The Impact of Forensic Audit Evidence on Court Decisions in Financial Crime Investigations

Posted: Jan 25, 2022

• Kendall Pierce
• Isla Ford
• Chase Harper

Abstract

The landscape of financial crime investigation has undergone profound transformation in recent decades, driven by technological advancement and increasing complexity in financial systems. Forensic audit evidence, once confined to traditional accounting records and paper trails, now encompasses sophisticated digital methodologies including blockchain analysis, artificial intelligence-driven pattern recognition, and complex network analysis of financial transactions. This evolution presents both opportunities and challenges for judicial systems tasked with adjudicating financial crimes. The critical intersection between forensic accounting evidence and judicial decision-making represents an understudied domain with significant implications for legal outcomes, evidentiary standards, and the administration of justice in financial crime cases. This research addresses a fundamental gap in understanding how different types of forensic audit evidence influence court decisions in financial crime investigations. While previous research has examined forensic accounting techniques or judicial decision-making in isolation, few studies have systematically analyzed the relationship between evolving audit methodologies and legal outcomes. The novelty of our approach lies in examining this relationship through both quantitative analysis of case outcomes and qualitative assessment of judicial reasoning patterns, providing a comprehensive understanding of how forensic evidence shapes legal decisions. Our research is guided by three primary questions: First, how do different categories of forensic audit evidence correlate with conviction rates and sentencing outcomes in financial crime cases? Second, what patterns emerge in judicial reasoning when evaluating technologically sophisticated versus traditional audit evidence? Third, how has the evolution of forensic audit methodologies