Credit Scores: Performance and Equity
Albanesi, Stefania, Vamossy, Domonkos F.
–arXiv.org Artificial Intelligence
Credit scores are critical for allocating consumer debt in the United States, yet little evidence is available on their performance. We benchmark a widely used credit score against a machine learning model of consumer default and find significant misclassification of borrowers, especially those with low scores. Our model improves predictive accuracy for young, low-income, and minority groups due to its superior performance with low quality data, resulting in a gain in standing for these populations. Our findings suggest that improving credit scoring performance could lead to more equitable access to credit.
arXiv.org Artificial Intelligence
Aug-30-2024
- Country:
- North America > United States
- District of Columbia > Washington (0.04)
- Minnesota (0.04)
- Missouri (0.04)
- North America > United States
- Genre:
- Research Report
- Experimental Study (0.93)
- New Finding (1.00)
- Research Report
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