scholarly journals THE EFFECTIVENESS OF FRAUD TRIANGLE ON DETECTING FRAUDULENT FINANCIAL STATEMENT: USING BENEISH MODEL AND THE CASE OF SPECIAL COMPANIES

2015 ◽  
Vol 3 (3) ◽  
pp. 786
Author(s):  
Aprillia Aprillia ◽  
Orlin Cicilia ◽  
Rafaela Pertiwi Sergius
Keyword(s):  
Logistic Regression ◽  
Regression Method ◽  
Financial Information ◽  
Financial Statement ◽  
Fraud Triangle ◽  
Financial Statement Fraud ◽  
Real Condition ◽  
Logistic Regression Method ◽  
Total Accrual ◽  
Illegal Action

Fraudulent financial statement is a serious problem and to be a threat to stakeholders, especially for investor. The thing is happened because there is illegal action done intentionally, such as disclosing financial information that doesn’t match with the real condition. The purpose of this research is to acquire a effectiveness of empirical proof of fraud triangle consisting of Pressure, Opportunity, and Rationalization in detecting financial statement fraud that are indicated by using Beneish Model. The sample of this research consists of 39 companies are indicated doing fraud and 57 companies aren’t indicated doing fraud listing at BEI (Bursa Efek Indonesia) in 2012 – 2014. Test of this research uses logistic regression method. Based on the result and conclusion, this research shows that opportunity (independent commissioner ownership) has significant effect to fraudulent financial statement while pressure (AGROW), financial target (ROA), and rationalization (Total accrual) don’t have significant effect to fraudulent financial statement.

Pendeteksian Financial Statement Fraud melalui Komponen Fraud Triangle

2021 ◽  
Vol 5 (2) ◽  
pp. 125
Author(s):  
Nurul Aini ◽  
Eman Sukanto
Keyword(s):  
Logistic Regression ◽  
Financial Stability ◽  
Stock Exchange ◽  
External Pressure ◽  
Financial Statement ◽  
Fraud Triangle ◽  
Financial Statement Fraud ◽  
Auditor Change

<p><em>The aim of this study is deemed to analyze the influence of fraud triangle as a tool to detect the fraud in a financial statement. The research focuses on the trading sector companies from 201</em><em>4</em><em> to 2016 that are listed on the Indonesia Stock Exchange. After selecting these companies, 24 of them become the definite samples. They are divided into companies that are probable doing financial </em><em>statement </em><em>fraud and those which are not based on the model of Beneish M-Score. For that, this research uses logistic regression. The results show that those that have significant effect on financial statement fraud are external pressure, ineffective monitoring, and financial stability. And those insignificant variables include auditor change, financial target, and the nature of industry. </em></p>

Can the Fraud Triangle Detect Financial Statement Fraud? (An Empirical Study of Manufacturing Companies in Indonesia)

2021 ◽  
Vol 15 (3) ◽  
pp. 28-38
Author(s):  
Irine Herdjiono ◽  
Berkah Nadila Kabalmay
Keyword(s):  
Logistic Regression ◽  
Empirical Study ◽  
Stock Exchange ◽  
External Pressure ◽  
Financial Statement ◽  
Fraud Triangle ◽  
Manufacturing Companies ◽  
Financial Statement Fraud ◽  
Financial Need

This study examines the effect of the following factors on financial statement fraud: (1) external pressure, (2) personal financial need, (3) financial targets, (4) the nature of industry, (5) ineffective monitoring, and (6) rationalization. The population in this study consisted of companies listed on the Indonesia Stock Exchange (IDX) over the period 2016-2018. The analysis was conducted with the help of the logistic regression method.The results of this study indicate that external pressure, financial targets and the nature of industry have an effect on financial statement fraud, while personal financial need, ineffective monitoring and rationalization have no effect on financial statement fraud. Thus, this study contributes to the understanding that not all aspects of the fraud triangle can detect fraud.

scholarly journals PENDETEKSIAN LAPORAN KEUANGAN MELALUI FAKTOR RESIKO, TEKANAN DAN PELUANG (BERDASARKAN PRESS RELEASE OJK 2008-2012)

2015 ◽  
Vol 2 (1) ◽  
pp. 29 ◽  
Author(s):  
Noval Dwi Aditya Nugraha ◽  
Deliza Henny
Keyword(s):  
Financial Stability ◽  
Stock Exchange ◽  
Total Sample ◽  
Financial Statement ◽  
Managerial Ownership ◽  
Fraud Triangle ◽  
Financial Statement Fraud ◽  
Financial Report ◽  
External Pressures ◽  
Logistic Regression Method

This study aims to obtain empirical evidence about the effectiveness of the fraud<br />triangle is the pressure, opportunity, and rationalization in detecting fraudulent<br />financial statements. Based on the theory of fraud triangle Cressey adopted in SAS 99. The variables of the fraud triangle that is used is the pressure that consists of financial stability is proxied by AGROW, external pressures are proxied by LEV, a proxy for managerial ownership OSHI, a proxy for the financial targets ROA, liquidity proxied by (WCTA) and capital turnover is proxied by (SATA); and opportunities which consists of monitoring the effectiveness of control is proxied by IND. Detection of financial statement fraud in this study obtained from the annual report and press releases OJK during 2008-2012 as the dependent variable The population of this study is that non-financial companies listed on the Indonesia Stock Exchange 2008-2012. The total sample of this study is 130 firms, consisting of 13 companies who violate the OJK rules that contain elements of fraud, and being penalized, and the 13 companies that did not commit fraud financial report (based on the type of industry and total assets are equal). Hypothesis testing using logistic regression method. The results of this study indicate that external pressures and financial targets, has significant effect on the financial statement fraud, while financial stability, managerial ownership, liquidity, capital turnover, effectiveness of supervision, does not affect the financial fraud<br /><br />

scholarly journals Analisis Faktor Risiko Yang Mempengaruhi Financial Statement Fraud : Prespektif Diamond Fraud Theory

2020 ◽  
Vol 20 (2) ◽  
Author(s):  
Titi Purbo Sari ◽  
Dian Indriana Tri Lestari
Keyword(s):  
Financial Stability ◽  
External Pressure ◽  
Financial Statement ◽  
Fraud Triangle ◽  
Financial Statement Fraud ◽  
Discretionary Accrual ◽  
Auditor Change ◽  
Jones Model ◽  
Financial Need ◽  
Total Accrual

Meningkatnya berbagai kasus skandal akuntansi di dunia menyebabkan berbagai pihak berspekulasi bahwa manajemen telah melakukan kecurangan pada laporan keuangan. Penilaian faktor risiko kecurangan banyak yang mengadopsi beberapa standar pengauditan mengenai pendeteksian kecurangan (yakni SAS No.82, ISA 240, dan SAS No.99), dan merujuk pada teori Fraud Triangle. Wolfe dan Hermanson (2004), meningkatkan pendeteksian kecurangan fraud triangle dengan mempertimbangkan elemen keempat, yaitu kemampuan (capability) dan dikenal sebagai Fraud Diamond. Penelitian ini bertujuan untuk menguji pengaruh Fraud Diamond terhadap financial statement fraud. Sampel penelitian ini adalah 29 perusahaan di subsektor perbankan yang terdaftar di Bursa Efek Indonesia periode 2014-2018 dengan menggunakan 128 laporan tahunan. Metode analisis data yang digunakan adalah metode analisis regresi linear berganda. Variabel independen dalam penelitian ini terdiri financial stability, external pressure, personal financial need, financial target, nature of industry, ineffective monitoring, opinion auditor, change in auditor, total accrual, dan change in director. Sedangkan variabel dependen dalam penelitian ini adalah Financial Statement Fraud yang diproksikan dengan nilai discretionary accrual dari Modified Jones Model. Hasil penelitian menunjukkan bahwa variabel personal financial need dan total accrual yang berpengaruh positif dan signifikan terhadap financial statemanet fraud. Adapun variabel financial stability, external pressure, financial target, nature of industry, ineffective monitoring, opinion auditor, change in auditor, dan change in director tidak dapat digunakan untuk mendeteksi kecurangan laporan keuangan.

Fraud of Financial Statements at Listed Enterprises on Ho Chi Minh City Securities Department

2018 ◽  
Vol 34 (4) ◽  
Author(s):  
Nguyen Tien Hung ◽  
Huynh Van Sau
Keyword(s):  
New York ◽  
Financial Reporting ◽  
Financial Statements ◽  
Financial Statement ◽  
Viet Nam ◽  
Fraud Triangle ◽  
Fraudulent Financial Reporting ◽  
Financial Statement Fraud ◽  
Corporate Fraud ◽  
Two Factors

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.

FRAUD TRIANGLE ANALYSES IN DETECTING FRAUDULENT FINANCIAL STATEMENT USING FRAUD SCORE MODEL

2020 ◽  
Vol 25 (1) ◽  
pp. 29-44
Author(s):  
Mariati ◽  
Emmy Indrayani
Keyword(s):  
Financial Stability ◽  
Linear Regression Analysis ◽  
Financial Statements ◽  
Multiple Linear Regression Analysis ◽  
External Pressure ◽  
Financial Statement ◽  
Fraud Triangle ◽  
Financial Statement Fraud ◽  
Financial Condition ◽  
Score Model

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.

scholarly journals Prediksi Not Operational Transaction Menggunakan Logistic Regression pada Bank XYZ di Kota Kupang

AITI ◽  
2020 ◽  
Vol 17 (1) ◽  
pp. 42-55
Author(s):  
Radius Tanone ◽  
Arnold B Emmanuel
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Regression Method ◽  
Learning Approach ◽  
Know How ◽  
Independent Variables ◽  
Machine Learning Approach ◽  
Logistic Regression Method ◽  
Python Programming

Bank XYZ is one of the banks in Kupang City, East Nusa Tenggara Province which has several ATM machines and is placed in several merchant locations. The existing ATM machine is one of the goals of customers and non-customers in conducting transactions at the ATM machine. The placement of the ATM machines sometimes makes the machine not used optimally by the customer to transact, causing the disposal of machine resources and a condition called Not Operational Transaction (NOP). With the data consisting of several independent variables with numeric types, it is necessary to know how the classification of the dependent variable is NOP. Machine learning approach with Logistic Regression method is the solution in doing this classification. Some research steps are carried out by collecting data, analyzing using machine learning using python programming and writing reports. The results obtained with this machine learning approach is the resulting prediction value of 0.507 for its classification. This means that in the future XYZ Bank can classify NOP conditions based on the behavior of customers or non-customers in making transactions using Bank XYZ ATM machines.  

scholarly journals Talent Performance Analysis Using People Analytics Approach

2021 ◽  
Vol 4 (1) ◽  
pp. 216-230
Author(s):  
Fahreza Nasril ◽  
Dian Indiyati ◽  
Gadang Ramantoko
Keyword(s):  
Logistic Regression ◽  
Multinomial Logistic Regression ◽  
Research Question ◽  
Development Program ◽  
Individual Performance ◽  
Study Data ◽  
Regression Method ◽  
Process Data ◽  
Logistic Regression Method ◽  
The Right

The purpose of this study was to answer the research question "How is the prediction of Talent Performance in the following year with the application of People Analytics?" and knowing the description of employees who are potential talents, the resulting performance contributions, to the description of the development and retention efforts needed by Talent in order to be able to maintain their future performance and position as Talents compared to the previous People Analytics method using predictive analysis, namely prediction of Talent Performance in the year next. In this study, data analysis using the Multivariate Logistic Regression method is used to get the Prediction of the Performance of Talents who become the object of research in the form of individual performance quickly and precisely in accordance with the patterns drawn by individual Performance score data in previous years. And can provide insight regarding the projected strategies that need to be done to maintain the improvement of individual talent performance in the years of the assessment period. It also helps management in making decisions about the right Talent development program and determining which Talents are priorities. The population in this study were the talents of employees of PT. Angkasa Pura II (Persero) with a managerial level consisting of: Senior Leader, Middle Leader, and First Line Leader who has a Person Grade (PG) range of 13 to 21. The sample used is Middle Leader level talent with specified criteria and through a process data cleansing. The results of this study indicate that the variable that significantly affects the performance of the following year is the performance of the previous 2 years. Then prediction analysis can be done using these independent variables with the Multinomial Logistic Regression method, and to get prediction results with better accuracy can be done by the Random Forest method.

scholarly journals FRAUD PENTAGON THEORY DALAM FINANCIAL STATEMENT FRAUD PADA PERUSAHAAN TERDAFTAR di JAKARTA ISLAMIC INDEX (JII) PERIODE 2014-2017 (Perspektif F-Score Model)

2019 ◽  
Vol 4 (2) ◽  
pp. 128-138
Author(s):  
Faiz Rahman Siddiq ◽  
Agus Endrianto Suseno
Keyword(s):  
Financial Stability ◽  
External Pressure ◽  
Financial Statement ◽  
Fraud Triangle ◽  
Financial Statement Fraud ◽  
Purposive Sampling ◽  
Auditing Standards ◽  
Score Model ◽  
Financial Need

Financial statement fraud biasa disebut dengan kecurangan laporan keuangan yang merupakan kesengajaan dalam melakukan kelalaian dan kesalahan ketika  membuat laporan keuangan dengan penyajian yang tidak sesuai pada prinsip akuntansi berterima umum. Statement on Auditing Standards (SAS) No.99 menjelaskan tentang salah saji yang berhubungan dengan auditor dalam mengaudit laporan keuangan terhadap fraud diantaranya adalah (1) salah saji dari kesalahan suatu laporan keuangan merupakan suatu  pengungkapan yang direncanakan guna menipu pengguna laporan keuangan, (2) penyalahgunaan aset atau istilah lain pencurian dan penggelapan sering dijadikan sebagai salah saji dalam laporan keuangan. Fraud pentagon theory merupakan pengembangan dari teori fraud sebelumnya yaitu fraud triangle (Cressey, 1953) dan fraud diamond (Wolf and Hermanson,2004). Populasi penelitian ini adalah perusahaan yang tergabung dalam Indeks JII (Jakarta Islamic Index) pada tahun 2014-2017. Teknik pengambilan sampel dengan menggunakan metode purposive sampling. Metode analisis data yang digunakan dalam penelitian ini adalah analisis regresi linear berganda. Financial statement fraud dalam penelitian menggunakan perspektif F-Score Model. Hasil penelitian ini adalah pressure (Financial Stability, dan Financial Target), dan Opportunity (Nature of Industry) berpengaruh terhadap financial statement fraud. Sedangkan Pressure (External Pressure dan Personal Financial  Need), Rationalization (Change in Auditor), Competence (Change of Director) dan Arrogance (Frequent Number of CEO’s Picture dan Dualism Position) tidak berpengaruh terhadap financial statemnt fraud.

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