Financial Statement Fraud Risk Factors and Auditor Response Strategies

Abstract

This research introduces a novel, multi-dimensional framework for assessing financial statement fraud risk that moves beyond traditional checklists and binary indicators.
We propose that fraud risk exists on a dynamic continuum influenced by three interconnected domains: organizational narrative coherence, transactional ecosystem entropy,
and digital behavioral residue. Traditional audit approaches often treat fraud risk factors as static and isolated, whereas our methodology recognizes the complex, adaptive
nature of modern financial deception. We developed and tested a Continuous Anomaly
Resonance Detection (CARD) system that employs natural language processing to analyze management’s explanatory narratives alongside financial data, network theory to
map transactional ecosystems for entropy signals, and forensic analysis of digital audit trails for behavioral inconsistencies. Our longitudinal study of 47 publicly traded
companies over a three-year period revealed that narrative incoherence—discrepancies
between official explanations and quantitative patterns—predicted subsequent fraud
detection with 78