Beneish M-Score Model Research Articles

Using the Beneish M-score Model to Detect Financial Statement Fraud in the Microfinance Industry in Ghana

Using the Beneish M-score Model to Detect Financial Statement Fraud in the Microfinance Industry in Ghana

Deteksi Manipulasi Laporan Keuangan Menggunakan Model Beneish M-Score pada BUMN yang Terdaftar di Pasar Modal

Inefficiency, mismanagement, political elements, conflicts of interest are some of the causes of problems in SOE. The purpose of this study is to provide empirical evidence of manipulation of the financial statements of SOEs. By using a sample of 16 state-owned companies with 10 years of observation, we find that there are 98 companies classified as manipulators and 62 non-manipulator companies out of 160 company year observations. We offer to use the Beneish M-Score model to detect manipulation of financial statements involving 8 financial variables namely, DSRI, GMI, AQI, SGI, DEPI, SGAI, LVGI and TATA. Our research findings are that GMI and TATA affect the manipulation of financial statements. Our findings show that SOEs improve permanent income by increasing sales and accounts receivable data so that margins are more acceptable by relevant users. Suboptimal margins are evidence that there are inefficiencies in SOEs. In addition to GMI, SOE management also utilises the flexibility of the company's accruals by improving the cash element, and the company's liabilities to assets so that it appears to have a good solvency value as a representation that SOEs have promising subsequent growth

Kemampuan Beneish M-Score Dalam Memprediksi Fraudulent Financial Reporting

The aim of this research is to determine the ability of the Beneish M-Score model to predict fraudulent financial reporting in banking companies in Indonesia. The research was conducted on all banking companies listed on the Indonesia Stock Exchange (IDX) in 2017-2021. The method of determining the sample using a non-probability method with purposive sampling technique. The data analysis technique used is discriminant analysis. The results showed that the Beneish M-Score was able to predict fraudulent financial reporting. The practical implication of this research is that investors can consider the Beneish M-Score before making economic decisions. The Beneish M-Score analysis can be an indication (red flag) of a company committing fraudulent financial reporting.
 Keywords: Fraudulent Financial Reporting; Beneish M-Score; Discriminant Analysis

Fraud triangle and earnings management based on the modified M-score: A study on manufacturing company in Indonesia

This study combines the concept of a fraud triangle and a modified Beneish M-score to detect factors that trigger earnings management. The modified M-score formula used in this study contains five original and four additional ratios. A sample of 284 manufacturing companies listed on the Indonesia Stock Exchange in the period 2017–2019 is used. Based on the logistic regression test and t-test, the results show that asset growth, changes in receivables to sales, and auditor changes have a negative relationship and debt ratio has a positive relationship with earnings management. In addition, return on assets has no relationship with earnings management. In other words, manipulator firms are subject to greater pressure on leverage and have fewer independent commissioners. This study is the first to utilise the modified Beneish M-score model to detect earnings management in manufacturing companies in Indonesia. The effectiveness of this model makes it a valuable tool in detecting fraud and is expected to be useful for future research.

Deteksi Financial Statement Fraud : Model Beneish M-Score, dan Model F-Score

The research aims to find out which model is most effective in detecting financial statement fraud by using the Beneish M-Score model and the F-Score model. The research population of the banking sector is listed on the Indonesia Stock Exchange for the period 2018 - 2020 with a total of 48 banks. The research sample totaled 40 banks using a purposive sampling method. The results of the study stated that by calculating the index using the beneficial M-Score model, it showed that there were indications of banks committing financial statement fraud in 2018 at 2.5%, in 2019 at 95% and in 2020 at 97.5%. Meanwhile, using the F-Score model in 2018 it was 5%, in 2019 it was 7.5% and in 2020 it was 5%. Based on these two models, an effective model for detecting financial statement fraud is the Beneish M-Score model.
 Keywords: Financial Statement Fraud; Model Beneish M-Score; Model F-Score.

The impact of financial reporting manipulations on the bankruptcy likelihood: A study of Nordic banks

The phenomenon of financial reporting manipulations and bankruptcy likelihood has always been a topic of interest among researchers. Corporate managers can have the motivation to compromise the financial reporting quality to hide the deteriorating financial health of the firms, nonetheless, if such practices go unabated then such firms can be exposed to serious outcomes in the form of their increased bankruptcy likelihood (Berglund & Makinen, 2016). The abovementioned outcome can be even more threatening in the banking sector due to its inherent nature. The current study aims to examine the impact of financial accounting manipulations on the likelihood of bankruptcy in Nordic banks. Beneish M-score model and Jones model have been applied to evaluate earnings quality, whereas financial distress has been measured by Altman Z-score model (Ebaid, 2022). Based on the analysis of secondary data collected from 33 Nordic banks for the period 2011–2018, the findings disclose that there is an absence of any systematic application of financial accounting manipulations measures, with a few exceptions, by the Nordic banks. Furthermore, there is no evidence to suggest that financial accounting manipulations increase the bankruptcy likelihood of banks. The current study is not only amongst the fewest empirical studies on the said topic conducted in the context of Nordic banks, but it also adds to methodological refinements by including two distinct measures of financial reporting quality to enhance the reliability and robustness of empirical findings.

An empirical study to detect agency problems in listed corporations: The emerging market study

The aim of this paper is to shed the light on the concepts of agency theory by measuring one of the problems that arise from it, which is represented by earnings management (EM) practices. The research problem is demonstrated by the failure of some Iraqi banks and their subsequent placement under the supervision of the Central Bank of Iraq, which was attributed, in part, to the inadequacy of the agency model in protecting stakeholders in shareholding institutions, as well as EM, pushed professional institutions to adopt the corporate governance model as a method to regulate the problem of accounting information asymmetry between the parties to the agency. We are using the Beneish M-score model and the financial analysis equations in the Beneish model for bank data for both the income statement and the financial position to do so. The sample includes 30 Iraqi banks listed on the Iraq Stock Exchange from 2014 to 2017, with the goal of inferring agency problems through EM practices. The results show that there are problems for the agency in the research sample banks throughout the research periods, and the percentages of those problems vary from one year to another. Apart from detecting agency problems, the art of financial ratios that have been used can be useful for auditors in conducting financial analyses, and thus they can be used as tools to detect fraud, given those agency problems resulting from profit manipulation are only aspects of fraud in the financial statements.

DETEKSI KECURANGAN LAPORAN KEUANGAN DI MASA PANDEMI COVID-19 DENGAN MODEL BENEISH M-SCORE DAN MODEL F-SCORE

The purpose of this study is to detect fraudulent financial statements committed by companies. This detection is carried out by 2 (two) methods, namely the Beneish M-Score method and the F-Score model. The Beneish M-Score model is a predictive model of financial statement fraud, the ratios contained in it have been proven to have the ability to predict financial statement fraud (Beneish, 1999). The F-Score is a measure used as a tool to detect material misstatements in financial statements (Pardosi, 2015). Data analysis of go-public companies in Indonesia listed in 2019 and 2020 was obtained from Osiris. The results of the study concluded that the average value of financial statement fraud decreased during the covid-19 pandemic, with an average decline of 74%. Paired t-test results are also shown in the sig value. (2-tailed) that the F-Score and M-Score calculations show a number greater than 0.05 which means that there is no significant difference in the F-Score and M-Score values ​​before and during the COVID-19 pandemic. It was concluded that the COVID-19 pandemic did not affect financial statement fraud in Indonesia.

Predicting Auditor’s Opinion on Financial Statements of Public Enterprises Based on Indicators of the Beneish M-score Model

Abstract Considering the burning problem of corruption and non-transparency of public enterprises in the Federation of Bosnia and Herzegovina (FBiH), the paper aims to investigate whether the Beneish M-score model can be used to predict inaccurate financial statements. Where, the cause of inaccurate financial statements are intentional or unintentional errors. On a sample of 200 financial statements of public enterprises and related audit reports issued by the Audit Office of the Institutions in FBiH, we made a link between the Beneish M score model with its partial indicators (DSRI, GMI, AQI, SGI, DEPI, SGAI, LVGI, TATA) and four types of opinions: positive, opinion with distraction, negative and refraining from giving opinions. The research was conducted using descriptive statistics and an artificial neural network with the “scaled conjugate gradient backpropagation (trainscg)” algorithm for pattern recognition and classification. The research results show that it is possible on the basis of 8 partial indicators (DSRI, GMI, AQI, SGI, DEPI, SGAI, LVGI, TATA) i.e. 24 balance sheet position for their calculation, predict the auditor’s opinion on the quality of financial statements of public companies with an accuracy ranging between 98 and 100% in repeated procedures. The results of the research have their practical usefulness and can serve to researchers, creditors, customers, suppliers and state auditors in planning resources and priorities for performing financial audits at public companies in the FBiH.

Determinan Deteksi Financial Statement Fraud

This study aims to empirically test the determinants of financial statement fraud detection with the Beneish M-Score, F-Score and Altman Z-Score models. The difference between this study and the previous study is that this study adds the F-Score model variable which is a financial statement fraud detection model developed using the scaled logistic probability technique. The population of this study is all banks listed on the Indonesia Stock Exchange. The samples in this study were perbankan that met the purposive sampling criteria. Based on the results of statistical tests obtained from the results of the study, the Beneish M-Score model has a significant effect on the financial statementt fraud variables, namely the Gross Margin Index (GMI) and the Asset Quality Index (AQI) variable while the Days Sales in Receivables Index (DSRI) variable, Leverage Index (LVGI), Total Accruals to Total Assets (TATA), and the Sales General and Administrative Expenses Index (SGAI) have no effect on the financial statement fraud variable. The F-Score variable states that only the Change in cash sales (Ch CS) variable has a significant effect on financial statement fraud while the change in receivable variable (Ch Rev), change in inventories (Ch Inv) and the change in earnings variable (Ch Ear) have a significant effect on the financial statement fraud variable. Meanwhile, the Altman Z-Score variable states that the Z-Score1 variable and the Z-Score3 variable have a significant effect on the financial statement fraud variable while the Z-Score2 variable and the Z-Score5 variable have no significant effect.

Earnings manipulation behavior in the banking industry of Bangladesh: the strategical implication of Beneish M-score model

PurposeThis study aims to determine the number of companies involved in earnings manipulation. Additionally, this study has empirically investigated the common manipulation items among the companies.Design/methodology/approachBangladesh's listed commercial banks are selected as a sample for this study, and financial data from 2009 to 2018 were collected. The likely and nonlikely manipulator Beneish model (1999) divides the sample into two groups. Based on the M-score of the model, the banks are put into two groups. To identify the most influential variables, an independent samplet-test was done with the help of Statistical Package for Social Sciences (SPSS).FindingsThe findings show that banks in Bangladesh have an unstable trend in making manipulated financial reports. Results of thet-test reveal that overstating revenues, increasing intangible assets, lessening cost and accruals are the most appealing items for preparing a fraudulent financial report. The findings of this research work will help the investors take the right decision having the idea of manipulation in the banking sector of Bangladesh.Originality/valueIn the presence of many irregularities in the banking sector Bangladesh, very few studies have been carried out in forensic accounting and fraudulent financial reporting practices. Much research has focused on earnings management techniques. This research specifically focuses on identifying earnings manipulation in financial statements for micro-level variables like accounting accruals, intangible assets, etc. This will help policy-makers and financial statement readers to be proactive while reading financial statements and taking any investment decision.

COVID-19 PANDEMIC AND FRAUDULENT ACTIONS IN THE FINANCIAL STATEMENTS: THE CASE OF HOTEL COMPANIES IN THE REPUBLIC OF SERBIA

The quality of information presented in the financial statements of companies may be impaired due to fraudulent activities. One of the frequently used instruments that indicates that fraud has been committed in the financial statements is the Beneish M-score model. The purpose of the research is to examine the exposure of hotel companies in the Republic of Serbia to the risk of fraud in financial statements, as well as to determine whether there has been a change in that risk due to the COVID-19 pandemic. The research was conducted on a sample of 100 randomly selected hotel companies, and their financial reports for 2019 and 2020 were observed. There was a high risk of fraud based on the recognition of costs of sales, management and administration, and borrowing in both observed years, as well as a high risk of fraud based on the recognition of income and gross margin index in 2020. Further, it was determined that in the year of the COVID-19 pandemic, there was an increase in the risk of fraud in the financial statements based on the gross margin index and recognition of selling, management and administration costs. Microenterprises are exposed to a higher risk of fraud based on the recognition of costs of sales, management and administration compared to medium-sized ones. Limited liability companies are more exposed to risk based on the recognition of sales revenue, accrual item and total risk (measured by the 8-variable model) compared to joint-stock companies. On the other hand, joint-stock companies are more exposed to the risk of fraud based on gross margin and general risk of fraud (measured by the 5-variable model) compared to limited liability companies.

Does Model Reflect on Reality? Exploring Beneish M Score on Selected Private Commercial Banks in Nepal

This research explores if possible fraudulent financial statement is present in private commercial banks in Nepal. This study examines the viability of Beneish M-score model in detecting probable earning manipulation considering the sample of 16 private commercial banks including the joint ventures. The published annual report (income statement and balance sheet) of the year 2018 and 2019 of respective banks are used as a secondary source of information. This research employs Beneish M-score equation and threshold value -2.22 as keys to analysis. The result shows even four banks are engaging in income manipulation, the Beneish model cannot identify the deception on the financial statement. Though the given model is suggested for manufacturing companies, the researcher has used it to explore the Banks—this is the limitation of this research. Further investigation of these tools combined with other fraud detection models is suggested to discover financial manipulation and relationship with the stock market return.

Fraudulent financial reporting: an application of fraud diamond to Toshiba’s accounting scandal

PurposeThe purpose of this paper is to examine Toshiba’s fraudulent financial reporting in relation to the fraud diamond (pressure, opportunity, rationalisation and capability).Design/methodology/approachA quantitative empirical research, analysing secondary data from Toshiba’s published annual reports before restatement, from 2008–2014 has been used. A simultaneous equations approach was used to test the hypothesis. Excel software was used to analyse secondary data and to carry out correlation analysis and descriptive statistics analysis.FindingsThis study uncovers evidence that pressure proxied by return on assets (ROA), the opportunity proxied by ineffective monitoring (BDOUT), rationalisation proxied by audit opinion (AO) and capability proxied by board member changes (BCHANGE) had moderate to strong relationship to financial statement fraud (FSF) (proxied by Beneish M-score model). However, ROA has a negative and significant effect on Toshiba’s FSF. BDOUT, AO and BCHANGE have positive and significant effect on Toshiba’s FSF. Furthermore, there is no multicollinearity problem within the four variables. Overall, this study has statistically proven that all dimensions of fraud diamond are required for the explanation of Toshiba’s accounting scandal.Originality/valueAlthough a few studies discuss the four dimensions (fraud diamond), none, to our surprise, exists which explain the circumstances led Toshiba’s high-level executives to commit fraud. This study is the first thorough investigation of Toshiba’s accounting scandal that uses all four dimensions to explain Toshiba’s FSF.

Bankruptcy Risk Prediction in Ensuring the Sustainable Operation of Agriculture Companies

In recent decades, predicting company bankruptcies and financial troubles has become a major concern for various stakeholders. Furthermore, because financially sustainable businesses are affected by numerous highly complex factors, both internal and external, the situation is even more complex. This paper applies Altman’s Z-score models; more precisely, the paper applies the initial Z-score model (a model for manufacturing companies), the Z′-score model (for companies operating in emerging markets), and the Z-score bankruptcy probability calculation. Therefore, this paper offers the results of the application of different Z-score models and the calculation of bankruptcy probability on a sample of agricultural companies listed on the Belgrade Stock Exchange in the period 2015–2019. In addition, different Z-score models are used for the same sample so that the difference between their results and application can be determined. In addition, the validity of the data published in the financial statements of the respective companies was confirmed using the Beneish M-score model with five and eight variables. The results obtained by applying Altman’s Z-score model (initial and adapted to emerging markets) indicate that a certain number of companies had impaired financial stability during the observed period, i.e., that they were in danger of bankruptcy. In addition, based on the results obtained using the Beneish M-score model, it was identified that a number of companies showed signals that indicate possible fraudulent financial reporting. Further, it was found that less than half of the observed companies reported on environmental protection in their annual reports, and they did so by providing a modest amount of information. The originality and value of the paper lies in suggesting that policymakers in the Serbian emerging markets should pay more attention to the operations of companies from the observed sector, as well as to their financial and non-financial reporting. Future research should focus on comparisons with agricultural companies from the same sector whose securities are listed on stock exchanges in the region.

Testing of Fraudulent Financial Statements With the Beneish M-Score Model for Manufacturing Companies Listed in the Indonesian Stock Exchange


 
 
 Fraudulent financial statements are disclosures of a company’s financial condition which are intentionally made inaccurate by eliminating values. This study aimed to examine the effect of using the Beneish M-Score model against fraud reports of manufacturing companies listed in the Indonesian Stock Exchange in 2016 -2018. Purposive sampling was used and the sample consisted of 69 companies. The results showed that the Days Sales in Receivables Index, Gross Margin Index and Total Accrual to Total Asset had a significant positive effect on financial statement fraud, while the Asset Quality Index, Sales Growth Index, Depreciation Index, Sales General and Administrative Expenses Index, and Leverage Index did not affect fraudulent financial statements.
 
 
 
 Keywords: fraud, Beneish, logistic regression
 
 
 
 
 

Application Of Beneish M-Score Model In Detecting Probable Earnings Manipulation In Malaysian Public Listed Companies

Earnings manipulation involves alteration, adjustment, exploitation, and even timing of transactions in financial statements with the intention to report a sound economic performance in a company. This act could jeopardize the company’s financial performance in the long run and also make its stakeholders to suffer significant losses. Therefore, a tool to detect or predict earnings manipulation would be helpful to the stakeholders, practitioners, regulators, academicians, and professionals in the accounting field. Besides, an early detection tool is needed to alarm the enforcement agencies to make further investigations or legal actions. Therefore, the aim of this study is to analyse the Beneish M-Score models and its eight accounting variables to detect the likelihood to engage in earnings manipulation in the case of Malaysian PLCs (Public Listed Companies). The financial data of 80 of PLCs from 2015 to 2017 were gathered. This study applied Beneish Model as a detection tool for earnings manipulation and anomalies of red flags and to classify the companies into two groups, which are manipulators and non-likely manipulators. The Independent T-tests were analysed to identify dominating ratios. The results of this study found that M-Score and its three indexes were significantly different for manipulators and non-likely manipulators, which are Sales Growth Index (SGI), Total Accruals to Total Assets (TATA) and Days' Sales Receivable index (DSRI). The percentage of manipulators had slightly decreased in 2016 and gradually increased in 2017. Hence, the inflation or overestimation of sales and revenues, as well as accruals, could signals earnings manipulation.

Primena Beneish M-Score i Altman Z-Score modela kod otkrivanja finansijskih prevara i neuspeha kompanije

Bankruptcy is a risk that any company can face, regardless of its size. The importance of predicting a company's bankruptcy for years before its development is enormous, and it is important for financial sustainability. Financial reporting is an important platform for making financial decisions of investors and creditors. In recent years, the frequency of false financial reporting by firms has increased and there are concerns about investors' confidence in capital market. Academics and industry experts adopt a variety of risk management techniques to detect fraudulent financial reporting. A case study was applied in this paper. Based on publicly available financial data (disclosed financial statements) of a domestic textile company for the period 2017-2020, whose shares are listed on the stock exchange, a survey was conducted based on the application of Altman's Z-Score model and Beneish M-Score model. Financial distress is an important criterion to monitor when assessing the likelihood of fraud reporting. When a company is operating poorly, there is a greater motivation to engage in fraudulent financial reporting. The findings show that the results differ according to the applied method in terms of identifying the possibility of bankruptcy and the possibility of fraud in the financial statements of the observed company. The results of the study can be important to investors, auditors, regulators, bankers, tax and other government bodies.

Detekcija prevara u finansijskom izveštavanju kod malih i srednjih entiteta iz oblasti prerađivačke industrije

The importance of forensic accounting has been growing in recent years, especially when it comes to small and medium enterprises (SMEs). These entities do not have sufficiently developed accounting functions, they do not invest enough in staff who are not consequently motivated to present certain items of financial statements in a precise manner and in accordance with accounting standards. This results in reporting errors. The other side of the coin are the manipulations that happen with the intention and goal of presenting better business than the real situation to banks and other stakeholders. In this research paper, Beneish's M-Score model with five variables (M5) was applied as a method of forensic accounting, in order to detect manipulations in SMEs from sector C-Manufacturing in Serbia. The sample includes 73 companies, and only for 3 of them the M (5) Score exceeded the reference value and indicated a high risk of manipulation. The situation is different when looking at model variables individually; however, the results of the Mann-Whitney test indicate that there is no statistically significant difference in the level of liquidity and profitability of a firm depending on whether an entity manipulated from the individual model variables point of view or not.

Could globally used Beneish M-score predict the manipulation of the accounting statements in the Slovak republic?

Research background: Globalization is characteristic by many companies which are doing their business worldwide in various tax policies, so they are able to use the possibilities of creative accounting for their own benefit. And although the term creative accounting is concerned mainly with multinational companies, it is not an unknown technique also for local companies. Purpose of the article: The PwC’s Global Economic Crime and Fraud Survey proved that economic crime is constantly evolving worldwide. At present, there is a huge number of frauds, which include corruption, misappropriation of assets, or fraudulent reporting. These papers are focused only on accounting fraud and creative accounting as the way to adjust accounting books and reports. Methods: The aim of the papers is to analyse the detection ability of the Beneish M-score model in the specific condition of the Slovak republic. These specific conditions consider tax minimization as the key factor for creative accounting implementation. The analysis was made with a Slovak company that was legally convicted of intentional manipulation of the accounting statements. Findings & Value added: The consideration of the specific condition in M-score for Slovak republic showed the best detection ability to reveal the frauds. As our study reveals, reduced M – score5 was unreliable in the condition of the Slovak republic and although Beneish consider 3 indicators as redundant it seems that in the condition of the Slovak republic it is important to carefully consider their implementation.