Help banks, insurers, and fintech firms adopt AI safely—with model risk management, explainability, and compliance frameworks designed for SR 11-7, FCRA, ECOA, and other financial regulations.
Federal regulators (Fed, OCC, CFPB) demanding explainability, fairness testing, and model risk management
Impact: AI projects blocked or delayed 6-12 months
SR 11-7 requirements for model validation, documentation, and governance are extensive and specialized
Impact: Expensive validation, ongoing compliance burden
ECOA and FCRA require explainable credit decisions without bias across protected classes
Impact: Fear of discrimination lawsuits, penalties
Core banking platforms from 1980s-90s with limited APIs and outdated technology
Impact: Difficulty integrating modern AI
Fraudsters using AI themselves; traditional rules-based systems falling behind
Impact: Rising fraud losses ($billions annually)
Customers expect instant decisions, personalized service, and digital-first experiences
Impact: Loss to fintech competitors
Financial data is high-value target; regulators demand robust security
Impact: Breaches, penalties, reputational damage
Margin compression, compliance costs, and technology debt consuming profits
Impact: Need to do more with less
Compliant-by-design AI solutions that regulators approve and deliver measurable ROI.
We speak regulator—and build AI that passes their scrutiny.
Complete model lifecycle management that satisfies regulators and auditors.
Model Development Document (MDD)
Comprehensive documentation of all development decisions
Data Dictionary & Lineage
Complete data source documentation
Code Repository
Version-controlled model code
Independent Validation Report
Third-party assessment of model quality
Limitations Documentation
Known model assumptions and boundaries
Approval Recommendation
Pass/conditional pass/fail determination
AI that explains its decisions in ways regulators and consumers understand.
Example Explanation:
"Loan denied due to: 1) Debt-to-income ratio 48% (threshold 43%), 2) Credit utilization 85% (threshold 50%), 3) Recent delinquency in past 12 months"
Example:
"If debt-to-income ratio decreased from 48% to 40%, loan would likely be approved"
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Typical Budget Range: $250K–$2M+ per use case (depends on institution size and complexity)
We've helped clients successfully navigate Fed, OCC, CFPB, and state regulator examinations.
Model risk management practices
Model validation quality and independence
Fair lending compliance and testing
AI explainability and transparency
Data quality and governance
Model monitoring and outcomes analysis
Third-party risk management
Model inventory completeness
Documentation quality
Governance structure and effectiveness
Material Findings Related to Our AI
Successful Examinations
Regulatory Relationships
Regulatory Guidance
Client: $12B regional bank, 150 branches
Manual underwriting, 7-14 day turnaround, 32% abandonment
AI loan underwriting with document extraction
SR 11-7 validated, FCRA/ECOA compliant
Faster Processing
7-14 days → 15 minutes
Annual Savings
More Loans Funded
Reduced abandonment
Payback Period
✓ Passed Fed Examination with Zero Findings
Client: P&C insurer, $5B premium, 500K claims/year
21-day average claims processing, high fraud, customer complaints
Automated claims intake, fraud detection, payment processing
Fair claims handling, audit trails, state regulatory approval
Faster Processing
21 days → 3 days
Claims Auto-Processed
Fraud Detection Improved
Annual Savings
✓ NPS Improved +34 Points
Client: Neobank, 2M customers, $500M deposits
Fraud losses $8M annually, false positives alienating customers
Real-time fraud detection with ML
Model validation, monitoring, ongoing governance
Fraud Losses Reduced
56% reduction
False Positive Reduction
Customer Friction
Significantly reduced
Payback Period
See how we're transforming operations across different sectors
Comprehensive AI solutions tailored for financial services
Let's discuss how to implement AI that satisfies regulators and delivers ROI.
Get a free assessment of your AI readiness and regulatory compliance gaps
Schedule Compliance ReviewDiscuss SR 11-7 model risk management for your AI initiatives
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