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UK insurtech startup Wrisk secures $15m series B
British InsurTech startup Wrisk has secured €13.9 million (US$15 million) in its series B funding round.
The funding will support growth and expansion across the UK and Europe, co-led by Mundi Ventures and Opera Tech Ventures, with participation from existing investors QBN and Volution.
Founded in 2016, Wrisk offers a data-driven platform for automotive brands to provide embedded insurance solutions.
The company currently supports insurance programs for manufacturers such as BMW, MINI, Volvo, Mercedes-Benz, Jaguar Land Rover, and Stellantis.
The new capital will enhance Wrisk’s data and intelligence capabilities and scale its partner programs.
🔗 Source: EU-Startups
🧠 Food for thought
1️⃣ EV revolution driving fundamental shifts in automotive insurance models
Electric vehicles are fundamentally changing how insurance works in the automotive sector, creating opportunities for data-driven platforms like Wrisk.
EVs have a 31% higher average claims loss cost compared to traditional vehicles due to their unique construction and repair complexity 1.
The EV market is projected to exceed $900 billion by 2030 (growing at 9.8% annually), with EVs expected to account for half of new car sales by 2035 23.
This transformation is forcing insurers to develop new risk assessment frameworks as vehicle technology shifts from mechanical to software-defined systems.
Insurance platforms that can integrate with vehicle data systems become increasingly valuable as OEMs need partners who understand both traditional auto insurance and the unique challenges of connected, electric vehicles.
2️⃣ Telematics and real-time data transforming risk assessment models
The insurance telematics market is projected to reach $18.7 billion by 2032, growing at 18.4% annually, as insurers shift from demographic-based to behavior-based pricing 4.
Wrisk’s approach of harmonizing data across connected car systems, telematics, and customer interactions addresses a fundamental industry challenge: creating holistic risk profiles from previously siloed information sources.
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