The Integration of Artificial Intelligence in Forensic Accounting: A Game-Changer

Authors

  • Ferdouse Ara Tuli Assistant Professor, Department of Business Administration, ASA University Bangladesh, Dhaka, Bangladesh
  • Upendar Rao Thaduri ACE Developer, iMINDS Technology Systems, Inc., Pittsburgh, PA 15243, USA

Keywords:

Forensic Accounting, Artificial Intelligence, Data Analytics, Fraud Detection, Financial Crimes, Ethical Considerations

Abstract

The introduction of AI into forensic accounting changes the investigative landscape. This article examines how machine learning, natural language processing, and predictive analytics have transformed forensic accounting. Forensic accountants use AI to detect and prevent financial crime faster and more accurately than before. Real-time monitoring, anomaly detection, and pattern recognition allow professionals to spot inconsistencies and patterns that may go unnoticed quickly. AI helps trace digital transactions and mitigate cyber threats in cybersecurity and digital forensics as it evolves. The benefits are great, but data privacy and ethical issues require cautious navigation. This article shows how AI integration in forensic accounting can simplify investigations, improve risk management, and change financial analysis. The paper examines future trends and the need for continual education, emphasizing the symbiotic relationship between AI and human expertise in forensic accounting integrity and efficacy.

Downloads

Download data is not yet available.

References

Adesina, K., Erin, O., Ajetunmobi, O., Ilogho, S., Asiriuwa, O. (2020). Does Forensic Audit Influence Fraud Control? Evidence From Nigerian Deposit Money Banks. Banks and Bank Systems, 15(2), 214-229. https://doi.org/10.21511/bbs.15(2).2020.19

Akinbowale, O. E., Klingelhöfer, H. E., Zerihun, M. F. (2020). An Innovative Approach in Combating Economic Crime Using Forensic Accounting Techniques. Journal of Financial Crime, 27(4), 1253-1271. https://doi.org/10.1108/JFC-04-2020-0053

Asadullah, A., Sadia, R., & Abdullah, A. (2022). How can Proactive Behavior be Encouraged in Hospitals of Bangladesh? A Three-Time Lags Study. Asian Business Review, 12(3), 57–66. https://doi.org/10.18034/abr.v12i3.655

Carnes, K. C., Gierlasinski, N. J. (2001). Forensic Accounting Skills: Will Supply Finally Catch Up to Demand?. Managerial Auditing Journal, 16(6), 378-382. https://doi.org/10.1108/02686900110395514

Chen, S., Ahmmed, S., Lal, K., & Deming, C. (2020). Django Web Development Framework: Powering the Modern Web. American Journal of Trade and Policy, 7(3), 99–106. https://doi.org/10.18034/ajtp.v7i3.675

Chukwu, N., Asaolu, T. O., Uwuigbe, O. R., Uwuigbe, U., Umukoro, O. E. (2019). The Impact of Basic Forensic Accounting Skills on Financial Reporting Credibility Among Listed Firms in Nigeria. IOP Conference Series. Earth and Environmental Science, 331(1). https://doi.org/10.1088/1755-1315/331/1/012041

Dekkati, S. (2020). Blender and Unreal Engine Character Design and Behavior Programming for 3D Games. ABC Journal of Advanced Research, 9(2), 115-126. https://doi.org/10.18034/abcjar.v9i2.704

Dekkati, S. (2021). Python Programming Language for Data-Driven Web Applications. International Journal of Reciprocal Symmetry and Theoretical Physics, 8, 1–10. https://upright.pub/index.php/ijrstp/article/view/90

Dekkati, S. (2022). Automotive Software Engineering: Real-World Necessity and Significance. Engineering International, 10(1), 33–44. https://doi.org/10.18034/ei.v10i1.674

Dekkati, S., & Thaduri, U. R. (2017). Innovative Method for the Prediction of Software Defects Based on Class Imbalance Datasets. Technology & Management Review, 2, 1–5. Retrieved from https://upright.pub/index.php/tmr/article/view/78

Dekkati, S., Gutlapalli, S. S., Thaduri, U. R., & Ballamudi, V. K. R. (2022). AI and Machine Learning for Remote Suspicious Action Detection and Recognition. ABC Journal of Advanced Research, 11(2), 97-102. https://doi.org/10.18034/abcjar.v11i2.694

Deming, C., Dekkati, S., & Desamsetti, H. (2018). Exploratory Data Analysis and Visualization for Business Analytics. Asian Journal of Applied Science and Engineering, 7(1), 93–100. https://doi.org/10.18034/ajase.v7i1.53

Desamsetti, H., & Dekkati, S. (2023). Impact of Digitization on Uplifting Business Expansion. Preprints. https://doi.org/10.20944/preprints202309.1691.v1

Fadilah, S., Maemunah, M., Nurrahmawati, N. Lim, T. N., Sundary, R. I. (2019). Forensic Accounting: Fraud Detection Skills for External Auditors. Polish Journal of Management Studies, 20(1), 168-180. https://doi.org/10.17512/pjms.2019.20.1.15

Fadziso, T., Thaduri, U. R., Dekkati, S., Ballamudi, V. K. R., & Desamsetti, H. (2023). Evolution of the Cyber Security Threat: An Overview of the Scale of Cyber Threat. Digitalization & Sustainability Review, 3(1), 1–12. https://doi.org/10.6084/m9.figshare.24189921.v1

Hosen, M. S., Ahmmed, S., & Dekkati, S. (2019). Mastering 3D Modeling in Blender: From Novice to Pro. ABC Research Alert, 7(3), 169–180. https://doi.org/10.18034/ra.v7i3.654

Koehler, S., Desamsetti, H., Ballamudi, V. K. R., & Dekkati, S. (2020). Real World Applications of Cloud Computing: Architecture, Reasons for Using, and Challenges. Asia Pacific Journal of Energy and Environment, 7(2), 93-102. https://doi.org/10.18034/apjee.v7i2.698

Popoola, O. M. J., Che-Ahmad, A. B., Samsudin, R. S. (2015). An Empirical Investigation of Fraud Risk Assessment and Knowledge Requirement on Fraud Related Problem Representation in Nigeria. Accounting Research Journal, 28(1), 78-97. https://doi.org/10.1108/ARJ-08-2014-0067

Rahman, S. S., & Dekkati, S. (2022). Revolutionizing Commerce: The Dynamics and Future of E-Commerce Web Applications. Asian Journal of Applied Science and Engineering, 11(1), 65–73. https://doi.org/10.18034/ajase.v11i1.58

Rasmussen, D. G., Leauanae, J. L. (2004). Expert Witness Qualifications and Selection. Journal of Financial Crime, 12(2), 165-171. https://doi.org/10.1108/13590790510624954

Sadia, R., Tuli, F. A., & Lal, K. (2023). Digitization History and its Impact on the Economy, Employment, and Society. Global Disclosure of Economics and Business, 12(1), 15-24. https://doi.org/10.18034/gdeb.v12i1.706

Skerrett, J., Neumann, C., Mateos-Garcia, I. (2011). A Bayesian Approach for Interpreting Shoemark Evidence in Forensic Casework: Accounting for Wear Features. Forensic Science International (Online), 210(1), 26-30. https://doi.org/10.1016/j.forsciint.2011.01.030

Tiwari, R. K., Debnath, J. (2017). Forensic Accounting: A Blend of Knowledge. Journal of Financial Regulation and Compliance, 25(1), 73-85. https://doi.org/10.1108/JFRC-05-2016-0043

Wong, S., Venkatraman, S. (2015). Financial Accounting Fraud Detection Using Business Intelligence. Asian Economic and Financial Review, 5(11), 1187-1207. https://doi.org/10.18488/journal.aefr/2015.5.11/102.11.1187.1207

Downloads

Published

2023-10-30

How to Cite

Tuli, F. A., & Thaduri, U. R. (2023). The Integration of Artificial Intelligence in Forensic Accounting: A Game-Changer. Asian Accounting and Auditing Advancement, 14(1), 12–20. Retrieved from https://4ajournal.com/article/view/80

Issue

Vol. 14 No. 1 (2023): January - December

Section

Articles

License

Copyright (c) 2023 Asian Accounting and Auditing Advancement

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.