Address Risk Scope

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.