Model Validation
Field Guide
A Practical Handbook for High-Risk Model Review in the Age of AI and Alternative Data
Master the essential checklists and frameworks for validating models and ensuring regulatory compliance in financial services.
Model Validation
Field Guide
A Practical Handbook for High-Risk Model Review in the Age of AI and Alternative Data
Master the essential checklists and frameworks for validating models and ensuring regulatory compliance in financial services.
Why This Guide Matters
Stay Compliant, Stay Competitive
Meet FDIC and OCC requirements with comprehensive validation frameworks designed for high-risk models.
Practical Checklists
Step-by-step validation checklists covering conceptual soundness, data quality, and process verification.
Risk Management
Identify and mitigate model risks before they impact your business or regulatory standing.
What's Inside the Guide
Based on SR 11-7 regulatory guidance, this field guide provides practical checklists for the requirements and tests you need to run for comprehensive model validation.
1. Conceptual Soundness
- Model purpose and design validation
- Variable selection assessment
- Assumption and limitation review
2. Data Quality Assessment
- Data source appropriateness
- Bias and fairness testing
- Quality control procedures
3. Process Verification
- Code review and testing
- Mathematical verification
- Implementation controls
4. Outcomes Analysis
- Back-testing and benchmarking
- Sensitivity and stress testing
- Fair lending analysis
5. Ongoing Monitoring
- Performance tracking
- Threshold management
- Alert systems
6. Governance Framework
- Access and change controls
- Documentation standards
- Role definitions
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This guide is designed for compliance, legal, and data science teams working with high-risk models in financial services.
Ready to Strengthen Your Model Validation?
Download your free copy of the Model Validation Field Guide and start implementing best practices for high-risk AI model review today.