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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24Cited by 0

Artificial Intelligence, Corporate Governance and the Regulation of Financial Systemic Risk: Compliance Frameworks, Liquidity Risk Management and Market Stability in Algorithm-Driven Capital Markets

Northon Salomao de Oliveira

As artificial intelligence assumes an increasingly dominant role in global capital markets, financial regulation faces an unprecedented institutional challenge: how can legal systems govern autonomous algorithms capable of making trading decisions at speeds beyond human supervision? This article examines the intersection of artificial intelligence, corporate governance, financial compliance, and systemic risk, demonstrating how high-frequency trading and deep learning architectures have transformed market microstructure while exposing critical weaknesses in traditional regulatory frameworks. Drawing on a comparative analysis of the United States, the European Union, the United Kingdom, Brazil, Singapore, and Switzerland, the study identifies regulatory asymmetries, governance failures, and opportunities for algorithmic regulatory arbitrage. Building upon empirical evidence from major market disruptions and interdisciplinary insights from law, economics, sociology, and computer science, the article proposes the Dynamic Algorithmic Resilience Framework (DARF), an innovative governance model centered on continuous stress testing, explainable AI, real-time supervisory mechanisms, and strengthened board accountability. The research argues that preserving financial stability in algorithm-driven markets requires shifting from reactive enforcement toward proactive, technology-integrated governance capable of embedding the rule of law directly into autonomous financial systems. Artificial Intelligence, Corporate Governance, Systemic Risk, Algorithmic Trading, High-Frequency Trading (HFT), Financial Regulation, Capital Markets, Liquidity Risk, Explainable Artificial Intelligence (XAI), Market Microstructure, Regulatory Compliance, Algorithmic Governance, Macroprudential Policy, Financial Stability, Deep Learning, Regulatory Arbitrage, Risk Management, Autonomous Trading Systems, Comparative Financial Law, Dynamic Algorithmic Resilience Framework (DARF)

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