EFEKTIVITAS MODEL BENEISH M-SCORE DAN MODEL F-SCORE DALAM MENDETEKSI KECURANGAN LAPORAN KEUANGAN
Article Sidebar
Main Article Content
Abstract
Penelitian ini menguji efektivitas model Beneish M-Score dan model F-Score dalam mendeteksi kecurangan laporan keuangan. Seturut dengan peningkatan skandal kecurangan, pemangku kepentingan memerlukan model deteksi yang dapat diandalkan sehingga mengurangi asimetri informasi dan kerugian. Model Beneish M-Score dan model F-Score diuji secara empiris untuk mengevaluasi hubungan dan signifikansi kedua model dengan kecurangan laporan keuangan. Hipotesis dalam penelitian ini antara lain: model Beneish M-Score dan model F-Score secara parsial efektif dalam mendeteksi kecurangan laporan keuangan, dan variabel-variabel dalam model Beneish M-Score dan model F-Score secara parsial dan simultan memiliki hubungan positif dengan kecurangan laporan keuangan. Menggunakan metode partial least squares structural equation modelling, hipotesis diuji menggunakan data emiten yang terdaftar di bursa efek Amerika Serikat. Hasil pengujian menunjukkan bahwa kedua model terbukti efektif dan memiliki korelasi positif yang kuat terhadap kecurangan laporan keuangan.
This research investigates the effectiveness of Beneish M-Score and F-Score models in detecting fraudulent of financial statements. In the rise of financial statement frauds cases, stakeholders require reliable detection model to minimize information asymmetry and damages. These models were empirically tested to evaluate the correlation and significance of both models with the fraudulent of financial statements. The hypotheses of this research were: Beneish M-Score and F-Score models were partially effective in detecting the fraudulent of financial statements, and the variables of the Beneish M and the F-Score models were partially and simultaneously correlated with the fraudulent of financial statements. With the partial least squares structural equation modelling, the hypotheses were tested using data from public companies which were listed in the United States’ Stock Exchange. The outcome of this test shows that both models are partially effective and correlated positively with the fraudulent of financial statements.
Article Details
References
Alpeyev, P. dan Amano, T. (2015, 20 Juli) “Toshiba to restate at least 152 billion Yen of past profits”. Bloomberg. (Retrieved from: https://www.bloomberg.com/news/articles/2015-07-20/toshiba-to-restate-152-billion-yen-of-past-profits-after-probe).
Aris, N. A., Arif, S.M.M., Othman, R., dan Zain, M. M. (2015) “Fraudulent financial statement detection using statistical techniques: The case of small medium automotive enterprise”. Journal of Applied Business Research 31(4): 1469.
Association of Certified Fraud Examiner. (2016) Report to The Nations on Occupational Fraud and Abuse. (Retrieved from: https://www.acfe.com/rttn2016/docs/2016-report-to-the-nations.pdf)
Balachandran, S.V. (2009, Januari 7) “The Satyam scandal”. Forbes. (Retrieved from: https://www.forbes.com/2009/01/07/satyam-raju-governance-oped-cx_sb_0107balachandran.html#6f199f33044c).
Beneish, M.D. (1999) “The detection of earnings manipulation”. Financial Analysts Journal 24 – 36.
Bhavani, G. dan Amponsah, C.T. (2017) “M-Score and Z-Score for detection of accounting fraud”. Accountancy Business and the Public Interest 68 – 86. (Retrieved from: http://visar.csustan.edu/aaba/BhavaniAmponsah2017.pdf).
Bloomberg (2001, Desember 17) “The fall of Enron”. Bloomberg. (Retrieved from: https://www.bloomberg.com/news/articles/2001-12-16/the-fall-of-enron).
Cecchini, M., Aytug, H., Koehler, G.J., dan Pathak, P. (2010) “Making words work: Using financial text as a predictor of financial events”. Decision Support Systems 50: 164 – 175.
Dechow, P.M., Ge, W., Larson, C.R., dan Sloan, R.G. (2011) “Predicting material accounting misstatements”. Contemporary Accounting 28 (1): 17–82.
Detik Finance (2009, September 9) “Usai manipulasi keuangan”. Waskita Karya segera direstrukturisasi. Detik Finance. (Retrieved from: https://finance.detik.com/berita-ekonomi-bisnis/1200038/usai-manipulasi-keuangan-waskita-karya-segera-direstukturisasi).
Hery, S.E. (2016) Auditing dan Asurans. Jakarta: PT Grasindo.
Higson, A. (2003) Corporate financial reporting: theory and practice. London: Sage Publications.
Jensen, M. C. dan Meckling, W. H. (1976) “Theory of the firm: Managerial behavior, agency costs and ownership structure”. Journal of Financial Economics 3(4): 305-360. doi:10.1016/0304-405X(76)90026-X.
Rahadiana, R. (2009, Agustus 28) “Tiga direksi Waskita dinonaktifkan”. Tempo. (Retrieved from: https://bisnis.tempo.co/read/194968/tiga-direksi-waskita-dinonaktifkan).
Repousis, S. (2016) “Using Beneish model to detect corporate financial statement fraud in Greece”. Journal of Financial Crime 23 (4): 1063 – 1073.
Scott, W.R. (2015) Financial accounting theory (7th ed.). United States: Pearson Education.
Singleton, T.W. dan Singleton, A.J. (2010) Fraud auditing and forensic accounting (4th ed.). New Jersey: John Wiley & Sons.
Spence, M. (1973) “Job market signaling”. The Quarterly Journal of Economics 87 (3): 355-374.
Tarjo dan Herawati, N. (2015) “Application of Beneish M-Score Models and Data Mining to detect financial fraud”. Social and Behavioral Sciences 211: 924 – 930.
Tran, M. (2002, Agustus 9) “WorldCom accounting scandal”. Guardian. (Retrieved from: https://www.theguardian.com/business/2002/aug/09/corporatefraud.worldcom2).
Tuanakotta, T.M. (2013) Mendeteksi manipulasi laporan keuangan. Jakarta: Salemba Empat.
Wolfe, D. dan Hermanson, D. (2004) “The fraud diamond: considering the four elements of fraud”. The CPA Journal 74 (2): 38-42.