Using data mining techniques to measure tax risk of value added taxes

Document Type : Original Article

Authors
Mohammad Masihi 1
Ahmad Yaghoobnejad 2
Amirreza Keyghobadi 3
Taghi Torabi 4
1 Ph.D student, financial management department, UAE branch , islamic azad universityt
2 Associate professor of accounting department, centeral branch of tehran, islamic azad university
3 Asistant professor of Department of Accounting , centeral branch of tehran, islamic azad university
4 associat profesoor of economics, science and research branch of tehran, islamic azad universit
Abstract
In this paper using data mining to studied taxpayers risk value added taxes. the importance of assessing the taxpayers risk of value added taxes in order to formulate an effective plan for choosing taxpayers for tax audit with the goal of increasing efficiency and effectiveness, in the country's value added taxes system. In this research taxpayers are catogorized into three, risk_free , low_ risk and risk _averse groups. To assess tax risk two techniques, data mining machin backup vector and logistic regression have been used. The research community consist of large legal entities in Tehran.that wich have been subject to tax audit in value added taxes system in 2012 to 2015. In this research, variables are include corporate governance mechanisms, special corporate features, the nature of the activity of the pioneers of the control system and tax ratios wich are used to train and use the model. The research's results show two techniques LSVM ,Logistic, have a reliability of 70percent and a kind of integration into the results of these two techniques has been achieved nearly 83 percent of reliability has a higher potential.
Keywords
data mining techniques
tax risk
value added taxes
tax audit
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