The Data Playbook Podcast

• S2 E6. 5 Years Kate 🎂: Inside KBC’s AI Playbook - The Data Playbook Podcast with Kris Peeters & Dr. Barak Chizi

  What happens when a bank decides that AI and IP are so strategic they must be built in-house - then actually follows through for more than a decade?In this episode of The Data Playbook, Dr. Barak Chizi, Chief Data & Analytics Officer at KBC Group, joins Kris Peeters to reveal how KBC built one of Europe’s most mature AI organisations and what it took to bring Kate, their AI assistant, to life, and keep her evolving for 5 years.You’ll hear how KBC:Grew from early machine learning to 2,000+ AI use cases in productionDeveloped an AI-driven anti-money laundering platform and commercialised it for other banksScaled Kate, now celebrating 5 years and upgraded with GPT.Uses the U-model to govern AI safely from idea to productionKeeps ROI at the centre of every AI projectStays vendor-independent while still leveraging hyperscaler LLMsBuilds diverse, high-calibre AI teams with a rigorous recruitment approachExplores soft logic and modelling customer intent as the next frontier of financial AIIf you want to understand how to turn AI from experiments into a true competitive advantage, this conversation is your playbook.🌐 More at www.dataminded.com and subscribe to our channel.Show notes:The Foundation of Soft Logic👉 https://link.springer.com/book/10.1007/978-3-031-58233-2Dan Ariely – Predictably Irrational👉 https://www.amazon.com/Predictably-Irrational-Revised-Expanded-Decisions/dp/0061353248/⏱️ Chapters00:00 – Intro to The Data Playbook & today’s guest01:15 – Barak’s backstory: 25 years in AI & high-dimensional data03:02 – What a CDAO does at KBC & enabling 24/7 AI-assisted service04:55 – Towards continuous, machine-supported customer journeys06:37 – The U-Model: KBC’s framework for data & AI projects08:35 – Flagship AI products, finite project lifecycle & retraining10:07 – Prioritising AI use cases across 5 countries12:31 – ROI mindset, conservative risk culture & data as an asset14:21 – Why KBC keeps AI in-house & limits external consultants18:17 – Beyond data warehouses: from reporting to prediction22:21 – AI-driven AML platform & the creation of SKY25:30 – Patents, AI IP and KBC’s competitive positioning27:25 – Generative AI at KBC since 2018 & early transformer experiments29:11 – Pragmatic tech choices: LLMs vs ML vs simple automation31:42 – Avoiding GenAI hype and focusing on customer value33:03 – Why KBC built Kate: 24/7 banking & impatient customers35:28 – From FAQ bot to execution engine: Kate’s end-to-end capabilities37:07 – Customer reactions, branches vs digital & Kate’s 2026 roadmap39:24 – Multi-LLM strategy, vendor independence & design partnerships40:44 – Inside Kate’s architecture: NLU, open source & KBC-built layers42:37 – Proactive AI: timing, context and personalised offers44:51 – Soft logic, consciousness & modelling customer intent49:19 – Building a diverse, 24-nationality AI team at KBC51:37 – Recruitment process, tests & how candidates are evaluated55:21 – What KBC looks for in modern data scientists57:15 – Lessons after 10 years at KBC & book recommendation

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• S2 E5. Beyond Hyperscalers: How to Run Modern Data Platforms on European Clouds - The Data Playbook Podcast with Kris Peeters & Niels Claeys

  EU clouds without the hype. Niels Claeys (Partner & Lead Data Engineer at Dataminded, and our technical hiring lead) breaks down data sovereignty vs. Cloud Act, GDPR realities, and a portable, Kubernetes-first stack with Iceberg, Trino, and Airflow. We compare Scaleway, OVH, Exoscale, UpCloud, look at cost drivers, encryption/KMS, egress policies, and how to avoid vendor lock-in plus when best-of-breed beats all-in-one and why “keep it simple” still wins.What you’ll learn:When EU clouds make more sense than hyperscalers (and when they don’t)Designing a portable platform: Terraform/Tofu for infra, Argo CD for appsTable formats 101: why Apache Iceberg over plain Parquet/CSVQuery layer choices: Trino for open SQL across object storage & DBsOrchestration in practice: Airflow patterns, dependencies, SLAsSecurity & governance: OPA for fine-grained policies, IAM, catalogsCost & ops: egress, managed services gaps, version lag, troubleshootingTeam skills: what to hire for, and the “hard questions” Niels asks in interviews🌐 More at ⁠www.dataminded.com⁠ — and subscribe!Chapters00:00 Intro & why EU clouds now04:40 Compliance & legal: GDPR, Cloud Act, sovereignty11:55 Platform blueprint: Kubernetes + Iceberg + Trino + Airflow20:30 Catalogs, OPA, IAM & access control27:10 EU providers deep dive: Scaleway, OVH, Exoscale, UpCloud36:20 Cost, encryption/KMS, egress & performance43:10 Best-of-breed vs all-in-one (and glue work)51:00 Getting started: IaC, Argo CD, day-2 ops56:40 Hiring: interview signals & practical takeawaysKeywordsEU cloud, European cloud providers, data sovereignty, GDPR, Cloud Act, Kubernetes data platform, Apache Iceberg, Trino, Airflow, vendor lock-in, OPA, Argo CD, Terraform, Exoscale, Scaleway, OVH, UpCloud

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• S2 E4. Build vs Buy in the GenAI Era: Inside Belfius’ Data & AI Strategy - The Data Playbook Podcast with Kris Peeters & Hannes Heylen

  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 learnHow to pick first AI cases that prove €ROI (fraud models)Designing a claims copilot: summarization, completeness & coverage checksWhere AI agents fit (GenAI + ML + humans) across the claims flowBuild vs. buy in 2025: foundation models, vendor flexibility, cost controlContent/data governance as the make-or-break for LLM apps“First make it work, then right, then cheap”: an AI operating model for CIO/CDOGuest: Hannes Heylen, Head of Data & AI, Belfius Insurance🌐 More at ⁠www.dataminded.com⁠Chapters:00:00 Why AI now in financial services06:30 GenAI’s impact on text-heavy insurance processes18:40 AI agents across claims31:00 Governance > model tweaks38:00 Fraud detection: the € case41:30 Claims copilot (“Nestor”) & lab-to-prod55:00 Lessons for CIOs/CDOsTopics: ROI-first use cases • Claims automation • AI agents (GenAI + ML + human-in-the-loop) • Governance • Vendor flexibility & costs

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• S2 E3. How imec scales research with data platforms: governance, workbenches, and adoption - The Data Playbook Podcast with Kris Peeters & Wim Vancuyck

  In this episode of The Data Playbook, we go inside imec, one of the world’s leading semiconductor research institutes, to explore how they scale data governance, self-service, and innovation in one of the most data-intensive environments on Earth.Our guest, Wim Vancuyck, Manager of ICT for Data & Research Enablement, leads imec’s data strategy - bridging IT, researchers, and business to accelerate R&D through digital solutions. Wim’s mission: make imec a data-driven research organisation that turns raw measurements into insights and intellectual property faster and more securely.Wim explains how imec built a research data platform that empowers thousands of scientists through:Purpose-based access control, linking people, platforms, and data assetsFour self-service workbenches for Power BI, Data Engineering, Data Science & AI, and Application DevelopmentA clear platform vision built on efficiency, scalability, and reliabilityA governance model that supports both compliance and creativityA pragmatic stance on shadow IT: embrace, standardise, and professionalize itA bottom-up adoption strategy driven by early adopters and community engagementHe also discusses his evolution from technical architect to data leader, and what it takes to manage change in a 5,000-person R&D organisation, balancing technical depth with people leadership.🎙️ Guest: Wim Vancuyck - Manager ICT, Data & Research Enablement, imec🌐 More at: www.dataminded.com#DataPlaybook #imec #SemiconductorR&D #DataGovernance #PurposeBasedAccessControl #DataMesh #PlatformEngineering #SelfServiceAnalytics #CIO #CDO #DataLeadership #ResearchDataPlatform #DataStrategy

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• S2 Ep2. Federated Data Governance in Banking: How ABN AMRO Scaled from 300 Data Owners to 15 Data Domains - The Data Playbook Podcast

  How do you turn governance from a bottleneck into a business accelerator - in a bank?In this episode of The Data Playbook, host Kris Peeters talks with Jan Mark Pleijsant, Senior Data Strategy & Governance Advisor at ABN AMRO Bank, about their move from 300+ dispersed data owners to 15 clear, business-aligned data domains and what it took to make federated governance work in a highly regulated environment.You’ll learn:Why “governance police” fails and how a federated model balances autonomy with oversight.How ABN AMRO defined domains by the nature of data (customer, loans, payments) rather than shifting business units driving stability across reorganisations.What “governance by design” looks like in practice (policies, standards, data lineage, quality, clear ownership).The evolution from golden (source-aligned) datasets to consumer-ready data products (“pre-packaged salads”) that speed time-to-insight.Why executive sponsorship, domain maturity, and delivery discipline are the real success factors.How to measure domain maturity, prioritize critical reports (e.g., regulatory & exec dashboards), and avoid endless debates over definitions by making differences explicit.Who should listen: CIOs, CDOs, Heads of Data, and Data Leaders building scalable, compliant data platforms in complex organizations - especially in financial services.Chapters:00:00 Intro & context (POA Summit)03:12 Why banks need strong data governance07:45 Federation vs. centralization (and pitfalls)13:10 From 300 owners to 15 domains19:40 Designing domains that don’t break with reorgs26:05 Data products vs. datasets—what changed33:20 Governance by design: policy → product40:05 Measuring maturity & building momentum47:30 Risks, success factors, and the next 24 months🌐 More at https://www.dataminded.com/#DataGovernance #FederatedGovernance #DataDomains #DataProducts #DataLeadership #BankingData #ABNAMRO #DataStrategy

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