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Title
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Shapley value for tax audit data valuation
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Author
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Abstract
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| Tax authorities have access to unprecedented levels of information on taxpayers. However, these vast amounts of data lead to new challenges, with tax authorities running the risk of being overwhelmed by the enormous amount of incoming data. We present a valuation technique to quantify the value of features for tax audit prediction. Our approach, rooted in the game-theoretical Shapley value, effectively assigns importance to features derived from various Directives on Administrative Cooperation within the European Union and the OECD's automatic exchange of information. We show that our results can be used for global explanations of the predictive model, feature selection and determining which data should be acquired or cleaned with priority, similar to active feature acquisition. Our results can assist tax authorities in managing the large amounts of data they receive under the different disclosure regulations. |
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Language
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English
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Publication
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Antwerp
:
University of Antwerp
,
2023
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Volume/pages
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24 p.
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Full text (open access)
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