Detecting Accounting Frauds in Publicly Traded U.S. Firms: A Machine Learning Approach

Abstract

This paper studies how machine learning techniques can facilitate the detection of accounting fraud in publicly traded US rms. Existing studies often mimic human experts and employ the nancial or nonnancial