Towards Fair AI: Mitigating Bias in Credit Decisions—A Systematic Literature Review
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Teresa Bono & Karen Croxson & Adam Giles, 2021. "Algorithmic fairness in credit scoring," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 585-617.
- Joseph L. Breeden & Eugenia Leonova, 2021. "Creating Unbiased Machine Learning Models by Design," JRFM, MDPI, vol. 14(11), pages 1-15, November.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Ana Belen Tulcanaza-Prieto & Alexandra Cortez-Ordoñez & Chang Won Lee, 2023. "Influence of Customer Perception Factors on AI-Enabled Customer Experience in the Ecuadorian Banking Environment," Sustainability, MDPI, vol. 15(16), pages 1-22, August.
- Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska, 2025. "Efficiency versus fairness in link recommendation algorithms," Documents de travail du Centre d'Economie de la Sorbonne 25001, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
- Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
More about this item
Keywords
algorithmic fairness; machine learning; credit scoring; algorithmic bias; artificial intelligence;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jjrfmx:v:18:y:2025:i:5:p:228-:d:1641302. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.