The Ethical and Regulatory Challenges of AI-Driven Financial Decision-Making in Global Markets

Abstract

The integration of artificial intelligence (AI) into financial decision-making has fundamentally transformed global markets, introducing unprecedented efficiency alongside profound ethical and regulatory challenges. This paper presents a narrative review of the ethical and regulatory challenges arising from AI-driven financial decision-making. Drawing on recent literature (2020–2025) across computer science, law, finance, and public policy, it examines five intersecting dimensions: ethical frameworks, regulatory responses, algorithmic bias and explainability, governance architectures, and emerging policy directions. The analysis reveals that existing regulatory frameworks, designed for human decision-makers, remain inadequate for adaptive machine learning systems, while technical opacity continues to undermine fairness and accountability. The paper's main contribution is in pulling these areas together and identifying where they interact, particularly between lifecycle aligned regulation and multi layered governance, which prior reviews have largely treated separately. It offers policy recommendations for regulators, financial institutions, and technology developers, with a focus on cross border harmonization and domain specific regulatory design.