Model Change Control Made Clear - How Banks Manage Model Updates, Risk and Retirement
3 December 2025·11 min
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Model change control is one of the most critical and risk sensitive stages in the entire model lifecycle. In this session, we break down how financial institutions manage model updates, enhancements, redevelopments, and retirements in a safe, transparent, and well governed way. If change is not controlled properly, even a small tweak can introduce significant risk. When managed well, change becomes a source of improvement, innovation, and trust.
This lesson is essential for anyone working in model development, validation, analytics, risk, audit, or governance—especially in organisations supervised by the PRA, ECB, Federal Reserve, MAS, or other global regulators.
📌 What You Will Learn in This Session
• What counts as model change
Understand the full range of modifications—from recalibration and parameter updates to structural redevelopment and system migration.
• How to distinguish material vs non material change
Learn how firms tier change significance, and why material changes require independent validation, governance approval, and updated risk classification.
• The end to end change control workflow
See how change requests are raised, assessed, validated, approved, deployed, and tracked through the model governance system.
• Post deployment testing and production assurance
Explore how banks ensure updated models run correctly, interact with downstream systems, and maintain expected behaviour before activation.
• How to retire a model safely
Discover the governance steps, documentation requirements, and transition planning needed when a model becomes obsolete or no longer fit for purpose.
• Managing parallel development, dependencies, and version control
Understand why uncontrolled development is a major risk—and how firms use repositories, lineage, and dependency mapping to prevent it.
• Change control for AI and machine learning models
Examine the unique challenges of retraining, explainability, concept drift, and determining when a retrained model becomes a “new” model.
• Global regulatory expectations
See how PRA SS1/23, SR 11 7, ECB guidance, MAS frameworks and other regulators assess model change management and documentation discipline.
🎯 Who This Session Is For
• Model developers and quantitative analysts
• Model validators and model risk specialists
• Risk managers, compliance teams, and internal auditors
• Senior leaders accountable for governance and oversight
• Anyone seeking to understand how model change affects decision making and regulatory compliance
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🔍 Keywords
model change control, model risk management, PRA SS1 23, SR 11 7, ECB TRIM, MAS FEAT, model retirement, model redeployment, model governance, model lifecycle, change management in banking, AI model retraining, version control, model inventory, challenger models, risk management training, the industry portal
model change controlmodel lifecyclemodel risk managementPRA SS1 23SR 11 7model governancemodel updatesmodel redevelopmentmodel retirementmodel validationmodel monitoringchange management banking
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