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Exploring Explainable AI in the Financial Sector: Perspectives of Banks and Supervisory Authorities

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Artificial Intelligence and Machine Learning (BNAIC/Benelearn 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1530))

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Abstract

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 financial 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) explainability requirements and explainability requirements of the broader AI system in relation to applicable laws and regulations.

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Author information

Authors and Affiliations

  1. HU University of Applied Sciences Utrecht, Utrecht, Netherlands

    Ouren Kuiper, Martin van den Berg & Stefan Leijnen

  2. De Nederlandsche Bank, Amsterdam, Netherlands

    Joost van der Burgt

Authors
  1. Ouren Kuiper
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  2. Martin van den Berg
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  3. Joost van der Burgt
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  4. Stefan Leijnen
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Corresponding author

Correspondence to Ouren Kuiper .

Editor information

Editors and Affiliations

  1. University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Luis A. Leiva

  2. Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg

    Cédric Pruski

  3. University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Réka Markovich

  4. University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Amro Najjar

  5. University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Christoph Schommer

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Kuiper, O., van den Berg, M., van der Burgt, J., Leijnen, S. (2022). Exploring Explainable AI in the Financial Sector: Perspectives of Banks and Supervisory Authorities. In: Leiva, L.A., Pruski, C., Markovich, R., Najjar, A., Schommer, C. (eds) Artificial Intelligence and Machine Learning. BNAIC/Benelearn 2021. Communications in Computer and Information Science, vol 1530. Springer, Cham. https://doi.org/10.1007/978-3-030-93842-0_6

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  • DOI: https://doi.org/10.1007/978-3-030-93842-0_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-93841-3

  • Online ISBN: 978-3-030-93842-0

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