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The financial sector has undergone a significant transformation with the advent of financial technology (FinTech), which has put pressure on the business models of incumbents and has raised several concerns, including some related to instances of misbehavior. This article examines the existing body of literature on misconduct in the FinTech industry, encompassing a range of unethical behaviors, the underlying causes that contribute to such activities, and viable strategies to alleviate associated concerns. We employ a bibliometric and scientometric analysis, as well as topic modeling, a machine learning approach applied to natural language. Through a comprehensive examination of academic output, we highlight noteworthy patterns and promising areas of study. We also discuss the possible advantages and disadvantages linked to the integration of developing technologies such as artificial intelligence and machine learning in the realm of fraud prevention and detection.
Brogi et al. (2024) studied this question.