The Supervisory Toolkit for AI Use in Capital Markets is a practical resource designed to support financial regulators and supervisors in overseeing the adoption of artificial intelligence within the capital markets sector. As AI technologies become increasingly integrated into trading, asset management, and risk profiling, the toolkit provides a structured framework for monitoring risks and ensuring market integrity. For finance professionals, it offers critical insights into the regulatory expectations and compliance standards likely to govern future AI deployments.

Organisation behind the tool

The tool was developed and issued by the International Organization of Securities Commissions (IOSCO), the global standard-setter for securities regulation.

What the tool does

The toolkit functions as a guidance document that assists supervisors in assessing the governance, development, and use of AI. Key features include:

• Guidance on supervisory approaches to AI-driven algorithmic trading and investment strategies.
• Frameworks for evaluating the internal governance and risk management controls of financial institutions.
• Checklists for supervisors to ensure firms maintain data quality, transparency, and explainability in their AI models.
• Methods for monitoring potential systemic risks, such as flash crashes or pro-cyclicality, stemming from AI.

Target audience

The primary audience includes national securities regulators and financial supervisors. It is also highly relevant for compliance officers, risk managers, and legal professionals within financial institutions.

Relevance to finance professionals

Finance professionals can apply the toolkit to several areas of operation:

• Risk assessment – understanding the specific operational and technical risks associated with AI-driven market activities.
• ESG analysis – align with emerging social metrics regarding the ethical use of technology and algorithmic bias.
• Investment context – identifying the regulatory boundaries for automated asset management and high-frequency trading.
• Compliance and reporting – preparing for future regulatory examinations by aligning internal AI governance with international best practices.