Detecting the manipulation of earnings in the company: triangulation of methods

• Main Author: Svabova Lucia
• Format: Article
• Language: English
• Published: EDP Sciences 2021-01-01
• Series: SHS Web of Conferences
• Subjects: earnings management; earnings manipulation; discriminant model; propensity score model; beneish model
• Online Access: https://www.shs-conferences.org/articles/shsconf/pdf/2021/03/shsconf_glob20_02061.pdf

Research background: Earnings management is a current topic in the world of financial management. It can be considered as a global phenomenon of today’s modern approach to the reporting of accounting information and related accounting decisions of managers, which may affect the overall results of financial statements. Many companies use earnings management as a tool to maintain stable profit growth or prevent “red numbers” from appearing in financial statements that are not beneficial to the company. Purpose of the article: Understanding what earnings management represents and why it is performed is essential for users of a company’s financial statements. However, detecting manipulation in companies is not easy, because Earnings management is successful if it is invisible. Therefore, statistical models are usually used to detect these practices. The aim of this paper is to show that the use of several methods strengthens the results obtained and is more probably to reveal possible manipulation of earnings in companies. Methods: In this study, we used triangulation of methods to detect Earnings management in companies: one of the most frequently used model in this area, Beneish model, but also the model for Slovak companies M-score SVK, which was created under the inspiration of the Beneish model and finally, the model of the company’s propensity score of manipulation. Findings & Value added: The study provides a global view of the possibilities of applying these three models to detect manipulation in the company. The idea of triangulation of methods is based on the consideration that if all the methods detect possible manipulation, it is very likely that it actually happens in the company.