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

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
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article

AI-powered credit risk assessment and algorithmic fairness in digital lending: A comprehensive analysis of the United States digital finance landscape

Zenodo (CERN European Organization for Nuclear Research)
FinTech, Crowdfunding, Digital Finance
article

AI-powered credit risk assessment and algorithmic fairness in digital lending: A comprehensive analysis of the United States digital finance landscape

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Bowling Green State University (US)
Reduced inequalities
Openalex Percentile: Top 33%
FinTech, Crowdfunding, Digital Finance
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