<![CDATA[This study provides a bibliometric analysis of ethical considerations in AI applications for fraud detection based on data from ScienceDirect spanning 2020 to 2024. The analysis identifies “artificial intelligence” as a core focus in the literature, alongside a marked increase in attention to ethical concerns, including data privacy, transparency, and accountability. Additionally, the study reveals progress in applying advanced technologies like blockchain, ChatGPT, and fintech within fraud detection frameworks, which increasingly demand ethical scrutiny. Key findings emphasize the necessity for comprehensive ethical frameworks to ensure transparency, accountability, and public trust in AI-driven fraud detection systems. Practical implications suggest that organizations should prioritize ethical dimensions within AI strategies, enhancing both trust and the effectiveness of detection mechanisms. By using bibliometric analysis, this study finds new trends and gaps in the ethical aspects of using AI to find fraud, which adds new information that hasn’t been fully explored in other studies.]]>
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