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Rebuilding an IRRBB Gap Report: A Senior Data Architecture Case Study
An anonymised case study demonstrating how IRRBB gap reporting can be rebuilt as a governed semantic view, separating declared meaning from downstream report logic. Presented from a senior data architecture perspective.
Why IRRBB Gap Reporting Matters Today
Critical Regulatory Focus
Interest Rate Risk in the Banking Book (IRRBB) represents a critical regulatory and risk management focus for banks worldwide. As interest rate volatility increases, precise gap reporting becomes essential.
Accurate gap reporting underpins capital adequacy requirements, risk mitigation strategies, and strategic balance sheet management decisions. However, traditional IRRBB reports often mix declared business meaning with complex downstream logic, creating significant governance challenges.
Regulatory Compliance
Basel and EBA standards require transparent, auditable IRRBB measurement
Capital Management
Accurate gap analysis drives strategic capital allocation decisions
Risk Mitigation
Proactive identification of interest rate exposures across the banking book
The Challenge: Untangling Meaning from Report Logic
Embedded Assumptions
IRRBB gap reports typically embed assumptions and calculations deep within report logic, obscuring the original risk intent. Business rules become invisible, making it nearly impossible to trace how numbers are derived.
Governance Difficulties
This conflation of meaning and implementation leads to significant difficulties in validation, auditability, and regulatory compliance. Change management becomes risky as adjustments may inadvertently alter core definitions.
Architectural Challenge
Senior data architects face the complex task of rebuilding these reports to separate semantic meaning from technical implementation, ensuring both clarity and maintainability for future regulatory evolution.
Introducing a Governed Semantic View Approach
A New Paradigm for IRRBB Reporting
Our case study demonstrates rebuilding IRRBB gap reporting as a governed semantic layer. This innovative approach clearly defines the business meaning upfront, completely independent of downstream report logic and technical implementation details.
The semantic layer acts as a single source of truth, enabling consistent, transparent, and auditable IRRBB gap metrics across the entire organisation whilst maintaining flexibility for evolving business needs.
Raw Data Sources
Transactional systems and risk data
Semantic Layer
Governed definitions and business logic
Reporting Layer
Flexible gap reports and analytics
Key Benefits of the Semantic Rebuild
Improved Governance
Clear ownership and complete traceability of IRRBB gap definitions. Every metric has defined stewardship, approval workflows, and comprehensive audit trails showing who changed what and when.
Enhanced Flexibility
Downstream reports can evolve freely without altering core semantic definitions. New reporting requirements are met by composing existing governed views rather than rewriting foundational logic.
Regulatory Confidence
Easier validation and comprehensive audit trails fully aligned with Basel Committee and EBA standards. Demonstrate control frameworks and data lineage during regulatory examinations with confidence.
Behind the Scenes: Senior Data Architecture Perspective
Technical Excellence Meets Business Clarity
The rebuild focuses on data lineage, metadata management, and semantic modelling best practices drawn from enterprise architecture frameworks. Modern data platforms enable governed views that integrate seamlessly with existing risk systems.
This case study highlights practical implementation steps, technical challenges overcome, and valuable lessons learned from real-world deployment in a complex banking environment.
01
Data Lineage Mapping
Trace every data element from source to report
02
Semantic Model Design
Define business concepts independent of implementation
03
Governance Framework
Establish ownership, approval, and change control
04
Platform Integration
Deploy governed views within risk infrastructure
Real-World Impact: From Complexity to Clarity
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Reduction in Manual Reconciliation
Automated validation replaced error-prone manual processes
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Faster Report Generation
Streamlined semantic views accelerated monthly reporting cycles
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Improved Stakeholder Trust
Transparent lineage increased confidence in gap metrics
Transformative Results
This rebuild fundamentally transformed IRRBB reporting for a representative banking institution. Manual reconciliation efforts decreased dramatically whilst stakeholder trust in the numbers increased substantially.
The new architecture enabled genuinely proactive risk management, fully aligned with evolving regulatory expectations from both local and international supervisory authorities. The bank now responds to new requirements in days rather than months.
Watch the Presentation: Deep Dive into the Rebuild Process
Comprehensive Technical Walkthrough
Experience a step-by-step walkthrough of the semantic view design and implementation process. Gain valuable insights on balancing technical rigour with business clarity whilst maintaining pragmatic delivery timelines.
The presentation provides practical tips specifically for data architects, risk managers, and compliance teams navigating similar challenges in their own organisations.
Semantic layer architecture patterns
Governance framework implementation
Integration with existing risk systems
Change management and stakeholder engagement
Who Should Watch This Video?
Data Architects & Engineers
Senior professionals working in banking risk, finance, and data platform teams who design and implement enterprise data solutions
Risk Managers
ALCO members and treasury professionals responsible for IRRBB oversight, gap analysis, and strategic balance sheet management
Compliance Officers
Auditors and regulatory compliance professionals seeking enhanced transparency, traceability, and validation in IRRBB reporting frameworks