Exploring the Relationship Between Corporate Governance Practices and Fraud Detection Capabilities in Firms

Posted: Dec 16, 2007

• Damian Torres
• Liam Rivera
• Rowan Bishop

Abstract

This research investigates the complex relationship between corporate governance mechanisms and fraud detection capabilities within modern organizations, employing a novel computational framework that integrates natural language processing, network analysis, and machine learning techniques. Unlike traditional approaches that examine governance practices in isolation, our methodology develops a multidimensional governance index that captures both structural and behavioral dimensions of corporate oversight. We analyze governance documentation, board communication patterns, and internal control systems from a diverse sample of 350 publicly traded companies across multiple industries. Our findings reveal several counterintuitive relationships: while board independence shows a positive correlation with fraud detection, excessive independence beyond optimal thresholds may actually diminish detection effectiveness due to reduced institutional knowledge. Similarly, we identify a paradoxical relationship between audit committee expertise and fraud detection, where specialized financial expertise demonstrates diminishing returns while cross-disciplinary expertise in technology and behavioral sciences shows unexpectedly strong predictive power. The research introduces the concept of 'governance network resilience' as a critical mediator between governance structures and fraud outcomes, demonstrating that organizations with more decentralized communication patterns among governance actors detect fraudulent activities 47