Where data turns into risk numbers
How BCBS 239, RDARR and MRM govern one dependency chain, why lineage breaks at the model boundary, and why poor input data drives model risk.
E-book
Bridging Data Governance and Model Risk Management
An integrated foundation for BCBS 239, ECB RDARR and trustworthy AI
October 12, 2026
Download the e-book
What's inside
Close the blind spot where data turns into risk numbers
In most banks, lineage, data quality evidence and accountability stop exactly where data enters a model. In this e-book, Jos Gheerardyn, CEO and Co-founder of Yields, explains why data governance and MRM should run as linked systems of record, and how banks can get there.
Who owns the chain
A shared RACI for the data-to-model chain, how the two regimes classify the same objects differently, and why supervisors are moving from principles to enforcement.
Link the platforms, don't merge them
Six integration patterns, from cross-referencing objects to integrated risk reporting, and how AI agents and MCP lower the cost of integration.
A roadmap to integrated oversight
Seven recommendations and a phased roadmap starting with Tier 1 models and high-risk AI, including what the EU AI Act's Article 10 means for data governance.
The e-book at a glance
The e-book in numbers
2/31
G-SIBs fully compliant with all BCBS 239 Principles
6
Integration patterns, from simple to ambitious
7
Recommendations for linking data governance and MRM
4
Roadmap phases, from foundation to integrated oversight
Who it's for
Written for the teams that own the data-to-model chain
For leaders who need to show supervisors that the data behind material models is governed.
Heads of MRM and model validation connecting data quality evidence to model limitations, approvals and validation.
Chief Data Officers and data governance leads extending lineage and CDE ownership across the model boundary.
CROs and RDARR programme leads building credible evidence for BCBS 239 and the ECB's RDARR expectations.
AI governance and compliance leads evidencing the EU AI Act's data governance requirements for high-risk AI systems.
About the
Author(s)
Jos Gheerardyn
CEO and Co-founder
Jos Gheerardyn is the co-founder and Chief Executive Officer (CEO) of Yields. Prior to his current role, he worked as both a manager and an analyst in the field of quantitative finance. With nearly 20 years of experience, he has worked with leading international investment banks and start-up companies. Jos is the author of multiple patents that apply quantitative risk management techniques to the energy balancing market. Jos holds a PhD in superstring theory from the University of Leuven.
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