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Howden HX's Flandro: Use Data to Tell The Story

London City Scenery big data graphic background
London City Scenery big data
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The biggest challenge that insures face today is using all of their data to make the best decisions, said David Flandro, head of analytics for Howden HX.

David Flandro, Head of Analytics for Howden HX, said insurers need access to real-time information to make the best decisions. Click below to watch a video interview with Flandro and Meg Green, managing editor of Insider Engage, or read on to see an edited transcript of the discussion.


MG: What are the big areas of discussion this year around renewals?

DF: There are a lot of areas of discussion, Meg, and I think it comes from the coalescence of events that we've seen over the last couple of years. And it's really coming to the fore now. Among these are social inflation, heightened catastrophe losses, a lot of things happening on the asset side, certainly with interest rates. And then as you know, we're in the midst right now of COP26, so sustainability is a major topic, and the effect of climate on losses.

MG: What challenges do you see in insurance analytics today?

DF: The biggest challenge today, in my opinion Meg, is to take all of the data that we have happening around all of these events, to put it into a format that everybody can understand, and then to use those data to tell the story, so that management teams can make the very best decisions possible with the data and information we have.

MG: How do you see insurance analytics evolving going forward?

DF: Well, Meg, I think that it's going to evolve quite significantly now. I think that we're in an age where we have the technology and the data and the computing power to do some really interesting things. And if you don't mind, I'd like to show you really quickly how we do this using the Nova Terminal.

If, for example, you want to look at global insurance pricing, and how pricing in multiple lines of business is being affected by all these factors, you should be able to see it in real time. In this example, we can show you updates every two weeks across a range of different lines of business. Likewise, if you wanted to look at catastrophe losses, not at the end of the year (a quarter after the year ends), but right now, you know, and see, for example, what's happening in Europe, vis-á-vis the rest of the world, you should be able to see that in real time. We can also show you claims, we can show you buyer behaviour, and we can show you a multitude of other things like counterparty risk and peer comparisons, and we have all of this at the touch of a button.

And so really, it's taking an interface like that, putting data behind it that are homogenous, and that are updated frequently, and giving people the opportunity to tell the story for themselves so that they can make informed decisions. And I think that this really is how analytics is going to change now and in the future. It's the use of data and the ability to take that data and make good decisions with it.

MG: David, could you tell us what the source of your data is?

DF: Well, there are about 200 different sources of data that go into Nova, Meg. And there are two types of data. There are public data that go in and proprietary data. And the public data's strength is really, as I said, the homogeneity and consistency of the data. We've worked very hard to make sure that everything is directly comparable, company by company, region by region, line of business by line of business. I would say the main strength of the proprietary data is the frequency, which gives you insight now when you need it, but there are over 200 sources, and we're always adding new ones.

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