Posted: Dec 23, 2018
The detection of financial statement misstatements represents a critical function within the global financial ecosystem, serving as a cornerstone of market integrity and investor confidence. While extensive research has examined firm-level determinants of audit quality, a significant gap persists in understanding how individual audit partner characteristics influence misstatement detection capabilities. This study addresses this void by developing and testing a novel computational framework that quantifies the relationship between specific partner attributes and audit effectiveness. Traditional auditing literature has predominantly focused on structural factors such as audit firm size, industry specialization, and regulatory frameworks. However, the human element of auditing—the individual partner making critical judgments—remains underexplored through rigorous empirical methods. Our research pioneers an interdisciplinary approach that bridges computational linguistics, psychology, and accounting to examine how partners' cognitive styles, professional backgrounds, and behavioral patterns manifest in audit outcomes.
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Abstract Views: 977
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