Comparative Analysis of Alternative Credit Scoring Models: Expanding Access and Identifying Limitations

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Alternative credit scoring models significantly improve credit access for underserved populations, expanding financial inclusion.
Upstart's AI-driven model increases borrower approvals by 44.28%, with substantial loans to low-income communities.
Fintech companies evaluated show impressive borrower demographics, with 63% first-time digital borrowers at Tala.
Despite success, issues like data privacy concerns and algorithmic fairness challenges limit the effectiveness of these models.

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Comparative analysis shows alternative credit scoring improves access for underserved borrowers, indicating equity challenges remain.

Ruhaan Munjuluri (2025) studied this question.

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