CMT is accelerating its adoption of telematics data across commercial motor insurance underwriting, aiming to enhance risk assessment and pricing accuracy. The move could reshape industry practices for insurers and fleet operators alike.
- CMT plans to expand telematics use in 40% more commercial motor policies by 2026
- 75% of new commercial motor quotes will incorporate telematics data by mid-2026
- Over 2 million vehicles are already part of CMT’s telematics tracking network
- Driving behavior metrics such as harsh braking and speed violations are key inputs
- PGR, ALL, SCHW, and TROW are among entities likely affected by increased telematics demand
- Shift supports usage-based pricing to improve risk accuracy and claims management
CMT has announced a strategic initiative to broaden the use of real-time telematics data in determining premiums for commercial vehicle fleets. This expansion builds on existing pilot programs and targets a 40% increase in telematics-enabled policies by the end of 2026. By leveraging driving behavior metrics—such as harsh braking, speed deviations, and idle time—the insurer aims to refine underwriting models and better align pricing with actual risk exposure. The shift reflects a growing industry trend toward usage-based insurance (UBI), where policy pricing is dynamically adjusted based on actual vehicle operation. With over 2 million vehicles currently tracked via CMT’s telematics network, the company plans to integrate this data into 75% of new commercial motor quotes by mid-2026. This represents a significant scaling effort beyond traditional actuarial methods that rely on historical claims data and static vehicle classifications. Companies like PGR, ALL, SCHW, and TROW are positioned to benefit from increased demand for integrated telematics platforms and data analytics services. Fleet operators using these systems may see reduced premiums through improved safety records, while insurers reduce claim frequency and severity. Conversely, those delaying adoption risk being priced out of competitive markets due to less accurate risk profiling. Market observers note that the integration of behavioral data into pricing could lead to more dynamic discounting models and faster claims resolution, improving customer retention and operational efficiency across the commercial insurance value chain.