Business Search: Scores & Ratings
This guide explains how to interpret and utilize our scores and ratings to make confident risk decisions for your business.
Business Search returns two automated scores (KYB and Risk) with every completed search. These ratings help you make faster approval decisions without building complex rules. This guide explains what each rating means, how they're calculated, and how to use them in your verification workflow.
For an overview of Business Search, see Business Search: Basics. For complete verification workflows, see Business Search: Best Practices.
Scores vs. Ratings: A Quick Reference
Baselayer provides two types of evaluations to support different decision-making styles:
- Scores: Numerical values (0-100) for granular analysis and custom thresholds
- Ratings: Letter grades (A, B, C, F) for quick, consistent decision gates
Most customers use ratings for automated decisioning (simple and fast) while exposing scores to analysts for manual review cases (detailed and tunable).
Rating Scale
| Rating | Score Range | Interpretation |
|---|---|---|
| A | 90-100 | Strong assessment with perfect or near-perfect matching |
| B | 80-89 | Good-quality assessment with minor discrepancies |
| C | 60-79 | Weaker assessment with significant data matching issues |
| F | 0-59 | Critical concerns identified, including potential red flags |
KYB Rating & Score
The KYB rating evaluates the quality of the business verification search and initial company assessment.
Key Factors Influencing KYB Scores
| Factor | Description |
|---|---|
| Business Name Match | Accuracy between submitted name and official records |
| Address Match | Distance and relationship between submitted address and official records |
| Tax ID Verification | Whether the submitted TIN matches official business records |
| Secretary of State Registration | Existence of SoS registration in the state of the submitted address |
| Registration Status | Whether the domestic SoS registration is active |
What Each Rating Means
- A Rating (90-100): Highly reliable business verification with all key identifiers matching official records
- B Rating (80-89): Generally reliable verification with minor discrepancies in name or address matching
- C Rating (60-79): Verification with notable discrepancies; certain data points like TIN or address could not be adequately matched
- F Rating (0-59): Significant verification concerns, potentially including inactive registration status or critical mismatches
Risk Rating & Score
The Risk rating identifies potential financial risk factors common in lending and payment processing evaluations. It incorporates broader signals around financial, operational, and behavioral risk, combining Baselayer identity data with liens, litigations, application velocity, industry patterns, and business age.
Key Factors Influencing Risk Scores
| Factor | Description |
|---|---|
| Time in Business | Age of business operations |
| Litigations & Bankruptcies | Impact of existing lawsuits and bankruptcies |
| Liens (UCC & Tax) | Severity of tax and non-tax liens |
| Industry Category | Relationship to high-risk Merchant Category Codes (MCCs) |
| Website Analysis | Website legitimacy and consistency with submitted information |
| Inquiry Tracking | Frequency and volume of financial applications within the Baselayer network |
| KYB Score | High-quality identity verification reduces risk |
| Watchlist Hits | Potential involvement of sanctioned or prohibited individuals or entities |
Note: Risk scores incorporate data from optional products like liens, litigations, and website analysis. These products enrich risk assessment but aren't required for baseline scoring.
What Each Rating Means
- A Rating (90-100): Low-risk profile with established business history and no significant risk indicators
- B Rating (80-89): Generally low-risk with minor concerns in one or more categories
- C Rating (60-79): Moderate risk profile with multiple minor concerns or a single material concern
- F Rating (0-59): High-risk profile with multiple significant risk indicators
High-Severity Risk Flags
These scenarios carry disproportionately high predictive value within Baselayer’s identity and inquiry network.
The presence of any one of the following automatically lead the Risk Rating to C or F, depending on severity:
- Bankruptcy proceedings, eviction actions, or class-action lawsuits filed within the last five years
- High application velocity: more than four distinct-institution inquiries within seven days across the Baselayer Network
- Watchlist hits on OFAC, CSL, CNS, or FBI lists
- Recent tax liens, particularly those filed within the last five years
In these scenarios, Baselayer applies constraints to ensure consistent and conservative risk assessment.
Additional Risk Contributors
The scenarios below are considered lower-severity flags. Individually, they may not significantly impact the rating, but multiple occurrences in combination can still lead to a C or F:
- Time in business < 6 months, especially when paired with high inquiry velocity
- Multiple medium-risk litigations within the last five years
- A high volume of non-tax liens, inconsistent with the business’s operational age or size
- Inconsistent application patterns observed across the Baselayer Identity Network (e.g., varying TINs, names, or addresses)
- Low-quality KYB results - specially C or F KYB ratings
- Website and online-presence red flags, such as inactive or parked domains, or lack of operational signals
These indicators are incorporated into the weighted model and may interact with other components to downgrade the final rating.
Webhooks and Rating Updates
Because liens and litigations are requested after a search is first completed, Baselayer recalculates risk whenever new court or SoS data changes a business’s profile. When this affects the KYB or Risk score, Baselayer emits the webhook:
BusinessSearch.Updated
This ensures downstream systems stay aligned with newly discovered information (e.g., bankruptcy filed today, litigation discovered tomorrow, SoS status updated next week).
Making Decisions with Scores & Ratings
Recommended Approaches
- Automated Decision Frameworks
- A Ratings: Consider for straight-through processing
- B Ratings: Treat as verified, but establish certain risk limits
- C Ratings: Set thresholds based on your risk tolerance for specific data points, or manually review
- F Ratings: Consider for automatic enhanced review or rejection
- Manual Review Prioritization
- Focus reviewer attention on specific factors driving lower scores
- Use the granular components of the scores to guide additional verification steps
- Risk Policy Integration
- Incorporate both KYB and Risk ratings into your decision matrix
- Consider different weight allocations based on your business priorities
Real-World Example
A financial services company might structure their initial onboarding rules as:
| KYB Rating | Risk Rating | Outcome |
|---|---|---|
| A/B | A/B | Auto-approve |
| A/B | C | Manual review |
| C/F | A/B/C | Manual review |
| Any | F | Decline |
Continuous Improvement
Baselayer continuously refines scoring models based on:
- Emerging fraud and default patterns across the network
- Regulatory changes and compliance requirements
- Customer feedback and observed outcomes
If you've identified risk factors strongly correlated with fraud or default in your portfolio, share this with your Baselayer account manager to help improve risk assessment accuracy.
Next Steps
Implement ratings in your workflow:
- Business Search: Best Practices - Decision logic using ratings and rules
- Business Search: API Quickstart - Where to find scores in the API response
Understand contributing factors:
- Web Presence & Orderables - Website analysis and industry prediction
- Lien Search - How liens affect Risk ratings
- Docket Search - How litigation and bankruptcy affect Risk ratings
Handle edge cases:
- Handling IRS Outages - TIN verification impacts on KYB ratings
- Sole Proprietor Verification - Low KYB ratings for unregistered businesses
Need Additional Support?
Contact your Baselayer account manager for assistance with:
- Customizing rating thresholds for your use case
- Understanding specific rating outcomes
- Sharing risk patterns to improve scoring models
- Questions about implementation
Updated about 1 month ago
