Technology now makes it possible for tax practitioners to accurately anticipate the outcome of tax disputes. This article demonstrates how using machine-learning algorithms to study legal source data, such as past court decisions and revenue rulings, can provide novel and valuable insights into how tax disputes may be resolved.
The dispute we focus on in this inaugural installment of Blue J Predicts is Cross Refined Coal.1 The D.C. Circuit heard oral arguments April 12 in an appeal of the Tax Court’s decision, which found in favor of the taxpayer. The IRS appealed on the basis that the Tax Court incorrectly found the existence of a partnership for federal tax purposes.
Blue J predicts with 90 percent confidence that the appeal will be dismissed on the issue of whether a partnership exists. This article examines how a machine-learning model can generate this prediction based on the facts of the case, and it identifies the strengths and weaknesses of the parties’ positions using machine learning.
1Cross Refined Coal LLC v. Commissioner, No. 19502-17 (2019) (bench op.).
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