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Our data says that the document:
Borger, Melsom ; Christian Bakke, Vennerod ; Petter Eilif, de Lange ; Sjur, Westgaard. (2022) Explainable AI for Credit Assessment in Banks.
In: JRFM. RePEc:gam:jjrfmx:v:15:y:2022:i:12:p:556-:d:986356.
Full description at Econpapers
cites:
[CrossRef] Bibal, Adrien, Michael Lognoul, Alexandre De Streel, and Benoît Frénay. 2021. Legal requirements on explainability in machine learning. Artificial Intelligence and Law 29: 149–69. [CrossRef] Breiman, Leo. 1998. Arcing classifier (with discussion and a rejoinder by the author). The Annals of Statistics 26: 801–49. [CrossRef] Brown, Iain, and Christophe Mues. 2012. An experimental comparison of classification algorithms for imbalanced credit scoring data sets. Expert Systems with Applications 39: 3446–53. [CrossRef] Bücker, Michael, Gero Szepannek, Alicja Gosiewska, and Przemyslaw Biecek. 2021. Transparency, auditability, and explainability of artificial intelligencemodels in credit scoring. Journal of the Operational Research Society 73: 70–90. [CrossRef] Bussmann, Niklas, Paolo Giudici, Dimitri Marinelli, and Jochen Papenbrock. 2020a. Explainable AI in Fintech Risk Management.
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