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Segmenting female students' perceptions about Fintech using Explainable AI.

Christos Adam1,2

  • 1Department of Economics, University of Crete, Rethymnon, Greece.

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|December 27, 2024
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Summary

Financial Technology (Fintech) adoption by women reveals two groups: "Fintech-friendly" and "Fintech-sceptical." Perceived benefits like convenience drive Fintech adoption, informing stakeholder strategies.

Keywords:
FintechSHAPXAIclassificationclusteringmachine learningspectral clusteringwomen

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Area of Science:

  • Social Sciences
  • Technology and Innovation
  • Gender Studies

Background:

  • Financial Technology (Fintech) is suggested to reduce the gender gap.
  • Evidence indicates Fintech has not yet achieved this objective.
  • Women's perceptions and adoption of Fintech tools remain unclear.

Purpose of the Study:

  • To segment women's perceptions of Fintech tools.
  • To interpret these segments using machine learning.
  • To identify factors influencing Fintech adoption among women.

Main Methods:

  • Machine learning techniques were employed for segmentation.
  • Analysis focused on identifying key differentiating factors between segments.
  • Qualitative interpretation of segment characteristics.

Main Results:

  • Two distinct segments emerged: 'Fintech-friendly' and 'Fintech-sceptical'.
  • Key drivers for the 'Fintech-friendly' group include perceived benefits: ease of use, time-space convenience, and overall advantageous nature.
  • Factors contributing to skepticism require further investigation.

Conclusions:

  • Women's perceptions of Fintech are not uniform, necessitating targeted approaches.
  • Highlighting convenience and ease of use can encourage Fintech adoption.
  • Stakeholders should consider tailored education and user experiences for diverse segments.