📄 Abstract
The rapid adoption of Artificial Intelligence (AI) in financial systems has revolutionized decision-making, risk management, and compliance processes. Yet, this transformation has also created profound ethical and governance dilemmas. While AI enhances accuracy and operational efficiency, it simultaneously amplifies issues of bias, opacity, and accountability, raising questions about the moral legitimacy and regulatory adequacy of algorithmic finance. The core problem this review addresses is the absence of an integrated governance framework that effectively aligns technological innovation with ethical responsibility and regulatory coherence. Existing systems remain fragmented: financial institutions adopt AI for competitive advantage, regulators struggle to keep pace, and ethical safeguards are often reactive or inconsistent. Consequently, fairness and accountabilityessential principles for market integrity and social trustare inadequately embedded across the AI lifecycle. This study harmonizes conceptual and policy perspectives by comparing key international frameworks, including the EU Artificial Intelligence Act (Regulation (EU) 2024/1689), the U.S. NIST AI Risk Management Framework (2023), the Blueprint for an AI Bill of Rights (2022), and Singapores Model AI Governance Framework (2022). Findings reveal enduring tensions between innovation and moral oversight. The paper proposes a triadic AI Ethical Risk Governance Model integrating fairness, accountability, and policy alignment as pillars for responsible AI in finance. Ultimately, embedding these principles throughout the AI lifecycle is vital to ensuring ethical legitimacy, public trust, and sustainable digital finance.
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📚 How to Cite:
Joshua Pallapati , Matthew Oman-Amoako , ARTIFICIAL INTELLIGENCE AND ETHICAL RISK GOVERNANCE IN FINANCIAL DECISION-MAKING: EXAMINING FAIRNESS, ACCOUNTABILITY, AND POLICY ALIGNMENT , Volume 13 , Issue 4, April 2026, EPRA International Journal of Economics, Business and Management Studies (EBMS) , DOI: https://doi.org/10.36713/epra26817