AI-powered credit risk assessment and algorithmic fairness in digital lending: A comprehensive analysis of the United States digital finance landscape
The integration of artificial intelligence (AI) in credit risk assessment has fundamentally transformed the digital lending landscape in the United States, offering unprecedented opportunities for financial inclusion while simultaneously raising critical concerns about algorithmic fairness and discrimination. This comprehensive analysis examines the current state of AI-powered credit risk assessment systems, evaluating their effectiveness in improving lending decisions while addressing the persistent challenges of bias mitigation and regulatory compliance. Through examination of industry data, regulatory frameworks, and emerging technologies, this study provides insights into the evolution of fair lending practices in the digital age. The findings suggest that while AI technologies have significantly enhanced the efficiency and accuracy of credit assessments, substantial work remains to ensure equitable outcomes across diverse demographic groups. This research contributes to the growing body of literature on responsible AI in finance and provides recommendations for practitioners, policymakers, and researchers working toward more inclusive financial systems.
Institutions
- Bowling Green State University (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-06-30
- DOI
- https://doi.org/10.5281/zenodo.17383619
- Primary Topic
- FinTech, Crowdfunding, Digital Finance
- Type
- article
- Field-Weighted Citation Impact
- 0.00