Policy issues in derivatives markets related to artificial intelligence: an analysis

The prevalence of artificial intelligence (AI) in the derivatives market has surged in recent years, giving rise to new policy considerations while also amplifying existing challenges. By 2023, almost all major financial institutions involved in derivatives trading revealed that they had integrated AI into their operations. A comprehensive survey conducted in 2024 across financial firms indicated that about 89% of participants were utilizing generative AI internally. Generative AI utilizes machine learning techniques to create novel content like computer codes, text, or videos. Most companies employing machine learning and other predictive AI technologies predominantly utilized them for risk management, fraud detection, operational procedures, and regulatory compliance tasks.

In a detailed assessment of AI applications within the derivatives market in 2024, the Technology Advisory Committee of the Commodity Futures Trading Commission (CFTC) underscored the importance of understanding the manner in which AI models are employed in the financial services industry, particularly in the derivatives market. AI has the potential to streamline various processes in derivative trading, such as facilitating risk management, surveillance, fraud identification, strategy execution, and trading strategy back-testing. AI’s increased utilization has led to enhanced efficiencies in back-office tasks and trade execution. Notably, generative AI has empowered investment firms to process vast quantities of unstructured data to refine their analytical trading tools.

Nonetheless, the mounting usage of AI brings about new risks and prompts congressional inquiries regarding the oversight of the CFTC and derivatives regulation. Critical policy challenges encompass ensuring robust cybersecurity measures and safeguarding against third-party risks associated with external information technology services. Additionally, concerns arise regarding the prevention of market manipulation due to generative AI and ensuring market transparency and stability during swift trade executions facilitated by AI models. Despite the CFTC issuing a Request for Comment on the Use of Artificial Intelligence in CFTC-Regulated Markets in January 2024, further directives on these matters are awaited.

Third-party risks are substantial, as suggested by the CFTC, wherein potential harms may arise from relying on third parties to carry out services on behalf of registered entities. The Institute of International Finance’s 2024 survey on AI application underlined that 94% of financial firms anticipated an upsurge in their adoption of third-party AI/ML solutions in the upcoming year. Such risks may encompass operational, financial, cybersecurity, or regulatory issues posed by third-party vendors or service providers.

The issue of cybersecurity risks tied to third-party concentration was emphasized by a May 2025 Government Accountability Office (GAO) study. Financial instability may result from leaning on a concentrated group of third-party AI service providers, amplifying systemic risk within the sector. CFTC Commissioner Kristin Johnson, in June 2025, delineated cybersecurity risks as a rising concern that could be worsened by concentration risks. Notable cybersecurity breaches, such as the $1.5 billion loss encountered by Bybit cryptocurrency exchange in February 2025, have intensified the need for heightened vigilance in the face of increased AI adoption in financial processes.