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Artificial Intelligence for detecting and preventing procurement fraud

Author

Listed:
  • Chiji Longinus Ezeji

    (School of Public Management Governance and Public Policy, College of Business and Economics, University of Johannesburg, South Africa)

Abstract

The utilization of powerful machine learning models in artificial intelligence offers novel prospects for the identification of fraudulent activities. Artificial Intelligence (AI) is a revolutionary technological tool that enhances the ability to detect and prevent fraud by improving efficiency and effectiveness. This research offers a thorough examination of the utilization of artificial intelligence technology in the realm of procurement fraud prevention and detection. Additionally, it highlights the obstacles that arise when employing machine learning techniques for the purpose of identifying and preventing fraudulent activities. A mixed methods approach was employed in this study, wherein data was collected through an unstructured interview and questionnaire. We conducted a comprehensive review of relevant scholarly articles and online resources. The findings indicate that fraudsters are progressively advancing in their skills, which poses a significant challenge in detecting fraudulent activities. The advent of AI in fraud detection has demonstrated its transformative impact. AI has achieved unparalleled precision and velocity in crime detection and prevention, surpassing the capabilities of any human. Artificial intelligence (AI) enhances the capacity for automation. Accessing unstructured data in the form of spreadsheets, digital documents, and email inboxes poses a significant issue for the procurement function. In order to achieve a successful procurement transformation, businesses should prioritize the creation of essential tools, guarantee acceptance through the establishment of a superior user experience, and integrate both novel and pre-existing technology. It is imperative to disseminate knowledge to the general public regarding the escalating sophistication of artificial intelligence (AI) in the realm of fraud detection and prevention. This includes elucidating the potential benefits of AI in identifying patterns of suspicious activities, assessing its efficacy in predicting potential threats or fraudulent activities prior to their manifestation, and exploring its utility in analyzing historical data pertaining to both familiar and unfamiliar forms of fraudulent behavior.

Suggested Citation

  • Chiji Longinus Ezeji, 2024. "Artificial Intelligence for detecting and preventing procurement fraud," International Journal of Business Ecosystem & Strategy (2687-2293), Bussecon International Academy, vol. 6(1), pages 63-73, January.
    • Handle: RePEc:adi:ijbess:v:6:y:2024:i:1:p:63-73
    DOI: 10.36096/ijbes.v6i1.477
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    References listed on IDEAS

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    1. Nerissa C. Brown & Richard M. Crowley & W. Brooke Elliott, 2020. "What Are You Saying? Using topic to Detect Financial Misreporting," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 58(1), pages 237-291, March.
    2. Dan Amiram & Zahn Bozanic & Ethan Rouen, 2015. "Financial statement errors: evidence from the distributional properties of financial statement numbers," Review of Accounting Studies, Springer, vol. 20(4), pages 1540-1593, December.
    3. Dan Amiram & Zahn Bozanic & Ethan Rouen, 2015. "Erratum to: Financial statement errors: evidence from the distributional properties of financial statement numbers," Review of Accounting Studies, Springer, vol. 20(4), pages 1594-1595, December.
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    Cited by:

    1. Sepideh Khalafi & Sasan Bagherpanah, 2026. "Intelligent Detection and Prevention of Financial Fraud Using Fingerprints: An AI and Machine Learning-Based Approach," International Journal of Business and Management, Canadian Center of Science and Education, vol. 21(2), pages 1-80, March.

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