Ai and Fraud Prevention: Bibliometric Analysis and Keyword Mapping in the Context of Sustainability
| DOWNLOAD | DOI: 10.62897/COS2024.2-1.145 |
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Author: Nikolett Gyurián Nagy, Norbert Gyurián Széchenyi István University, Kautz Gyula Faculty of Economics, Department of Leadership and Marketing, Egyetem tér 1, 9026 Győr, Hungary J. Selye University, Faculty of Economics and Informatics, Bratislavská cesta 3322, 945 01 Komárno, Slovakia |
Abstract: The exponential growth of the digital economy is creating new opportunities and challenges for corporate security, particularly in the area of fraud. Not only can fraud cause significant finan-cial losses, but it can also have a negative impact on consumer confidence and corporate image, making effective protection key to corporate sustainability. Artificial intelligence (AI) systems, particularly Machine Learning (ML) technologies, offer a promising solution to mitigate offline and online fraud, enabling companies to anticipate and mitigate such risks. The paper builds on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) model to provide an overview of the use of AI technologies in the mitigation of fraud. The study aims to provide a comprehensive picture of how AI can reduce the success rate of fraud. The study also highlights how AI can help to promote corporate sustainability. In the literature review, studies from the selected scientific database were analysed, using inclusion and exclusion criteria to select those that provide relevant information on the role of AI technologies in identifying and addressing offline or online fraud. The results demonstrate that machine learning algorithms are particularly effective in detecting fraudulent activities by recognising patterns in large da-tasets. Furthermore, the study identified key trends and clusters in the scientific literature that show the growing role of AI and machine learning in fraud prevention, with a notable focus on the financial sector. Despite the benefits, challenges such as ethical concerns, misuse of AI, and the need for transparency in AI decision-making remain crucial. These findings highlight the necessity for companies to adopt AI strategically, balancing its potential and associated risks for a secure, sustainable digital economy.
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