Fair or Flawed? Assessing AI’s Impact on Credit Decisions |
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© 2024 by IJCTT Journal | ||
Volume-72 Issue-12 |
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Year of Publication : 2024 | ||
Authors : Vikas Agarwal | ||
DOI : 10.14445/22312803/IJCTT-V72I12P115 |
How to Cite?
Vikas Agarwal, "Fair or Flawed? Assessing AI’s Impact on Credit Decisions," International Journal of Computer Trends and Technology, vol. 72, no. 12, pp. 128-132, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I12P115
Abstract
The adoption of AI in financial decision-making, especially credit scoring, has sparked concerns about fairness and bias in outcomes. This study examines how biases in AI models affect protected groups, exploring fairness metrics and mitigation techniques to address these challenges. Using industry datasets, it highlights the trade-off between accuracy and equity, showcasing ways to design fairness-aware systems. The findings emphasize transparency, continuous monitoring, and ethical practices as critical for responsible AI use in banking. By addressing bias, financial institutions can ensure inclusive and unbiased credit decision processes, balancing performance with equity in the rapidly evolving landscape of AI-driven finance.
Keywords
Credit score, Fairness, Bias, AI, Machine learning.
Reference
[1] Magali Gruet, ‘That’s Just Common Sense’. USC Researchers Find Bias in up to 38.6% of ‘Facts’ used by AI, USC Viterbi School of Engineering, 2022. [Online]. Available: https://viterbischool.usc.edu/news/2022/05/thats-just-common-sense-usc-researchers-find-bias-in up-to-38-6-of-facts-used-by-ai/
[2] Wilhelmina Afua Addy et al., “AI in Credit Scoring: A Comprehensive Review of Models and Predictive Analytics,” Global Journal of Engineering and Technology Advances, vol. 18, no. 2, pp. 11-129, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Pal Dru Koi, How AI is Revolutionizing Credit Scoring: A Glimpse into the Future of Finance, Medium, 2023. [Online]. Available: https://medium.com/technologyone/how-ai-is-revolutionizing-credit-scoring-a-glimpse-into-the-future-of-finance-5188b60597d6
[4] Role of AI in Credit Scoring, Niyogin, 2024. [Online]. Available: https://www.niyogin.com/blogs/role-of-ai-in-credit-scoring
[5] Faisal Kamiran, and Toon Calders, “Data Preprocessing Techniques for Classification without Discrimination,” Knowledge and Information Systems, vol. 33, pp. 1-33, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Alessandro Castelnovo, “A Clarification of the Nuances in the Fairness Metric Landscape,” Scientific Reports, vol. 12, pp. 1-21, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Rachel K.E. Bellamy, AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias, arxiv, pp. 1-20, 2018.
[CrossRef] [Google Scholar] [Publisher Link]