scholarly journals Literature Review: Research Reflection of Financial Statements Fraud Detection Methods in Indonesia

2021 ◽  
Vol 6 (4) ◽  
pp. 355-358
Author(s):  
Putri Intan Prastiwi ◽  
. Payamta

This study aims to identify methods in the detection of fraud in financial statements conducted by researchers in Indonesia. This research has been published on the website of the Ministry of Research and Technology with the SINTA 1 and SINTA 2 indexes. This research was conducted with a literature study on financial statement fraud in Indonesia. The research method used is a descriptive qualitative method by taking data from literacy studies on the research of fraud detection methods in Indonesia. The results of this study indicate that the fraud detection method used in financial reports in Indonesia is using the fraud Triangle method. The article of these studies is expected to provide input, insight, and information to all parties such as company management, auditors, and users of financial statements about various methods of detecting financial statement fraud in Indonesia.

Author(s):  
Nguyen Tien Hung ◽  
Huynh Van Sau

The study was conducted to identify fraudulent financial statements at listed companies (DNNY) on the Ho Chi Minh City Stock Exchange (HOSE) through the Triangular Fraud Platform This is a test of VSA 240. At the same time, the conformity assessment of this model in the Vietnamese market. The results show that the model is based on two factors: the ratio of sales to total assets and return on assets; an Opportunity Factor (Education Level); and two factors Attitude (change of independent auditors and opinion of independent auditors). This model is capable of accurately forecasting more than 78% of surveyed sample businesses and nearly 72% forecasts for non-research firms.  Keywords Triangle fraud, financial fraud report, VSA 240 References Nguyễn Tiến Hùng & Võ Hồng Đức (2017), “Nhận diện gian lận báo cáo tài chính: Bằng chứng thực nghiệm tại các doanh nghiệp niêm yết ở Việt Nam”, Tạp chí Công Nghệ Ngân Hàng, số 132 (5), tr. 58-72.[2]. Hà Thị Thúy Vân (2016), “Thủ thuật gian lận trong lập báo cáo tài chính của các công ty niêm yết”, Tạp chí tài chính, kỳ 1, tháng 4/2016 (630). [3]. Cressey, D. R. (1953). Other people's money; a study of the social psychology of embezzlement. New York, NY, US: Free Press.[4]. Bộ Tài Chính Việt Nam, (2012). Chuẩn mực kiểm toán Việt Nam số 240 – Trách nhiệm của kiểm toán viên đối với gian lận trong kiểm toán báo cáo tài chính. [5]. Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of financial economics, 3(4), 305-360.[6]. Võ Hồng Đức & Phan Bùi Gia Thủy (2014), Quản trị công ty: Lý thuyết và cơ chế kiểm soát, Ấn bản lần 1, Tp.HCM, Nxb Thanh Niên.[7]. Freeman, R. E. (1984). Strategic management: A stakeholder approach. Boston: Pitman independence on corporate fraud. Managerial Finance 26 (11): 55-67.[9]. 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. Available at SSRN 1295494.[10]. Lou, Y. I., & Wang, M. L. (2011). Fraud risk factor of the fraud triangle assessing the likelihood of fraudulent financial reporting. Journal of Business and Economics Research (JBER), 7(2).[11]. Perols, J. L., & Lougee, B. A. (2011). The relation between earnings management and financial statement fraud. Advances in Accounting, 27(1), 39-53.[12]. Trần Thị Giang Tân, Nguyễn Trí Tri, Đinh Ngọc Tú, Hoàng Trọng Hiệp và Nguyễn Đinh Hoàng Uyên (2014), “Đánh giá rủi ro gian lận báo cáo tài chính của các công ty niêm yết tại Việt Nam”, Tạp chí Phát triển kinh tế, số 26 (1) tr.74-94.[13]. Kirkos, E., Spathis, C., & Manolopoulos, Y. (2007). Data mining techniques for the detection of fraudulent financial statements. Expert Systems with Applications, 32(4), 995-1003.[14]. Amara, I., Amar, A. B., & Jarboui, A. (2013). Detection of Fraud in Financial Statements: French Companies as a Case Study. International Journal of Academic Research in Accounting, Finance and Management Sciences, 3(3), 40-51.[15]. Beasley, M. S. (1996). An empirical analysis of the relation between the board of director composition and financial statement fraud. Accounting Review, 443-465.[16]. Beneish, M. D. (1999). The detection of earnings manipulation. Financial Analysts Journal, 55(5), 24-36.[17]. Persons, O. S. (1995). Using financial statement data to identify factors associated with fraudulent financial reporting. Journal of Applied Business Research (JABR), 11(3), 38-46.[18]. Summers, S. L., & Sweeney, J. T. (1998). Fraudulently misstated financial statements and insider trading: An empirical analysis. Accounting Review, 131-146.[19]. Dechow, P. M., Sloan, R. G., & Sweeney, A. P. (1996). Causes and consequences of earnings manipulation: An analysis of firms subject to enforcement actions by the SEC. Contemporary accounting research, 13(1), 1-36.[20]. Loebbecke, J. K., Eining, M. M., & Willingham, J. J. (1989). Auditors experience with material irregularities – Frequency, nature, and detectability. Auditing – A journal of practice and Theory, 9(1), 1-28. [21]. Abbott, L. J., Park, Y., & Parker, S. (2000). The effects of audit committee activity and independence on corporate fraud. Managerial Finance, 26(11), 55-68.[22]. Farber, D. B. (2005). Restoring trust after fraud: Does corporate governance matter?. The Accounting Review, 80(2), 539-561.[23]. Stice, J. D. (1991). Using financial and market information to identify pre-engagement factors associated with lawsuits against auditors. Accounting Review, 516-533.[24]. Beasley, M. S., Carcello, J. V., & Hermanson, D. R. (1999). COSO's new fraud study: What it means for CPAs. Journal of Accountancy, 187(5), 12.[25]. Neter, J., Wasserman, W., & Kutner, M. H. (1990). Applied statistical models.Richard D. Irwin, Inc., Burr Ridge, IL.[26]. Gujarati, D. N. (2009). Basic econometrics. Tata McGraw-Hill Education.[27]. McFadden, D. (1974). Conditional Logit Analysis of Qualita-tive Choice Behavior," in Frontiers in Econometrics, P. Zarenm-bka, ed. New York: Academic Press, 105-42.(1989). A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration," Econometrica, 54(3), 1027-1058.[28]. DA Cohen, ADey, TZ Lys. (2008), “Accrual-Based Earnings Management in the Pre-and Post-Sarbanes-Oxley Periods”. The accounting review.


2020 ◽  
Vol 25 (1) ◽  
pp. 29-44
Author(s):  
Mariati ◽  
Emmy Indrayani

Company’s financial condition reflected in the financial statements. However, there are many loopholes in the financial statements which can become a chance for the management and certain parties to commit fraud on the financial statements. This study aims to detect financial statement fraud as measured using fraud score model that occurred in issuers entered into the LQ-45 index in 2014-2016 with the use of six independent variables are financial stability, external pressure, financial target, nature of industry, ineffective monitoring and rationalization. This study using 27 emiten of LQ-45 index during 2014-2016. However, there are some data outlier that shall be removed, thus sample results obtained 66 data from 25 companies. Multiple linear regression analysis were used in this study. The results showed that the financial stability variables (SATA), nature of industry (RECEIVBLE), ineffective monitoring (IND) and rationalization (ITRENDLB) proved to be influential or have the capability to detect financial statement fraud. While the external pressure variables (DER) and financial target (ROA) are not able to detect the existence of financial statement fraud. Simultaneously all variables in this study were able to detect significantly financial statement fraud.


2020 ◽  
Vol 2 (1) ◽  
pp. 117
Author(s):  
Iwan Budiyono ◽  
Melati Sari Dewi Arum

<p class="IABSSS"><strong>Purpose</strong> - The purpose of study was to examine the effect financial statement fraud based on the fraud triangle with a number of variables such as financial stability, external pressure, financial target, personal financial needs, opportunity and rasionalization in companies listed in Jakarta Islamic Index (JII) period 2012-2018.</p><p class="IABSSS"><strong>Method </strong>- The population are all companies listed in JII period 2012-2018. The sample is 6 companies that were feasible to analyze. The data used in this research is secondary data obtained from the annual report. The data analysis model applied multiple linier regression data panel  using SPSS 25.</p><p class="IABSSS"><strong>Result</strong> - The results showed that the fraud triangle in the categories of financial stability, external pressure, financial targets, personal financial needs, opportunity and rationalization simultaneously affect the fraudulent financial statements. Furthermore financial stability, personal financial needs and opportunity partially negatively related and had no significant effect on financial statement fraud; while external pressures, financial targets and rationalization have positive and significant effects on financial statement fraud on companies listed in JII period 2012-2018.</p><p class="IABSSS"><strong>Implication</strong> - Companies Registered in JII are suggested to improve the financial performance in accordance with sharia principles.</p><strong>Originality</strong> - This research is the first study using multiple linier regression data panel.


2021 ◽  
Author(s):  
Ahmed M. Khedr ◽  
Magdi El Bannany ◽  
Sakeena Kanakkayil

Fraudulent financial statements are deliberate furnishing and/or reporting incorrect statistics, and this has become a major economic and social concern as the global market is witnessing an upsurge in financial accounting fraud, costing businesses billions of dollars a year. Identifying companies that manipulate financial statements remains a challenge for auditors, as fraud strategies have become increasingly sophisticated over the years. We evaluate machine learning techniques for financial statement fraud detection, particularly a powerful ensemble technique, the XGBoost algorithm, that help to identify fraud on a set of sample companies drawn from the MENA region. The issue of the class imbalance in the dataset is addressed by applying the SMOTE algorithm. We found that XGBoost algorithm outperformed other algorithms in this study: Logistic Regression (LR), Decision Tree (DT), Vector Machine Support (SVM), Adaboost, and RandomForest. The XGBoost algorithm is then optimised to obtain the optimum performance.


2019 ◽  
Vol 20 (6) ◽  
pp. 1210-1237
Author(s):  
Shi Qiu ◽  
Hong-Qu He ◽  
Yuan-sheng Luo

A financial report restatement reflects errors in the previous financial statement, and thus it increases investors’ doubt about the credibility of the financial statement. The primary objective of this paper is to examine whether restatement announcements imply increased fraud risks in Chinese firms in the context that up to one quarter of listed companies have restated their financial reports in China, and explore the implications of the content, severity and reasons for restatements with respect to fraud. In this paper, firms with financial restatements prove to be more likely to be labeled as fraudulent by regulators in China. Second, the following results also are revealed: (1) financial statements, except balance sheet restatements, provide insights into the revelation of fraudulent behaviors, (2) the severity of restatements is positively correlated with future fraud disclosures, and (3) restatements due to negligence are positively correlated with future fraud occurrences. These results imply that restatement announcements and their different characteristics provide important information for detecting financial statement fraud.


2018 ◽  
Vol 23 (2) ◽  
pp. 191-199
Author(s):  
Sidik Nur Fajri

The purpose of this study was to determine whether financial stability, external pressure, personal financial need, financial targets, ineffective monitoring, and audit quality affect the financial statement fraud by collecting empirical evidence. The object of research is the companies from sector property and real estate which listing on the Indonesia Stock Exchange, with research period in 2010-2012. The samples in this study were selected based on purposive sampling method with a total sample of 14 companies. The analysis technique used in this research is multiple regression analysis using SPSS. These results indicate that the variable external pressure, personal financial need and audit quality effect on the financial statements fraud, meanwhile variables financial stability, financial targets, ineffective monitoring had no effect on the financial statements fraud. Variables financial stability, external pressure, personal financial need, financial targets, ineffective monitoring and audit quality simultaneously effect on the financial statements fraud. Keywords: Financial Statement Fraud, Fraud Triangle


2020 ◽  
pp. 1-4
Author(s):  
Chetana R. Marvadi

In the business environment, rms are expected to disclose accurate and reliable nancial information. Financial statement fraud is actions which are taken to intentionally distort a company's reported nancial performance. Major corporate nancial statement Frauds get away in the name of creative accounting. But, they need to be studied for lessons learned and strategies to avoid or reduce the incidence of such frauds in the future. It is essential for shareholders, particularly the common man who does not have any access to the company except reported nancial numbers. This research paper attempts to detect the practices of nancial statement fraud in the Pharmaceutical Sector in India for investors' interest using Earnings quality, De Angelo and Beneish models of fraud detection. The result conrms the presence of nancial statement fraud in the companies under study. It is therefore expected that the study will help to improves investor's belief of a company's performance, as reected in their nancial numbers.


2018 ◽  
Vol 3 (2) ◽  
pp. 161
Author(s):  
Poppy Indriani

Effect of Diamond Fraud in Financial Statement Fraud detection. This study aimed to get empirical evidence regarding the effectiveness of diamond fraud in detecting fraudulent financial statements. Variables - variables of diamond fraud is financial stability is proxied by ACHANGE, external pressure proxied with leverage, financial targets are proxied by the ROA, nature of industry proxied by inventory, ineffective monitoring proxied by BDOUT, audit opinion and change of directors. Financial statement fraud detection in this study using the F-score models. The results of this study indicate that external pressure, financial targets, ineffective monitoring, audit opinion and change of directors does not have influence in detecting fraudulent financial statements. While the financial stability and nature of industry to have an influence in detecting fraudulent financial statements.


2020 ◽  
Vol 10 (3) ◽  
pp. 231-244
Author(s):  
Zakharia Sabatian ◽  
Francis M. Hutabarat

Financial statements are a form of a report presented by a company that shows the financial performance of the company. In many cases of financial report fraud committed by Public Accounting Firm, they beautify the financial statements so that many investors are interested in the company. Therefore, this study aims to examine the influence of the Fraud Triangle factor in detecting fraudulent financial statements. The object of this study uses the financial statements of the Cigarettes and Cosmetics subsectors that are listed on the Indonesia Stock Exchange in the period 2016-2018. This study uses thirty sample data using purposive methods based on criteria. Data analysis using logistic linear regression analysis. The results showed that Rationalization had a significant effect on financial statement fraud. Meanwhile, Financial Stability, External Pressure, Personal Financial Need, Financial Targets, Ineffective Monitoring, Nature of Industry have no significant effect on financial statement fraud.Keywords: Fraud, Pressure, Opportunity, Rationalization, Financial Statement Fraud


2021 ◽  
Vol 11 (1) ◽  
pp. 133-149
Author(s):  
Ramdany Ramdany ◽  
Resty Harmenawati ◽  
Samukri Samukri

This study aims to measure the level of fraudulent financial statements with the fraud triangle model. The independent variables are pressure, opportunity, rationalization, and the dependent variable is fraudulent financial statements. The population in this study is companies listed on the Indonesia Stock Exchange (IDX) in 2014-2018 with a sample of 100 companies. Data analysis techniques using multiple linear regression. The results show that the pressure with proxies the financial stability and financial target and the opportunity with proxy the nature of industry has significant effect on the financial statement fraud. Meanwhile, the opportunity with proxies the ineffective monitoring and rationalization have not significant effect on the financial statement fraudulent.


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