Corporate Governance and Financial Fraud Detection

Maria Tragouda, Michalis Doumpos and Constantin Zopounidis

Chapter 8 in Governance and Financial Performance:Current Trends and Perspectives, 2023, pp 171-191 from World Scientific Publishing Co. Pte. Ltd.

Abstract: In this chapter, we approach fraud detection using the fraud diamond theory, which utilizes the concepts of motivation, opportunity, pressure, and a fraudster’s ability to perform fraudulent acts. The dataset used includes information of Greek companies obtained from the Athens Stock Exchange from 2014 to 2019. We employ a machine learning approach (ML) to develop a model for identifying fake financial reports. The results are quite satisfactory in terms of accuracy and open the possibility of providing a basis for the study of other variables that affect elements of corporate governance. The development of a financial statement fraud identification and risk assessment (FFS) model could act as an early warning system and mitigate losses for investors, auditors, and all other internal and external stakeholders.

Keywords: Corporate Governance System; Agency Theory; Return on Assets; Stock Return; Firm Performance; Responsible Management and ESG (search for similar items in EconPapers)
JEL-codes: G3 G34 M14 M41 (search for similar items in EconPapers)
Date: 2023
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