Belfius Insurance’s Head of Data & AI, Hannes Heylen shares how his team scaled GenAI - from a fraud detection flywheel to “Nestor,” a claims copilot that speeds summaries, completeness and coverage checks. We unpack AI agents in the claims flow, build-vs-buy decisions, and why content/data governance drives LLM quality. Plus: a pragmatic delivery mantra - make it work, then right, then cheap - for CIOs, CDOs and Heads of Data.

What you’ll learn

• How to pick first AI cases that prove €ROI (fraud models)
• Designing a claims copilot: summarization, completeness & coverage checks
• Where AI agents fit (GenAI + ML + humans) across the claims flow
• Build vs. buy in 2025: foundation models, vendor flexibility, cost control
• Content/data governance as the make-or-break for LLM apps
• “First make it work, then right, then cheap”: an AI operating model for CIO/CDO

Guest: Hannes Heylen, Head of Data & AI, Belfius Insurance

🌐 More at ⁠www.dataminded.com⁠

Chapters:

00:00 Why AI now in financial services

06:30 GenAI’s impact on text-heavy insurance processes

18:40 AI agents across claims

31:00 Governance > model tweaks

38:00 Fraud detection: the € case

41:30 Claims copilot (“Nestor”) & lab-to-prod

55:00 Lessons for CIOs/CDOs

Topics: ROI-first use cases • Claims automation • AI agents (GenAI + ML + human-in-the-loop) • Governance • Vendor flexibility & costs