Transparency, auditability, and explainability of machine learning models in credit scoring
| Autor: | Gero Szepannek, Alicja Gosiewska, Przemyslaw Biecek, Michael Bücker |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Marketing
021103 operations research Computer science Strategy and Management education 0211 other engineering and technologies 02 engineering and technology Management Science and Operations Research Transparency (behavior) humanities Management Information Systems Risk analysis (engineering) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing ComputingMilieux_MISCELLANEOUS health care economics and organizations |
| Zdroj: | Journal of the Operational Research Society. 73:70-90 |
| ISSN: | 1476-9360 0160-5682 |
| DOI: | 10.1080/01605682.2021.1922098 |
| Popis: | A major requirement for credit scoring models is to provide a maximally accurate risk prediction. Additionally, regulators demand these models to be transparent and auditable. Thus, in credit scori... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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