The artificial intelligence governance framework for finance: A control-by-design approach to algorithmic decision-making in accounting

The rapid integration of artificial intelligence (AI) into financial and accounting systems has redefined decision-making processes, creating both opportunities for efficiency and risks related to transparency, bias, and regulatory compliance. Traditional governance mechanisms often lag behind technological innovation, resulting in accountability gaps in algorithmic decision-making. This paper introduces the Artificial Intelligence Governance Framework for Finance (AIGF-F), a control-by-design model aimed at embedding governance, risk management, and ethical oversight directly into AI-driven accounting systems. The framework emphasizes proactive governance through three core dimensions: algorithmic transparency, embedded control mechanisms, and adaptive regulatory alignment. It incorporates auditability features such as algorithmic audit trails, explainability protocols, and fairness metrics to ensure that AI outputs remain accountable to stakeholders. By adopting a control-by-design philosophy, the AIGF-F moves governance from a reactive supervisory function to an integral component of system architecture, minimizing risks before they materialize. The framework also highlights the role of augmented human oversight, ensuring that accountants and auditors remain central in interpreting AI-driven insights and validating ethical boundaries. Furthermore, the model demonstrates how financial institutions can balance innovation with compliance by integrating dynamic monitoring tools and continuous feedback loops that adjust controls in response to evolving data environments and regulatory landscapes. For practitioners, the AIGF-F offers a structured approach to implementing AI responsibly in areas such as financial reporting, auditing, fraud detection, and compliance monitoring. For regulators, it provides a scalable framework for establishing adaptable supervisory structures capable of keeping pace with algorithmic complexity. Ultimately, this study positions AI governance not as a barrier but as an enabler of sustainable financial transformation. By embedding governance into design, the AIGF-F enhances trust, accountability, and resilience in AI-enabled accounting systems, contributing to the broader discourse on ethical and responsible digital finance. Keywords: Artificial Intelligence Governance, Control-By-Design, Algorithmic Decision-Making, AI In Accounting, Financial Reporting, Auditability, Explainability, Fairness Metrics, Compliance Monitoring, Ethical AI.