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Financial Statement Manipulations in Global Corporations: An Audit-Based Analysiss Using the Beneish M-Score Model

Authors: Shaik Azeem Hussain, Dr. Kiran Kumar M;

Financial Statement Manipulations in Global Corporations: An Audit-Based Analysiss Using the Beneish M-Score Model

Abstract

This paper focuses on the probability of manipulation of financial statements in twenty large international companies, including ten Indian companies and ten non-Indian companies, in the future (2021- 2025) through the Beneish M-Score model. The sample size is 100 publicly traded firm-years based on annual reports prepared in Ind AS, IFRS and US GAAP financial reporting frameworks. All the eight Beneish variables are included to determine composite M-Scores which are compared to the standard threshold of -2.22.The results show that about 95 percent of the observations lie below the manipulation threshold, implying that financial reporting integrity of the sampled firms is high. Nevertheless, the individual cases of high M-Scores can be traced among a few companies, whose increase or decrease is mainly caused by changes in the Sales Growth Index and indicators based on accruals. The comparison of cross country shows no statistically significant difference in mean M-Scores between non-Indian and Indian corporations and a larger variability among non-Indian corporations.The findings emphasize the applicability of the Beneish M-Score as a beneficial analytical instrument to promptly identify possible earnings manipulation. The research has a practical implication to the auditors, the regulators and investors as it supports risk-based assessment and improves the quality of financial reporting evaluation in multinational corporate settings.

Keywords

Beneish M-Score; Earnings Management; Financial Statement Manipulation; Forensic Accounting; Multinational Corporations; Audit Risk; Accrual Analysis; Cross- Jurisdictional Reporting

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green