Motor insurer · InsurTech
Every underwriting signal you need. One VRM, one call.
Motor underwriters need fuel type, engine size, emissions standard, and maintenance history at quote time — not just the vehicle make and model. Chasing the customer for this data adds friction and yields unreliable answers. Zyfy pulls it directly from DVLA and DVSA: authoritative, structured, and available at the point of a quote request.
Relevant signals
These fields are returned on every response and are ready to wire into your application logic.
| Signal | Relevance | What it tells you |
|---|---|---|
| fuelType | Critical | Petrol, diesel, electric, or hybrid_electric from DVLA. Fuel type correlates with claim frequency, repair cost, and fire risk profile. |
| engineCapacityCc | Critical | Engine displacement in cubic centimetres from DVLA. A direct proxy for performance tier when model name alone is ambiguous. |
| signals.euroEmissionStandard | High | Euro 1–6 or electric from DVLA. Older standards correlate with higher vehicle age and maintenance overhead — useful as a risk proxy. |
| signals.co2EmissionsGPerKm | High | CO₂ output in grams per kilometre from DVLA. Correlates with engine size and vehicle class — useful for commercial fleet risk banding. |
| signals.failureClusters | High | Categories of recurring MOT failure items, e.g. "brakes", "steering", "lights". Brake or steering clusters are direct safety and claim risk indicators. |
| vehicleAgeYears | Medium | Age in decimal years from year of manufacture. Older vehicles have higher parts costs and increased frequency of mechanical claims. |
| signals.ncapSafetyRating.overallStars | Medium | Euro NCAP overall safety star rating 0–5 matched by make and year. Safety assist and adult occupant sub-scores provide additional granularity for newer vehicle risk banding. |
Live example
A real-world request and the response it returns.
Request
curl https://zyfy.uk/v1/vehicle/AB12CDE \
-H "X-API-Key: your_api_key"Response
{
"registration": "AB12CDE",
"make": "BMW",
"model": "3 SERIES",
"colour": "BLACK",
"fuelType": "diesel",
"engineCapacityCc": 2143,
"yearOfManufacture": 2009,
"vehicleAgeYears": 17,
"monthOfFirstRegistration": "2009-06",
"summary": {
"vehicleRiskLevel": "medium",
"motRiskLevel": "medium",
"conditionBand": "fair"
},
"signals": {
"co2EmissionsGPerKm": 186,
"euroEmissionStandard": "EURO 4",
"ulezCompliant": false,
"taxStatus": "taxed",
"taxDueDate": "2026-07-01",
"motStatus": "valid",
"motExpiryDate": "2026-05-22",
"odometerTrend": "consistent",
"latestOdometerMiles": 118540,
"motPassRate": 0.75,
"totalMotTests": 12,
"totalMotFailures": 3,
"totalAdvisoryCount": 11,
"lastMotDate": "2025-05-22",
"lastMotResult": "passed",
"failureClusters": ["brakes", "steering", "lights"]
},
"enrichmentPending": false
}Example data is illustrative only. Responses shown include a subset of signals for clarity — the full response contains additional fields. See the signal reference for the complete list.
What you get
- ✓ Verified vehicle data at quote time — Engine size, fuel type, and emissions standard come directly from DVLA — not self-reported by the customer. Eliminate a source of deliberate and accidental misrepresentation.
- ✓ MOT history as a maintenance proxy — Repeated brake failures, oil leaks, and suspension advisories in MOT history correlate with poor maintenance. Surface this at underwriting, not at claims.
- ✓ No additional customer friction — The customer provides a VRM and you look everything else up. No lengthy questionnaires. No document uploads. Fewer drop-offs at the quote stage.
- ✓ Consistent risk banding input — Structured enums (fuel_type, euro_emission_standard) and integers (engine_capacity_cc) feed cleanly into existing risk models without normalisation overhead.
Enrich every quote with verified DVLA vehicle data.
Free tier includes 100 requests per month. No credit card, no sales call.