Do FinTech algorithms reduce gender inequality in banks loans? A quantitative study from the USA
The potential of FinTech algorithms to decrease gender bias in credit decisions is limited by the impartiality of the data used to train them. If the data is partial or biased, the algorithmic decision-making process may also be discriminatory, exacerbating existing inequalities. In this study, the...
Saved in:
| Main Authors: | Ziheng Song, Shafiq Ur Rehman, Chun PingNg, Yuan Zhou, Patick Washington, Ricardo Verschueren |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Journal of Applied Economics |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/15140326.2024.2324247 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Does FinTech credit scale stimulate financial institutions to increase the proportion of agricultural loans?
by: Akm Mohsin, et al.
Published: (2022-12-01) -
The moroccan banking system and FinTech deployment: an overview of the literature
by: Luca Federico Battanta, et al.
Published: (2025-03-01) -
Financial technology and credit risk management: the case of non-performing loans in Tanzanian banks
by: Omary Juma Ally, et al.
Published: (2025-12-01) -
Unlocking Entrepreneurship in the FinTech Era: The Role of Tax Compliance in Business Performance
by: Konstantinos S. Skandalis, et al.
Published: (2025-03-01) -
Modeling of FinTech market development (on the example of Ukraine)
by: Alina Bukhtiarova, et al.
Published: (2018-12-01)