Evaluasi Efektivitas Pengukuran Laporan Keuangan: A Systematic Literature Review
Abstract
This article explores financial report fraud, factors that cause fraud and formulas for detecting fraud. The method used in this research is Systematic Literature Review (SLR), which involves the analysis of articles published from 2000 to 2023. Based on the data, 26 initial articles were obtained from Scopus in the analysis period, and only 13 articles were analyzed effectively. The findings show that the M-Score and F-Score models are widely used in identifying financial statement fraud. It is known that using the M-Sore, F-Score and Benford's law formulas has its own advantages and disadvantages depending on the sample and country studied. This paper provides insight for academics, practitioners, and policy makers to help detect and prevent fraud as well as develop it to make it easier for investors and auditors to detect fraud that occurs in financial reports.
Keywords: Fraud, Fraud Detection, Systematic Literature Review, Financial Statement Fraud
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References
Aboud, A., & Robinson, B. (2020). Fraudulent financial reporting and data analytics: an explanatory study from Ireland. Accounting Research Journal, 35(1), 21-36. https://doi.org/10.1108/arj-04-2020-0079
Ali, A., Abd Razak, S., Othman, S. H., Eisa, T. A. E., Al-Dhaqm, A., Nasser, M., . . . Saif, A. (2022). Financial Fraud Detection Based on Machine Learning: A Systematic Literature Review. Applied Sciences, 12(19), 9637. https://doi.org/10.3390/app12199637
Aquilani, B., Silvestri, C., Ruggieri, A., & Gatti, C. (2017). A systematic literature review on total quality management critical success factors and the identification of new avenues of research. The TQM Journal, 29(1), 184-213. https://doi.org/10.1108/tqm-01-2016-0003
Ashtiani, M. N., & Raahemi, B. (2022). Intelligent Fraud Detection in Financial Statements Using Machine Learning and Data Mining: A Systematic Literature Review. IEEE Access, 10, 72504–72525.
Aviantara, R. (2021). Scoring the financial distress and the financial statement fraud of Garuda Indonesia with «DDCC» as the financial solutions. Journal of Modelling in Management, 18(1), 1-16. https://doi.org/10.1108/jm2-01-2020-0017
Beneish, M. D., Lee, C. M. C., & Nichols, D. C. (2013). Earnings Manipulation and Expected Returns. Financial Analysts Journal, 69(2). https://doi.org/https://doi.org/10.2469/faj.v69.n2.1
Bliss, M. A., & Gul, F. A. (2012). Political connection and cost of debt: Some Malaysian evidence. Journal of Banking & Finance, 36(5), 1520-1527. https://doi.org/10.1016/j.jbankfin.2011.12.011
Bologna, G. J., Lindquist, R. J., & Wells, J. T. (1993). The Accountant's Handbook of Fraud and Commercial Crime. John Wiley and Sons, Inc.
Boubakri, N., Guedhami, O., Mishra, D., & Saffar, W. (2012). Political connections and the cost of equity capital. Journal of Corporate Finance, 18(3), 541-559. https://doi.org/10.1016/j.jcorpfin.2012.02.005
Çalıyurt, K. T. (2021). Introduction Chapter: Why It Is Time to Talk About Fraud Quadrangle: Negative Pressure, Unethical Rationalization, Unsufficient Control-Auditing, and Moral Erosion. 1-16. https://doi.org/10.1007/978-981-15-1928-4_1
Chen, S., Goo, Y.-J. J., & Shen, Z.-D. (2014). A hybrid approach of stepwise regression, logistic regression, support vector machine, and decision tree for forecasting fraudulent financial statements. ScientificWorldJournal, 2014, 968712. https://doi.org/10.1155/2014/968712
Chena, Y.-J., Lioua, W.-C., Chenb, Y.-M., & Wu, J.-H. (2019). Fraud detection for financial statements of business groups. International Journal of Accounting Information Systems, 32, 1-23. https://doi.org/10.1016/j.accinf.2018.11.004
Christian, N., Resnika, Yukie, H., Sitorus, R., Angelina, V., Sherly, & Febrika. (2022). Pendeteksian Fraudulent Financial Reporting Dengan Earnings Manipulation Financial Shenanigans: Studi Kasus Pt Envy Technologies Indonesia Tbk. Jurnal Ilmiah Akuntansi dan Bisnis, 7(1).
Claessens, S., Feijen, E., & Laeven, L. (2008). Political connections and preferential access to finance: The role of campaign contributions. Journal of Financial Economics, 88(3), 554-580. https://doi.org/10.1016/j.jfineco.2006.11.003
Cressey, D. R. (1950). The Criminal Violation of Financial Trust. American Sociological Review, 15(6), 738-743.
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
Demetriades, P., & Owusu-Agyei, S. (2022). Fraudulent Financial Reporting: An Application Of Fraud Diamond To Toshiba’s Accounting Scandal. Journal of Financial Crime, 29(2), 729-763. https://doi.org/10.1108/JFC-05-2021-0108
Desai, N. (2020). Understanding the Theoretical Underpinnings of Corporate Fraud. Vikalpa: The Journal for Decision Makers, 45(1), 25-31. https://doi.org/10.1177/0256090920917789
Fitri, F., Syukur, M., & Justisa, G. (2019). Do The Fraud Triangle Components Motivate Fraud In Indonesia? Australasian Accounting, Business and Finance Journal, 13(4), 63-72. https://doi.org/10.14453/aabfj.v13i4.5
Golbeck, J. (2023). Benford's Law applies to word frequency rank in English, German, French, Spanish, and Italian. PLoS One, 18(9), e0291337. https://doi.org/10.1371/journal.pone.0291337
Goldman, E., Rocholl, J., & So, J. (2013). Politically Connected Boards of Directors and The Allocation of Procurement Contracts. Review of Finance, 17(5), 1617-1648. https://doi.org/10.1093/rof/rfs039
Harb, E. G., Nasrallah, N., El Khoury, R., & Hussainey, K. (2023). Applying Benford's law to detect accounting data manipulation in the pre- and post-financial engineering periods. Journal of Applied Accounting Research, 24(4), 745-768. https://doi.org/10.1108/jaar-05-2022-0097
Hassan, T., Kabir Hassan, M., Mohamad, S., & Chaw Min, C. (2012). Political patronage and firm performance: Further evidence from Malaysia. Thunderbird International Business Review, 54(3), 373-393. https://doi.org/10.1002/tie.21468
Isong, B. E. (2013). A Systematic Review of Fault Tolerance in Mobile Agents. American Journal of Software Engineering and Applications, 2(5), 111. https://doi.org/10.11648/j.ajsea.20130205.11
Kamal, M. E. M. (2016). Detecting Financial Statement Fraud by Malaysian Public Listed Companies: The Reliability of the Beneish M-Score Model. Jurnal Pengurusan, 46, 23-32.
Karen, K., Yenanda, K., & Evelyn, V. (2022). Analisa Pelanggaran Kode Etik Akuntan Publik Pada Pt Garuda Indonesia Tbk. SIBATIK JOURNAL: Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, dan Pendidikan, 2(1), 189-198. https://doi.org/10.54443/sibatik.v2i1.519
Kassem, R., & Higson, A. (2012). The New Fraud Triangle Model. Journal of Emerging Trends in Economics and Management Sciences, 3(3), 191-195.
Kaur, B., Sood, K., & Grima, S. (2022). A systematic review on forensic accounting and its contribution towards fraud detection and prevention. Journal of Financial Regulation and Compliance, 31(1), 60-95. https://doi.org/10.1108/jfrc-02-2022-0015
Kuckertz, A., & Block, J. (2021). Reviewing systematic literature reviews: ten key questions and criteria for reviewers. Management Review Quarterly, 71(3), 519-524. https://doi.org/10.1007/s11301-021-00228-7
Mansour, A. a. Z., Ahmi, A., & Popoola, O. M. J. (2020). The Personality Factor of Conscientiousness on Skills Requirement and Fraud Risk Assessment Performance. International Journal of Financial Research, 11(2), 405. https://doi.org/10.5430/ijfr.v11n2p405
Marais, A., Vermaak, C., & Shewell, P. (2023). Predicting financial statement manipulation in South Africa: A comparison of the Beneish and Dechow models. Cogent Economics & Finance, 11(1). https://doi.org/10.1080/23322039.2023.2190215
Maulidi, A. (2020). Storytelling of bureaucratic white-collar crimes in Indonesia: is it a matter of reciprocal norm? Journal of Financial Crime, 27(2), 573-586. https://doi.org/10.1108/jfc-07-2019-0087
Nawawi, A., & Salin, A. S. A. P. (2018). Employee fraud and misconduct: empirical evidence from a telecommunication company. Information & Computer Security, 26(1), 129-144. https://doi.org/10.1108/ics-07-2017-0046
Pattanasak, P., Anantana, T., Paphawasit, B., & Wudhikarn, R. (2022). Critical Factors and Performance Measurement of Business Incubators: A Systematic Literature Review. Sustainability, 14(8), 4610. https://doi.org/10.3390/su14084610
Pavlović, V., Knežević, G., Joksimović, M., & Joksimović, D. (2019). Fraud Detection in Financial Statements Applying Benford's Law with Monte Carlo Simulation. Acta Oeconomica, 69(2), 217-239. https://doi.org/10.1556/032.2019.69.2.4
Pupokusumo, A. W., Handoko, B. L., Willy, Ricky, & Hendra, E. (2022). Benford’s Law As A Tool In Detecting Financial Statement Fraud. Journal of Theoretical and Applied Information Technology, 100(14).
Putri, N. S., & Januarti, I. (2023). Perspektif Fraud Diamond dalam Mendeteksi Kemungkinan Kecurangan Laporan Keuangan. E-Jurnal Akuntansi, 33(3). https://doi.org/10.24843/EJA.2023.v33.i03.p03
Qin, R., & Wang, W. (2021). Identification of Accounting Fraud Based on Support Vector Machine and Logistic Regression Model. Complexity, 2021, 1-11. https://doi.org/10.1155/2021/5597060
Rad, M., Amiri, A., Ranjbar, M. H., Salari, H., & McMillan, D. (2021). Predictability of financial statements fraud-risk using Benford’s Law. Cogent Economics & Finance, 9(1). https://doi.org/10.1080/23322039.2021.1889756
Ravisankar, P., Ravi, V., Raghava Rao, G., & Bose, I. (2011). Detection of financial statement fraud and feature selection using data mining techniques. Decision Support Systems, 50(2), 491-500. https://doi.org/10.1016/j.dss.2010.11.006
Repousis, S., Lois, P., & Veli, V. (2019). An investigation of the fraud risk and fraud scheme methods in Greek commercial banks. Journal of Money Laundering Control, 22(1), 53-61. https://doi.org/10.1108/jmlc-11-2017-0065
Sabău, A.-I., Mare, C., & Safta, I. L. (2021). A Statistical Model of Fraud Risk in Financial Statements. Case for Romania Companies. Risks, 9(6), 116. https://doi.org/10.3390/risks9060116
Salehi, M., & Norouzi, F. (2023). The effect of corporate lobbying on fraud and money laundering. Journal of Money Laundering Control, 26(3), 553-583. https://doi.org/10.1108/jmlc-01-2022-0017
Tahir, T., Rasool, G., & Gencel, C. (2016). A systematic literature review on software measurement programs. Information and Software Technology, 73, 101-121. https://doi.org/10.1016/j.infsof.2016.01.014
Uwuigbe, O. R., Olorunshe, O., Uwuigbe, U., Ozordi, E., Asiriuwa, O., Asaolu, T., & Erin, O. (2019). Corporate Governance and Financial Statement Fraud among Listed Firms in Nigeria. IOP Conference Series: Earth and Environmental Science, 331(1), 012055. https://doi.org/10.1088/1755-1315/331/1/012055
Vousinas, G. L. (2019). Advancing theory of fraud: the S.C.O.R.E. model. Journal of Financial Crime, 26(1), 372-381. https://doi.org/10.1108/jfc-12-2017-0128
Warshavsky, M. (2012). Analyzing Earnings Quality as a Financial Forensic Tool. Financial Valuation and Litigation Expert Journal, 39, 16-20.
Wilantari, N. M., & Ariyanto, D. (2023). Determinan Fraud Hexagon Theory dan Indikasi Financial Statement Fraud. E-Jurnal Akuntansi, 33(1). https://doi.org/10.24843/EJA.2023.v33.i01.p07
Wolfe, D. T., & Hermanson, D. R. (2004). The Fraud Diamond: Considering the Four Elements of Fraud. The CPA Journal, 74(12), 38.
Yuwono, Y. P., & Marlina, M. A. E. (2021). Peran Fraud Triangle dalam Mendeteksi Financial Statement Fraud di Perusahaan Perbankan ASEAN. E-Jurnal Akuntansi, 31(3). https://doi.org/10.24843/EJA.2021.v31.i03.p15
Zager, L., Malis, S. S., & Novak, A. (2016). The Role and Responsibility of Auditors in Prevention and Detection of Fraudulent Financial Reporting. Procedia Economics and Finance, 39, 693-700. https://doi.org/10.1016/s2212-5671(16)30291-x
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
Ali, A., Abd Razak, S., Othman, S. H., Eisa, T. A. E., Al-Dhaqm, A., Nasser, M., . . . Saif, A. (2022). Financial Fraud Detection Based on Machine Learning: A Systematic Literature Review. Applied Sciences, 12(19), 9637. https://doi.org/10.3390/app12199637
Aquilani, B., Silvestri, C., Ruggieri, A., & Gatti, C. (2017). A systematic literature review on total quality management critical success factors and the identification of new avenues of research. The TQM Journal, 29(1), 184-213. https://doi.org/10.1108/tqm-01-2016-0003
Ashtiani, M. N., & Raahemi, B. (2022). Intelligent Fraud Detection in Financial Statements Using Machine Learning and Data Mining: A Systematic Literature Review. IEEE Access, 10, 72504–72525.
Aviantara, R. (2021). Scoring the financial distress and the financial statement fraud of Garuda Indonesia with «DDCC» as the financial solutions. Journal of Modelling in Management, 18(1), 1-16. https://doi.org/10.1108/jm2-01-2020-0017
Beneish, M. D., Lee, C. M. C., & Nichols, D. C. (2013). Earnings Manipulation and Expected Returns. Financial Analysts Journal, 69(2). https://doi.org/https://doi.org/10.2469/faj.v69.n2.1
Bliss, M. A., & Gul, F. A. (2012). Political connection and cost of debt: Some Malaysian evidence. Journal of Banking & Finance, 36(5), 1520-1527. https://doi.org/10.1016/j.jbankfin.2011.12.011
Bologna, G. J., Lindquist, R. J., & Wells, J. T. (1993). The Accountant's Handbook of Fraud and Commercial Crime. John Wiley and Sons, Inc.
Boubakri, N., Guedhami, O., Mishra, D., & Saffar, W. (2012). Political connections and the cost of equity capital. Journal of Corporate Finance, 18(3), 541-559. https://doi.org/10.1016/j.jcorpfin.2012.02.005
Çalıyurt, K. T. (2021). Introduction Chapter: Why It Is Time to Talk About Fraud Quadrangle: Negative Pressure, Unethical Rationalization, Unsufficient Control-Auditing, and Moral Erosion. 1-16. https://doi.org/10.1007/978-981-15-1928-4_1
Chen, S., Goo, Y.-J. J., & Shen, Z.-D. (2014). A hybrid approach of stepwise regression, logistic regression, support vector machine, and decision tree for forecasting fraudulent financial statements. ScientificWorldJournal, 2014, 968712. https://doi.org/10.1155/2014/968712
Chena, Y.-J., Lioua, W.-C., Chenb, Y.-M., & Wu, J.-H. (2019). Fraud detection for financial statements of business groups. International Journal of Accounting Information Systems, 32, 1-23. https://doi.org/10.1016/j.accinf.2018.11.004
Christian, N., Resnika, Yukie, H., Sitorus, R., Angelina, V., Sherly, & Febrika. (2022). Pendeteksian Fraudulent Financial Reporting Dengan Earnings Manipulation Financial Shenanigans: Studi Kasus Pt Envy Technologies Indonesia Tbk. Jurnal Ilmiah Akuntansi dan Bisnis, 7(1).
Claessens, S., Feijen, E., & Laeven, L. (2008). Political connections and preferential access to finance: The role of campaign contributions. Journal of Financial Economics, 88(3), 554-580. https://doi.org/10.1016/j.jfineco.2006.11.003
Cressey, D. R. (1950). The Criminal Violation of Financial Trust. American Sociological Review, 15(6), 738-743.
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
Demetriades, P., & Owusu-Agyei, S. (2022). Fraudulent Financial Reporting: An Application Of Fraud Diamond To Toshiba’s Accounting Scandal. Journal of Financial Crime, 29(2), 729-763. https://doi.org/10.1108/JFC-05-2021-0108
Desai, N. (2020). Understanding the Theoretical Underpinnings of Corporate Fraud. Vikalpa: The Journal for Decision Makers, 45(1), 25-31. https://doi.org/10.1177/0256090920917789
Fitri, F., Syukur, M., & Justisa, G. (2019). Do The Fraud Triangle Components Motivate Fraud In Indonesia? Australasian Accounting, Business and Finance Journal, 13(4), 63-72. https://doi.org/10.14453/aabfj.v13i4.5
Golbeck, J. (2023). Benford's Law applies to word frequency rank in English, German, French, Spanish, and Italian. PLoS One, 18(9), e0291337. https://doi.org/10.1371/journal.pone.0291337
Goldman, E., Rocholl, J., & So, J. (2013). Politically Connected Boards of Directors and The Allocation of Procurement Contracts. Review of Finance, 17(5), 1617-1648. https://doi.org/10.1093/rof/rfs039
Harb, E. G., Nasrallah, N., El Khoury, R., & Hussainey, K. (2023). Applying Benford's law to detect accounting data manipulation in the pre- and post-financial engineering periods. Journal of Applied Accounting Research, 24(4), 745-768. https://doi.org/10.1108/jaar-05-2022-0097
Hassan, T., Kabir Hassan, M., Mohamad, S., & Chaw Min, C. (2012). Political patronage and firm performance: Further evidence from Malaysia. Thunderbird International Business Review, 54(3), 373-393. https://doi.org/10.1002/tie.21468
Isong, B. E. (2013). A Systematic Review of Fault Tolerance in Mobile Agents. American Journal of Software Engineering and Applications, 2(5), 111. https://doi.org/10.11648/j.ajsea.20130205.11
Kamal, M. E. M. (2016). Detecting Financial Statement Fraud by Malaysian Public Listed Companies: The Reliability of the Beneish M-Score Model. Jurnal Pengurusan, 46, 23-32.
Karen, K., Yenanda, K., & Evelyn, V. (2022). Analisa Pelanggaran Kode Etik Akuntan Publik Pada Pt Garuda Indonesia Tbk. SIBATIK JOURNAL: Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, dan Pendidikan, 2(1), 189-198. https://doi.org/10.54443/sibatik.v2i1.519
Kassem, R., & Higson, A. (2012). The New Fraud Triangle Model. Journal of Emerging Trends in Economics and Management Sciences, 3(3), 191-195.
Kaur, B., Sood, K., & Grima, S. (2022). A systematic review on forensic accounting and its contribution towards fraud detection and prevention. Journal of Financial Regulation and Compliance, 31(1), 60-95. https://doi.org/10.1108/jfrc-02-2022-0015
Kuckertz, A., & Block, J. (2021). Reviewing systematic literature reviews: ten key questions and criteria for reviewers. Management Review Quarterly, 71(3), 519-524. https://doi.org/10.1007/s11301-021-00228-7
Mansour, A. a. Z., Ahmi, A., & Popoola, O. M. J. (2020). The Personality Factor of Conscientiousness on Skills Requirement and Fraud Risk Assessment Performance. International Journal of Financial Research, 11(2), 405. https://doi.org/10.5430/ijfr.v11n2p405
Marais, A., Vermaak, C., & Shewell, P. (2023). Predicting financial statement manipulation in South Africa: A comparison of the Beneish and Dechow models. Cogent Economics & Finance, 11(1). https://doi.org/10.1080/23322039.2023.2190215
Maulidi, A. (2020). Storytelling of bureaucratic white-collar crimes in Indonesia: is it a matter of reciprocal norm? Journal of Financial Crime, 27(2), 573-586. https://doi.org/10.1108/jfc-07-2019-0087
Nawawi, A., & Salin, A. S. A. P. (2018). Employee fraud and misconduct: empirical evidence from a telecommunication company. Information & Computer Security, 26(1), 129-144. https://doi.org/10.1108/ics-07-2017-0046
Pattanasak, P., Anantana, T., Paphawasit, B., & Wudhikarn, R. (2022). Critical Factors and Performance Measurement of Business Incubators: A Systematic Literature Review. Sustainability, 14(8), 4610. https://doi.org/10.3390/su14084610
Pavlović, V., Knežević, G., Joksimović, M., & Joksimović, D. (2019). Fraud Detection in Financial Statements Applying Benford's Law with Monte Carlo Simulation. Acta Oeconomica, 69(2), 217-239. https://doi.org/10.1556/032.2019.69.2.4
Pupokusumo, A. W., Handoko, B. L., Willy, Ricky, & Hendra, E. (2022). Benford’s Law As A Tool In Detecting Financial Statement Fraud. Journal of Theoretical and Applied Information Technology, 100(14).
Putri, N. S., & Januarti, I. (2023). Perspektif Fraud Diamond dalam Mendeteksi Kemungkinan Kecurangan Laporan Keuangan. E-Jurnal Akuntansi, 33(3). https://doi.org/10.24843/EJA.2023.v33.i03.p03
Qin, R., & Wang, W. (2021). Identification of Accounting Fraud Based on Support Vector Machine and Logistic Regression Model. Complexity, 2021, 1-11. https://doi.org/10.1155/2021/5597060
Rad, M., Amiri, A., Ranjbar, M. H., Salari, H., & McMillan, D. (2021). Predictability of financial statements fraud-risk using Benford’s Law. Cogent Economics & Finance, 9(1). https://doi.org/10.1080/23322039.2021.1889756
Ravisankar, P., Ravi, V., Raghava Rao, G., & Bose, I. (2011). Detection of financial statement fraud and feature selection using data mining techniques. Decision Support Systems, 50(2), 491-500. https://doi.org/10.1016/j.dss.2010.11.006
Repousis, S., Lois, P., & Veli, V. (2019). An investigation of the fraud risk and fraud scheme methods in Greek commercial banks. Journal of Money Laundering Control, 22(1), 53-61. https://doi.org/10.1108/jmlc-11-2017-0065
Sabău, A.-I., Mare, C., & Safta, I. L. (2021). A Statistical Model of Fraud Risk in Financial Statements. Case for Romania Companies. Risks, 9(6), 116. https://doi.org/10.3390/risks9060116
Salehi, M., & Norouzi, F. (2023). The effect of corporate lobbying on fraud and money laundering. Journal of Money Laundering Control, 26(3), 553-583. https://doi.org/10.1108/jmlc-01-2022-0017
Tahir, T., Rasool, G., & Gencel, C. (2016). A systematic literature review on software measurement programs. Information and Software Technology, 73, 101-121. https://doi.org/10.1016/j.infsof.2016.01.014
Uwuigbe, O. R., Olorunshe, O., Uwuigbe, U., Ozordi, E., Asiriuwa, O., Asaolu, T., & Erin, O. (2019). Corporate Governance and Financial Statement Fraud among Listed Firms in Nigeria. IOP Conference Series: Earth and Environmental Science, 331(1), 012055. https://doi.org/10.1088/1755-1315/331/1/012055
Vousinas, G. L. (2019). Advancing theory of fraud: the S.C.O.R.E. model. Journal of Financial Crime, 26(1), 372-381. https://doi.org/10.1108/jfc-12-2017-0128
Warshavsky, M. (2012). Analyzing Earnings Quality as a Financial Forensic Tool. Financial Valuation and Litigation Expert Journal, 39, 16-20.
Wilantari, N. M., & Ariyanto, D. (2023). Determinan Fraud Hexagon Theory dan Indikasi Financial Statement Fraud. E-Jurnal Akuntansi, 33(1). https://doi.org/10.24843/EJA.2023.v33.i01.p07
Wolfe, D. T., & Hermanson, D. R. (2004). The Fraud Diamond: Considering the Four Elements of Fraud. The CPA Journal, 74(12), 38.
Yuwono, Y. P., & Marlina, M. A. E. (2021). Peran Fraud Triangle dalam Mendeteksi Financial Statement Fraud di Perusahaan Perbankan ASEAN. E-Jurnal Akuntansi, 31(3). https://doi.org/10.24843/EJA.2021.v31.i03.p15
Zager, L., Malis, S. S., & Novak, A. (2016). The Role and Responsibility of Auditors in Prevention and Detection of Fraudulent Financial Reporting. Procedia Economics and Finance, 39, 693-700. https://doi.org/10.1016/s2212-5671(16)30291-x
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
Published
2023-11-30
How to Cite
HENI, Heni; PAYAMTA, Payamta.
Evaluasi Efektivitas Pengukuran Laporan Keuangan: A Systematic Literature Review.
E-Jurnal Akuntansi, [S.l.], v. 33, n. 11, p. 2872-2886, nov. 2023.
ISSN 2302-8556.
Available at: <https://ojs.unud.ac.id/index.php/akuntansi/article/view/107817>. Date accessed: 14 nov. 2024.
doi: https://doi.org/10.24843/EJA.2023.v33.i11.p04.
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