Baselayer’s Litigation & Bankruptcy Search provides a programmatic way to surface lawsuits, regulatory actions, and bankruptcy proceedings associated with a business.
Litigation data is a critical part of KYB, credit underwriting, fraud prevention, and operational risk assessment.

This guide details:

How to request and retrieve litigation and bankruptcy data
How to interpret docket structures
How to differentiate high-risk vs contextual legal activity
How to use match levels correctly
How to operationalize litigation insights into automated decisioning
How to adapt decisioning logic for different types of underwritings

1. Introduction: Why Litigation Data Matters

Legal proceedings can impact a business’s finances, operations, reputation, and regulatory exposure. Litigation insights help answer:

Is the business involved in bankruptcy proceedings?
Is the business facing financial, contractual, or regulatory disputes?
Are there patterns of lawsuits indicating structural or operational issues?
Does the business appear repeatedly across multiple courts or jurisdictions?

Baselayer’s litigation search retrieves:

Lawsuits (civil, commercial, federal, and state court cases)
Bankruptcy proceedings
Regulatory or administrative cases
Trademarks, service marks, and patent application history
Docket details and documents (when requested)

Litigation data is used in identity verification, credit decisioning, fraud screening, vendor risk assessments, and manual underwriting workflows.

Key Concepts (Glossary)

Docket

A legal case record filed in a court, including metadata such as title, case type, court venue, and case status.

Bankruptcy Case

A legal proceeding under federal bankruptcy law, most commonly Chapter 7 or Chapter 11.

Case Type

A textual classification provided by the court (e.g., contract dispute, fraud, eviction, class action, small claims, trademark).

Match Level

Indicates how closely the docket matches the business name:

EXACT → exact legal-name match

SIMILAR → fuzzy match or name variant (e.g., alias, partial match, attorney error)

Some Baselayer users review all matches (including SIMILAR) to avoid missing anything; others only surface EXACT matches to reduce false positives.

Status

The status of a legal case as provided directly by the court or jurisdiction (e.g., Open, Closed, Pending, Disposed, Terminated).
Status values vary significantly by court and are not standardized across states or court systems.

Baselayer also provides a simplified normalized_status field (open or closed) to offer a consistent, easy-to-use version of case status across jurisdictions.

Court

The jurisdiction where the case was filed (e.g., NY Supreme Court, US Bankruptcy Court, Trademark Trial and Appeal Board).

Risk Level

A Baselayer-generated assessment of the severity or importance of a docket (high, medium, low, no_risk).
This field provides an at-a-glance signal to help customers easily prioritize reviews.

2. How to Request a Litigation Search

A litigation search is a two-step process:

Step 1: Initiate the Search

Use the business_id obtained from a Business Search.

POST /docket_searches  
{  
  "business_id": "uuid"  
}

Upon submission, Baselayer emits:

DocketSearch.submitted → search started
DocketSearch.completed → results ready

A standard request takes 5–20 seconds depending on the jurisdiction and the number of dockets retrieved.

Step 2: Retrieve the Results

The DocketSearch.completed webhook contains the complete results.
You can also retrieve them via API:

GET /docket_searches/{search_request_id}

The response includes an array of dockets, each representing one legal case.

Retrieving Case Details & Documents

Note:

Most customers do not need case details or exhibits for standard workflows.
If you expect to rely on documents or detailed case timelines, your Baselayer representative can help you design the right approach based on your jurisdictions, product needs, expected usage and cost.

The main litigation search returns high-level docket information.
If you need additional context or documents for a specific case, Baselayer provides two optional endpoints: details and exhibits.

Both follow a simple two-step workflow:

PUT request → initiates retrieval

GET request → returns the full data once ready

Case Details

PUT /dockets/{docket_id}/details

Initiates retrieval of the case’s detailed timeline, including updates, filings, and court actions.

Retrieve the results with:

GET /dockets/{docket_id}/details

The updates array for the docket will now include a chronological list of case events (hearing notices, filings, motions, orders). Some updates may reference exhibits associated with that event.

Details are helpful when you need a clearer view of how the case has progressed, but most customers only use this for deeper underwriting on large or complex exposures.

Exhibits (Documents)

PUT /dockets/exhibits/{docket_exhibit_id}

Initiates retrieval of a specific exhibit (e.g., a PDF document referenced in the case details) when available.

Retrieve the document with:

GET /dockets/exhibits/{docket_exhibit_id}

Availability varies by court, and some jurisdictions may require access fees.

3. Understanding the Returned Data

Each docket includes the following key structured fields:

is_bankruptcy: Indicates whether the case is a bankruptcy proceeding
bankruptcy_type: Specifies the bankruptcy classification (e.g., Chapter 7, Chapter 11)
case_type: The court-provided description of the nature of the case (e.g., contract dispute, eviction, trademark)
normalized_status: Baselayer’s standardized case status (open or closed), derived from the raw status from court data
risk_level: Baselayer’s assessment of case severity (high, medium, low, no_risk)
match_level: Indicates how closely the case title matches the business name (EXACT, SIMILAR)
court / title / docket_number: Identifiers and context for the case, provided directly by the court
date_filed: The date when the case was originally filed
last_synced_at: The date and time when Baselayer last synced this docket with the court’s system

Not all courts provide complete metadata. Coverage varies by jurisdiction, and older or county-level cases may be partially populated or missing certain fields.

4. How Baselayer Categorizes Risk Levels

Baselayer provides a risk_level per docket as an at-a-glance signal.
This categorization combines case type, case age, match level, and court metadata.

The following logic is intentionally simplified for customers:

High Risk

risk_level = high if any of the following:

Court or filing indicates financial or legal exposure
Bankruptcy cases
Eviction or class action cases

Medium Risk

Cases filed within the last 5 years that are not closed and do not meet other risk criteria.

Low Risk

Cases filed more than 5 years ago, or small claims cases.

No Risk

Trademarks, service marks, IP filings, or administrative filings.

Dockets with normalized_status = closed are also categorized as no_risk.

Important:

While Baselayer provides this field out-of-the-box, customers can build their own internal categorization rules and decisioning workflows on top of it, tailored to your risk appetite and credit policy.

Baselayer is happy to support the design of these workflows. We have supported hundreds of customers in building litigation-driven underwriting and KYB logic, and can advise on best practices, typical patterns, and the most effective ways to operationalize this signal.

5. Best Practices for Interpretation

1. Always Prioritize Bankruptcy Proceedings

Any docket with is_bankruptcy = TRUE is a critical event.
Regardless of ticket size or risk tolerance, a recent bankruptcy indicates:

Insolvency
Court-supervised restructuring or liquidation
Restrictions or prohibitions on extending credit

As a best practice, always flag bankruptcy cases for review if date_filed is within the last 5–7 years.
Older bankruptcies can still be relevant for certain lenders but generally carry lower immediate risk.

2. Evaluate Open, Recent, and Relevant Civil Cases

Civil cases that are open and recent (filed within the last 5 years) often signal ongoing operational or financial issues such as:

Contract or payment disputes
Fraud or misrepresentation allegations
Vendor, supplier, or customer conflicts

Open + recent = higher risk.
Closed or very old cases typically pose low immediate concern.

Important note on case status:

Courts use hundreds of different status codes, and terminology varies widely across jurisdictions. To ensure consistency, Baselayer only marks a docket as normalized_status = closed when 100% certain the case is resolved.

This conservative approach avoids mistakenly classifying an active case as closed, but it may result in some cases remaining marked as “open” even when they are resolved.

For decisioning, customers should treat normalized_status as a safe, conservative indicator of whether a case may still be active.

3. Understand the Case Type

Courts use multiple case types, so this field should be treated as a signal, not a strict taxonomy. Some case types are more relevant to underwriting, while others are largely informational.

Case type is most useful for helping you define which dockets should always enter your manual review process.
As a best practice, create an internal list of “must-review” or high-risk case types, for example:

Bankruptcies
Evictions
Class actions
Fraud, regulatory, or significant financial disputes

These cases carry higher potential impact and should always be surfaced to an underwriter.

At the same time, consider removing clearly low-relevance case types - such as trademarks, service marks, or patent filings - to reduce noise and keep your review workflow focused.

Baselayer’s risk_level offers a strong starting point for this categorization, but customers may tailor the case types they care about based on their own product, industry, or risk policies.

4. Use Match Levels Correctly

Court records in the U.S. are highly fragmented: different courts maintain separate databases with inconsistent search capabilities. Because most jurisdictions do not provide reliable identifiers (such as EINs or registration numbers), litigation searches must rely primarily on business name matching.

The match_level field indicates how closely the court’s case title aligns with the business name you searched. This field helps determine how closely a docket aligns with the business being reviewed.

Customers differ in how strict they want to be, so match level should be aligned with your internal risk appetite and operational model.

EXACT matches

A precise match to the business name.
High confidence the case refers to the entity being reviewed.

SIMILAR matches

A close but not perfect match. This may indicate:

A DBA or trade name
A partial match
A name variant
A variation used by counsel
A related entity or affiliate

SIMILAR matches help avoid missing relevant cases, but may introduce occasional false positives for similarly named companies.

Recommendation:

Match level strategy typically depends on operational priorities:

If minimizing noise is the priority:
High velocity of operations / automation focus
Small to medium-sized loan tickets
Concerns about false positives
→ use EXACT only

If thoroughness is the priority:
Deep due diligence and underwriting
Medium to large-sized loan tickets
"Can't miss anything" mindset
→ use EXACT + SIMILAR

5. Patterns Matter

Multiple cases, especially of the same type, are often more meaningful than a single docket.

Examples:

Repeated payment disputes
Multiple lender cases
Recurring employment or contractor claims
Multiple recent evictions or class actions

Patterns suggest structural issues in operations or finances.

6. Recommended Risk Flags & Thresholds

Litigation data varies widely across jurisdictions, case types, and match levels. Baselayer’s risk_level classification is designed to simplify this complexity and provide a consistent signal for prioritization, incorporating key attributes like case type, case age, status, match level, and court metadata.

High-Risk Litigation Cases (Always Flag)

If risk_level = high, the case should enter your manual review process - regardless of loan size or automation level.
This category already captures the most material scenarios, including:

Bankruptcy proceedings
Significant financial or operational disputes
Evictions, class actions, and similar high-severity categories

For additional accuracy, you can filter by cases where date_filed is under 5-7 years old - to ensure recency and importance of the case.

Contextual Litigation Cases (Review Only When Relevant)

Cases categorized as medium, low, or no_risk are typically informational.
These should be escalated only when:

they align with your internal list of “must-review” case types,
they relate to other risk signals in the file, or
your product or industry requires broader scrutiny (e.g., marketplaces or compliance-heavy businesses)

This avoids unnecessary noise while preserving full transparency.

If you want to take your review a level deeper, you may also surface dockets where risk_level = medium. This category can include many case types and may provide relevant context depending on your product, industry, or underwriting model.

Baselayer’s Recommendation

Small-Ticket, High-Velocity Products

Goal: maximize speed, minimize noise.

Recommended:

Flag only dockets where risk_level = high
- Optionally surface risk_level = medium dockets for certain case types or industries
Display all other dockets as a non-blocking tag (“Dockets Present”)
Use EXACT match_level by default
- Optionally surface SIMILAR matches for certain case types or industries

Mid- to Large-Ticket Underwriting

Goal: full visibility and thorough due diligence.

Recommended:

Include all dockets (EXACT + SIMILAR) in the underwriting package
Always highlight high-risk cases
Use contextual cases to understand stability, governance, and operational maturity
Pay attention to repeated case patterns

7. Putting It All Together

Baselayer’s litigation data brings clarity to a fragmented court system and helps you understand a business’s legal and financial exposure.

When used effectively, it strengthens your underwriting, fraud detection, and KYB workflows without overwhelming your teams.

To operationalize the product effectively:

Start withrisk_level : treat all high-risk dockets as must-review cases.
Usematch_level intentionally: rely on EXACT for automation-heavy flows; include SIMILAR for deeper due diligence.
Define your own “must-review” case types such as bankruptcies, evictions, or major financial disputes.
Remove low-relevance case types where appropriate (e.g., trademarks) to reduce noise.
Review patterns, not just isolated cases: multiple similar filings often reveal underlying structural issues.
Adapt the workflow to your product:
- small-ticket → review only high-risk signals
- large-ticket → incorporate full litigation context

Following these practices ensures litigation data becomes a precise, scalable input to your credit, KYB, and risk workflows; delivering the right signals without creating unnecessary friction.