DAISORO

F3.2 / Insurance Product Intelligence

Coverage & Exclusions Ontology

Structured coverage, exclusions, sub-limits, deductibles, add-ons, policy wording evidence, and plain-English term normalization across motor products.

secondary priority

Financial Services & Insurance

Insurance Product Intelligence

Scoped file delivery / Cloud/data-platform push

Schema preview

Coverage Ontology

sample structure
01Product, coverage type, and policy wording reference
02Exclusion, sub-limit, deductible, and add-on labels
03Plain-English normalized term
04Evidence URL/archive and captured date
05QA/confidence state and version hash

What it captures

  • Product, coverage type, and policy wording reference
  • Exclusion, sub-limit, deductible, and add-on labels
  • Plain-English normalized term
  • Evidence URL/archive and captured date
  • QA/confidence state and version hash

Decision workflows supported

  • Product design
  • Coverage benchmarking
  • Compliance/transparency review preparation
  • Value scoring beyond price

Buyer roles

  • Motor underwriting teams
  • Pricing and actuarial teams
  • Product and distribution leaders
  • Claims and repair strategy teams
  • Data and AI teams

Delivery models

  • Scoped file delivery
  • Cloud/data-platform push
  • Schema/API integration scoping

Decision workflows supported

Pricing strategy

Monitor offer changes, bundle mechanics, channel variance, and competitor moves.

CVM / retention

Feed churn, retention, and portfolio-risk workflows with structured market signals.

Data & AI ingestion

Use stable IDs, schema fields, evidence references, and version states in AI pipelines.

Regulatory transparency

Review public terms, fair-use labels, evidence, and change history without overclaiming legal status.

Sample structure

Non-downloadable field preview

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This preview shows the record structure without presenting field examples as live data.

Product, coverage type, and policy wording referenceidentifier / label
Exclusion, sub-limit, deductible, and add-on labelsidentifier / label
Plain-English normalized termstructured value
Evidence URL/archive and captured datestructured value
QA/confidence state and version hashevidence metadata

Dataset scope

Planned; market, source, and document availability dependent.

No legal interpretation or compliance guarantee is implied.

Source tier, Evidence URL or archive, Captured date, Screenshot or document reference where available, Version hash, QA/confidence state

Proof fields travel with the record.

Records are designed to preserve the source, capture state, and QA context needed for downstream review.

Source URLCapture timestampScreenshot referenceDocument referenceVersion hashQA state

Offer change trail.

1First seencapturevh_01a2
2Promo price addedprice deltavh_02b7
3Eligibility changedrule updatevh_03c4
4Allowance updatedbundle deltavh_04f9
5Offer retiredstatus changevh_05d1

Related datasets

Adjacent signals

Request sample dataset
F3.1

Multi-Carrier Quote Matrix

Financial Services & InsuranceInsurance Market Intelligence

Observable motor-insurance quote intelligence structured by carrier, channel, persona, vehicle, coverage level, premium, deductible, add-ons, quote outcome, and evidence.

Competitive quote benchmarkingPricing simulation
Market and countryCarrier, broker, aggregator, and direct channel
View dataset
F3.3

Insurance Comparison Engine

Financial Services & InsuranceInsurance Market Intelligence

Comparison layer designed to turn quote, coverage, vehicle, and evidence records into value rankings, coverage gaps, segment positioning, and executive-ready market views.

Executive market intelligenceProduct and pricing decisions
Quote record referenceCoverage ontology reference
View dataset

Next step

Request a sample or map this dataset to your workflow.

DAISORO can discuss market scope, evidence depth, delivery model, and sample structure for your workflow.

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