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Developing a Framework for Fraud Risk and Financial Crimes Platforms in Companies Based on Managerial Cognitive Styles Meshkin, Masoud; Ranjbar, Mohammad Hossein; Shahdadi, Khosro Moradi
Jurnal Cita Hukum Vol. 13 No. 2 (2025): Summer Edition
Publisher : Fakultas Syariah dan Hukum, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jch.v13i2.46342

Abstract

There has been a rise in financial misconduct and white-collar crimes in today's competitive economic landscape. The notable surge in observed accounting fraud cases has drawn significant attention from investors, academic researchers, the media, the public, and financial regulators. This study aims to develop a model to mitigate fraud risk in companies, grounded in managers' cognitive styles. A qualitative grounded theory approach was employed to construct this model, and the categorized indicators were validated using both a confirmatory factor analysis model and the Q-model approach. In this study, insights from 10 accounting and auditing professionals were used to identify and validate indicators aligned with the foundational model. Based on identified concepts related to fraud risk platforms, the findings led to the formulation and validation of a paradigm encompassing 22 primary categories. These categories include Supervisory, Economic, Political, and Social Factors, Managerial Pressure, Organizational Determinants, Management Cognitive Style, Governance Factors, Corporate Structural Variables, Managerial Motivational Drivers, Industry-Specific Factors, Legislative and Regulatory Framework, Employee-Related Determinants, Individual-level Determinants, Cultural Influences, Managerial Incompetence, Financial Literacy of Executives, Ethical Considerations and Organizational Commitment, Organizational Consequences, Ethical Consequences, Effectiveness Strategies, and Organizational Efficiency Strategies. These categories were incorporated into the paradigm framework as dimensions of causal conditions, contextual factors, intervening factors, strategies, and outcomes. The categorization of indicators in this proposed model was validated through confirmatory factor analysis with Smart PLS, further reinforcing the findings.