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2022 | OriginalPaper | Chapter

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

Authors : Ouren Kuiper, Martin van den Berg, Joost van der Burgt, Stefan Leijnen

Published in: Artificial Intelligence and Machine Learning

Publisher: Springer International Publishing

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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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previous chapter Object Detection with Semi-supervised Adversarial Domain Adaptation for Real-Time Edge Devices
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Metadata
Title
Exploring Explainable AI in the Financial Sector: Perspectives of Banks and Supervisory Authorities
Authors
Ouren Kuiper
Martin van den Berg
Joost van der Burgt
Stefan Leijnen
Copyright Year
2022
Book
Artificial Intelligence and Machine Learning

Print ISBN: 978-3-030-93841-3

Electronic ISBN: 978-3-030-93842-0

Copyright Year: 2022

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

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