Artificial Intelligence in Auditing: Enhancing Fraud Detection and Risk Assessment

Authors

  • Dr. Manoranjan Dash

    Professor, Department of Management, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India

  • Dr.A.S. Princy

    Assistant Professor, Master of Business Administration, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India

  • M. Sunil Kumar

    Assistant Professor, Department of Mechanical Engineering, Faculty of Engineering and Technology, Jain (Deemed-to-be University), Ramanagara District, Karnataka, India

  • J. Guntaj

    Centre of Research Impact and Outcome, Chitkara University, Rajpura, Punjab, India

  • Romil Jain

    Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, India

  • Dr. Aditya Yadav

    Assistant Professor, Business Management, Maharishi University of Information Technology, Uttar Pradesh, India

  • Dr. Sadaf Hashmi

    Associate Professor, ISME, ATLAS SkillTech University, Mumbai, India

How to Cite

Dash, D. M. ., Princy , D. ., Kumar , M. S. ., Guntaj , J. ., Jain , R. ., Yadav , D. A. ., & Hashmi , D. S. . (2025). Artificial Intelligence in Auditing: Enhancing Fraud Detection and Risk Assessment. International Journal of Accounting and Economics Studies, 12(SI-1), 71-75. https://doi.org/10.14419/18h1yf22

Received date: May 15, 2025

Accepted date: June 3, 2025

Published date: August 28, 2025

DOI:

https://doi.org/10.14419/18h1yf22

Keywords:

Fraud Detection; Risk Management; AI; Software Development; Management Techniques

Abstract

Artificial Intelligence (AI) transforms the audit landscape by enhancing fraud detection and risk assessment with unprecedented speed and accuracy. This study explores the application of AI in forensic accounting to identify financial irregularities using advanced machine learning models. AI-driven approaches such as supervised and unsupervised algorithms can efficiently detect anomalies in financial data, reducing false positives and improving audit reliability. Through statistical analysis and conceptual modeling, we highlight how AI contributes to a dynamic fraud prevention ecosystem. This research underscores the role of AI in reshaping audit methodologies and proposes a framework to integrate AI into risk management practices.

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How to Cite

Dash, D. M. ., Princy , D. ., Kumar , M. S. ., Guntaj , J. ., Jain , R. ., Yadav , D. A. ., & Hashmi , D. S. . (2025). Artificial Intelligence in Auditing: Enhancing Fraud Detection and Risk Assessment. International Journal of Accounting and Economics Studies, 12(SI-1), 71-75. https://doi.org/10.14419/18h1yf22

Received date: May 15, 2025

Accepted date: June 3, 2025

Published date: August 28, 2025