ANALYSIS OF FRAUD TRIANGLE FACTORS AND FINANCIAL DISTRESS THAT INFLUENCE FINANCIAL STATEMENT FRAUD IN REAL ESTATE COMPANIES LISTED ON THE IDX
DOI:
10.54443/ijebas.v5i3.3266Published:
2025-06-30Downloads
Abstract
This study aims to determine the influence of fraud triangle factors including financial stability, external pressure, opportunity and rationalization and financial distress on financial statement fraud in Real Estate companies listed on the IDX in 2018 - 2022. The study was conducted based on the 2022 ACFE report that financial statement fraud has the highest average loss of any type of fraud and it is known that the Real Estate industry is the industry that experiences the most average losses from fraud. The sampling technique used was purposive sampling with a sample of 33 companies during 5 years of observation so that the total number of observation samples was 165. The analysis technique used was regression analysis on quantitative data with panel data on Eviews software version 13. The results of the study indicate that opportunity and financial distress have a positive effect on financial statement fraud and rationalization has a negative effect on financial statement fraud. While financial stability and external pressure do not affect financial statement fraud.
Keywords:
fraud triangle, financial situation, financial statement fraudReferences
Afrizalita, Desi, Cheisviyanny, Charoline. (2023). The Influence of Supervisor Relationship and Machiavellian Traits on Dysfunctional Audit Behavior. Journal of Accounting Exploration (JEA), 5(3), 1181-1191. Retrieved from
http://jea.ppj.unp.ac.id/index.php/jea/article/view/587
Alfarago, D., Syukur, M. & Mabrur, A. (2023). The Likelihood of Fraud from The
Fraud Hexagon Perspective: Evidence from Indonesia. ABAC Journal, 43(1), 34-51. Retrieved from
http://www.assumptionjournal.au.edu/index.php/abacjournal/article/view/7183
Altman, Edward I. (1968). Financial Ratios, Discriminant Analysis and The Prediction of Corporate Bankruptcy. The Journal of Finance, 23(4). Retrieved from
Altman, EI, Danovi, Alessandro, Falini, Alberto. (2010). Z Score Models' Application to Italian Companies Subject to Extraordinary Administration. The Journal of Applied Finance, 23(1). Retrieved from
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2686750
Andrew, Candy & Robin. (2022). Detecting Fraudulent Financial Statements Using Fraud SCORE Model and Financial Distress. International Journal of Economics, Business and Accounting Research (IJEBAR), 6(1), 211-222. Retrieved from
https://www.jurnal.stie-aas.ac.id/index.php/IJEBAR/article/view/4394
Association of Certified Fraud Examiners. 2022. Occupational Fraud 2022: A Report to The Nations. Association of Certified Fraud Examiners.
Aviantara, Ryan. (2023). Scoring the Financial Distress and The Financial Statement Fraud of Garuda Indonesia with “DDCC” as The Financial Solutions. Journal of Modeling in Management, 18(1), 1-16. Retrieved from
Beasley, Mark S. (1996). An Empirical Analysis of the Relation Between the Board of Directors Composition and Financial Statement Fraud. The Accounting Review, 71(4), 443-465. Retrieved from
Beaver, W. H. (1966). Financial Ratios as Predictors of Failure. Journal of Accounting Research. Retrieved from
Beneish, M.D. (1999). The Detection of Earnings Manipulation. Financial Analysts Journal, 55(5), 24-36. Retrieved from
Cressey, D. R. (1953). Other People's Money: A Study in the Social Psychology of Embezzlement. Glencoe, Ill.: Free Press.
Damayanti, RE & Suryani, E. (2019). The Influence of Financial Stability, External Pressure, Ineffective Monitoring and Audit Opinion on Indications of Financial Report Fraud (Study on Manufacturing Companies in the Basic and Chemical Industry Sectors Listed on the Indonesia Stock Exchange in 2013-2017. E-Proceeding of Management, 6 (2), 3141-3147. Retrieved from
https://openlibrarypublications.telkomuniversity.ac.id/index.php/management/article/view/10133
Farias, FZ, Martinez, Maria del CV, Cervantes, Pedro AM (2021). Explanatory Factors of Business Failure: Literature Review and Global Trends. Sustainability, 13, 1-25. Retrieved fromhttps://www.mdpi.com/2071-1050/13/18/10154
Fatkhurrizqi, MA & Nahar, A. (2021). Fraud Triangle Analysis in Determining the Occurrence of Financial Statement Fraud. Financial: Journal of Accounting, 7(1), 14-25. Retrieved from
https://financial.ac.id/index.php/financial/article/view/221
Fitri, FA, Syukur, M. & Justisa, G. (2019). Do The Fraud Triangle Components Motivate Fraud in Indonesia? Australasian Accounting, Business and Finance Journal, 13(4), 63-72. Retrieved from
Gusni, Gusni, Wiludjeng, Sri, Wiludjeng, Sri, Silviana. (2019). Predicting Financial Distress: A Case Study of Indonesian Coal Firm. Global Business and Management Research: An International Journal, 11(1), 186. Retrieved from
https://www.proquest.com/openview/0478cc4c62048e789174e9dc8e2e31a1/1?cbl=696409&pq-origsite=gscholar
Girau, E., A., Bujang, Imbarine & Jidwin, AP (2022). Corporate Governance Challenges and Opportunities in Mitigating Corporate Fraud in Malaysia. Journal of Financial Crime, 29(2), 620-638. Retrieved from
Ghozali, Imam & Ratmono, Dwi (2017). Multivariate Analysis and Econometrics. Theory, Concept and Application with Eviews 10. Edition 2. Diponegoro University Publishing Agency.
Hakami, TA, Rahmat, MM, Yacoob, MH & Saleh, NM (2020). Fraud Detection Gap between Auditor and Fraud Detection Models: Evidence from Gulf Cooperation Council. Asian Journal of Accounting and Governance, 13(1), 1-13. Retrieved from
Halteh, Khaled. (2023). Preempting Fraud: A Financial Distress Prediction Perspective on Combating Financial Crime. Journal of Money Laundering Control, 26(6), 1194-1202. Retrieved from
https://www.emerald.com/insight/content/doi/10.1108/jmlc-01-2023- 0013/full/html?casa_token=vu1HZrFtu50AAAAA%3AlHDrEp43S96FnLPksZ_uHublyM9DVEb63y6w3CaTamJaAEgjTJJcwEalHtB_Uj7ORUp5rLMKqxePaKu4UUyRA0dFu6RvEB1CbinVoOyM3lNMKGHmpdS39Q
Ikbal, Muhammad. (2020). Explores The Specific Context of Financial Statement Fraud Based on Empirical from Indonesia. Universal Journal of Accounting and Finance, 8(2), 29-40. Retrieved from
Irwandi, SA, Faisal, IG & Pamungkas, ID (2019). Fraudulent Financial Statement Detection: Beneish M-Score Model. WSEAS Transactions on Business and Economics, 16, 271-281. Retrieved from
Izzalqurny, TR, Subroto, Bambang & Ghofar, Abdul. (2019). Relationship Between Financial Ratio and Financial Statement Fraud Risk Moderated by Auditor Quality. International Journal Research in Business and Social Science, 8(4), 2147-4478. Retrieved from
https://www.ssbfnet.com/ojs/index.php/ijrbs/article/view/281
Khaksar, J., Salehi, M. & Dashtbayaz, M.L. (2021). The Relationship Between Auditor Characteristics and Fraud Detection. Journal of Facilities Management, 20(1), 79-101. Retrieved from
Kukreja, G., Guota, S. M., Sarea, A. M. & 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. Retrieved from
Lagasio, Valentina, Brogi, Marina, Galluci, Carmen, Santulli, Rosalia. (2023). May Board Committees Reduce the Probability of Financial Distress? A survival Analysis on Italian Listed Companies. International Review of Financial Analysis, 87. Retrieved from
https://www.sciencedirect.com/science/article/abs/pii/S1057521923000777
Lastanti, SH, Murwaningsari, Etty & Umar, Haryono. (2022). The Effect of Hexagon Fraud on Fraud Financial Statement with Governance and Culture as Moderating Variables. Accounting, Auditing & Information Research Media, 22(1), 143-156. Retrieved from
https://www.e-journal.trisakti.ac.id/index.php/mraai/article/view/13533
Li, Yuanhui, Li, Xiao, Xiang, Erwei & Djajadikerta, H.G. (2020). Financial Distress, Internal Control, and Earnings Management: Evidence from China. Journal of Contemporary Accounting & Economics, 16, 1-18. Retrieved from
Liu, Y., Wu, B. & Zhang, M. (2023). Can Independent Directors Identify The Company's Risk of Financial Statement Fraud: Evidence from Predicting Financial Fraud Based on Machine Learning. China Journal of Accounting Studies, 11(3), 465-492. Retrieved from
https://www.tandfonline.com/doi/full/10.1080/21697213.2023.2239670
Lokanan, Mark. (2021). Applying Four Quantitative Prediction Techniques to Detect Fraud in Financial Statements. Journal of Forensic and Investigative Accounting, 13, 362-383. Retrieved from
Maninggarjati, ER, Wulaningrum, Ratna, Fitri, Syukur, Justisaana, Rahmawati & Putra, DT (2022). Financial Distress Analysis of Coal Mining Companies. Advances in Social Science, Education and Humanities Research, 647, 482-486. Retrieved from
https://www.atlantis-press.com/proceedings/icast-ss-21/125971028
Miller, K. D. & Reuer, Jeffrey (1996). Measuring Organizational Downside Risk. Strategic Management Journal, 17(2). Retrieved from
Nugroho, DS & Diyanti, Vera. (2022). Hexagon Fraud in Fraudulent Financial Statements: The Moderating Role of Audit Committee. Indonesian Journal of Accounting and Finance, 19(1), 46-67. Retrieved from
https://scholarhub.ui.ac.id/jaki/vol19/iss1/3/
Nuristya, ER & Ratmono, Dwi. (2022). The Role of Audit Report Lag in Mediating The Effect of Auditor Switching and Financial Distress on Financial Statement Fraud. Sriwijaya International Journal of Dynamic Economics and Business, 6(2), 165-184. Retrieved from
https://sijdeb.unsri.ac.id/index.php/SIJDEB/article/view/323
Nejad, MY, Khan, AS & Othman, J. (2024). A Panel Data Analysis of the Effect of Audit Quality on Financial Statement Fraud. Asian Journal of Accounting Research, 9(4), 422-445. Retrieved from
https://www.emerald.com/insight/content/doi/10.1108/ajar-04-2023-0112/full/html
Ozcelik, Hakan. (2020). An Analysis of Fraudulent Financial Reporting Using The Fraud Diamond Theory Perspective: An Empirical Study on The Manufacturing Sector Companies Listed on The Borsa Istanbul. Economics and Financial Analysis, 102, 131-153. Retrieved from
https://www.emerald.com/insight/content/doi/10.1108/s1569375920200000102012/full/html
Pranadipta, Ruth & Natsir, Khairina. (2023). Financial, Non-Financial, and Macro-Economic Factors That Affect The First Day Profit Rate When Conducting an Initial Public Offering. International Journal of Application on Economics and Business (IJAEB), 1, 276-289. Retrieved from
https://scholar.google.com/scholar?hl=id&as_sdt=0%2C5&q=FINANCIAL%2C+NON-FINANCIAL%2C+AND+MACRO- ECONOMIC+FACTORS+THAT+AFFECT+THE+FIRST+DAY+PROFIT+RATE+WHEN+CONDUCTING+INITIAL+PUBLIC+OFFERING&btnG=
Qiu, S., He, H. C. & Luo, Y. S. (2019). The Value of Restatement to Fraud Prediction. Journal of Business Economics and Management, 20(6), 1210-1237. Retrieved from
https://ijspm.vgtu.lt/index.php/JBEM/article/view/10489
Qawqzeh, HK, Endut, WA, Rashid, N., & Dakhlah, MM (2020). Impact of The External Auditor's Effectiveness on The Financial Reporting Quality: The Mediating Effect of Audit Quality. Journal of Critical Reviews, 7(6), 1197-1208. Retrieved from
Rahman, M. J. & Jie, X. (2022). Fraud Detection Using Fraud Triangle Theory: Evidence from China. Journal of Financial Crime, 31(1), 101-118. Retrieved from
https://www.emerald.com/insight/content/doi/10.1108/jfc-09-2022- 0219/full/html?casa_token=F8QVJyeAKjEAAAAA%3AWEbMfqp0- l6S6emON1HnuwoQbMviVRgYpm0EJUFR8_bIFaUYFDDmsLrYDfREP8zfc32- IyUlYoDwXlyi0fbiB3Q8Gl1wtkdVWDDTosKLQCa1NufRVaJfg
Ratmono, Dwi, Darsono, Darsono & Cahyonowati, Nur. (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. Retrieved from
Sadique, RBM, Ismail, AM, Roudaki, J., Alias, N. & Clark, MB (2019). Corporate Governance Attributes in Fraud Deterrence. International Journal of Financial Research (IJFR), 10(3), 51-62. Retrieved from
https://researcharchive.lincoln.ac.nz/entities/publication/b2fc590f-38ac-4ed7-a166-70721446071b
Sadjiarto, Arja, Jonathan, Enrico & Santoso, PJ (2023). Financial Distress, Fraud Reasons and Fraudulent Financial Reporting Indication. Proceedings of the Ninth Padang International Conference on Economics Education, Economics, Business and Management, Accounting and Entrepreneurship (PICEEBA). Retrieved from
https://www.atlantis-press.com/proceedings/piceeba-22/125988028
Safiq Muhamad & Seles, Wike. (2019). The Effects of External Pressures, Financial Targets and Financial Distress on Financial Statement Fraud. Advances in Economics, Business and Management Research, 73, 57-61. Retrieved from
https://www.atlantis-press.com/proceedings/aicar-18/55913634
Saleh, MAS, Aladwan, Mohammad, Alsinglawi, Omar, & Almari, MOS (2021). Predicting Fraudulent Financial Statements Using Fraud Detection Models. Academy of Strategic Management, 20(3), 1-17. Retrieved from
Sandria, Ferry. (2021). A Series of Financial Report Scandals in the Indonesian Stock Market, Indofarma-Hanson. CNBC Indonesia. Accessed via:
Sari, IP, Tjandra, Timotius, Firmansyah, Amrie & Trisnawati, Estralita. (2021). Earnings Management Practices in Indonesia: Audit Committee, Independent Commissioner, Operating Cash Flow. Journal of Accounting Science, 13(2), 310-322. Retrieved from
https://ejournals.umn.ac.id/index.php/Akun/article/view/2376
Skousen, C. J., Smith, K. R. & Wright, C. J. (2009). Detecting and Predicting Financial Statement Fraud: The Effectiveness of The Fraud Triangle and SAS No. 99. Financial Economics, 13, 53-81. Retrieved from
https://www.emerald.com/insight/content/doi/10.1108/s15693732(2009)0000013005/full/html
Sood & Bhushan (2022). Factors Impacting Banking Frauds in India: a Conceptual Framework. International Journal of Business and Globalisation, 31(4). Retrieved from
https://www.inderscienceonline.com/doi/abs/10.1504/IJBG.2022.127129
Sunarsip. (2021). Property Outlook 2022 and Its Growth Prerequisites. CNBC Indonesia. Retrieved from
Suprianta, Alviani. (2019). The Role of Independent Directors in Realizing Good Corporate Governance. Jurnal Yuridis, 6(1), 67-93. Retrieved from
Syahria, R., Kusumawati, F. & Ervanto, AD (2019). Detecting Financial Statement Fraud Using Fraud Diamond (A Study on Banking Companies Listed on The Indonesia Stock Exchange Period 2012-2016). Asia Pacific Fraud Journal, 4(2), 183-190. Retrieved from
Tarighi, H., Hosseiny, ZN, Abbaszadeh, MR, Zimon, G. & Haghighat, D. (2022), How Do Financial Distress Risk and Related Party Transactions Affect Financial Reporting Quality? Empirical Evidence from Iran. Risks, 10(3), 46. Retrieved from
https://www.mdpi.com/2227-9091/10/3/46
Toit, Elda Du. (2024). The Red Flad of Financial Statement Fraud: A Case Study. Journal of Financial Crime, 31(2), 311-321. Retrieved from
https://www.emerald.com/insight/content/doi/10.1108/jfc-02-2023-0028/full/html
Umar, H., Partahi, D. & Purba, R. (2020). Fraud Diamond Analysis in Detecting Fraudulent Financial Reports. International Journal of Scientific & Technological Research, 9(3), 6638-6646.
Utami, ER & Pusparani, NO (2019). The Analysis of Fraud Pentagon Theory and Financial Distress for Detecting Fraudulent Financial Reporting in Banking Sector in Indonesia (Empirical Study of Listed Banking Companies on Indonesia Stock Exchange in 2012-2017). Advances in Economics, Business and Management Research, 102, 60-65. Retrieved from
https://www.atlantis-press.com/proceedings/icaf-19/125922011
Law no. 8 of 1995 concerning Capital Markets.
Wajdi, Farid, et al. (2024). Quantitative Research Methods. First printing. Publisher: Widina Media Utama.
Windharma, Fandry & Susilowati, Endah. (2020). Auditor Switching, Financial Distress and Financial Statement Fraud Practices with Audit Report Lag as Intervening Variable. Journal of Accounting and Strategic Finance, 3(2), 243-257. Retrieved from
https://jasf.upnjatim.ac.id/index.php/jasf/article/view/362
WR, D V. R, & Suryani, E. (2019). The Influence of Fraud Triangle Factors on Financial Statement Fraud. Journal of Assets (Accounting Research), 11(2), 301-314.
Yanara, Chanida. (2023). Factors Influencing Financial Statement Fraud: An Analysis of The Fraud Diamond Theory from Evidence of Thai Listed Companies. WSEAS Transactions on Business and Economics, 20, 1659-1672. Retrieved from
Zhou, Leiruo, Duan, Yunlong & Wei, Wei. (2023). Research on the Financial Data Fraud Detection of Chinese Listed Enterprises by Integrating Audit Opinions. KSII Transactions on Internet and Information Systems, 17(12), 3218-3241. Retrieved from
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