Connected Car Data Driven Fraud Detection

Multiple data streams, contextualised. We combine connected vehicle signals, telemetry and external data sources to reconstruct events, expose contradictory narratives and reduce fraudulent claims costs.

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Our Process

Investigate. Understand. Act.

Data in context before connection. Evidence in context before recovery or repudiation.

Step 1

Investigate

Ingest signals and conduct real-time fraud checks.

Step 2

Understand

Combine multiple data points to build a full picture.

Step 3

Act

Instruct police with confidence and maximise recovery outcomes.

Real-time checks at point of ingestion

Automated signals screened on every case

Export marker present

PNC marker present

V5C issued within last three months

MOT and TAX expiry

Mileage discrepancy

Number of active policies

Plate changes

Vehicle digital footprint and sale history

Data in context

Why signal alone is not enough

These checks help highlight potential fraud before attempting a vehicle connection.

We look at data in context before instructing police recovery.

Manual fraud intervention can materially improve outcomes.

Fraud casework in practice.

Three examples of connected vehicle intelligence in action.

Case 1 | £75,000 BMW theft claim

WHAT THE DATA SHOWED

Vehicle data showed the BMW in the Republic of Ireland.
Additional checks showed it had been there for 2 years.
Conflicting MOT dates and reversing mileage were linked to an MOT station known to police for fraudulent MOTs.

OUTCOME

We proved the customer had never even seen the vehicle.

Insurer fully repudiated the claim

Case 2 | Vehicle 4 miles from the insured

WHAT THE DATA SHOWED

Vehicle location pings placed the vehicle 4 miles from the insured.
Address research showed the property owner was related to the claimant.

OUTCOME

A warrant was obtained to search the premises and recover the vehicle

Insurer sold the vehicle and pressed charges against the policyholder

Case 3 | One VRM, three insured vehicles

WHAT THE DATA SHOWED

Our data showed the vehicle insured by three different people at different locations.
We traced the correct vehicle, validated its provenance, and confirmed the two additional vehicles were stolen vehicles on cloned plates / VINs.

OUTCOME

We identified one cloned vehicle being sold unwittingly by a well-known dealership.

Insurer fully repudiated the claim

How OEM Data Supports Fraud Detection

Each fraud scenario draws on a different layer of connected vehicle data. Here is what is available, and when.

On-demand

SVR Claims Fraud

OEM location data validates or contradicts the theft narrative
Real-time data exposes ghost and cloned vehicles
Enhanced vehicle capability allows us to work with law enforcement to prove vehicle authenticity

Event data

Crash Claims Fraud

OEM crash event data provides objective reconstruction of impact timing, location and force
Airbag, seatbelt and panel damage data validates or contradicts the claimed incident
Impact severity and direction to validate or challenge injury claims
Vehicle speed and trajectory immediately before impact from event recorder signals

Snapshot / Always-on

Policy Validation Fraud

Validate overnight risk address against location data from policy inception
Mileage verification from odometer data across all vehicle brands
Class-of-use verification at inception against actual usage patterns
Highlight misrepresented vehicle usage, misrated garaging or fronted policies

What Connected Signals Reveal

Connected vehicle data provides a rich, objective picture that is impossible to fabricate and difficult to contradict. Each use case draws on a different layer of signal, from on-demand location pings to always-on telemetry and event recorder data.

SVR Claims FraudOn-demand

Theft narrative validationOEM location data confirms or contradicts the account

Ghost and cloned vehiclesReal-time data exposes identity fraud

Law enforcement authenticityEnhanced capability to prove vehicle authenticity

Crash Claims FraudEvent data

Crash reconstructionImpact timing, location and force

Airbag and seatbelt dataDeployment and restraint status

Panel damage signalsImpact direction and severity

Pre-impact speed and trajectoryEvent recorder data immediately before impact

Policy Validation FraudSnapshot / Always-on

Risk address validationOvernight location vs declared address

Mileage verificationOdometer data from all vehicle brands

Class-of-use verificationUsage patterns against declared cover

Journey variabilityTrip frequency, time-of-day and route regularity

Day 1

Baseline data from inception

OEM connectivity provides baseline connected data from policy inception, building a truthful picture before any claim is ever made.

KEY ADVANTAGE

No customer hardware needed

Unlike aftermarket telematics, OEM data cannot be manipulated by the policyholder or installed in another vehicle. While signals can be jammed, the data itself cannot be fabricated, providing a clean, trusted signal for fraud investigation.