Classifying Restatements: An Application of Machine Learning and Textual Analytics

Abstract

ABSTRACT Restatements of audited financial statements are used for evaluating reporting quality and audit quality, and for other evaluative purposes. We constructed a machine learning algorithm to classify restatements by management intent based on the language in restatement announcements. Our machine learning classification is as reliable as other commonly used automated methods such as those based on market reaction, restatement direction, and magnitude. Our method does not require a dictionary of words and is applicable when other automated methods are not, for example, when restatements are announced contemporaneously with financial results and when net income is not restated. For large samples, the use of such a classification algorithm is less tedious and less time-consuming, and more consistent, replicable, and scalable than manual classification. Data Availability: Data are available from public sources cited in the text. JEL Classifications: G38; M41; M42; M48.

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