State Licensing Data Integration: Technical Guide

Integrating with state licensing data improves verification accuracy and reduces manual effort. Organizations with direct state integrations verify licenses 5x faster than those using manual methods. This guide covers the technical aspects of building state licensing data integrations.

State Data Landscape

Current Accessibility

Data Source	Access Type	Coverage
Nursys (nursing)	API available	45+ states
NMLS (mortgage)	API available	All states
FSMB (physicians)	API available	All states
State board websites	Scraping/manual	Varies
Direct state APIs	Limited	~25 states

Data Availability Tiers

Tier 1 - API access:

• Real-time queries
• Structured data response
• Authentication required
• Rate limits apply

Tier 2 - Bulk data:

• Periodic data dumps
• CSV/XML formats
• Update schedules vary
• May require agreement

Tier 3 - Manual only:

• Website lookup required
• No programmatic access
• Most labor intensive
• Least reliable for automation

API Integration Approaches

Direct State Board APIs

When available, connect directly:

Request: GET /api/v1/licenses/{license_number}
Response: {
  "license_number": "RN12345",
  "status": "ACTIVE",
  "expiration_date": "2027-03-31",
  "discipline": [],
  "compact_member": true
}

Implementation considerations:

• Authentication methods vary
• Rate limiting differs by state
• Error handling essential
• Caching improves performance

National Database APIs

Leverage consolidated databases:

NMLS Consumer Access:

• All MLO licenses nationally
• Real-time status
• Disciplinary history
• Company associations

Nursys:

• Participating state nursing licenses
• Quick confirm or detailed reports
• Disciplinary alerts
• Compact status

Aggregator Services

When direct access unavailable:

• Third-party verification APIs
• Higher cost per verification
• Wider coverage
• Simplified integration

Data Modeling

License Entity Structure

interface ProfessionalLicense {
  // Identifiers
  licenseNumber: string;
  stateCode: string;
  professionType: string;

  // Holder information
  holderName: {
    first: string;
    last: string;
    middle?: string;
    suffix?: string;
  };

  // Status
  status: 'ACTIVE' | 'INACTIVE' | 'SUSPENDED' | 'REVOKED' | 'EXPIRED';
  issueDate: Date;
  expirationDate: Date;

  // Additional data
  compactMember: boolean;
  restrictions: string[];
  disciplinaryActions: DisciplinaryAction[];

  // Metadata
  lastVerified: Date;
  verificationSource: 'PRIMARY' | 'SECONDARY';
}

Handling State Variations

Different states return different data:

Field	State A	State B	Your System
Name	”John Smith"	"SMITH, JOHN”	Normalized
Status	”CURRENT"	"ACTIVE”	Mapped
Expiration	”03/31/2027"	"2027-03-31”	Standardized

Build normalization layer to handle variations.

Implementation Architecture

Component Design

┌─────────────────┐     ┌──────────────────┐     ┌─────────────┐
│  Your System    │────▶│  Integration     │────▶│  State      │
│  (HR/Cred)      │     │  Layer           │     │  APIs       │
└─────────────────┘     └──────────────────┘     └─────────────┘
                              │
                              ▼
                        ┌──────────────────┐
                        │  Data Store      │
                        │  (Cache/DB)      │
                        └──────────────────┘

Key Components

Integration layer responsibilities:

• Route requests to appropriate source
• Handle authentication
• Normalize responses
• Manage rate limits
• Handle errors gracefully

Caching strategy:

• Cache verification results
• Set appropriate TTL (24-72 hours typical)
• Invalidate on known changes
• Balance freshness vs. performance

Error Handling

Common Error Scenarios

Error Type	Handling Strategy
Rate limit exceeded	Implement backoff, queue requests
Source unavailable	Fall back to cached data, flag for manual
Invalid license number	Validate format before request
No record found	Distinguish from errors, verify format
Authentication failure	Refresh credentials, alert on persistent

Resilience Patterns

Circuit breaker:

• Open circuit after repeated failures
• Prevent cascade failures
• Auto-recover after timeout

Retry logic:

• Exponential backoff
• Maximum retry limits
• Different strategies by error type

Compliance Considerations

Data Privacy

When handling license data:

• Store only necessary fields
• Implement access controls
• Log all access
• Retention policies
• Secure transmission (TLS)

Terms of Use

State databases often require:

• Signed agreements
• Usage restrictions
• Attribution requirements
• Prohibited resale
• Audit rights

FCRA Considerations

If verification affects employment:

• Understand FCRA applicability
• Provide required disclosures
• Allow dispute processes
• Document procedures

Monitoring and Maintenance

Health Monitoring

Track key metrics:

• API availability by source
• Response times
• Error rates
• Cache hit ratios
• Verification volumes

Alerting

Set alerts for:

• Source outages
• Elevated error rates
• Rate limit approaches
• Certificate expirations
• Authentication failures

Ongoing Maintenance

Plan for:

• API version changes
• State website redesigns
• New state requirements
• Credential rotation
• Schema updates

Performance Optimization

Batch Processing

For high-volume verification:

• Batch requests where APIs support
• Process during off-peak hours
• Parallelize across sources
• Prioritize based on expiration

Caching Strategy

Scenario	Cache TTL
Active license	24-48 hours
Recently verified	72 hours
Disciplinary status	12-24 hours
Compact membership	7 days

Rate Limit Management

• Distribute requests over time
• Implement queue system
• Monitor approaching limits
• Request limit increases if needed

Testing Strategies

Unit Testing

• Mock API responses
• Test normalization logic
• Verify error handling
• Check validation rules

Integration Testing

• Use sandbox environments where available
• Test with real responses (carefully)
• Verify end-to-end flows
• Load testing for volume

Monitoring in Production

• Real transaction monitoring
• Comparison with manual verification
• Anomaly detection
• Regular audits

Key Takeaways

• State data accessibility varies significantly
• Build a normalization layer for consistency
• Implement robust error handling
• Cache strategically for performance
• Plan for ongoing maintenance

Explore our licensing data API for simplified access to professional licensing data.