Auditor Change Prediction Using Data Mining and Audit Reports

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Author(s): Wikil Kwak (University of Nebraska at Omaha, USA), Xiaoyan Cheng (University of Nebraska at Omaha, USA), Yong Shi (University of Nebraska at Omaha, USA), Fangyao Liu (Southwest Minzu University, China)and Kevin Kwak (University of Nebraska at Omaha, USA)
Copyright: 2023
Pages: 13
Source title: Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch001

Keywords: Data Analysis and Statistics / Information Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

Data mining applications in accounting and finance areas are increasing; however, there are still not many classification or prediction studies in the auditing area. This article revisits the prediction of auditor changes upon the receipt of a qualified opinion using data mining approaches in U.S. companies. Overall, the prediction rates of several data mining approaches show reasonably well using financial and other data. The authors hope to see more applications of data mining tools in accounting or finance areas in the future. However, a qualified audit opinion does not add significant incremental information value in predicting auditor changes.

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Auditor Change Prediction Using Data Mining and Audit Reports

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