Integrating Artificial Intelligence in Financial Auditing: Enhancing Accuracy and Efficiency

• Author(s): Titilayo Silifat Shehu
• Paper ID: 1708448
• Page: 518-537
• Published Date: 30-06-2022
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 5 Issue 12 June-2022

Abstract

This paper examines the transformative impact of artificial intelligence on financial auditing practices, with particular focus on anomaly detection and fraud identification. As financial data volumes grow exponentially and transactions become increasingly complex, traditional sample-based auditing methods face significant limitations in providing comprehensive assurance. Through analysis of current applications and case studies, this research demonstrates how AI technologies—including machine learning algorithms, deep learning networks, natural language processing, and robotic process automation—are reshaping core audit functions from risk assessment to journal entry testing and revenue recognition. The integration of these technologies enables a shift from retrospective, sample-based verification toward comprehensive, real-time monitoring with predictive capabilities. The study identifies implementation challenges related to data quality, model explainability, skills gaps, and regulatory considerations, while providing practical solutions and frameworks for addressing these barriers. Key findings reveal significant improvements in audit efficiency, risk coverage, and anomaly detection across various organizational implementations. The research concludes that strategic AI integration, when coupled with appropriate human oversight and professional judgment, offers unprecedented opportunities to enhance audit quality while reducing fraud risk. As the auditing profession navigates this technological transformation, continued collaboration between practitioners, regulators, technologists, and educators will be essential to realize the full potential of AI-enhanced auditing.

Keywords

Artificial Intelligence; Machine Learning; Financial Auditing; Anomaly Detection; Continuous Auditing; Fraud Prevention

Citations

IRE Journals:
Titilayo Silifat Shehu "Integrating Artificial Intelligence in Financial Auditing: Enhancing Accuracy and Efficiency" Iconic Research And Engineering Journals Volume 5 Issue 12 2022 Page 518-537

IEEE:
Titilayo Silifat Shehu "Integrating Artificial Intelligence in Financial Auditing: Enhancing Accuracy and Efficiency" Iconic Research And Engineering Journals, 5(12)