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The rapid proliferation of generative artificial intelligence (GenAI) across banking, capital markets, and insurance is fundamentally reshaping how financial institutions create content, assess risk, interact with customers, and make decisions. While GenAI promises transformative efficiency gains, it simultaneously introduces novel ethical hazards and exposes critical gaps in existing regulatory frameworks. This paper examines the principal ethical challenges arising from GenAI deployment in finance including synthetic identity fraud, algorithmic bias, opacity in decision-making, and data-privacy violations and maps them against the evolving global regulatory landscape spanning the European Union AI Act (2024), U.S. agency guidance from the SEC, OCC, CFPB, FINRA, and FinCEN, and international standards issued by the Basel Committee on Banking Supervision and the Financial Stability Board. The paper identifies four structural governance gaps: jurisdictional fragmentation, model-risk blind spots, accountability diffusion, and inadequate audit mechanisms. Drawing on existing risk-management literature and regulatory precedent, it proposes a tiered, risk-based governance framework termed PRISM (Proportionality, Responsibility, Integrity, Surveillance, and Model-risk) to guide financial institutions and policymakers in deploying GenAI responsibly.