Presenting the Development of the Beneish Model with Emphasis on Economic Features using Neural Network, Vector Machine, and Random Forest
As the business process becomes more complex, financial statement distortion risk increases. In this regard, researchers have been looking for models to detect fraud in financial statements. Beneish (1997) predicted earning manipulation using financial ratios and accruals. Since economic pressure is...
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| Format: | Article |
| Language: | English |
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Ferdowsi University of Mashhad
2022-12-01
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| Series: | Iranian Journal of Accounting, Auditing & Finance |
| Subjects: | |
| Online Access: | https://ijaaf.um.ac.ir/article_42173_ab4e5be4eb5f62e7541a247aaa3a5dcd.pdf |
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| _version_ | 1846109636464214016 |
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| author | Kiumars Pourgadimi Jamal Bahri Sales Saeed Jabbarzadeh Kangarloie Akbar Zavar Rezaee |
| author_facet | Kiumars Pourgadimi Jamal Bahri Sales Saeed Jabbarzadeh Kangarloie Akbar Zavar Rezaee |
| author_sort | Kiumars Pourgadimi |
| collection | DOAJ |
| description | As the business process becomes more complex, financial statement distortion risk increases. In this regard, researchers have been looking for models to detect fraud in financial statements. Beneish (1997) predicted earning manipulation using financial ratios and accruals. Since economic pressure is presented as a manager’s external motivation to manipulate income, the Beneish model is developed based on economic variables, including Inflation Rate, GDP Growth, Exchange Rate, and Economic Growth Rate. The fitting of the random forest, vector machine, and neural network was used to fit the extended model. The results show that the accuracy of the random forest model is 99.96% which is more than the neural network and vector models, 96.1% and 93.62%, respectively. The final results show that the developed model is more accurate than the basic Beneish model. The results show that economic factors play a significant role in fraudulent financial reporting which should be considered when analyzing financial reporting. |
| format | Article |
| id | doaj-art-3a1172f5ee6748c1a2b84f0f20e694c3 |
| institution | Kabale University |
| issn | 2717-4131 2588-6142 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | Ferdowsi University of Mashhad |
| record_format | Article |
| series | Iranian Journal of Accounting, Auditing & Finance |
| spelling | doaj-art-3a1172f5ee6748c1a2b84f0f20e694c32024-12-25T06:52:55ZengFerdowsi University of MashhadIranian Journal of Accounting, Auditing & Finance2717-41312588-61422022-12-0164152810.22067/ijaaf.2022.4217342173Presenting the Development of the Beneish Model with Emphasis on Economic Features using Neural Network, Vector Machine, and Random ForestKiumars Pourgadimi0Jamal Bahri Sales1Saeed Jabbarzadeh Kangarloie2Akbar Zavar Rezaee3Department of Accounting, Urmia Branch, Islamic Azad University, Urmia, IranDepartment of Accounting, Urmia Branch, Islamic Azad University, Urmia, IranDepartment of Accounting, Urmia Branch, Islamic Azad University, Urmia, IranDepartment of accounting, Urmia University, Urmia, IranAs the business process becomes more complex, financial statement distortion risk increases. In this regard, researchers have been looking for models to detect fraud in financial statements. Beneish (1997) predicted earning manipulation using financial ratios and accruals. Since economic pressure is presented as a manager’s external motivation to manipulate income, the Beneish model is developed based on economic variables, including Inflation Rate, GDP Growth, Exchange Rate, and Economic Growth Rate. The fitting of the random forest, vector machine, and neural network was used to fit the extended model. The results show that the accuracy of the random forest model is 99.96% which is more than the neural network and vector models, 96.1% and 93.62%, respectively. The final results show that the developed model is more accurate than the basic Beneish model. The results show that economic factors play a significant role in fraudulent financial reporting which should be considered when analyzing financial reporting.https://ijaaf.um.ac.ir/article_42173_ab4e5be4eb5f62e7541a247aaa3a5dcd.pdfbenish modelaudit quality characteristicsneural networkvector machine and random forest |
| spellingShingle | Kiumars Pourgadimi Jamal Bahri Sales Saeed Jabbarzadeh Kangarloie Akbar Zavar Rezaee Presenting the Development of the Beneish Model with Emphasis on Economic Features using Neural Network, Vector Machine, and Random Forest Iranian Journal of Accounting, Auditing & Finance benish model audit quality characteristics neural network vector machine and random forest |
| title | Presenting the Development of the Beneish Model with Emphasis on Economic Features using Neural Network, Vector Machine, and Random Forest |
| title_full | Presenting the Development of the Beneish Model with Emphasis on Economic Features using Neural Network, Vector Machine, and Random Forest |
| title_fullStr | Presenting the Development of the Beneish Model with Emphasis on Economic Features using Neural Network, Vector Machine, and Random Forest |
| title_full_unstemmed | Presenting the Development of the Beneish Model with Emphasis on Economic Features using Neural Network, Vector Machine, and Random Forest |
| title_short | Presenting the Development of the Beneish Model with Emphasis on Economic Features using Neural Network, Vector Machine, and Random Forest |
| title_sort | presenting the development of the beneish model with emphasis on economic features using neural network vector machine and random forest |
| topic | benish model audit quality characteristics neural network vector machine and random forest |
| url | https://ijaaf.um.ac.ir/article_42173_ab4e5be4eb5f62e7541a247aaa3a5dcd.pdf |
| work_keys_str_mv | AT kiumarspourgadimi presentingthedevelopmentofthebeneishmodelwithemphasisoneconomicfeaturesusingneuralnetworkvectormachineandrandomforest AT jamalbahrisales presentingthedevelopmentofthebeneishmodelwithemphasisoneconomicfeaturesusingneuralnetworkvectormachineandrandomforest AT saeedjabbarzadehkangarloie presentingthedevelopmentofthebeneishmodelwithemphasisoneconomicfeaturesusingneuralnetworkvectormachineandrandomforest AT akbarzavarrezaee presentingthedevelopmentofthebeneishmodelwithemphasisoneconomicfeaturesusingneuralnetworkvectormachineandrandomforest |