AI Summary
5 min readIn the OTC markets that make up roughly half of global trading volume, people still type prices into chat windows with their fingers, watch responses with their eyeballs, and scribble numbers on scratch paper. Matthew Cheung, CEO of ipushpull, has spent two decades building communications infrastructure for financial markets, and he argues that this messy, unstructured chat data is about to become the most valuable untapped resource in finance — unlocked by the convergence of large language models, AI agents, and a governance framework that treats compliance not as a burden but as a performance engine.
Why chat won the interface war
Cheung sees the evolution of human-computer interaction in financial services as a clear progression: graphical user interfaces in the 1990s, APIs in the 2000s, and now agents as the next interface moment. But the underlying channel that connects all of them is chat. More than half the world's population uses chat platforms, from WhatsApp's three billion users to Microsoft Teams inside enterprises. Chat has been around for 50 years, but it was always designed for human-to-human communication. The problem was that the data inside those conversations — the prices, the axes, the market color, the relationship-building chit-chat — was completely unstructured and effectively inaccessible.
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What you'll learn
- 1 (00:45) **Opening & Guest Introduction** - Dave Greeley welcomes Matthew Cheung, CEO of ipushpull, to discuss chat, AI agents, and governance in financial services.
- 2 (03:14) **Why Chat Won the Interface War** - Matthew argues that chat/messaging is the universal interface because it’s how over half the world’s population communicates daily.
- 3 (07:42) **The Four Pillars: Chat, Data, AI, Governance** - Matthew introduces his framework for the next enterprise era, centered on extracting value from chat data.
- 4 (10:57) **The Untapped Reservoir of Chat Data** - Matthew explains how LLMs unlock historical chat data that was previously too unstructured to use.
- 5 (14:58) **Privacy and Historical Data Concerns** - Matthew addresses whether the ability to mine chat data raises new privacy risks.
- 6 (18:52) **The Autonomy Slider** - Matthew explains the concept of an autonomy slider for governing AI agent behavior, from human-in-control to fully autonomous.
- 7 (20:50) **Regulatory Frameworks for AI in Markets** - Matthew references the IOSCO paper “Supervisory Toolkit for AI and Capital Markets” (May 2026) as a key governance reference.
+ Full timestamped outline available in the app
Show Notes
This week, we close out our How to Raise Your Agent series with Matthew Cheung, CEO of ipushpull. David Greely sits down with Matthew to discuss how chat won the interface war in financial services, how AI is unlocking a trove of chat data for enterprise use, and why governance will be the key to who wins in a world of messaging and AI agents.
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