Journal Screenshot

International Journal of Academic Research in Accounting, Finance and Management Sciences

Open Access Journal

ISSN: 2225-8329

Strategic Business Use of AI in Improving Fraud Management, Internal Audit and Governance: Opportunities and Challenges

Emmanuel Lumbwe, Asif Mahbub Karim, Joseph Adaikalam

http://dx.doi.org/10.6007/IJARAFMS/v14-i4/23549

Open access

Artificial intelligence (AI) has arisen as a transformative power, reforming several facets of business operations. In the setting of fraud management, internal audit, and governance, AI presents abundant prospects for enhancing efficiency, accurateness, and proficiencies that were earlier unachievable. This paper aims to discover the strategic business use of AI in these serious domains, highlighting both the probable benefits and the challenges that organizations must overcome. The research commences by providing a synopsis of the budding landscape of AI and its prevalent use across different industries. It then probes into the detailed behaviors in which AI can be leveraged to improve fraud management, internal audit, and governance practices. For example, AI-powered irregularity detection algorithms can boost the identification of fraudulent actions, while AI-driven data analytics can restructure internal audit processes and offer profound insights into organizational risks and compliance issues. The paper also recognizes the difficulties that organizations face in the effective application of AI-driven solutions. These include the need for strong data governance frameworks, the incorporation of AI with prevailing systems and workflows, the upskilling of personnel to work along with intelligent technologies, and the ethical contemplations surrounding the use of AI in delicate business functions. Through an all-inclusive examination of case studies and industry best practices, the research suggests real-world guidance for establishments seeking to harness the influence of AI to reinforce their fraud management, internal audit, and governance competences. The findings highlight the standing of bring into line AI strategies with comprehensive business objectives, nurturing a philosophy of modernization and data-driven decision-making, and employing the technological, organizational, and ethical encounters that may rise. This paper backs to the increasing body of knowledge on the strategic applications of AI in business, providing valued perceptions for academics, practitioners, and policymakers involved in the transformative possibility of AI in the area of fraud management, internal audit, and governance.

Agrawal, S., & Nadakuditi, S. (2023). AI-based Strategies in Combating Ad Fraud in Digital Advertising: Implementations, and Expected Outcomes. International Journal of Information and Cybersecurity, 7(5), 1–19.
https://publications.dlpress.org/index.php/ijic/article/view/93
Alazzabi, W. Y. E., Mustafa, H., & Karage, A. I. (2020). Risk management, top management support, internal audit activities and fraud mitigation. Journal of Financial Crime, ahead-of-print(ahead-of-print). https://doi.org/10.1108/jfc-11-2019-0147
Alles, M., Rutgers Business School, & Gray, G. L. (2015). The pros and cons of using big data in auditing: a synthesis of the literature and a research agenda. http://jebcl.com/symposium/wp-content/uploads/2015/09/The-Pros-and-Cons-of-Using-Big-Data-in-Auditing-A-Synthesis-of-the-Literature-UWCISA-Revised.pdf
Cecil, A. (2021). A qualitative study on predictive models in accounting fraud detection. https://digitalcommons.liberty.edu/cgi/viewcontent.cgi?article=4302&context=doctoral
Chambers, R. (2024, August 12). Deepfake Technology Presents Genuine Risks That Internal Auditors Can’t Ignore - Audit Beacon. Audit Beacon.
https://www.richardchambers.com/deepfake-technology-presents-genuine-risks-that-internal-auditors-cant-ignore/
Couceiro, B., Pedrosa, I., & Marini, A. (2020). State of the Art of Artificial Intelligence in Internal Audit context. 2020 15th Iberian Conference on Information Systems and Technologies (CISTI). https://doi.org/10.23919/cisti49556.2020.9140863
DigitalOcean. (2024). Understanding AI Fraud Detection and Prevention Strategies. Digitalocean.com.
https://www.digitalocean.com/resources/articles/ai-fraud-detection
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., & Medaglia, R. (2021). Artificial Intelligence (AI): Multidisciplinary Perspectives on Emerging challenges, opportunities, and Agenda for research, Practice and Policy. International Journal of Information Management, 57(101994). https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Highradius (2024). How AI is helping in automating the Audit Process. (2024, January 29). https://www.highradius.com/resources/Blog/leveraging-ai-in-accounting-audit/ KPMG (2024). AI deepfakes increasing fraud risks for businesses, KPMG survey finds - KPMG Canada. (2024, March 11). KPMG. https://kpmg.com/ca/en/home/media/press-releases/2024/03/deepfakes-pose-major-fraud-risks-to-canadian-businesses.html
KPMG (n.d.). Transforming internal audits through the power of AI. Kpmg.com. https://kpmg.com/us/en/articles/2024/transforming-internal-audits-power.html
Levitt, K. (2023, December 13). How Is AI Used in Fraud Detection? NVIDIA Blog. https://blogs.nvidia.com/blog/ai-fraud-detection-rapids-triton-tensorrt-nemo/
Mark Anthony Camilleri. (2023). Artificial intelligence governance: Ethical considerations and implications for social responsibility. Expert Systems.
https://doi.org/10.1111/exsy.13406
McCafferty, J. (2024, February 29). Demystifying AI and Its Algorithms: What Internal Auditors Need to Know - Internal Audit 360. Internal Audit 360.
https://internalaudit360.com/demystifying-ai-and-its-algorithms-what-internal-auditors-need-to-know/
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The Ethics of algorithms: Mapping the Debate. Big Data & Society, 3(2), 1–21.
Mohammed, D., Asokan, K., & Kavitha Arunasalam. (2023). Anti-fraud measures and corporate policies to combat financial fraud in the financial institutes of Malaysia. E3S Web of Conferences, 389, 09028–09028.
https://doi.org/10.1051/e3sconf/202338909028
Ngai, E. W. T., Hu, Y., Wong, Y. H., Chen, Y., & Sun, X. (2011). The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature. Decision Support Systems, 50(3), 559–569.
https://doi.org/10.1016/j.dss.2010.08.006
Olubusola Odeyemi, Kehinde Feranmi Awonuga, Noluthando Zamanjomane Mhlongo, Ndubuisi Leonard Ndubuisi, Funmilola Olatundun Olatoye, & Andrew Ifesinachi Daraojimba. (2023). The role of AI in transforming auditing practices: A global perspective review. World Journal of Advanced Research and Reviews, 21(2), 359–370. https://doi.org/10.30574/wjarr.2024.21.2.0460
Oyinkansola, B. (2022). The impact of ai on internal auditing: transforming practices and ensuring compliance. Finance & Accounting Research Journal, 4(6), 350–370. https://doi.org/10.51594/farj.v4i6.1316
Papagiannidis, E., Enholm, I. M., Dremel, C., Mikalef, P., & Krogstie, J. (2022). Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes. Information Systems Frontiers. https://doi.org/10.1007/s10796-022-10251-y
Qatawneh, A. M. (2024). The role of artificial intelligence in auditing and fraud detection in accounting information systems: moderating role of natural language processing. International Journal of Organizational Analysis. https://doi.org/10.1108/ijoa-03-2024-4389
Raisch, S., & Krakowski, S. (2021). Artificial Intelligence and Management: the Automation–Augmentation Paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072
Samson, D., Black, S., & Ellis, A. (2022). Business Model Transformation. https://doi.org/10.4324/9781003255529
Sridhar, M., & Vidyashree. (2024). The role of Artificial intelligence in Auditing: current applications and future prospects Harshini srinivas (PES3UG21BC062) Under the guidance of External Guide Internal Guide. International Journal of Novel Research and Development, 9(5), 572. https://www.ijnrd.org/papers/IJNRDTH00148.pdf
Theiia (2024). The Role of Internal Audit in End-to-End Responsible AI Governance. Theiia.org. https://www.theiia.org/en/content/videos/webinar/2024/the-role-of-internal-audit-in-end-to-end-responsible-ai-governance/
West, D., & Allen, J. (2018, April 24). How Artificial Intelligence Is Transforming the World. Brookings; The Brookings Institution. https://www.brookings.edu/articles/how-artificial-intelligence-is-transforming-the-world/
Wirjo, A., Calizo, S., Niño Vasquez, G., & Andres, E. (2022). APEC Policy Support Unit Artificial Intelligence in Economic Policymaking. https://www.apec.org/docs/default-source/publications/2022/11/artificial-intelligence-in-economic-policymaking/222_psu_artificial-intelligence-in-economic-policymaking.pdf
Wolterskluwer (n.d.). Artificial intelligence in auditing: Enhancing the audit lifecycle. Www.wolterskluwer.com. https://www.wolterskluwer.com/en/expert-insights/artificial-intelligence-auditing-enhancing-audit-lifecycle

Lumbwe, E., Karim, A. M., & Adaikalam, J. (2024). Strategic Business Use of AI in Improving Fraud Management, Internal Audit and Governance: Opportunities and Challenges. International Journal of Academic Research in Accounting, Finance and Management Sciences, 14(4), 328–354.