Evaluating the efficacy of modified Beneish and Dechow models for detecting earnings management in Polish companies

Abstract

Purpose: This article analyzes the role of several variants of the M-Score models and the F-Score model in the detection of earnings management in Poland. Previous research on earnings management concentrated only on the use of the original Beneish M-Score model.

Design/methodology/approach: The sample comprises 60 observations of nonfinancial Polish companies listed on the Warsaw Stock Exchange that received a monetary fine from the Polish Financial Supervision Authority (UKNF Board) for violation of International Financial Reporting Standards (IFRS) in the years 2010–2021. For each fraud observation, we selected the control observations based on industry (obtained from the SIC code), financial year and size of total assets.

Findings: The results indicate that the five-element M-Score model with a marginal value (−2.76) has the highest F-measure and the second-best accuracy in detecting earnings management than the F-Score model for the Polish sample. Moreover, the proprietary M-Score models usually had lower F-measure and accuracy than the original M-Score models, except for the model by Sylwestrzak (2022).

Research limitations/implications: Future research comparing the F-Score and M-Score models needs to include a larger sample of control companies due to the potential for choice-based sample bias.

Practical implications: The choice of an appropriate detection model and cut-off threshold may affect the conclusions regarding the analyzed sample.

Originality/value: The research provides empirical evidence of the appropriateness of modifying the M-Score model for country conditions and verifying the usefulness of the M-Score models modified by other authors.