June 22nd 2025; AI reshaping Markets—transforming trading systems, accelerating product innovation, and prompting a regulatory rethink. From smarter, interoperable infrastructure to real-world AI tools in compliance and advisor analytics, the focus is shifting from speed to contextual intelligence. As regulators grapple with how to respond – AI is no longer peripheral, it’s becoming central to how markets operate.
1. Another Week, Another Conference Dominated by AI in Trading
At ACI Global in Paris this week, the message was clear: AI in trading isn’t about speed—it’s about smarts. Success hinges on contextual intelligence, clean data, and interoperability. AI’s real-time ability to synthesize and surface insights is transforming how market participants are able to act on signals. Smarter system design and better data quality are driving a shift toward human-AI collaboration, not competition. ACI’s emphasis on education, ethics, and industry collaboration will be essential to building an intelligent, integrated financial system (read more here – https://bit.ly/3HQIwos).
2. One to Watch for Future Innovation
Entrepreneur Evan Schnidman (formerly of Prattle and Liquidnet) has moved to Fidelity Labs to accelerate AI product development with a startup mentality. Schnidman is pushing for rapid prototyping and validation, expanding beyond SaaS into agentic, AI-native products. Noteworthy ventures include:
- Saifr – AI-powered compliance tools
- CatchLight – Analytics for financial advisor-client engagement
Both demonstrate the potential of combining proprietary data sets with applied machine learning. Read more here
3. Rethinking Scale: Small Language Models & Empowerment Tech
The conversation around LLMs is evolving fast. At #FIXNordics 2024, Haroon Hassan championed the rise of Small Language Models (SLMs)—and now NVIDIA echoes that view in a recent paper. They argue that large LLMs are often overkill for tightly scoped financial tasks: expensive, centralized, and error-prone. In contrast, SLMs are lighter, faster, and more controllable, making them well-suited to Agentic AI use cases—even running securely on local infrastructure. It’s all part of a broader shift toward “Empowerment Tech”—where AI enhances individual decision-making rather than reinforcing centralized control.
Meanwhile, ESMA has just published a joint report with the Institut Louis Bachelier and The Alan Turing Institute on responsible LLM use: Leveraging Large Language Models in Finance: Pathways to Responsible Adoption
Key takeaways include:
– Applications: research, sentiment analysis, compliance automation
– Risks: data privacy, bias, and reputational harm
– Principles: security, fairness, accountability
– Recommendations: risk-aware training and clearer guidelines
4. Data Dilemmas: Rights, Use, and Tensions
Perplexity AI is in the spotlight—praised by legendary investor Howard Marks for aiding his daily market notes (see LinkedIn), but simultaneously facing legal threats from the BBC over content scraping – read more here FT coverage of BBC’s legal threat
In the UK, the Data (Use and Access) Act just received Royal Assent. It provides clarity on automated decision-making and Digital ID infrastructure for the emerging smart data economy. Read more here – ICO press release
5. Regulatory Momentum: UK, US & Global AI Governance
At a recent summit, FCA CEO Nikhil Rathi warned that AI is evolving faster than regulators can respond. While the UK has no plans for standalone AI legislation, it will continue to rely on principles-based regulation grounded in fairness, transparency, and accountability.
With growing systemic risks flagged by the Bank of England and IMF, including AI-driven volatility and algorithmic collusion, the UK’s newly launched AI Safety Institute is taking a more active role. For financial firms, the message is clear: robust AI governance is no longer optional—it’s essential.
In the US, new SEC Commissioner Paul Atkins is reversing course on several Gensler-era policies. Meanwhile, federal agencies are preparing to release the AI Action Plan mandated under Executive Order 14179, signed in January by President Trump.
With the 180-day deadline landing on July 22, internal coordination is heating up across agencies like the OSTP, OMB, and NSC. Expect frameworks soon – designed to reduce regulatory friction and position the U.S. as a global AI leader – Read more here
As always, thank you for reading! Let me know what you found helpful, what you disagreed with — and what you’d like to see more of.
Many thanks,
Rebecca
