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InsTech - insurance & innovation with Matthew Grant & Robin Merttens

Matt Coleman, Chief Risk Officer: The Demex Group: Underwriting weather: reducing uncertainty with claims-driven models (365)

InsTech - insurance & innovation with Matthew Grant & Robin Merttens

InsTech

Entrepreneurship, Investing, Business

4.8 • 50 Ratings

🗓️ 27 July 2025

⏱️ 22 minutes

🧾️ Download transcript

Summary

At its best, parametric insurance delivers clarity when volatility strikes. But scaling that promise takes more than models: it takes real claims data, market feedback and the ability to solve for both reinsurers’ confidence and cedents’ earnings risk. In this episode, Matthew Grant speaks with Matt Coleman, Chief Risk Officer at The Demex Group, a reinsurance MGA using a new modelled loss index to reshape how the market covers severe convective storms, one of the fastest-growing sources of weather-driven loss. Our conversation picks up where our previous webinar left off, and explores how Demex has grown distribution, secured broker support and validated its approach in a live risk environment. In this conversation Matt touches on: Why 2025 has already seen above-average tornado, wind and hail activity and how recoveries are already flowing How Demex’s RCR Re cover mimics indemnity but pays out on a modelled index Why omitting sensors and relying on robust weather and claims data reduces basis risk The advantages of training models on cedents’ actual ground-up claims, not diluted industry averages What reinsurers want in secondary peril covers and how Demex packages risk to match that appetite Why broker engagement has been critical to growth, and what their clients are asking for What it means to build in response to a genuine market problem not just to push a technology Along the way, Matthew and Matt talk about why carriers are willing to share granular claims data when the product is strong enough and why early validation matters in parametric. If you like what you’re hearing, please leave us a review on whichever platform you use or contact Matt Coleman or Matthew Grant on LinkedIn. Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning. Continuing Professional Development This InsTech Podcast Episode is accredited by the Chartered Insurance Institute (CII). By listening, you can claim up to 0.5 hours towards your CPD scheme. By the end of this podcast, you should be able to meet the following Learning Objectives: Specify the role of brokers in distributing innovative reinsurance solutions and educating cedents Identify the challenges and advantages of building a reinsurance product in direct response to market demand Explain why reinsurers prefer weather-driven indices over indemnity-based uncertainty If your organisation is a member of InsTech and you would like to receive a quarterly summary of the CPD hours you have earned, visit the Episode 365 page of the InsTech website or email [email protected] to let us know you have listened to this podcast. To help us measure the impact of the learning, we would be grateful if you would take a minute to complete a quick feedback survey.

Transcript

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0:00.0

Hello, welcome or welcome back to the INSTEC podcast.

0:12.8

Zoya here.

0:14.0

And this week we're joined by Matt Coleman, Chief Risk Officer at the Demix Group,

0:18.3

back behind the mic for another deep dive into one of the most

0:21.0

talked about corners of reinsurance, which is parametrics. In this conversation, we get an

0:26.6

update on Demics' parametric stop-loss reinsurance product and explore how it's responding to a year

0:32.6

of quite intensive convective storm activity across the US. Throughout the podcast, we also ask,

0:38.9

are parametric structures finally bridging the protection gap for mid-frequency events like hail,

0:44.4

tornadoes and straight line winds? And what is it about this moment in the market that's made

0:49.8

reinsurers willing to get behind secondary peril coverage again? So whether you're new to parametric insurance or already familiar and friendly with the world of

0:58.5

modelling, grab a tea or coffee and let's jump into the conversation.

1:08.3

Matt, brilliant to have you.

1:10.2

I think we're at one of those times of year where the weather where you are in Oakland, California, is probably similar to what it is doing in London. So for us, it all feels a bit hot. For you, it might feel just about right. But great to have you joining us. Thank you so much, Matthew. It's a pleasure to be here. I bet it's on a British podcast we talk about the weather. Now, we've had you a couple of times. You're on the 10th of March, 2023 on the podcast, and we did what I thought was a wonderful webinar with you in December 2024. I definitely refer people to that, talking about some of what you're doing and hearing from John D. Martini. But we're going to get a catch-up today because it's been quite interesting following the growth and success of DEMX. So we're really looking forward to discussing a little bit more of what's happened since we last caught up. Yeah, it's been been very active business-wise and of course weather-wise this year as well. Can't avoid talking about the weather. So a little bit introduction to Demex for those that aren't familiar with you or maybe

2:03.4

need an update.

2:04.2

So you are a reinsurance MGA.

2:05.8

You offer parametric stop loss in reinsurance.

2:09.2

And in particular, the product you're offering is called retained climate risk or RCR re.

2:15.0

And it's for secondary weather perils.

2:16.4

So particularly severe convective storm, SCS, for those who don't speak, insurance and climate, that's thunderstorms, hail, wind, tornadoes, and I think Durantios as well, if I'm correct. They're driving over $70 billion in global losses we talked about on the webinar and actually starting to exceed, in some cases, this traditional cat, and your model is using proprietary weather and claims data to trigger payments

2:17.7

automatically. on the webinar and actually starting to exceed in some cases traditional cat. And your model's

2:35.6

using proprietary weather and claims data to trigger payments automatically when lofts

2:40.1

thresholds are met, hence the parametric piece, and reducing the basis risk. Matt, your chief risk

...

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