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5 February 2025

Delivering Pricing Sophistication At Ticker (Video)

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In this success story, Mike Ketteringham, Chief Underwriting Officer at Ticker, shares how Radar has aided its growth strategy.
United Kingdom Insurance

In this success story, Mike Ketteringham, Chief Underwriting Officer at Ticker, shares how Radar has aided its growth strategy.

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Radar: Delivering pricing sophistication at Ticker

Mike Ketteringham, Chief Underwriting Officer at Ticker, shares how Radar is helping to optimise its approach to pricing.

Radar is a complete, end-to-end analytics and model deployment solution. Built specifically for insurers by insurance experts, and continually enhanced by on-going investment, development and innovation.

Radar is licensed by over 500 different companies and 23/25 of the world's largest insurance groups.

Radar: ticker case study

MIKE KETTERINGHAM: I'm Mike Ketteringham. I'm Chief Underwriting Officer of Ticker. We're a digital insurer. Radar's definitely been a massive help to our growth strategy. When we started way back in 2018/2019, we were in the fortunate position we had a blank sheet approach. We were new to the market, so we had no legacy system issues.

Radar gives us the ability to react very quickly to market changes, which in todays market is absolutely essential

Radar gives us the ability to react very quickly to market changes, which in todays market is absolutely essential.

We went out to the market, we did look at a number of other providers, but we knew that to compete in the UK motor market, with all its complexity and the required sophistication, we needed a system that we could trust and that was scalable, that was robust and that had the capability to grow with us.

Clearly, at that point, we didn't have a huge amount of data, and we were a startup. When we cast forward now, we have hundreds and hundreds of millions of miles worth of driving data, amongst other things, that we are leveraging and bringing new factors into our pricing sophistication.

That's where Radar's been terrific, because we have the ability to very quickly turn the handle on that data, recognise whether we have productivity in the data set, and then we can quickly build new and hopefully novel rating factors.

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