How Connected Vehicle Data Is Transforming Commercial Auto Telematics and Pricing

20 February 2026

#telematics platform#IoT Standard#vehicle telematics

 

Commercial Auto Insurance Is Breaking — Telematics Might Finally Fix It

Commercial auto insurance is under pressure like never before. Claims severity has climbed 36% since 2020, driven by rising repair costs, medical inflation, and the growing cost of litigation. For fleets, this often means relentless double‑digit premium increases—even if their risk hasn’t changed.

In this post, you’ll learn why commercial auto telematics and usage‑based insurance models are accelerating, what held them back before, and how connected‑vehicle data platforms like ours can help insurers and fleets finally achieve more transparent, exposure‑based pricing.

At Cubic3, we specialise in transforming fragmented vehicle data into clean, trusted signals that OEMs—and their ecosystem partners—can use to power real‑time insights

Why Telematics Previously Fell Short

Insurers have experimented with telematics for years. In theory, telematics promised:

  • More accurate risk assessment
  • Real‑time visibility
  • Personalised, behaviour‑based premiums
  • Safer fleets through feedback and coaching

But the reality was messy.

Data was inconsistent. Integrations were painful. And OEMs couldn’t scale dozens of disparate data sources.

Common problems with telematics included:

  1. Privacy concerns and driver pushback
  2. Poor data quality across different devices
  3. No standard scoring frameworks for underwriting
  4. Too much data and not enough insight

Telematics delivered data, not decisions — which slowed adoption for both insurers and fleets.

What’s Changed: Connected Fleets and Mature Analytics

Fleets today are more connected than ever. Vehicles generate continuous streams of data — from networks, services, apps, infotainment, sensors, and onboard systems.

The real shift is that modern platforms can now unify that data and make it usable.

Cubic3’s Explore3 platform already does this for OEMs: it brings network, service, and user data into one intelligent environment, giving a single, consistent view of how vehicles are being used across fleets and regions. While the platform is designed for OEMs, the same data foundations can enable partners like insurers to access structured, normalised usage insights that support fairer, more transparent pricing models.

This is the crucial evolution: The ecosystem now has the tools to trust, standardise, and scale connected‑vehicle data.

Why Pay‑Per‑Mile and Usage‑Based Pricing Are the Next Evolution

Traditional underwriting relies on proxies: industry, fleet size, garaging, location, loss history. But commercial exposure changes constantly. Drivers change, routes change, vehicle usage changes – and risk varies week by week.

Usage‑based models—such as pay‑per‑mile—offer a more accurate and equitable alternative, because premiums track real exposure.

Not all miles carry the same risk. A mile at night in congested London traffic isn’t the same as a mile on an open motorway at midday.

This is why access to continuous, trustworthy vehicle usage data matters so much. It allows insurers to price based on real activity, not historic assumptions.

By helping OEMs understand how vehicles are used—mile by mile, region by region — Explore3 creates the underlying data structure that insurers can build UBI products on top of. It means insights such as usage patterns, service consumption, and performance indicators can be transformed into auditable, underwriting‑ready signals.

Commercial Auto Telematics Only Works If the Data Is Trusted

Insurers often struggle not because they lack data—but because they lack consistent, standardised data they can trust.

Fleets are already juggling:

  • multiple telematics devices
  • camera systems
  • monitoring platforms
  • disconnected data feeds

Underwriting teams need data that is:

  • device‑agnostic
  • normalised
  • verifiable
  • explainable
  • auditable
  • scalable

This is where Explore3 becomes critical. By unifying and classifying vehicle data for OEMs — across services, apps, and vehicle fleets—it creates a “single source of truth” that partners across the ecosystem (including insurers) can rely on. It turns fragmented inputs into clean, structured telemetry capable of supporting exposure‑based pricing.

The Next Wave: Scalable, Continuous, Real‑Time Risk Pricing

Commercial auto has reached a turning point. Telematics can now finally deliver what it promised a decade ago — actionable, scalable underwriting insight.

Insurers, brokers, and fleets that align behind a common risk language will gain a competitive advantage through:

  1. More accurate pricing
  2. Reduced claims severity
  3. Improved fleet safety
  4. More predictable loss ratios

Exposure‑based insurance is no longer conceptual — it’s already on the road.

Is the Industry Ready to Price Risk in Real Time?

The real question isn’t whether telematics belongs in commercial auto insurance. It’s whether the industry is ready to turn connected‑vehicle data into real‑time, trusted, scalable underwriting capabilities.

Cubic3 can help fleets deliver exactly that — using AI, analytics, and device‑agnostic telematics to convert raw data into underwriting‑ready insights.

If you’re exploring how connected‑vehicle data can support usage‑based insurance or more transparent pricing models, our team at Cubic3 can help you understand what’s possible with Explore3’s connected‑car analytics and ecosystem partnerships.

Speak to Cubic3 to learn how trusted, unified vehicle data can transform your approach to commercial auto risk.

About Cubic3

Cubic3 provides advanced connectivity solutions for software-defined vehicles (SDVs) across 200+ countries. We help automotive, agriculture and transportation OEMs navigate the complexities of connecting vehicles while ensuring compliance with global regulations. With access to over 550 mobile networks, our smart connectivity empowers OEMs to innovate, scale and unlock new opportunities, driving efficiency and growth.