Explainable AI in the financial sector - Kiem

The project aims to map choices made in the implementation of explainable AI. To this end, we research literature and concrete use cases of financial service providers. The result is a practically useful checklist.

Objective

The project aims to investigate what is involved in the implementation of explainable AI. In addition, this project aims to apply for follow-up research to ultimately arrive at an approach and tools for explainable AI.

Results

A practical checklist with checkpoints that must be considered in the implementation of explainable AI linked to the AI lifecycle and a scientific paper with the results of this project. Besides a more extensive Whitepaper was written for Explainable AI in the Financial Sector. Finally, a paper was submitted to the HHAI2023 conference.

Duration

01 December 2021 - 30 November 2022

Approach

The research follows design science research. An artefact is developed from literature research and research into use cases in practice. The artefact in this case is a checklist that supports organizations in implementing explainable AI.

Relevance of the project

The results of this project will be used in the Master Human Centered AI.

This project is also linked to the research project Explainable AI in the Financial Sector.

HU researchers involved in the research

  • Stefan Leijnen
    • Professor
    • Research group: Artificial Intelligence
  • Danielle Sent
    • Senior lecturer
    • Research group: Artificial Intelligence
  • Jenia Kim
    • Researcher
    • Research group: Artificial Intelligence

Related research groups

Collaboration with knowledge partners

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