The use of Financial Technology (Fintech) has been proposed as a promising way to bridge the gender gap, both financially and socially. However, there is evidence that Fintech is far from achieving this objective, and that women's perceptions of Fintech usages are not clear. Therefore, the main objective of the this study is to segment women's perceptions toward Fintech tools and interpret these segments using machine learning methods. Two primary segments of women were produced, namely a “Fintech-friendly” group and a “Fintech-sceptical” group. The importance and reasonings behind the aforementioned segmentation are then examined. The most prominent factors affecting a woman being in the “Fintech-friendly” group are the perceived benefits of Fintech tools compared to the traditional ones, such as ease of usage, time-space convenience, and its advantageous nature. Finally, for Fintech stakeholders, implications for usability, ease, Fintech education, and tailored experiences may be advantageous approaches.

Segmenting female students' perceptions about Fintech using Explainable AI

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Journal Info

Category	Quartile
COMPUTER SCIENCE, INFORMATION SYSTEMS	2