Our Concept: A Fairer Future for Motor Insurance.

Magellan is rebuilding car insurance from the ground up. Using mobile telematics, behavioural analytics, and local partnerships, we will create a fairer, more transparent pricing model that rewards safer driving. 

A Broken System Hurting Good Drivers

Today’s pricing models rely on broad risk assumptions based on postcode, age and other generalisations. Millions of UK drivers face inflated premiums driven by outdated postcode-based pricing. Ethnic minority and lower-income areas are disproportionately impacted.

We believe it’s time for a fairer, smarter approach.

 

Good drivers are penalised for living in “high-risk” areas

Ethnic minority communities face disproportionate costs

Premiums are unaffordable for many households

Safer drivers are subsidising riskier ones

Data-Driven Insurance: Smarter Risk. Lower Costs. Safer Roads.

Magellan combines mobile-based telematics with behavioural analytics to fairly price motor insurance. Our technology-led model is built on three principles:

 

Good People

Partnering with local authorities, employers, and communities

Good Driving

Filtering drivers based on behaviour, not background

Good Outcomes

Reducing claims, cutting fraud, and delivering lower premiums

Our proprietary MagellanLite app lets drivers demonstrate their safety before they’re even offered a quote. Once insured, our full platform uses live data to help manage risk and reinforce good habits.

This approach means:

More accurate risk assessment

Better claims handling and fraud prevention

Fairer pricing for every policyholder

Insurance That Works for Everyone

Magellan’s insurance model is designed around people, not postcodes. We believe everyone deserves fair pricing, especially in communities where traditional insurance models have failed.

Our technology-first model means:

 

Drivers prove their behaviour, not their background

Data is used to reward safety, not penalise location

Insurance becomes part of a safer, community-based ecosystem