The Relationship Between Professional Judgment Frameworks and Consistency in Audit Conclusions

Posted: Sep 17, 1999

• Isabella Hunt
• Bryce Ford
• Hugo Campbell

Abstract

The exercise of professional judgment represents a cornerstone of audit quality and reliability in financial reporting systems worldwide. Despite decades of research into auditor decision-making processes, significant variability persists in audit conclusions reached by different professionals examining identical evidence. This inconsistency poses substantial risks to financial statement users, regulatory bodies, and capital markets that depend on uniform application of auditing standards. The fundamental research question driving this investigation concerns how structured professional judgment frameworks influence the consistency of audit conclusions across diverse practitioner contexts. Contemporary audit environments have grown increasingly complex, characterized by sophisticated financial instruments, intricate information systems, and evolving fraud schemes that challenge traditional audit approaches. In response, audit firms and standard-setters have developed various judgment frameworks intended to guide professionals through complex decision processes. However, the empirical evidence regarding the effectiveness of these frameworks in promoting consistency remains fragmented and often contradictory. Some studies suggest that highly structured frameworks enhance reliability by reducing cognitive biases, while others indicate that excessive structure may undermine professional expertise and contextual adaptation. This research makes several distinctive contributions to the audit judgment literature. First, we introduce a novel theoretical integration of cognitive load theory with professional judgment frameworks, proposing that the relationship between structure and consistency follows an inverted U-shape rather than a linear progression. Second, we develop and validate a comprehensive measurement approach for assessing audit conclusion consistency that captures both quantitative alignment and qualitative reasoning patterns. Third, our experimental design incorporates realistic complex scenarios drawn from forensic accounting and information systems auditing contexts, providing ecological validity often