Exploring Explainable AI in the Financial Sector: Perspectives of Banks
  and Supervisory Authorities
  Explainable artificial intelligence (xAI) is seen as a solution to making AI
systems less of a black box. It is essential to ensure transparency, fairness,
and accountability, which are especially paramount in the financial sector. The
aim of this study was a preliminary investigation of the perspectives of
supervisory authorities and regulated entities regarding the application of xAI
in the fi-nancial sector. Three use cases (consumer credit, credit risk, and
anti-money laundering) were examined using semi-structured interviews at three
banks and two supervisory authorities in the Netherlands. We found that for the
investigated use cases a disparity exists between supervisory authorities and
banks regarding the desired scope of explainability of AI systems. We argue
that the financial sector could benefit from clear differentiation between
technical AI (model) ex-plainability requirements and explainability
requirements of the broader AI system in relation to applicable laws and
regulations.
