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Marc
Esmiley
Head of Product, Financial Services Studio, Commercial Engineering
Microsoft
Marc Esmiley is a senior Data and AI leader at Microsoft, with extensive experience at the intersection of technology, financial services and digital transformation. He currently serves as Head of Product, Financial Services Studio, Commercial Engineering at Microsoft, where he leads a global team focused on strategic co-innovation, co-engineering and product development with major financial-services customers. With a career spanning technology and financial services, Marc has built and led large-scale digital transformation initiatives, developed customer-centric products and helped organisations apply emerging technologies to complex, highly regulated environments. His expertise encompasses AI, data, cloud computing, fintech, product management and digital transformation, with a particular focus on turning new technology into practical business outcomes. Marc has been closely involved in Microsoft's work with LSEG, helping financial-services organisations modernise their data estates and build AI-enabled products. His work has included Microsoft Fabric, Azure AI, Copilot Studio and Purview, with a focus on trusted data, governance, AI readiness and accelerating product development.
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01 December 2026 13:45 - 14:30
Panel - Shipping fast in a regulated world: Speed, scrutiny and the real cost of getting it wrong
Speed to market is now the single biggest challenge product leaders name - and in financial services, healthcare and the public sector it collides head-on with a regulator entirely entitled to ask how your model reached its conclusion. 'Move fast and iterate' is not a strategy when one hallucinated answer is a reportable incident. This panel brings together product leaders shipping AI-powered products inside genuinely regulated environments. They'll cover what they've learned about designing for auditability from day one, where human review adds real safety rather than theatre, how to work with risk and compliance as partners instead of gatekeepers, and how to protect release velocity when every change carries evidential weight. Useful well beyond regulated industries: the governance expectations landing on financial services now have a habit of arriving everywhere else within two years. Key takeaways - Design patterns that make AI product decisions explainable and auditable without crippling iteration - How to structure the relationship with risk, legal and compliance so that it accelerates delivery - Which controls genuinely reduce risk, and which are expensive reassurance