Exploring the Impact of Artificial Intelligence Algorithms on Auditor Decision Support Systems
Posted: Sep 02, 2022
Abstract
This research investigates the transformative effects of artificial intelligence algorithms on auditor decision support systems, presenting a novel methodological framework that integrates quantum-inspired optimization with traditional auditing processes. Unlike previous studies that focus primarily on rule-based AI applications in auditing, our approach introduces a hybrid neural-symbolic architecture capable of processing both structured financial data and unstructured contextual information. We developed and tested three distinct AI configurations: a deep learning ensemble for anomaly detection, a natural language processing system for contract analysis, and a quantum-inspired optimization algorithm for sampling strategy determination. Our experimental design involved 45 professional auditors across three financial institutions who utilized these systems in simulated audit environments. The results demonstrate significant improvements in fraud detection accuracy (38.7
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