warming, obviously and retirement is a spatial risk for life insurers to be concerned about: the continuing care retirement communities, assisted living facilities, rehab, whatever. Retirement is a special risk as well. Coastal properties and terrorism go without mentioning. As far as the liability products, that’s also spatial because commercial property/casualty insurers should be tracking the location and the time of the various loss events whether it is in a medical liability situation which docs and which hospitals are involved or product liability as we saw last year with the various recalls of toys from China. Where are those events happening, to what specific geo area? And by specific, I mean something a lot more granular than zip codes. I’m talking about census tracks or census blocks.
Naturally life insurance is also a spatial, spaced risk. People might be living in a supposed cancer cluster, they might be living in a flood zone or a wildfire zone or a tornado zone. Yes, those particular risks are doing to have deep impact on property, but people lose their lives in those events as well. My point here is that this is another area where insurers need to at a macro level have a very strong sense of place.
Three major levels: When you look at that sense of place: above ground, ground level and below ground. For above ground wind flows and wind zones come into play. For ground level we have man-made and natural land uses, but we also have elevation and vegetation, exposure to the sun, a variety of attributes that insurers need to take into effect for ground level.
Below ground, Superfund – the soil’s ability or inability to absorb or promulgate spills, the propensity for earthquakes or sink holes and who would look at what? Well, a property/casualty insurer – whether personal lines or commercial lines – I would submit needs to look at all three.
A life insurer primarily above ground to ground level depending on where the folks live they may be a little bit of below ground that they have to be concerned with.
Here we show more specificity of those major special perspectives: above, ground level and below ground, the key elements that insurers should be considering and some of the select insurance factors, like pollution flows or even the landslide or avalanche possibilities and as we said, a propensity for earthquakes, sink holes and subsidence. So, as insurers in their underwriting or their marketing or their distribution channels look at specific areas, they need to consider these various perspectives.
How do they do that? We submit that they should develop a framework and that framework has these key elements. They go from the insurance line of business to the time frame, the data analytics, modeling and visualization and of course the selected insurance value chain functions.
What we’re doing here, what we’re recommending is that insurers reposition their value chain from a spatial with a spatial or geo perspective. As an example, the insurance line of business could be commercial property casualty, could be personal lines, property casualty, could be individual lines – life and annuity, could be workers comp. It could be a specific coverage within one of those segments. How far down depends on the initiative that the insurance company wants to put into effect. The data could be external or internal. One of the external pieces of data could be data from telematics. We all know about ‘pay as you drive.’ We know about Progressive’s experiment and then implementation. We know Aviva U.K. is backing off of ‘pay and you drive’ in some of their locations and if you’ve read today’s press release – we’ll get into it a little bit later – Ivox and ISO have established a partnership to get into telematics and analytics for better and stronger risk management and risk mitigation.
But the data could be external - as I said it could be internal customer data, producer data. It could be external market data, it could be territory data. It could be data about the business and residential attributes – who is where, which businesses are where?
As far as the analytics goes you could decide that the initiative is for risk mitigation or more detailed for fraud detection or automated underwriting, as we just heard from Glen. The time frame is very important, too, and these are all interdependent, I just didn’t want to clutter the slide with a lot of lines throwing these all together, but they’re all interdependent, obviously. The time frame could either be the past or the present and if it’s the present, that really calls for the use of real time data. And again, we heard Glen talk about that and there are some other applications where real time data comes into play.
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