EVALUATING THE CORPORATE TAX PERFORMANCE AND ANALYZING THE TAX TRENDS THROUGH THE UTILIZATION OF DATA MINING ALGORITHMS

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SOHRABI BABAK; RAEESI VANANI IMAN; GHANOONI SHISHONE VAHIDEH

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Journal: FINANCIAL RESEARCH Year:2016 | Volume:17 | Issue:2 Page(s): 219-238

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Information Journal Paper

Title

EVALUATING THE CORPORATE TAX PERFORMANCE AND ANALYZING THE TAX TRENDS THROUGH THE UTILIZATION OF DATA MINING ALGORITHMS

Author(s)

SOHRABI BABAK | RAEESI VANANI IMAN | GHANOONI SHISHONE VAHIDEH | Issue Writer Certificate

Keywords

TAXATION ASSESSMENTQ2

CLUSTERINGQ1

PREDICTIONQ2

TREND ANALYSISQ2

DATA MININGQ2

Abstract

There is always a considerable difference between the corporate performance and the tax levy that is identified by the taxation authorities which has become a common practice. This fact has led to no fairness among taxpayers, a fact that influences the horizontal and vertical sides of equity. Horizontal equity is created when people feel the benefits of the tax gain that is proportional to the loss of benefits. People with more financial means should also pay more taxes that is equivalent to vertical equity. One reason for the difficulty of attaining the horizontal and vertical equities is to identify the taxpayers based on their previous taxation behavior and to deal with them effectively. The aim of this study is the design of a predictive system that evaluates the corporates taxation behavior based on their previous payments. The predicting system uses key performance variables that are identified during research and it will also help in the classification of companies based on their taxation behavior into three groups of high risk, medium risk and low risk. The system is specifically designed for the taxation authorities who are attempting to effectively assessing the risk of corporate taxes gaining. In this study, the taxation clusters of customers are identified and a decision tree is designed with 80% of accuracy by the utilization of CLUSTERING and classification algorithms and effective validation methods. The resulting models of applied algorithms investigate the taxation behavior of each customer and are capable of predicting the tax payment risk of taxpayers in the future with the addition of new corporates to the list.

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APA: Copy

SOHRABI, BABAK, RAEESI VANANI, IMAN, & GHANOONI SHISHONE, VAHIDEH. (2016). EVALUATING THE CORPORATE TAX PERFORMANCE AND ANALYZING THE TAX TRENDS THROUGH THE UTILIZATION OF DATA MINING ALGORITHMS. FINANCIAL RESEARCH, 17(2 ), 219-238. SID. https://sid.ir/paper/91167/en

Vancouver: Copy

SOHRABI BABAK, RAEESI VANANI IMAN, GHANOONI SHISHONE VAHIDEH. EVALUATING THE CORPORATE TAX PERFORMANCE AND ANALYZING THE TAX TRENDS THROUGH THE UTILIZATION OF DATA MINING ALGORITHMS. FINANCIAL RESEARCH[Internet]. 2016;17(2 ):219-238. Available from: https://sid.ir/paper/91167/en

IEEE: Copy

BABAK SOHRABI, IMAN RAEESI VANANI, and VAHIDEH GHANOONI SHISHONE, “EVALUATING THE CORPORATE TAX PERFORMANCE AND ANALYZING THE TAX TRENDS THROUGH THE UTILIZATION OF DATA MINING ALGORITHMS,” FINANCIAL RESEARCH, vol. 17, no. 2 , pp. 219–238, 2016, [Online]. Available: https://sid.ir/paper/91167/en

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