Assessing the Impact of Audit Methodologies on Detecting Errors in Complex Financial Transactions
Posted: Sep 18, 2018
Abstract
The increasing complexity of financial transactions presents significant challenges for traditional audit methodologies. Complex financial instruments, structured transactions, and sophisticated corporate structures have created environments where conventional audit approaches may fail to detect subtle errors and intentional misstatements. This research addresses the critical need for enhanced audit methodologies capable of navigating this complexity while maintaining audit quality and efficiency. This study introduces a novel hybrid audit methodology that integrates traditional approaches with computational techniques from data science and network analysis. The methodology preserves the judgment-based elements of traditional auditing while enhancing detection capabilities through algorithmic analysis of transaction patterns and relationships. Our research examines three primary research questions: How do detection rates for complex financial transaction errors compare across traditional, computational, and hybrid audit methodologies? What types of errors are most effectively identified by each methodological approach? How does methodological complexity impact audit efficiency and cost-effectiveness in complex financial environments?
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