SIGNAL GROUPS REFERENCE
Insurance Intelligence Signal Groups
Insurance Intelligence organizes detection into 4 signal groups covering 200 indicators across 40 languages.
All Signal Groups
Each signal group contains a set of specific indicators that the API can detect. Click a group to expand its signal list. Signal lists are available to customers - sign in to view them.
01
Claim Type
claim_type
50
50 signals - request access
for the complete list.
View 50 indicators
Claim Type
claim_type
The complete signal list is available to customers. Request access to view it.
02
Claim Fraud
claim_fraud
60
60 signals - request access
for the complete list.
View 60 indicators
Claim Fraud
claim_fraud
The complete signal list is available to customers. Request access to view it.
03
Claim Process
claim_process
40
40 signals - request access
for the complete list.
View 40 indicators
Claim Process
claim_process
The complete signal list is available to customers. Request access to view it.
04
Claim Details
claim_details
50
50 signals - request access
for the complete list.
View 50 indicators
Claim Details
claim_details
The complete signal list is available to customers. Request access to view it.
Reading Insurance Intelligence output
What you can safely infer from a result - and what you must not.
Intended task
Classify claim narratives into documented claim types and fraud-pattern signal groups - for routing and SIU review.
Input requirements
text- the only field analyzed; up to 4,096 Unicode code points. Over the limit is rejected withinput_too_long, never truncated.language- must be a language this analyzer supports. Unsupported codes are rejected with400 unsupported_language, never analyzed as a different language.analyzers- include"insurance"; up to 2 analyzers per request, one billed run each.- No context beyond
text- no user IDs, history, profiles, or attachments are read or inferred. - Analyzes the narrative text only - policy terms, claim history, and evidence files are not inputs.
Ordinary positive
“My parked car was hit overnight. The other driver left a note with their plate number and insurer.”
Safe inference: The narrative classifies as an auto claim with a third-party element - route it to the auto queue with subrogation flagged.
Confusing negative · Quotation
“The claimant's own witness said "we agreed to split the payout" - see the attached statement.”
What happens: Fraud-pattern signals can fire on the quoted statement. The signal flags that the language matches a documented fraud pattern - it does not weigh whose words they are or whether the statement is credible.
Why it's tricky: Claim files are full of quoted speech - witness statements, adjuster notes, reported conversations. A fraud-pattern signal on a narrative is a review trigger, never a finding: route it to your SIU, and let investigators weigh the evidence.
What you can safely infer
- Which documented claim types and fraud-pattern groups the narrative matched.
- That the same narrative on the same pinned configuration classifies identically - the receipt supports dispute review.
What you must not infer
- ✕That fraud occurred or that the claimant lied - fraud signals route review, they do not determine wrongdoing.
- ✕Coverage, liability, or payout decisions - those stay with your adjusters and policy terms.
- ✕That a claim with no fraud signal is verified legitimate - a missing signal is "not detected," never "cleared."
Boundary: Fraud signals are not proof of wrongdoing. They flag language consistent with documented fraud patterns so a reviewer looks - the determination stays with your SIU and your process.
Access the taxonomy through the API
Check Insurance Intelligence availability and endpoint programmatically via the public catalog endpoint - no authentication required. Include your API key to also retrieve taxonomy size and supported languages.
curl -X GET https://sentiqra.tech/v1/meta/domains/insurance \
-H "Authorization: Bearer sq_live_your_key_here"Example response (authenticated):
{
"catalog_version": "...",
"domain": {
"id": "insurance",
"name": "Insurance Intelligence",
"status": "production",
"taxonomy": { "groups": 4, "detection_labels": 200 },
"languages": [ ... ]
}
}Signals returned by the analyzers use code for the category or label slug - these correspond to the categories and indicators documented on this page.