Detecting of Fraudelent Financial Report: Perspective F Score Modeling - Himmah, Elok Faiqoh; Nugraha, Albi; Putri, Anike; Nadiyah Rahmani, Annisa (Universitas Trunojoyo Madura, 2025)
This study aims to detect fraud in financial statements using the F Score model and hexagon fraud determinants. These six proxies are used in the research model to analyse and detect possible fraudulent financial reporting in companies based on financial stability; capability, which is formed by changes in the board of directors; collusion, which is formed by the company's involvement in government projects; opportunity, which is formed by the nature of the industry; rationalisation, which is formed by changes in auditors; and ego, which is formed by the frequent appearance of the CEO's photo. The study approach is descriptive quantitative. The sampling technique is non-probability sampling using the purposive sampling method. This study involved a sample size of 30 companies, which collectively provided 150 annual reports. The data analysis method used is panel data regression analysis using Eviews software version 13. The results show that four of the six hexagonal fraud components significantly influence the potential for misleading financial reporting. Meanwhile, collusion, proxied by company involvement in government projects, and opportunity, proxied by industry nature, do not influence the likelihood of misleading financial reporting.