Telematics

What is Telematics in Insurance?

Telematics in the insurance context refers to the use of telecommunications and vehicle monitoring technology to collect granular data about how vehicles are driven — when, where, at what speed, with what braking behaviour, and at what times of day — and transmit this data to the insurer for use in pricing, risk assessment, and claims management. The term derives from the combination of "telecommunications" and "informatics," reflecting the technology's role in transmitting and analysing real-time vehicle data.

Telematics data is collected through several mechanisms: a plug-in OBD-II (on-board diagnostic) device fitted to the vehicle's diagnostic port; a purpose-built "black box" professionally installed in the vehicle; a smartphone app using the phone's accelerometer, GPS, and gyroscope; or, increasingly, data sourced directly from the vehicle's own connected systems via the manufacturer's API. Each collection method provides similar core data — speed, location, acceleration, braking, cornering — with varying degrees of precision and reliability.

How Telematics Data Drives Pricing

Traditional motor insurance pricing relies on demographic and statistical proxies for individual driving risk — age, postcode, vehicle type, occupation, claims history. These variables predict risk at a population level but are poor discriminators at the individual level: a 20-year-old in a high-risk postcode may be an excellent driver, while an experienced driver with a clean record may engage in risky driving behaviour. Telematics allows insurers to price based on observed individual behaviour rather than demographic proxies, rewarding genuinely safe drivers with lower premiums regardless of their demographic characteristics.

The key telematics risk factors used in pricing include: time of day (night-time driving carries higher risk per mile); speed (absolute speed and speed relative to road type); harsh braking (frequency and severity); harsh acceleration and cornering; total mileage (more miles driven increases exposure); motorway vs. urban driving mix; and, increasingly, distraction indicators such as phone use patterns. Machine learning models built on large telematics datasets can identify complex multivariate risk patterns that simpler scoring approaches miss.

Telematics in Claims Management

Telematics data provides significant value beyond pricing. In the event of an accident, the telematics device captures a detailed record of the vehicle's speed, braking, and direction in the seconds before, during, and after the collision. This crash data provides objective evidence of the circumstances of the accident — complementing or, where there are conflicting accounts, challenging the insured's account of events. It can accelerate fault determination, support subrogation claims, detect fraud (where the telematics data contradicts the claimed circumstances of the accident), and provide emergency services with the crash location in severe accidents.

Data Privacy and Regulatory Considerations

Telematics programmes collect substantial personal data about policyholders' movements, habits, and behaviour. This creates significant obligations under GDPR and UK data protection law: insurers must obtain clear, informed consent; use data only for defined, disclosed purposes; provide policyholders with access to their own data; and protect the data against breach or unauthorised use. The Information Commissioner's Office (ICO) has issued guidance on telematics data use, and insurers must ensure their data governance frameworks meet the legal standard. Policyholders increasingly expect transparency about how telematics data affects their premium and what data is retained — creating both a compliance obligation and a customer communications challenge.