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The Use of Artificial Intelligence in Tax Audit
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Mahmoud Nazarpour   , Seied hosein Naslmosavi * , Mir saeed Hoseini |
| azad university |
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Abstract: (2107 Views) |
Nowadays, knowledge is a valuable and strategic resource as well as an asset for evaluation and forecasting. Presenting these strategies in discovering corporate tax evasion has become a hot topic today and various solutions have been proposed. In the past, various approaches to identify tax evasion and the like have been presented, but these methods have not been very accurate and the overhead of calculations has also been high. Hence, in this study, a solution is proposed that is based on a combination of Bayesian network and SVM algorithm. In this research, the hybrid RAF set algorithm and hierarchical decision algorithm are used for pre-processing and selecting effective data. The proposed solution in Visual Studio environment using C # programming language and help from Veka library has been compared with popular methods such as ID3, Bayesian and SVM and it is found that this method has much higher accuracy than other methods. The case has been investigated and this indicates the robustness of the proposed method compared to the methods investigated.
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Article number: 9 |
| Keywords: Tax Audit, SVM Algorithm, Bayesian Network, Tax evasion, tax risk |
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Full-Text [PDF 773 kb]
(939 Downloads)
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Type of Study: Applicable |
Subject:
Auditing
Received: 2019/12/21 | Accepted: 2020/05/3 | Published: 2022/01/2
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