SR 11-7 AI Model Risk
Management.
The Federal Reserve's SR 11-7 guidance defines how banks must manage model risk — and AI models raise the stakes. Abacus provides the infrastructure to develop, validate, and govern AI models with full SR 11-7 compliance built into every layer.
The Three Pillars of SR 11-7 for AI Models
SR 11-7 (OCC 2011-12) establishes three pillars of model risk management. Each pillar requires specific controls that become significantly more complex when applied to AI and machine learning models.
Model Development & Implementation
AI models require rigorous development standards — from data lineage and feature engineering to training methodology and deployment controls.
Documented model purpose and design rationale
Training data lineage and quality assessment
Feature selection methodology and justification
Performance benchmarking against stated objectives
Model Validation
Independent validation of AI models must go beyond traditional back-testing to evaluate fairness, explainability, and adversarial robustness.
Independent review by qualified validators
Conceptual soundness evaluation of AI architecture
Outcome analysis including bias and fairness testing
Sensitivity analysis and adversarial stress testing
Governance & Controls
Board and senior management must maintain oversight of AI model risk through clear policies, defined roles, and comprehensive model inventories.
Board-approved AI model risk appetite statement
Comprehensive model inventory and tiering
Defined roles across three lines of defense
Escalation procedures for model limit breaches
Purpose-Built Infrastructure for SR 11-7 AI Compliance
Abacus Studio and AbacusOS provide the model governance framework banks need to satisfy SR 11-7 requirements for AI and machine learning workloads — from development through retirement.
Abacus Studio — Model Governance Workflows
End-to-end model lifecycle management with version control, automated documentation, and examiner-ready audit trails.
Model Inventory & Tiering
Centralized registry of every AI model with automated risk tiering based on materiality, complexity, and usage scope — aligned with SR 11-7 inventory requirements.
Automated Documentation
Auto-generated model cards, validation reports, and change logs that satisfy examiner expectations without manual document assembly.
Validation Workflow Engine
Structured workflows for independent model validation with role-based sign-offs, challenge documentation, and findings tracking.
AbacusOS — Secure Model Runtime
On-premise AI infrastructure with continuous monitoring, drift detection, and immutable audit logging for every model interaction.
Ongoing Monitoring & Drift Detection
Continuous performance monitoring with automated alerts for data drift, concept drift, and output degradation — a core SR 11-7 requirement for models in production.
Immutable Audit Trails
Every model invocation, parameter change, and administrative action generates tamper-proof log entries with cryptographic integrity verification.
On-Premise Deployment
All model inference runs on your infrastructure. No data leaves your environment, satisfying data residency and third-party risk requirements.
SR 11-7 compliance. Automated for AI.
Banks using Abacus govern AI models with the same rigor examiners expect — model inventory, independent validation, ongoing monitoring, and examiner-ready documentation built into every workflow.
Manual vs. Automated Model Risk Management
See how purpose-built AI model governance compares to traditional spreadsheet-based MRM processes for SR 11-7 compliance.
| # | Feature | Manual MRM | Abacus AI Governance |
|---|---|---|---|
| ROW-01 | Model Inventory | Spreadsheets and manual tracking | Centralized registry with auto-discovery |
| ROW-02 | Model Documentation | Word documents assembled manually | Auto-generated model cards and reports |
| ROW-03 | Validation Workflow | Email-based, unstructured review | Structured workflows with role-based sign-offs |
| ROW-04 | Ongoing Monitoring | Periodic manual reviews | Continuous drift detection and alerting |
| ROW-05 | Audit Trails | Fragmented logs across systems | Immutable, tamper-proof audit logging |
| ROW-06 | Examination Readiness | Weeks of preparation per exam | Always-on compliance packages |
SR 11-7 AI Compliance
Model risk management built for AI
From model development to retirement, every stage of the AI lifecycle governed to examiner standards — automatically.
SR 11-7 Compliance Across the Three Lines of Defense
SR 11-7 requires clear accountability across the three lines of defense. Abacus maps controls and reporting to each line, ensuring no gaps in AI model risk oversight.
First Line — Model Owners
Model developers and business units maintain day-to-day accountability for AI model performance, limits, and escalation procedures.
Real-Time
Monitoring
Automated
Escalation
Second Line — Risk Management
Independent model risk management teams validate models, enforce policies, and maintain the enterprise-wide model inventory.
Independent
Validation
Enterprise
Inventory
Third Line — Internal Audit
Internal audit assesses the effectiveness of model risk governance with full access to immutable logs and compliance reports.
Immutable
Audit Trails
On-Demand
Reporting
100%
Model Coverage
Every AI model inventoried and tiered
< 1hr
Exam Readiness
Generate compliance packages on demand
24/7
Monitoring
Continuous drift detection and alerting
Zero
Data Egress
All inference on your infrastructure
Deploy AI That Passes Every Audit
900K monthly users went live in under 24 hours. SOC 2 Type II, ISO 27001, and HIPAA certified from day one.
AI infrastructure for regulated industries. On-premise deployment, zero data egress, examiner-ready compliance. Trusted by 900K monthly users processing 8M queries daily.
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