This conceptual paper develops a normative governance framework for the ethical deployment of artificial intelligence (AI) systems in corporate bankruptcy prediction. Grounded in stakeholder theory, legitimacy theory, agency theory, and role-morality theory, the framework articulates five mutually reinforcing principles: fairness, transparency, auditability, accountability, and competence. Each principle is mapped to concrete organisational mechanisms. These mechanisms are theorised to influence key market outcomes, including liquidity, credit-risk premium, audit quality, and regulatory cost. As such, ethical AI governance is positioned as an institutional prerequisite for informationally efficient capital markets, rather than a post hoc compliance burden. The paper contributes by: 1) integrating fragmented insights from AI ethics, accounting theory, and regulation into a coherent conceptual model, 2) identifying market failures that arise from opaque algorithmic decision processes, 3) formulating empirically testable propositions linking governance mechanisms to market-level effects, 4) providing actionable guidance for practitioners and standard-setters that aligns with emerging regulatory mandates while minimising implementation cost, and 5) presenting preliminary empirical evidence and a structured research agenda to support future validation. Although the analysis focuses on bankruptcy prediction, the framework is generalisable to other high-risk accounting domains.
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