Credit, Code, and Consequence: How AI Is Reshaping Risk Assessment and Financial Equity

Abstract

Artificial Intelligence (AI) has transformed numerous sectors, with financial services among the most significantly impacted. In particular, credit risk evaluation has witnessed a paradigm shift through the adoption of machine learning and advanced data analytics. These technologies promise improved accuracy, efficiency, and inclusivity in credit decision-making. However, the path is not without obstacles. Issues such as algorithmic bias, data privacy concerns, lack of transparency, and the uneven pace of regulatory oversight pose challenges to achieving financial justice. This article explores the multifaceted application of AI in credit risk evaluation, critically analyzing both its potential and pitfalls. Through an interdisciplinary lens, we examine how AI can democratize access to credit, mitigate systemic discrimination, and improve institutional performance—while also highlighting the governance, ethical, and infrastructural prerequisites necessary for its responsible implementation.