🤔 Why are we doing this?

Currently, Zego's B2C business is heavily reliant on integrations with work providers, mainly Uber. In addition, insurance claims are responsible for a significant part of Zego's expenses (c. 60%).

We believe that by using app-based telematics data, there's an opportunity to reduce payouts associated directly with claims by up to 20%. Understanding individual risk and reducing the cost of claims will impact Zego's ability to price products and policies more fairly.

To do so, we need to be able to identify, quantify and influence a Zego customer driving behaviour. In other words, we asked:

How might we identify and reduce customer's risk through helping them improve their driving behaviour?

📎 How this document is structured

If you want to jump ahead:

B2C Open Market Telematics Proposition

Testing Strategy

Concept 1: Pick what you pay (30day)

Concept 1.1: Cashback (Annual)

Concept 2: Driver Wellbeing

Zego App Core Telematics Features

💡 What is success?

Improve driver's Actuarial Score by X% over Y weeks.

^ as a proxy for reducing risk (claims)