Governed Data as the Competitive Moat in the Agent Era - Regulation and What It Means for Markets

Inside NatWest's Approach to Agentic AI | Dr. Paul Dongha

In this episode of the ipushpull Capital Markets FinTech Forum podcast, Matthew Cheung sits down with Dr. Paul Dongha, Head of Responsible AI and AI Strategy at NatWest Group, to unpack what agentic AI actually means for banking, and why governance is what decides whether AI scales or stalls. Paul has been thinking about AI agents since before most people had heard the term. He finished his PhD on AI agent reasoning and the alignment problem back in the 1990s, then spent almost three decades putting it to work inside seven banks.  Today he leads NatWest's efforts to deploy AI in a way that's safe, transparent, and auditable, and he leads the bank's collaboration with the FCA, where he's live testing agentic AI. Before NatWest he was Group Head of Data and AI Ethics at Lloyds. He's also co-author of Governing the Machine, How to Navigate the Risks of AI and Unlock Its True Potential, an FT book of the month, and he's about to launch a new course called Responsible AI in Practice. In our conversation, we covered: - Why AI governance is the unlock for scaling AI, not a compliance burden - Why LLMs will become commodities, and the browser war that proves it The levels of autonomy, from human in control to on the loop - The alignment problem he studied in the 1990s, still unsolved today - Using customer data to bring back the bank manager who actually knew you - Why agents should be treated as tools, not given employee logins - MCP as a base layer, and the governance checks still missing - How the EU AI Act and FCA consumer duty fit what firms were doing anyway - Why AI literacy matters most, and taking the hype with a pinch of salt Connect with Dr. Paul Dongha: https://www.linkedin.com/in/paul-dongha/ Resources: https://www.amazon.co.uk/Governing-Machine-navigate-unlock-potential/dp/139942629X https://maven.com/georgiana-marsic/ai-governance-framework For more information go to: https://ipushpull.com

Governed Data as the Competitive Moat in the Agent Era - Regulation and What It Means for Markets

The EU AI Act isn't GDPR. It's product safety law. In this episode of the ipushpull Capital Markets FinTech Forum podcast, Matthew Cheung sits down with Rosie Nance, Senior Knowledge Lawyer at Norton Rose Fulbright, to unpack what the EU AI Act actually is, how it sits alongside existing regulation, and what the rise of agentic AI means for financial services firms operating across the UK, EU, and US. Rosie is part of Norton Rose Fulbright's data, cyber, and AI regulation team, advising financial services clients on AI Act compliance, specific use case rollouts, and the wider governance programmes needed to navigate a fast-moving regulatory landscape. She shares how firms should be thinking about provider vs deployer roles, high-risk use cases, and the multi-stakeholder effort now required to ship AI responsibly. In our conversation, we covered: - EU AI Act as a product safety framework - High risk AI use cases in finance - Data governance and audit trails for AI - Regulatory landscape across regions Resources: https://www.insidetechlaw.com/new-artificial-intelligence For more information go to: https://ipushpull.com

The Model Is Not the Moat: Alvin Wang Graylin on the Stanford Enterprise AI Playbook

Data is the real moat. Frontier models are becoming a commodity. In this episode of the ipushpull Capital Markets FinTech Forum podcast,  Matthew Cheung sits down with Alvin Wang Graylin, Digital Fellow at the Stanford Digital Economy Lab and co-author of The Enterprise AI Playbook: Lessons from 51 Successful Deployments With over 35 years of experience across AI, semiconductors, immersive computing, and cybersecurity at HTC, Intel, IBM, and Trend Micro, four founded startups, and investments in 100+ early-stage firms, Alvin shares the findings from a five-month Stanford study of 51 enterprise AI deployments across 41 organisations and 9 industries on how AI is actually being adopted inside large organisations. In our conversation, we covered: * Why MIT's "95% AI failure" headline collapsed under deeper methodology * Why data, not model choice, is the durable enterprise moat * The productivity gap between full automation and human-in-the-loop * Why two-thirds of successful AI rollouts started as failures * Why HR, legal, and compliance are the biggest internal blockers to enterprise AI * Why 65% of white-collar work in the US, UK, and East Asia is exposed to AI Resources: * https://digitaleconomy.stanford.edu/p... [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqblIwQnZxMS13TUVyMXBZTTc0eExjbGRHY2UwZ3xBQ3Jtc0treThodGw0X1BrUGMwcHJTd29hSGNreEtBWktUREN6OFpzUTQ2N0EydUtSX1dMaWpXWjFkbUVYU09Vd1JjT0hSZU1LLVc1SnRULTNSWEhjeWtWbmcxX0Y2aHlTNzlVMjhzNkVxZ3l3T3MyaU5lOGV4cw&q=https%3A%2F%2Fdigitaleconomy.stanford.edu%2Fpublication%2Fenterprise-ai-playbook%2F&v=o-3DLVmkECQ] * https://open.substack.com/pub/abundan... [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbjJST09WS0pKaXl0Q3Z4bTc3VHhXVmZSV0Vtd3xBQ3Jtc0tsZXAycHFkOXR6bGoyMXZadjhvc2JqY2w5YjA1UzVCTFAzRFR0QlZaMVV5bktrcFU0RUw2MURGbWt5S3FGSGE2WE9qOVpHemZxRmFubXJKeUJmQTBTUmlSR1p3SlJIUEd4WGYweWMyT0pHYmh4VHhFNA&q=https%3A%2F%2Fopen.substack.com%2Fpub%2Fabundanist%2Fp%2Fabundanism&v=o-3DLVmkECQ] * https://www.youtube.com/watch?v=pZXs0entv-c [https://www.youtube.com/watch?v=pZXs0entv-c] * OurNextReality.com Follow Alvin Wang Graylin: https://www.linkedin.com/in/agraylin/ ABOUT US: ipushpull is a cloud-based real-time data sharing and workflow automation platform. Used across sell-side and buy-side, and front to back office, ipushpull improves workflow efficiency by allowing cross application secure, audited, access-controlled live data sharing, collaboration, and workflow automation.  The API first platform handles static, live, and streaming data with APIs, integrations, and connectors into many data platforms, applications and services. For more information go to: https://ipushpull.com

Beyond the LLM: How Koch and ipushpull Automated Trade Capture from Chat

In this episode of the ipushpull Capital Markets FinTech Forum, Robert Kingham, Head of North America Sales, ipushpull, sits down with Tim Flynn, IT Leader at Koch Energy Services. Tim is a seasoned technology leader with over 20 years of experience delivering trading and risk management solutions in the energy markets. Currently leading technology for Koch Energy Services’ natural gas trading and marketing business In this conversation, we explore: - What was trade capture like before automation - How does Trade Capture & Booking turn chat into booked trades - How does AI trade capture improve compliance and auditability - Where is AI automation heading next for traders For more information go to: https://ipushpull.com

The Evolution of Fixed Income Markets: AI, Data & Automation

In this episode of the ipushpull Capital Markets FinTech Forum, Matthew Chung, CEO of ipushpull, sits down with Deniz Mace-Jones, Global Head of Rates and Credit Products and Electronic Distribution at UBS. With extensive experience across electronic trading and fixed income markets, Deniz shares valuable insights into how trading desks, technology, and regulation are transforming the landscape of global markets. In our conversation, we covered: * Evolution of fixed income electronification over the past decade * Impact of MiFID II and Dodd-Frank on trading structures * Differences between rates and credit markets * How automation is reshaping sales and trading workflows * Unlocking insights from unstructured data in trading chats * Role of AI in enhancing efficiency and decision-making * The future of market electronification and human expertise ABOUT US: ipushpull is a cloud-based real-time data sharing and workflow automation platform. Used across sell-side and buy-side, and front to back office, ipushpull improves workflow efficiency by allowing cross application secure, audited, access-controlled live data sharing, collaboration, and workflow automation.  The API first platform handles static, live, and streaming data with APIs, integrations, and connectors into many data platforms, applications and services. For more information go to: https://ipushpull.com