Garner, B. A. and Black, H. C. 2004. Black’s law dictionary. 8th ed. St. Paul, MN:
Thomson/West
Gibson, C.H. 2008. Financial reporting and analysis: using financial accounting
information. South-Western College Pub. 11th Edition, USA
Hu, H., Dou, B. and Wang, A. (2019). Corporate social responsibility information
disclosure and corporatre fraud - “risk reduction” effect or “window dressing”
effect? Sustainability. 11(1141): 1-25
Kaminski, K. A., Wetzel, T. S. and Guan, L. 2004. Can financial ratios detect fraudulent
financial reporting? Managerial Auditing Journal. 19(1): 15-28
Kirkos, E., Spathis, C. and Manolopoulos, Y. 2007. Data mining techniques for the
detection of fraudulent financial statements. Expert System with Applications. 32:
-1003
Kotsiantis, S., Koumanakos, E.,Tzelepis, D. and Tampakas, V. 2006. Forecasting
fraudulent financial statements using data mining. International Journal of
Computational Intelligence. 3(2): 104-110
Kreutzfeldt, R. and Wallace, W. 1986. Error characteristic in audit populations: Their
profile and relationship to environment factors. A Journal of Practice and Theory.
: 20-43
Lenard, M. J., Watkins, A. L. and Alam, P. 2007. Effective use of integrated technology
model for evaluating fraud in service-based computer and technology firms.
Journal of Emerging Technologies in Accounting. 4(1): 123-137
Li, Yuhao. 2010. The case analysis of the scandal of Enron. International Journal of
Business and Management. 5(10): 37-41
Lian, Y., Su, Z. and Gu, Y. 2010. Evaluating the effects of equity incentives using PSM:
evidence from China. Frontier of Business Research in China. 5(2): 266-290
Ozcan, Ahmet. 2016. Firm characteristics and accounting fraud: a multivariate approach.
Journal of Accounting, Finance and Auditing Studies. 2(2): 129-144
Persons, O. S. 1995. Using financial statement data to identify factors associated with
fraudulent financial reporting. Journal of Applied Business Research. 11(3): 38-
Priantara, Diaz. 2013. Fraud auditing and investigation. Mitra Wacana Media Publisher
Jakarta, Indonesia
Ravisankar, P., Ravi, V., Rao, G. R. and Bose, I. 2011. Detection of financial statement
and feature selection using data mining techniques. Decision Support Systems. 50:
-500
Rezaee, Zabihollah. 2002. Financial statement fraud: prevention and detection. John
Wiley & Sons, Inc. New York
Rosenbaum, P.R. and Rubin, D.B. 1983. The central role of the propensity score in
observational studies for causal effects. Biometrika. 70(1): 41-55
Rosenbaum, P.R. and Rubin, D.B. 1984. Reducing bias in observational studies using
subsclassification of the propensity score. Journal of the American Statistical
Association. 79(387): 516-524
Sadique, M. 2016. Corporate fraud: An empirical analysis of corporate governance and
earnings management in Malaysia, Doctoral Dissertation, Lincoln University,
New Zealand.
Skousen, C.J., Smith, K. R. and Wright, C.J. 2009. Detecting and predicting financial
statement fraud: The effectiveness of the fraud triangle and SAS No. 99. Emerald
Group Publishing Limited. 53-81
Song, X. P., Hu, Z. H., Du, J. G. and Sheng, Z. 2014. Application of machine learning
methods to risk assessment of financial statement fraud: Evidence from China.
Journal of Forecasting. 33: 611-626
Spathis, Charalambos. 2002. Detecting false financial statement using published data:
Some evidence from Greece. Managerial Auditing Journal. 17(4): 179-191
Spathis, C., Doumpos, M. and Zopounidis, C. 2002. Detecting falsified financial
statements: A comparative study using multicriteria analysis and multivariate
statistical techniques. European Accounting Review. 11(3): 509-535
Springate, G., L., V. 1978. Predicting the Possibility of Failure in a Canadian Firm. MBA
Research Project Simon Fraser University: unpublished
Summers, S. L. & Sweeney, J. T. 1998. Fraudulently misstated financial statements and
insider trading: An empirical analysis. The Accounting Review. 73(1): 131-146
Transparency International, 2019. Transparency International Indonesia. Retrieved from
https://www.transparency.org/country/IDN
Zainal, A., Rahmadana, M. F. and Zain, K. 2013. Power and likelihood of financial
statement fraud: Evidence from Indonesia. Journal of Advanced Management
Science. 1(4): 412-415