How can data manipulation matter in predicting the failure risk? Evidence from Romanian companies
Recent fraud scandals have raised concerns about the reliability of financial data disclosed in financial statements. The main purpose of this article is to investigate how financial data manipulation affects company failure risk. The research sample comprises 63 non-financial Romanian companies lis...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Vilnius Gediminas Technical University
2025-02-01
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| Series: | Journal of Business Economics and Management |
| Subjects: | |
| Online Access: | https://jbem.vgtu.lt/index.php/JBEM/article/view/22373 |
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| Summary: | Recent fraud scandals have raised concerns about the reliability of financial data disclosed in financial statements. The main purpose of this article is to investigate how financial data manipulation affects company failure risk. The research sample comprises 63 non-financial Romanian companies listed on the Bucharest Stock Exchange between 2015 and 2020. Three types of statistical methods were used to determine and consolidate the results. The results partially support the strand in literature according to which there is a correlation between manipulated data and failure risk. More specifically, the findings indicate that there is no statistically significant correlation between the Beneish Model and the Altman Z-score. However, after a more in-depth investigation taking into account the specific elements that indicate the existence of customized data in financial data, it was discovered that, among the eight Beneish model component variables, days' sales in a receivable index, sales growth index, and total accruals to total assets have a significant impact on the measurement of bankruptcy risk. This study constitutes an important contribution to the body of knowledge because it focuses not only on the relationship between the risk of failure and financial statement manipulation, but it examines also the significance of financial manipulation indicators in predicting the likelihood of bankruptcy. Our findings are valuable to decision makers seeking a deeper understanding of the reality behind financial data presented in financial statements.
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| ISSN: | 1611-1699 2029-4433 |