Institutionalizing explainability: On credit scoring, AI, and consumer agency

Kevin Bauer, Andrej Gill, Katja Langenbucher and Lucia Franke

No 116, SAFE White Paper Series from Leibniz Institute for Financial Research SAFE

Abstract: The paper starts from a situation of information asymmetry on credit markets and zooms in on AIenhanced credit scoring as an institutional response. It assumes the potential for expanding access to credit as well as the risk of discriminatory treatment of historically disadvantaged communities. Against this background, the paper explores legal requirements of "explainability", using two recent European Court of Justice decisions as illustrations. The paper gives an overview of XAI methods along with their socio-technical and legal limits. It contributes to the discussion by suggesting to treat explanations as a public good and designing an intermediary institution which would act as a go-between connecting consumer data subjects and scoring companies.

Keywords: AI-enhanced Credit Scoring; Explainability (XAI) and Law (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:safewh:334497

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