Usage Scope
Learn how Socure Address Risk predicts fraud risk and validates the linkage between an address and an identity.
Key outputs
Address Risk Score
Probabilistic score between 0.001 and 0.999 indicating the likelihood of fraud associated with a physical address.
- Higher scores = higher risk of fraud.
- Evaluates deliverability, tenure, property type, and fraud patterns.
- Powered by internal and external data sources.
- Multiple model scores may be returned in a single response.
Name–Address Correlation
Value between 0.01 and 0.99 showing how strongly an address is linked to the consumer’s name.
- Very high confidence for verified full-name matches.
- Supports fuzzy matching and partial matches (e.g., last name only).
- Reason codes explain the underlying correlation signals.
- Improves trust in onboarding, delivery checks, and profile updates.
Industries it fits
- Financial services: Account opening, fraud prevention, progressive onboarding
- E-commerce & retail: Checkout fraud prevention, shipping address validation, return abuse detection
- Logistics & delivery: Ensure goods are sent to legitimate, deliverable addresses
- Gaming & media: Detect fraud in prize delivery, bonus abuse, duplicate accounts
- Telecom: Validate residential addresses during profile changes and service setup
- Government & benefits: Verify residential addresses for eligibility and fraud prevention
- Plus other digital onboarding and fraud risk workflows
Business and operational outcomes
1. For fraud and risk teams
- Identify high-risk addresses in real time.
- Detect risky address types (e.g., correctional facilities, PO boxes, commercial drops).
- Leverage multiple model scores per call for testing and migration.
- Gain transparency with reason codes for both risk and correlation.
2. For growth and onboarding teams
- Progressive onboarding: Establish trust with minimal inputs (name + address).
- Reduced friction: Allow good users through while flagging suspicious addresses.
- Adaptive signals: Models tuned for different fraud/risk trade-offs.
3. For support and operations
- Fewer escalations: Clearer fraud signals reduce review queues.
- Transparent explanations: Reason codes help agents understand outcomes.
- Lightweight integration: Only a few required fields keep implementation fast.
Performance considerations
- Fast responses: Sub-second latency on average in production.
- Always available: 99.99%+ uptime with global redundancy.
- Built for scale: Supports tens of millions of risk checks per day.
- Smart models: Multiple models run in parallel to optimize accuracy and fraud capture.
Boundary conditions
- Name + address are required: Correlation accuracy improves when complete address details are included (e.g., city, postal code).
- Multiple models: Customers should test challenger vs. production models to tune thresholds.
- Available in USA only: This feature is limited to the U.S.A. and is not supported in other regions.
Updated 3 months ago