The current study has three contributions. First, the data mining
tool can be supported for filtering possible non-compliant VAT reports.
Instead of relying on manual methods and personal judgments
in selecting suspicious tax reports, tax authorities now
have a more scientific way of identifying possible evaders. Second,
although limited studies utilize mining association rules to detect
tax evasion, the mining outcome with association rules presented
in the current study provides a direction for future research within
tax field. Third, the current study has identified specific patterns
and significant features of illegal taxpayers. Thus, the tax auditors
can combine this method with their professional experience to detect
further cases of tax evasion.
The current study has three contributions. First, the data mining
tool can be supported for filtering possible non-compliant VAT reports.
Instead of relying on manual methods and personal judgments
in selecting suspicious tax reports, tax authorities now
have a more scientific way of identifying possible evaders. Second,
although limited studies utilize mining association rules to detect
tax evasion, the mining outcome with association rules presented
in the current study provides a direction for future research within
tax field. Third, the current study has identified specific patterns
and significant features of illegal taxpayers. Thus, the tax auditors
can combine this method with their professional experience to detect
further cases of tax evasion.
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