Beneish M-Score Research Articles

ANALYSIS OF FINANCIAL PERFORMANCE IN VARIOUS SECTORS: APPLICATION OF THE BENEISH M-SCORE MODEL IN CASABLANCA STOCK EXCHANGE MOROCCO

<p>This paper evaluates the financial performance of companies from different sectors on the Moroccan financial market, using the Beneish M-Score model. Initially developed to detect financial anomalies, the M-Score has evolved into a tool for assessing companies' overall financial performance and earnings quality. By analyzing financial indicators such as profitability, liquidity and operational efficiency, this study compares the financial dynamics of companies in sectors such as food, technology and transportation. The results highlight significant differences in performance, revealing both strengths and weaknesses in companies' financial management. The study also provides a comparison with industry standards, and offers recommendations for improving the assessment of financial performance using financial indicators and the M-Score.</p><p> </p><p><strong>JEL: </strong>G32, M41, L25</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0778/a.php" alt="Hit counter" /></p>

HOW DETECT FRAUD WITH HEXAGON MODEL ON FINANCIAL STATEMENT FRAUD IN PROPERTY AND REAL ESTATE INDONESIA

Examining how Freud's hexagon framework relates to financial statement fraud is the focus of this study. In total, ten factors were considered. Financial Target, Financial Stability, External Pressure, Change of Director, Nature of Industry, CEO Picture, Political Connection, Audit Opinion, CEO Education and Effective Monitoring. Financial statement fraud is measured using the Beneish M-Score Model. The research sample consists of industries in the property and real estate sector based on data from the Indonesia Stock Exchange (IDX) during the 2020-2022 period. The number of companies included in the sample was 35. This study uses panel data regression analysis for data analysis purposes. The results of this study indicate that Financial Target, Financial Stability, External Pressure, Change of Director, Nature of Industry, CEOPicture Audit Opinion and Effective Monitoring have no effect on the potential for fraudulent financial statements. While Change In Auditor and Political Connection have an effect on fraudulent financial statements in the Property and Real Estate sector.

Revitalizing the Forensic Accounting: An Exploratory Study on Mitigating the Financial Risk using Data Analytics

Risk mitigation and fraud prevention in the present times has more focus on digital metadata, wherein forensic accountants are required to make use of robust IT techniques and tools. Data Analytics has got huge implications for forensic accounting. With the ever-increasing electronic element of frauds in the present age of digitalization, and complexity of financial transactions and instruments, the challenges are growing multifold for the forensic accounting profession. The use of data analytics techniques, which enables the processing of large data in almost no time, simplify the task of forensic accountant to a large extent. It enables the identification of patterns and anomalies with the use of machine learning, deep learning, natural language processing, data mining and similar other statistical techniques. Beneish M-score and the Altman Z-score models are proven effective forensic accounting tools in fraud detection and insolvency prediction. This study has been undertaken to test the effectiveness and efficiency of these forensic tools in fraud detection and insolvency prediction with the case study of Bhushan Steel Ltd. Based upon the findings of the study, it is suggested that these models should be integrated with the data analytics, as these are highly effective and efficient in detection of financial statements frauds and this integration would equip the naïve investor in selection of financially sound company(s) to invest in. Data analytics is thus indispensable in the field of forensic accounting in the present era. Since, there is increased funding by many international funding agencies including the World Bank for empowering the forensic accountants and increasing awareness towards this profession, especially in developing countries; it can be hoped that the integration of data analytics with forensic accounting would gain momentum soon.

Do the fraud triangle components fuel complex financial fraud? A study of nonfinancial firms in Pakistan

Purpose Financial fraud is a severe corporate fraud committed for achieving various objectives, like attaining financial targets, lowering debt and providing good signals to the market. Such financial fraud deceives stakeholders and results in substantial financial losses. This study aims to detect financial fraud using the modified Beneish M-Score, the most appropriate forensic tool for fraud detection. Furthermore, the current study also examines the influential role of the fraud triangle’s elements (pressure, opportunity and rationalization) on financial fraud in nonfinancial firms during 2018–2021, offering insight for understanding and mitigating fraudulent activities in the corporate world. Design/methodology/approach Financial fraud is treated as a dependent variable measured through a modified Beneish M-score, while the fraud triangle elements (pressure, opportunity and rationalization) are measured through six proxies, which are financial stability, leverage, financial target, nature of the industry, the effectiveness of supervision and auditor changes. Findings The study's finding proclaimed that fraud triangle elements result in financial fraud. Findings unveil that all elements (pressure, opportunity and rationalization) of the fraud triangle significantly influence financial fraud. The study confirms that these elements must be considered to protect investors and provide a safe environment for investment. Originality/value Rare literature found addressing the detection of financial fraud and its nexus with the fraud triangle specifically in Pakistan where deficient governance is notably prevalent. This study attempts to fill such a gap and contribute to knowledge.

Detecting Earning Manipulation Using the Beneish M-Score Model: Evidence from Public Listed Companies in Malaysia

This paper aims to examine the association between earning manipulation using the Beneish M-Score Model and share price with market capitalisation as the control variable among public listed companies (PLCs) in Malaysia. The study was performed over a four-year period from 2017 to 2020 using the financial data of 65 PLCs under the Financial Times Stock Exchange (FTSE) Bursa Malaysia Top 100 Index, including various industries except the financial service industry. The Beneish M-Score Model comprised eight variables or ratios to identify earning manipulations, namely Days Sales in Receivable Index (DSRI), Gross Margin Index (GMI), Asset Quality Index (AQI), Depreciation Index (DEPI), Sales Growth Index (SGI), Sales, General and Administrative Index (SGAI), Total Accruals to Total Assets (TATA), and Leverage Index (LVGI). The market price was measured using the year-end share price. The findings found that there was a weak negative association as well as a statistically insignificant relationship between earning manipulation and share price, which suggests that earning manipulation is influenced by other factors excluding share price. The findings did not support the argument that there was a significant relationship between earning manipulation and share price where companies had been discovered to have engaged in earning manipulation. The study is crucial for the stakeholders that expect companies to achieve the maximum returns and stability in investments and to protect owners’ rights.

PENDETEKSIAN FINANCIAL STATEMENT FRAUD MENGGUNAKAN FRAUD HEXAGON PADA PERUSAHAAN YANG TERINDEKS IDXBUMN20

This research has a problem with financial statement fraud with the smallest percentage of cases but has the greatest impact on state losses among other frauds. This study aims to detect financial statement fraud using fraud hexagon in IDXBUMN20 indexed companies. There are six dimensions in the fraud hexagon consisting of stimulus, ability (Capability), conspiracy (Collusion), opportunity (Opportunity), rationalisation, and (arrogance). This study measures financial statement fraud using the Beneish M-Score. The population of this study were 20 BUMN companies indexed on IDXBUMN20. To select the sample, purposive sampling method was used for 15 state-owned companies for 3 years of observation with 45 observations. Logistic regression model as an analysis technique. Data processing with SPSS 26 which obtained results showing that financial stability proxy stimulus, auditor turnover proxy opportunity and ineffective supervision proxy rationalization affect financial statement fraud. While the change of directors proxy capability, the number of independent commissioners who hold concurrent positions proxy collusion, and the number of CEO photos in the annual report proxy arrogance have no effect on financial statement fraud.

HOW FRAUD HEXAGON MODEL ON FINANCIAL STATEMENT FRAUD IN ENERGY SECTOR COMPANIES?

Financial statement fraud is a discrepancy between the application of accounting principles and the preparation of financial statements with the aim of deceiving users of financial statements This study aims to analyze the effect of Hexagon Fraud on financial statement fraud. There are 10 variables used, namely financial targets, financial stability, change of directors, monitoring, ideal condition of the company, change of auditor, photo of the CEO, government projects, political connections, managerial ownership. Financial statement fraud is measured using the Beneish M-Score Model. The samples in this study are energy sector companies listed on the Indonesia Stock Exchange (IDX) in 2020-2021 with the number of samples used being 50 companies with 100 units of analysis taken based on the purposive sampling method. Data analysis in this study used panel data regression analysis with the EViews 13 analysis tool. The results of this study show that a company's Financial Target has an influence on the potential for financial statement fraud. Meanwhile, financial stability, change of directors, monitoring, ideal condition of the company, change of auditor, CEO photo, government projects, political connections, managerial ownership have no influence on the potential for financial statement fraud.

Effect of Hexagon Fraud Against Financial Statement Fraud with Company Size as Moderation

This research aims to determine the effect of hexagon fraud with company size moderating its effect on financial statement fraud. Hexagon fraud is measured through six components, namely, stimulus, capability, collusion, opportunity, rationalization and ego. Meanwhile, company size is measured through total assets and financial statement fraud is measured through the Beneish M-Score model. This research is included in descriptive quantitative research. Through purposive sampling, 35 companies were determined as samples for a 5-year observation period from a total population of 113 non-cyclical consumer sector companies as of 2022 listed on the Indonesia Stock Exchange. Data were processed using multiple linear regression. Based on the results of data analysis, it is known that partially hexagon fraud has a significantly positive effect on financial statement fraud, while company size has no effect on financial report fraud. As a moderator, company size can strengthen the influence of hexagon fraud on financial statement fraud. Simultaneous testing shows that hexagon fraud and company size influence financial statement fraud. However, both of them were only able to explain 9% of financial statement fraud with the rest explained by other variables.

The Beneish M-Score Model in Detecting Fraudulent Financial Reporting: The Hexagon Perspective Theory

This research aims to investigate the effect of fraud on fraudulent financial reports (FFR) using the hexagon theory. The seven factors were financial stability, external pressure, ineffective monitoring, auditor changes, director changes, arrogance, and collusion. This study has a population of health companies listed on the IDX in 2018-2021. This study uses a quantitative approach. Based on the logistic regression analysis, the study finds that financial stability, change director, and arrogance affect FFR. On the other hand, external pressure, ineffective monitoring, auditor change, and collusion do not affect FFR. Keywords:Fraudulent financial reporting, Hexagon theory, Beneish M-Score

MANIPULASI LABA DI SEKTOR KESEHATAN: STUDI SEBELUM, SAAT, DAN SESUDAH PANDEMI COVID-19 DI INDONESIA

This research aims to explore indications of earnings manipulation during the Covid-19 pandemic. The subject of this research concerns companies in the health sector listed on the Indonesia Stock Exchange (BEI). Tools to measure indications of earnings manipulation use the Earnings Quality Ratio, Revenue Quality Ratio, Accruals Earnings Management, Real Earnings Management, Beneish M-score model, and DechowF-score model. Based on the research results, this study reached three main conclusions. First, indications of earnings manipulation continue to increase between 2018 and 2022. Second, when the pandemic hit, earnings manipulation saw a significant increase, especially in 2021. Third, once the pandemic ended, indices There were still many cases of earnings manipulation, including manipulation of earnings quality, recording of false income, poor cash flow, production expenses and costs.

FINANCIAL REPORTING FRAUD: AUDIT COMMITTEE AS MODERATION

This study aims to investigate the influence of the audit committee in moderating the association between financial targets, financial stability, changes in directors, ineffective supervision, optimal conditions of the company, changes in auditors, the CEO's photograph, government projects, political connections, and managerial ownership on financial statement fraud. When examining instances of financial statement fraud, it is important to take into account the involvement of the audit committee in addition to other variables. The Beneish M-Score Model is used to quantify financial statement fraud. The study focuses on analyzing a sample of 49 infrastructure sector companies listed on the Indonesia Stock Exchange (IDX) between 2020 - 2021. The analysis employs panel data regression analysis with 98 units, utilizing the EViews 13 analytical tool to test the hypothesis. The findings of this study indicate that a company's financial target significantly impacts the likelihood of financial statement fraud. Factors such as financial stability, changes in directors, monitoring, the company's ideal condition, changes in auditors, CEO photographs, government projects, political connections, and managerial ownership do not affect the likelihood of financial statement fraud. The presence of an audit committee has a moderating effect on the occurrence of financial statement fraud as each independent variable becomes less influential.

The Ability of the Beneish M-Score To Detect the Trends of Fraud in the Indonesian Sharia Stock Index

The purpose of this study is to determine the level of ability of the Beneish M-Score in detecting financial statement fraud tendencies. This study uses a quantitative approach with logistic regression analysis techniques. The results of this study provide empirical evidence that is different from research on manufacturing companies, state-owned companies, banking, mining, non-financial companies, property companies, real estate and building construction. The contribution of the empirical results of this study shows that overall the Beneish M-Score model is unable to detect the tendency of fraudulent financial statements in Islamic companies. DSRI, GMI, AQI, SGI, DEPI, SGAI, LVGI, and TATA has no effect on fraudulent financial statements in sharia companies.

Application of Beneish M-Score to Detech Fraudulent Financial Statements in State-Owned Company in Indonesia

Introduction/Main Objectives: This study aims to determine which State-Owned Company are included in the manipulator, non-manipulator, and gray company groups. Background Problems: According to a study conducted in 2016 by the Association of Certified Fraud Examiners, the majority Fraud cases involved 81.2% of government agencies, 8.1% of State-Owned Enterprises, and 2.3% of private companies. The businesses designated by of State-Owned Company caused the most losses to the industrial sector due to fraud at 58.8%. Research Methods: This research uses a quantitative descriptive method. The objects in this study are State-Owned Company companies in Indonesia in 2018-2021. The research sample used a purposive sampling technique. Data analysis was performed using seven types of financial ratios contained in the Beneish M-score method. Finding/Results: The results showed that in 2018 there was 1 company that was included in the manipulator group, 22 companies were included in the non-manipulator group, and no company was included in the gray company group in 2018. Then in 2019 there were 3 companies that were included in the manipulator group, 17 companies are included in the non-manipulator group, and 3 companies are included in the gray company group. In 2020 there were 5 companies included in the manipulator, 16 non-manipulator companies, 2 companies included in the gray company group. And in the last year, namely 2021, there will be 1 company that is included in the manipulator group, 22 non-manipulator companies, and no company that is included in the gray company group in 2021.

Nexus Between Possibility of Fraudulent Financial Reporting and Corporate Governance: Evidence from Bangladesh

This paper intends to test the nexus between the possibility of fraudulent financial reporting and the corporate governance in Bangladesh. The content analysis of annual reports has been performed for 125 Bangladeshi listed manufacturing companies. In this study, we apply more than one fraud indicator models such as Altman Z-score and Beneish M-score models to determine more accurately the chance of fraudulent financial reporting. The chance of fraudulent financial reporting is determined based on whether either one or both of Altman Z-score and Beneish M-score models show red flags of potential fraud. This study found that board members with finance or accounting backgrounds are less likely to practice in misleading financial reporting since they may have the knowledge essential to understand fraudulent financial reporting strategies. This result implies that qualified directors may supervise financial reporting practices better, hence improving the quality of financial reports. Alternatively, some other components of corporate governance, such as board size, board independence, director ownership, gender diversity, and auditors' independence, have insignificant impacts on fraudulent financial reporting practices. This outcome indicates that these Bangladeshi corporate governance components may not be as strong in improving financial reporting credibility. In the context of Bangladesh, this is the first empirical study with management and policy implications. To the best of the writers’ knowledge, no article yet has been worked on the possibility of fraudulent financial reporting which calculated by multiple models and its relationship with the corporate governance in the context of Bangladesh.

Earnings Quality Assessment of Financial Statments Using the Beneish M-Score Model in Manufacturing Companies Listed on the Indonesia Stock Exchange (BEI)

This study aims to analyze and assess the level of manipulation of financial statements and to analyze the quality of earnings of manufacturing companies in terms of relevance based on Beneish M-score. The type of research used is qualitative with a descriptive approach. The object of this research is a manufacturing company listed on the Indoneisa Stock Exchange (IDX) totaling seven companies. The results of the study using the Beneish ratio index show that in 2019 the number of manufacturing companies classified as non-manipulators both LQ45 and non-LQ45 and in 2020 the results of the Beneish ratio index show that manufacturing companies are classified as non-manipulators, because the companies classified as non-manipulators have no more than three parameter indices of the eight parameter indices that have been determined. In the Beneish M-score results, there is one company that is classified as a manipulator where there is a possibility of an increase in the parameter index which affects profit and loss which causes the company to have poor prospects. Companies categorized as non-manipulator companies based on the Beneish M-score index can be assessed that the company has good financial performance, is able to manage items in the financial statements effectively and efficiently such as in profit and loss, good financial performance can indicate the company has good earnings quality, Beneish M-score results when associated with earnings quality in relevance means that the financial statements and measurement index on the company accurately reflect the company's operational performance, providing an accurate overview of the company's financial condition.

ANALYSIS OF THE UTILIZATION OF ALTMAN Z-SCORE, BENEISH M-SCORE, AND F-SCORE MODEL IN DETECTING FRAUDULENT OF FINANCIAL REPORTING: A LITERATURE REVIEW

Financial statement fraud has serious implications, and early detection through methods like Altman Z-Score, Beneish M-Score, and F-Score can help prevent losses. Although each method has strengths and weaknesses, combining them or adding additional measures can enhance fraud detection accuracy. This research aims to explore the use of Altman Z-Score, Beneish M-Score, and F-Score in detecting Fraudulent Financial Reporting. we intend to examine whether Altman Z-Score, Beneish M-Score, or F-Score have influence on detecting financial statement fraud, and what the comparative level is among these methods. The methodology employs a literature review approach using the SINTA and Scopus databases to gather information from scholarly publications in the last 10 years. The choice of these databases is based on the excellence of SINTA as a local Indonesian database and Scopus as a deep international data source. The research objectives include testing the influence of each method in detecting Fraudulent Financial Reporting and analyzing their comparative levels. The theoretical contribution involves enhancing knowledge for readers and researchers, providing references for further research. In practical terms, the research is expected to offer insights to readers, especially investors, for considering the most appropriate analytical method in identifying and preventing Fraudulent Financial Reporting in investment decision-making.

Corporate Sustainability with Forensic Auditing: An Evidence from India

The repercussions of fraud are huge and sufferers are many. An organisation's very existence and sustainability of an organisation is threatened by frauds, which remain unchecked due to weak corporate governance norms and inadequacy of audit function in detection of financial statement frauds. This culminates in the closure of the entity at the cost of the interests of various stakeholders. Forensic accounting and auditing not only help detect fraud but can also prevent fraud by strengthening the corporate governance practices in an organisation. ABG Shipyard Ltd., belonging to one of the oldest and most prestigious ABG groups in India, building warships and other vessels for the Indian Navy, was once considered to be the largest private shipping yard. The Global Financial Crisis hit the company in 2008, and the consequent failure to repay the loans led to the corporate failure and liquidation. The fraud at the company was detected through a forensic audit at the State Bank of India’s behest in 2019 and the Central Bureau of Investigation (CBI) was able to register the case by 2022. This study tries to understand what went wrong and how, by analysing the annual reports, audit reports and financial statements and computing of Beneish M-score and Altman Z-score. The study finds that the erring auditors, self-dealing promoters and faulty management are the root causes of this fraud.

The Applicability of the Beneish M-Score Method for Detecting Financial Statement Fraud in Manufacturing Companies during the Covid-19 Pandemic

The Applicability of the Beneish M-Score Method for Detecting Financial Statement Fraud in Manufacturing Companies during the Covid-19 Pandemic

THE EFFECT OF HEXAGON FRAUD ON FINANCIAL STATEMENT FRAUD (EMPIRICAL STUDY OF INFRASTRUCTURE SECTOR COMPANIES IN 2020-2022)

Financial statement fraud is a discrepancy between the application of accounting principles and the preparation of financial statements with the aim of deceiving users of financial statements. This study aims to analyze the effect of Fraud Hexagon on fraudulent financial statements. There are 10 variables used, namely Financial Targets, Financial Stability, External Pressure, Monitoring, Ideal conditions of a company, the position of a CEO, Managerial Ownership, Change of directors, Government Ownership, Political connections. Financial statement fraud is measured using the Beneish M-Score Model. The sample in this research is infrastructure sector companies listed on the Indonesia Stock Exchange (IDX) in 2020-2021 with a total sample of 27 companies. data analysis in this study using panel data regression analysis. The results of this study indicate that the financial targets and ideal conditions of a company have an influence on the potential for fraudulent financial reporting. Financial Stability, External pressure, Monitoring, the position of a CEO, Managerial Ownership, Change of directors, Government Ownership, Political connections have no influence on the potential for fraudulent financial reporting.

Detection of Creative Accounting in Agricultural Enterprises

The paper deals with the detection of creative accounting of enterprises in the agricultural sector to verify whether creative accounting is used to an increased extent by those farming enterprises that have been granted a bank loan; and then whether there is an effort to manipulate financial statements mainly in micro-small or medium and large enterprises. Four mathematical-financial models were applied to 150 accounting units with primarily agricultural activity to verify the hypotheses. Beneish M-score, Jones model, Altman Z-score and IN05 model were used. An increased risk of using creative accounting methods was identified in 28% of the investigated companies on average during the monitored period. Still, the assumption that the size of the accounting unit has a significant effect on the use of creative accounting methods was not proven. However, a higher motivation to manipulate financial statements can be expected in smaller accounting units due to their less stable financial position confirmed Altman Z-score and IN05 models. At the same time, a higher probability of using and a tendency to use creative accounting techniques were found among units that were granted a bank loan, which stems from the need to secure and maintain sufficient financing for business activities.