Detecting of Financial Statements Fraud Using Beneish M-Score Model and F Score Model

Meiryani, Meiryani; nolastname, Feronika; Sun, Yen; Fernando, Erick; Riantono, Ignatius Edward

doi:10.1145/3483794.3483801

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…Anning and Adusei (2020) use the probit regression and find that liquidity, leverage, profitability, change in auditor, and overall condition (Z-score) are incentives that predict the manipulation likelihood. Septiani et al (2020) note that in categorising the banks as manipulators or nonmanipulators, DSRI, GMI, AQI, DPI, and TATA ratios prove significant. Koowattanatianchai (2018) shows that only the accruals to assets ratio significantly and positively affect FSF manipulation index in Thailand.…”

Section: Discussionmentioning

confidence: 94%

“…Subjecting financial reports to forensic and statistical assessment help to detect and reduce associated risks to earnings manipulations. With recent evidence of prevalence of FSF in most global banks (Septiani et al, 2020), this study aims to examine reports of banks and other financial institutions in Nigeria, in order to detect the existence of manipulations as well as to identify the indicators that well predict the likelihood of manipulations. We apply the Beneish method and compute the different financial index use to dichotomise the firms into groups of likely manipulator and unlikely manipulators.…”

Section: Discussionmentioning

confidence: 99%

“…Beneish (1999) specifies probit model to estimate the probability that FSF equals 1. Some studies include price index, capital formation and/or Gross Domestic Product (Anning & Adusei, 2020;Koowattanatianchai, 2018), while some include others financial characteristics such as capital to sales ratio, liquidity, overall financial conditions and/or networking capital to sales (Septiani et al, 2020;Repousis, 2016;Kara et al 2015) specific to countries, industry and periods under investigation. The probit model to estimate the influence of financial ratios on the probability of FSF based on 8-and 5-variable models are respectively, equations ( 7) and (8).…”

Section: Modelsmentioning

confidence: 99%

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Financial Statements Fraud of Banks and other Financial Institutions in Nigeria

Gbadebo,

Akande,

Adekunle

2023

J. Professional Business Review

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Purpose: There is evidence that managers engage in opportunistic practice to manipulate reported performance to attract unsuspecting investors. This paper seeks to detect the likelihood of manipulations on the financial reports of financial service firms (banks and other financial institutions) as well as to identify the financial indicators that are the likely predictors of the probability of manipulations in Nigeria. Theoretical framework: The M-score models, from Beneish (1999), are employed as theoretical basis for the paper. The model use financial ratios computed using accounting data to confirm the probability that firms’ reported earnings are manipulated. Design/Methodology/Approach: The study uses data from the Nigerian Exchange Group, from 2010 to 2019 to compute M8/M5-scores and classify firms into likely manipulators and unlikely manipulators. In addition, a probit regression model was applied to establish financial ratios that significantly predict the likelihood of FSF amongst the financial firms. Findings: The results based on M8 (M5)-score indicate that 26.67% (23.33%) of firms likely manipulate financial books and exhibit the possibility of FSF. In addition, only sales in receivable, sales growth, depreciation expenses, leverage and accruals to assets ratios are found to be (positive) significant predictors of the probability of manipulations. Research, Practical & Social implications: The implication of the outcome is that subjecting financial statements to empirical and statistical scrutiny should not be ignored because it would detect and reduce associated risks to manipulations. Therefore, more regulatory interventions and empirical auditing of reports are needed to ensure their readability and reliability to the investors. Originality/Value: The study offers a novel and first evidence, based on Beneish M-score, to scrutinise reports of financial firms in Nigeria. The evidence ensures quality reporting of the financial statements in order to credibility as well as protect the integrity of the capital markets.

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Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 99%

Section: Modelsmentioning

confidence: 99%

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Financial Statements Fraud of Banks and other Financial Institutions in Nigeria

Gbadebo,

Akande,

Adekunle

2023

J. Professional Business Review

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Analysis on The Effectiveness of Augmented Artificial Intelligence Implementation in Preventing Fraudulent Financial Statement by Utilizing Beneish M-Score Model

Deniswara

Jonathan

Mulyawan

et al. 2022

Proceedings of the 2022 6th International Conference on E-Business and Internet

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Analysis of Measurement of Financial Difficulties and Financial Report Fraud (A Case Study at PT Asabri (Persero) 2010-2018)

Kusuma,

Rahmawati

2023

AKUMULASI

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This study aims to examine the financial health condition and whether there is an indication of fraudulent financial statements or not at PT ASABRI (Social Insurance for the Armed Forces of the Republic) in 2010-2018 by using the Altman Z-Score, Springate S-Score, Grover G-Score, Beneish M-Score, and Dechow F-Score methods. PT ASABRI became the object of the study due to the result of an audit conducted by the BPK (The Audit Board of the Republic of Indonesia) in 2021 that found fraud in financial management and investment funds at PT ASABRI. To measure financial distress, the researchers used the Altman, Springate, and Grover models. While to examine financial statement fraud, the researchers used the Beneish and Dechow models. The results revealed that each model showed varied results. In the financial distress model, the Altman Z-Score could show financial distress 4 times while the Springate S-Score showed financial distress 5 times in 9 years of observation. Moreover, the other models showed different results. The Grover G-Score model did not indicate any financial distress at PT ASABRI. While in the fraud model, the Beneish M-Score could detect indications of fraudulent statements at PT ASABRI 5 times in 8 years of observation. Different conditions occurred in the Dechow F-Score model that did not show fraudulent financial statements at PT ASABRI in 9 years of observation, from 2010 to 2018.

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Detecting of Financial Statements Fraud Using Beneish M-Score Model and F Score Model

Cited by 3 publications

References 6 publications

Financial Statements Fraud of Banks and other Financial Institutions in Nigeria

Financial Statements Fraud of Banks and other Financial Institutions in Nigeria

Analysis on The Effectiveness of Augmented Artificial Intelligence Implementation in Preventing Fraudulent Financial Statement by Utilizing Beneish M-Score Model

Analysis of Measurement of Financial Difficulties and Financial Report Fraud (A Case Study at PT Asabri (Persero) 2010-2018)

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