If Humans Fail, Machines Take Action: Assessment of Accounting Error Detection Using Machine Learning

62 Pages Posted: 18 Nov 2021

See all articles by Marius Gros

Marius Gros

Niederrhein University of Applied Sciences; Goethe University Frankfurt - Department of Accounting and Auditing

Anika Hanke

Goethe University Frankfurt - Faculty of Economics and Business Administration

Date Written: September 28, 2021

Abstract

Various accounting scandals have proven that current enforcement systems may fail to detect erroneous reporting or identify fraudulent actions. Therefore, enforcement systems should continuously reassess and update the applied methods. Existing studies have shown that textual information and machine learning techniques can substantially support accounting error detection. We use proprietary data from enforcement investigations conducted by the German enforcement system to gain insights into the feasibility of such applications. Our classification models consider a wide range of classification and feature selection methods based on three indicator categories: financial, linguistic, and content. In contrast to many previous studies, we evaluate the classification performance using a realistic imbalanced holdout sample. We observe that content features are particularly important error indicators, and the combination of indicator categories has a significant impact on error detection. Additionally, feature selection plays an essential role in preventing indicator overload. Our findings have important implications for the development of predictive error-detection systems.

Keywords: enforcement, error detection, feature selection, SMOTE, topic modeling

JEL Classification: C53, C88, M40, M41, M48

Suggested Citation

Gros, Marius F. and Hanke, Anika, If Humans Fail, Machines Take Action: Assessment of Accounting Error Detection Using Machine Learning (September 28, 2021). Available at SSRN: https://ssrn.com/abstract=3932486 or http://dx.doi.org/10.2139/ssrn.3932486

Marius F. Gros (Contact Author)

Niederrhein University of Applied Sciences ( email )

Germany

Goethe University Frankfurt - Department of Accounting and Auditing ( email )

Theodor-W.-Adorno-Platz 1
60323 Frankfurt
Germany

Anika Hanke

Goethe University Frankfurt - Faculty of Economics and Business Administration ( email )

Mertonstrasse 17-25
Frankfurt am Main, D-60325
Germany

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