How to select tax audit cases?: a literature review of research in tax avoidance

Muhammad Rheza Ramdhan
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Abstract

Currently, DGT is experiencing a shortage of tax auditors. As a result, DGT was unable to meet the tax collection goal. This issue, I think, may be addressed by developing a tax audit case selection model. This model employs the tax avoidance variable, which is assessed by the amount of adjustment in the modified tax assessment, as well as various factors classified as company characteristics, firm activities, and BOD characteristics. To develop this model, DGT should alter the format of tax returns in order to get the necessary information from taxpayers. Then, DGT must choose an analytical technique to evaluate the data. Because DGT has a large amount of data, I suggest utilizing the big data analytics approach, and I think that the regression model is outdated. So, I think that this approach will be useful in making DGT better in the future, since DGT may find it simpler to pick tax audit cases that will have a significant effect on tax collection. Unless DGT creates this paradigm, I think DGT will be unable to achieve its goal indefinitely. This article aims to describe certain tax avoidance measures and some tax avoidance factors that will be helpful in developing a tax audit case selection model. Furthermore, I'd want to show how DGT might evaluate such determinants in order to construct a suitable model.
如何选择税务审计案例?:对避税研究的文献综述
目前,DGT正面临着税务审计人员短缺的问题。因此,DGT无法完成税收征管目标。我认为,这个问题可以通过开发税务审计案例选择模型来解决。该模型采用了避税变量,通过修改后的税收评估中的调整量以及公司特征、公司活动和BOD特征等各种因素来评估避税变量。为了开发这个模型,DGT应该改变纳税申报表的格式,以便从纳税人那里获得必要的信息。然后,DGT必须选择一种分析技术来评估数据。因为DGT有大量的数据,我建议使用大数据分析方法,我认为回归模型已经过时了。因此,我认为这种方法将有助于DGT在未来变得更好,因为DGT可能会发现更容易选择对税收征收有重大影响的税务审计案例。除非DGT创造这种范式,否则我认为DGT将无法无限期地实现其目标。本文旨在描述某些避税措施和一些避税因素,这将有助于建立税务审计案例选择模型。此外,我想展示DGT如何评估这些决定因素,以便构建合适的模型。
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