Exploring Explainable AI in the Financial Sector

Authors Ouren Kuiper, Martin van den Berg, Joost van der Burgt, Stefan Leijnen
Published in Artificial Intelligence and Machine Learning
Publication date 2022
Research groups Artificial Intelligence
Type Lecture


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.

On this publication contributed

Language English
Published in Artificial Intelligence and Machine Learning
ISBN/ISSN URN:ISBN:978-3-030-93841-3
Key words Explainable AI, Artificial Intelligence, Financial Sector.
Digital Object Identifier 10.1007/978-3-030-93842-0_6

Ouren Kuiper