WEBVTT - Why Insurers Are Pulling Out of High-Risk Areas 0:00:10.720 --> 0:00:14.000 Hello, and welcome to another episode of the Odd Loots Podcast. 0:00:14.080 --> 0:00:15.400 I'm Tracy Alloway. 0:00:15.160 --> 0:00:16.280 And I'm Joe Whysenthal. 0:00:16.760 --> 0:00:23.040 Joe, do you do you like watching the weather? I 0:00:23.040 --> 0:00:25.280 can hear the pain in your voice as soon as 0:00:25.320 --> 0:00:25.720 I asked them. 0:00:26.120 --> 0:00:28.000 It's so funny. I didn't. I was wondering how you're 0:00:28.000 --> 0:00:31.080 gonna start this one. I hate rain. I hate rain 0:00:31.280 --> 0:00:34.199 so much. Other than that, I don't know. It's not 0:00:34.240 --> 0:00:36.520 a big thing for me. What about you up in Connecticut? 0:00:36.720 --> 0:00:38.159 Is it a bigger deal up there? 0:00:38.440 --> 0:00:42.560 I love weather. I am sort of an armchair meteorologist, 0:00:42.680 --> 0:00:45.239 by which I mean I have several weather apps. I 0:00:45.280 --> 0:00:48.879 get very excited about thunderstorms and other types of storms. 0:00:49.440 --> 0:00:54.400 My husband, however, does not. He gets extremely anxious whenever 0:00:54.440 --> 0:00:58.040 there's a forecast of a severe thunderstorm because inevitably it 0:00:58.160 --> 0:01:00.840 ends up dumping like two inches of where we are, 0:01:00.880 --> 0:01:02.560 and our basement starts to flood. 0:01:02.920 --> 0:01:05.520 I've lived in a house that had flood damage. It 0:01:05.600 --> 0:01:10.320 is extremely stressful experience too. I mean there's just like 0:01:10.360 --> 0:01:13.600 the direct issue of like cleaning up all of the 0:01:13.640 --> 0:01:17.000 lost damage and then like compensation and damage to the 0:01:17.040 --> 0:01:18.959 house is probably one of the more like sort of 0:01:19.000 --> 0:01:21.280 like stressful things a homeowner can deal with. 0:01:21.640 --> 0:01:24.880 Well, you know one of the stressful things happening right now, 0:01:24.920 --> 0:01:29.360 and we're recording this on let's see September eighth. There's 0:01:29.400 --> 0:01:33.240 a major hurricane brewing in the Atlantic right now, Hurricane Lee. 0:01:33.640 --> 0:01:36.600 It exploded from a tropical storm I think just two 0:01:36.640 --> 0:01:40.160 days ago into a category four hurricane. Now it's category 0:01:40.240 --> 0:01:43.560 five and there's a lot of deliberation about whether or 0:01:43.640 --> 0:01:46.240 not it's going to sort of run up the Atlantic coast, 0:01:46.600 --> 0:01:50.080 might even get into New England. So an interesting one to. 0:01:50.040 --> 0:01:52.840 Watch, yes, and I guess I guess by the time 0:01:52.840 --> 0:01:55.080 people listen to this will be resolved. But I'm glad 0:01:55.480 --> 0:01:58.640 you mentioned that. But it's also coming in the context 0:01:58.640 --> 0:02:00.680 of a time when there is a lot of anxiety 0:02:00.840 --> 0:02:04.360 about the property market and insurance. And this came up 0:02:04.440 --> 0:02:07.520 on our recent episode that we did with Howard Hughes 0:02:07.680 --> 0:02:12.240 Holding CEO. We talked about this huge surge in the 0:02:12.280 --> 0:02:14.840 cost that the company is paying for insurance. And there 0:02:14.840 --> 0:02:18.920 have been so many stories about natural disaster prone areas 0:02:19.200 --> 0:02:22.440 and homeowners are either just getting staggering sticker shock when 0:02:22.440 --> 0:02:25.160 it comes to the cost of homeowners insurance and other 0:02:25.200 --> 0:02:28.160 property insurance or there's no one at all, or you know, 0:02:28.240 --> 0:02:32.320 companies abandoning markets like Florida, like California, et cetera. 0:02:32.639 --> 0:02:35.359 Absolutely, and it's not just hurricanes and floods. Of course, 0:02:35.400 --> 0:02:40.120 we've seen wildfire risk becoming a more major thing, particularly 0:02:40.200 --> 0:02:42.960 in Hawaii and Maui. Recently, there have been a number 0:02:43.040 --> 0:02:46.840 of headlines, as you just mentioned, of certain insurance companies 0:02:46.919 --> 0:02:51.360 pulling out of markets all together because they're no longer profitable, 0:02:51.480 --> 0:02:54.079 or in some cases, like Florida, they haven't actually been 0:02:54.120 --> 0:02:58.200 profitable for a very very long time. And insurance premiums 0:02:58.240 --> 0:03:01.480 are going up all over the United States. But it's 0:03:01.520 --> 0:03:04.200 really interesting if you look at them on a regional basis. 0:03:04.240 --> 0:03:07.440 I think in Miami the average cost of insurance is 0:03:07.480 --> 0:03:11.000 something like five thousand dollars versus less than two thousand 0:03:11.040 --> 0:03:13.640 dollars for the rest of the US. So that gives 0:03:13.639 --> 0:03:17.640 you some idea of how this risk is starting to 0:03:17.760 --> 0:03:21.440 get repriced. But it opens up all these interesting questions 0:03:21.520 --> 0:03:26.160 about what is going to happen to cities, to houses, 0:03:26.320 --> 0:03:31.320 to other buildings that are in these natural disaster prone areas. 0:03:31.600 --> 0:03:33.880 You know, the thinking of things like flood insurance, which 0:03:33.919 --> 0:03:37.800 is already sort of socialized or there's publicly funded. There 0:03:37.840 --> 0:03:40.800 doesn't seem to be a lot of appetite politically to 0:03:41.080 --> 0:03:45.280 let property owners sort of completely be without insurance in 0:03:45.320 --> 0:03:48.320 other words, right, So it's like if the private market 0:03:48.600 --> 0:03:51.680 leaves an area, you don't really see politicians like, Okay, well, 0:03:51.680 --> 0:03:54.440 I guess we can't build here anymore. There's usually the 0:03:54.480 --> 0:03:56.360 government steps in in some way, maybe there's like a 0:03:56.400 --> 0:03:59.960 state insure, a national insurre in the case of flood. 0:04:00.000 --> 0:04:02.040 And of course this creates its own issues, and that 0:04:02.160 --> 0:04:04.560 it's sort of another one of these financial services that's 0:04:04.600 --> 0:04:07.040 like sort of post market, kind of like banking in 0:04:07.080 --> 0:04:09.840 some respects. And so there is a lot going on 0:04:10.080 --> 0:04:13.440 with this market. And you know, obviously comes in the 0:04:13.520 --> 0:04:16.560 time of other financial tightening financial conditions, comes at so 0:04:16.680 --> 0:04:18.919 much attention played to climate risk, and I think we 0:04:18.960 --> 0:04:20.640 need to understand more of this area. 0:04:20.720 --> 0:04:23.840 Absolutely, it's a complex market. It seems to be getting 0:04:23.920 --> 0:04:26.520 more complex by the day, So let's dig into it. 0:04:26.560 --> 0:04:28.600 I am very pleased to say that we really do 0:04:28.680 --> 0:04:30.640 have the perfect guest. We are going to be speaking 0:04:30.640 --> 0:04:34.000 with Melanie gall She's the co director of the Center 0:04:34.160 --> 0:04:38.360 for Emergency Management and Homeland Security at Arizona State University. 0:04:38.600 --> 0:04:42.880 She also manages the Spatial Hazard Events and Losses Database 0:04:42.960 --> 0:04:45.800 for the United States, something known as SHELDUS. We're going 0:04:45.880 --> 0:04:48.360 to dig into exactly what that is in a few minutes, 0:04:48.520 --> 0:04:51.120 but Melanie, thank you so much for coming on all thoughts. 0:04:51.920 --> 0:04:53.159 Thank you so much for having me. 0:04:53.800 --> 0:04:56.839 So maybe just to begin with, can you explain what 0:04:56.960 --> 0:05:00.360 the co director of the Center for Emergency MA Management 0:05:00.400 --> 0:05:03.360 and Homeland Security at Arizona State actually does. What does 0:05:03.400 --> 0:05:04.159 that entail? 0:05:04.600 --> 0:05:07.159 So I may be the kind of person that you 0:05:07.200 --> 0:05:10.919 don't necessarily directly associate with, that kind of you know, 0:05:11.160 --> 0:05:14.600 leadership position because by training, I am a geographer. I 0:05:14.720 --> 0:05:19.640 started out making maps, digital maps, and I came into 0:05:19.640 --> 0:05:24.640 the field of emergency management through a stint that I 0:05:24.720 --> 0:05:28.000 did in Africa. I was actually in Mozambique and I 0:05:28.000 --> 0:05:30.440 did training on you know, how do you collect data 0:05:30.520 --> 0:05:32.800 in the field with a GPS, this kind of information. 0:05:33.279 --> 0:05:36.320 And it was after a massive flood event and then 0:05:36.560 --> 0:05:39.280 I realized, ooh, there's a great connection between what I 0:05:39.320 --> 0:05:42.800 was doing geographic information system and emergency management because you 0:05:42.839 --> 0:05:45.000 need a lot of logistics support, you need to know 0:05:45.040 --> 0:05:47.440 where your stuff is, where you should set up shelters 0:05:47.680 --> 0:05:51.120 and alike. And that was my route into emergency management. 0:05:51.480 --> 0:05:54.400 And so what I do here now at Arizona State University, 0:05:54.440 --> 0:05:56.680 I teach. Obviously, we have a master's degree in an 0:05:56.720 --> 0:06:00.120 undergrad program in emergency management and homeland security, and I 0:06:00.200 --> 0:06:03.520 do numerous research projects. I work with out a nonprofit 0:06:03.640 --> 0:06:08.279 organizations here in Arizona. So it's really a broad variety 0:06:08.320 --> 0:06:10.200 of things. So it's very exciting as a job. 0:06:10.240 --> 0:06:13.720 I have to say, you mentioned data collection, and of 0:06:13.760 --> 0:06:16.920 course you have this database, and you know, it strikes 0:06:16.960 --> 0:06:22.520 me that collecting natural disaster data seems extremely difficult for 0:06:22.560 --> 0:06:25.360 all kinds of reasons. I mean, even something as simple 0:06:25.400 --> 0:06:28.919 as like tallying up the dollar amounts spent on recovery 0:06:29.200 --> 0:06:31.960 strikes difficult. And what these trends are and I could 0:06:32.040 --> 0:06:34.760 imagine that you could have an increase in dollar amounts 0:06:34.800 --> 0:06:37.400 for an area and because there's more disasters, or maybe 0:06:37.440 --> 0:06:39.839 because there's just more building and more people there that 0:06:40.000 --> 0:06:42.839 could also cause that, and so like disambiguating some of 0:06:42.839 --> 0:06:45.880 these effects. Talk to us a little bit about just 0:06:45.960 --> 0:06:48.360 the challenge of measurement, because if we're going to get 0:06:48.360 --> 0:06:51.479 into insurance and know like how much risk is in 0:06:51.520 --> 0:06:54.320 a given area that you have to start with, like, well, 0:06:54.320 --> 0:06:56.640 how much dollar what is the dollar value of the 0:06:56.680 --> 0:06:58.760 property in an area? So talk to us about the 0:06:58.839 --> 0:07:01.680 challenges of measuring these types of things. 0:07:02.480 --> 0:07:05.360 So let me start with telling you a little bit 0:07:05.360 --> 0:07:07.960 about where we get our data from, and then too 0:07:08.040 --> 0:07:12.480 the measurement because we are a secondary user of disaster 0:07:12.600 --> 0:07:15.720 loss information. So we get the vast majority of our 0:07:15.880 --> 0:07:20.360 data from the National Weather Service or better you know, 0:07:20.440 --> 0:07:23.920 the National Weather Service feeds the information to the National 0:07:23.960 --> 0:07:27.560 Centers for Environmental Information in CI, and that is where 0:07:27.600 --> 0:07:29.800 we get the majority of the data from. So it 0:07:29.880 --> 0:07:35.480 is actually your local forecast office, your local meteorologist that 0:07:35.560 --> 0:07:39.080 collects that information. So it is not an economist or 0:07:39.120 --> 0:07:41.800 an assessor or anything like this. So it's the local 0:07:41.840 --> 0:07:47.040 forecast office that collects that information. So I came into 0:07:47.080 --> 0:07:50.080 this arena of collecting disaster losses way back in the 0:07:50.160 --> 0:07:53.200 days when I was a PhD student, where my professor 0:07:53.520 --> 0:07:56.440 had this idea that as a geographer, it should be 0:07:56.440 --> 0:07:59.960 fairly easy to develop profiles for the country. You know, 0:08:00.480 --> 0:08:04.240 how does County A suffer more from hurricane damage than 0:08:04.280 --> 0:08:08.720 flood damage than County B and LO and behold, there 0:08:08.800 --> 0:08:13.360 was not really easily accessible database where you can get 0:08:13.360 --> 0:08:17.360 this information, and that was really the starting point for 0:08:17.440 --> 0:08:19.720 setting up this database. So now we are in the 0:08:19.760 --> 0:08:25.480 business of compiling data that is already assessed from different 0:08:25.520 --> 0:08:29.280 federal agencies. So NCI is one of our main data sources, 0:08:29.280 --> 0:08:32.640 and then we also use data from the US Geological Survey, 0:08:33.679 --> 0:08:39.880 especially related to geological hazards earthquake damage, volcanic eruption damage 0:08:39.880 --> 0:08:43.800 tsunamis analyte because the Weather Service obviously only collects data 0:08:43.840 --> 0:08:48.120 related to mitrological and hydrological events, but we are interested 0:08:48.160 --> 0:08:53.000 in compiling a database that covers all natural hazards. So 0:08:53.280 --> 0:08:56.680 we are vistly using data. And there's only a tiny 0:08:56.679 --> 0:08:59.280 fraction where we compile our own data, and that is 0:08:59.360 --> 0:09:03.880 landslide data. So landslide data is really not or has 0:09:03.960 --> 0:09:07.600 not been easily accessible. There was a Landslide Act passed 0:09:07.600 --> 0:09:10.360 a few years ago, so that now triggered the US 0:09:10.400 --> 0:09:15.000 Geological Survey to get most serious about collecting that data. 0:09:15.840 --> 0:09:19.440 And so we decided that we want to include landslide 0:09:19.480 --> 0:09:22.240 data in our database. And that's where we then started 0:09:22.720 --> 0:09:26.880 like scouring newspapers, websites, and we're applying the same sort 0:09:26.880 --> 0:09:31.160 of assessment methodology that the Weather Service is employing. Because 0:09:31.760 --> 0:09:37.880 the main users of our data are local planners, hazard 0:09:37.880 --> 0:09:42.439 mitigation planners. And hazard mitigation planners sit in the emergency 0:09:42.440 --> 0:09:46.240 management division of your county or of your state, and 0:09:46.640 --> 0:09:50.520 they are actually charged by law. They are not required 0:09:50.720 --> 0:09:53.400 to compile what it is called hazard mitigation plans, but 0:09:53.559 --> 0:09:57.480 they are incentivized to compile these hazard mitigation plans. And 0:09:57.559 --> 0:10:00.240 in these plans you have to do risk assessments. These 0:10:00.320 --> 0:10:03.680 risk assessments need to include a history of past losses 0:10:04.120 --> 0:10:06.920 and that's then when people tend to come to us. 0:10:07.720 --> 0:10:11.480 So measuring losses and assessing them goes exactly you know, Joe, 0:10:11.520 --> 0:10:14.559 you already mentioned it's a question of you know, how 0:10:14.600 --> 0:10:16.560 much property do we have in an area and what's 0:10:16.600 --> 0:10:22.360 the property worth. So there are two types of losses. 0:10:22.400 --> 0:10:25.680 There's what's called direct losses and indirect losses. So direct 0:10:25.720 --> 0:10:28.080 loss is when you see, you know, the destruction of 0:10:28.120 --> 0:10:33.000 a storm or a hurricane, like a loss directly tied 0:10:33.200 --> 0:10:37.200 to the event. That is what we include in our database. 0:10:37.240 --> 0:10:40.880 We only include direct proper damage, direct crrupt damage, injuries, 0:10:40.920 --> 0:10:43.840 and fatality, So that would be for instance, a person 0:10:44.200 --> 0:10:46.640 you know, who got injured or drowned in a flood 0:10:46.720 --> 0:10:50.720 or something like that. And the indirect losses is, for instance, 0:10:50.760 --> 0:10:53.000 when a business has to shut down for a given 0:10:53.040 --> 0:10:55.360 time because they can't operate their power is down or 0:10:55.360 --> 0:10:58.160 something like that. And the indirect losses we do not 0:10:58.200 --> 0:11:01.080 include in our database. So what I'm trying to say 0:11:01.120 --> 0:11:04.120 is even what we have in our database is way 0:11:04.600 --> 0:11:08.000 underestimating really the burden of losses that we have in 0:11:08.000 --> 0:11:09.560 the country from natural hazards. 0:11:10.440 --> 0:11:12.959 So I was going to ask, what happens when you 0:11:13.000 --> 0:11:15.680 see I mean, you just gave us a great summary 0:11:15.800 --> 0:11:18.280 of how tricky it can be to measure some of 0:11:18.320 --> 0:11:21.160 these costs. But what is happening if you get a 0:11:21.280 --> 0:11:25.280 wildly different estimate of the cost of a certain disaster? 0:11:25.440 --> 0:11:27.800 And for instance, one thing I read was that, I 0:11:27.840 --> 0:11:32.319 think the NCDC estimates that the damages from Hurricane Katrina 0:11:32.480 --> 0:11:34.920 or something like one hundred and twenty five billion dollars 0:11:35.360 --> 0:11:39.880 versus what Shelda says at eighty billion. What's happening there 0:11:39.920 --> 0:11:42.520 when you get a discrepancy like that, And does it 0:11:42.679 --> 0:11:46.280 matter in the real world in terms of contingency planning? 0:11:47.679 --> 0:11:50.960 So it does to some degree. So it matters when 0:11:51.000 --> 0:11:55.560 you as a community have to justify why you need 0:11:55.679 --> 0:11:58.960 money and why you want to invest to reduce the losses. 0:11:59.440 --> 0:12:04.280 So communities have to do cost benefit analyses to justify 0:12:04.360 --> 0:12:07.480 why it makes sense to invest maybe you know, building 0:12:07.480 --> 0:12:10.640 a new retention pond or you know changing their building 0:12:10.640 --> 0:12:14.160 codes and anything that has a price tag associated with it. 0:12:14.240 --> 0:12:17.359 You know, these communities have to run benefit cost analysis 0:12:17.480 --> 0:12:20.240 and say, what we're investing is reducing losses in the 0:12:20.280 --> 0:12:22.640 long run. And that's where it matters what you can 0:12:22.720 --> 0:12:26.599 document in terms of past hazards. So the discrepancy and 0:12:26.720 --> 0:12:29.720 estimates that you just mentioned is really that's our standard 0:12:29.760 --> 0:12:33.000 business because it is so tricky to estimate these losses. 0:12:33.320 --> 0:12:36.280 There's the direct, there's the indirect losses. There's also insured 0:12:36.320 --> 0:12:39.679 and uninsured losses. So it's always a question of sort 0:12:39.679 --> 0:12:41.920 of what slices of the pie and how much of 0:12:41.960 --> 0:12:45.040 the pie people looking at when they estimate losses. And 0:12:45.080 --> 0:12:48.760 that's also where you see you've probably seen it many times, Noah, 0:12:48.960 --> 0:12:53.559 the National Oceanic and Atmospheric Administration, they have what is 0:12:53.640 --> 0:12:57.600 called billion dollar events. They get cited all over and 0:12:58.080 --> 0:13:01.480 their estimates are always vast hire than what we have 0:13:01.600 --> 0:13:06.480 in our database because they rely heavily on enshort data 0:13:07.160 --> 0:13:10.240 and so in short data is again different from direct 0:13:10.280 --> 0:13:13.440 losses what we document, and this is where all these 0:13:13.480 --> 0:13:17.000 discrepancies come from. So in my line of business, when 0:13:17.000 --> 0:13:20.480 it comes to direct losses, we tend to be conservative. 0:13:20.559 --> 0:13:24.280 So if we have competing estimates, we use the lower 0:13:24.440 --> 0:13:26.840 estimate just to be on the safe side of not 0:13:27.040 --> 0:13:31.000 over estimating losses. But that really just you know, might 0:13:31.080 --> 0:13:34.520 aggravate the problem because we already have under estimation problem 0:13:34.559 --> 0:13:37.199 and then we are conservative. But that is the approach 0:13:37.240 --> 0:13:40.600 we've taken at the start of you know, developing this database. 0:13:40.880 --> 0:13:43.439 Well, I want to get into you know, obviously we 0:13:43.480 --> 0:13:46.160 want to get into what's happening right now and what 0:13:46.200 --> 0:13:48.640 we're seeing in insurance markets. But I think just to like, 0:13:49.120 --> 0:13:53.640 before we get to that, are the cost of natural 0:13:53.679 --> 0:13:56.400 disasters going up? And maybe that's a naive question, but 0:13:56.520 --> 0:13:58.400 I always have these states, Oh, is it just that 0:13:58.440 --> 0:14:02.200 we're getting more attention to natural disasters in the media, 0:14:02.360 --> 0:14:04.360 and is it just a sort of like is it 0:14:04.440 --> 0:14:06.520 just a narrative that there are more that there are 0:14:06.559 --> 0:14:09.280 more wildfires, et cetera, Or is it like, what are 0:14:09.320 --> 0:14:12.760 we actually seeing big picture in the data. Are things 0:14:12.840 --> 0:14:14.720 are we you know, is it getting worse? 0:14:16.000 --> 0:14:18.880 It is getting worse, So our risk is going up. 0:14:19.080 --> 0:14:22.920 We have more severe events, we have more events. The 0:14:23.080 --> 0:14:27.280 question is why do we see higher losses. So higher 0:14:27.320 --> 0:14:29.920 losses could be a function of simply having, you know, 0:14:30.000 --> 0:14:34.320 more events, more extreme events, and or it could also 0:14:34.400 --> 0:14:38.160 be a function of what you mentioned earlier, Joe, more 0:14:38.200 --> 0:14:42.040 people living in high risk areas, more property, or simply 0:14:42.040 --> 0:14:45.720 more value being accumulated in high risk areas. It could 0:14:45.800 --> 0:14:49.000 also be that maybe as a society we don't do 0:14:49.240 --> 0:14:52.320 enough to mitigate these losses so that we get outpaced 0:14:52.720 --> 0:14:56.160 by the risk that we're experiencing. Or it could also 0:14:56.200 --> 0:14:59.680 be that we have not as resilient of a society, 0:15:00.160 --> 0:15:07.120 resilient infrastructure, resilient residential homes, and or it could also 0:15:07.160 --> 0:15:09.680 be an increase in what we call social and nobility, 0:15:09.960 --> 0:15:13.960 meaning you have more people that lack the capacity to 0:15:14.040 --> 0:15:16.400 prepare for, respond to, or recover from an event. 0:15:32.400 --> 0:15:36.120 Let's pivot to insurance and talk about what's going on there, 0:15:36.160 --> 0:15:38.520 And maybe just to begin with, could you sort of 0:15:38.560 --> 0:15:42.120 walk us through the landscape of this type of insurance 0:15:42.160 --> 0:15:44.720 as it exists now, So let's say, you know, a 0:15:44.840 --> 0:15:50.920 hurricane happens in Florida. What's the sort of process by 0:15:50.960 --> 0:15:55.120 which a homeowner would expect to get reimbursed? Because my 0:15:55.240 --> 0:15:58.600 understanding is there's different layers of private insurance and then 0:15:58.640 --> 0:16:02.360 there's sort of federal potentially as well, and of course 0:16:02.400 --> 0:16:04.960 there are also the reinsurers who are sort of backing 0:16:05.400 --> 0:16:09.040 the upfront insurans. Can you walk us through how all 0:16:09.080 --> 0:16:11.200 that would work in a typical case. 0:16:12.160 --> 0:16:14.800 Yes, so you know, just let me stay again. I'm 0:16:14.800 --> 0:16:19.560 a geographer and training, I'm not an economists expert, but 0:16:19.600 --> 0:16:23.520 I can tell you that a it's very complex because 0:16:23.520 --> 0:16:26.760 it varies, like you said, from state to state. And 0:16:26.800 --> 0:16:29.160 I think what a lot of people don't realize is 0:16:29.720 --> 0:16:35.000 you might have to purchase different insurance policies to be covered. 0:16:35.520 --> 0:16:38.640 So I think most people assume all this is covered 0:16:38.720 --> 0:16:42.520 in my homeowner is insurance, and it is not, and 0:16:42.560 --> 0:16:46.360 it depends on where you live. Like, for instance, landslide 0:16:46.440 --> 0:16:50.720 risk not covered in any policy in any state in 0:16:50.760 --> 0:16:55.200 the US. So landslide risk is something that you cannot 0:16:55.320 --> 0:16:58.000 file an insurance claim on because you can't get insurance 0:16:58.000 --> 0:17:00.760 for it. So let's go to Florida. So if you 0:17:00.840 --> 0:17:04.280 live in Florida, so you would let's say ideal scenario, 0:17:04.400 --> 0:17:08.640 as a homeowner, you have homeowners insurance. You also have 0:17:08.840 --> 0:17:12.400 flood insurance from the federal government. Also, many people don't 0:17:12.440 --> 0:17:15.880 realize that that's a federal program because it's ministered by 0:17:15.920 --> 0:17:19.400 your local insurance agent. So you buy your flood insurance 0:17:19.440 --> 0:17:23.000 policy from your local agent, but actually you know the 0:17:23.040 --> 0:17:26.800 company that ensures you is the federal government. And then 0:17:27.359 --> 0:17:30.720 depending on what stayed you in and exactly how you 0:17:30.760 --> 0:17:34.879 know the policy works. You also have to buy wind insurance, 0:17:35.359 --> 0:17:39.800 and states have different sort of thresholds. You know, when 0:17:40.000 --> 0:17:42.879 is a storm actually a hurricane, does it have to 0:17:42.920 --> 0:17:45.840 reach a certain wind speed then for the wind insurance 0:17:45.880 --> 0:17:49.879 to pay out over the homeowners insurance. So for you 0:17:50.040 --> 0:17:53.240 as an individual a you have to navigate what do 0:17:53.280 --> 0:17:57.240 I want to ensure, what can I afford to ensure, 0:17:57.280 --> 0:17:59.280 what kind of different policies do I need to buy? 0:17:59.720 --> 0:18:02.960 And then when you actually have damage from an event, 0:18:03.480 --> 0:18:07.000 and we've seen this for instance after Hurricane Katrina, you 0:18:07.240 --> 0:18:10.399 very often might face a situation where you then have 0:18:10.480 --> 0:18:13.119 to argue with the insurance company if the damage that 0:18:13.200 --> 0:18:16.920 you have was caused by wind or cause by flooding amazing, 0:18:17.000 --> 0:18:21.240 and we've seen discrepancies where you know, one neighbor their 0:18:21.280 --> 0:18:26.280 wind insurance paid out because their insurance company said, yes, 0:18:26.320 --> 0:18:28.600 we recognize that this is wind damage, and the other 0:18:28.640 --> 0:18:31.879 neighbor didn't get anything from their policy because they're the 0:18:31.920 --> 0:18:34.360 insurance said, oh, this is flood damage that you have. 0:18:35.000 --> 0:18:40.800 So having insurance does not necessarily mean that policy is 0:18:40.840 --> 0:18:43.320 also going to kick in because they might be disputes 0:18:44.000 --> 0:18:46.440 with regard to what type of data, but what type 0:18:46.560 --> 0:18:48.920 hazard caused that damage? 0:18:50.119 --> 0:18:52.960 What insurance rates up so much? I mean, I know 0:18:53.040 --> 0:18:55.480 this is like the whole question, but if someone asked 0:18:55.480 --> 0:18:58.679 you that me why, Like in Florida, you know, I 0:18:58.720 --> 0:19:01.480 saw there's a stat forty two percent higher for home 0:19:01.520 --> 0:19:04.960 owned home insurance premiums. I mean I get that, like, okay, 0:19:05.320 --> 0:19:09.520 generally speaking, maybe natural disasters they're trending higher, but that 0:19:09.680 --> 0:19:12.840 is like a staggering amount. And you know, I'll add 0:19:12.880 --> 0:19:16.400 to that. You see when you see companies dessert a state, why, 0:19:16.480 --> 0:19:18.080 I mean, why can't why don't they just charge more? 0:19:18.080 --> 0:19:20.640 And what's happened in the last couple of years that's 0:19:20.680 --> 0:19:22.560 so different than in the past. 0:19:23.920 --> 0:19:26.680 So let's maybe start with the statements that these insurance 0:19:26.680 --> 0:19:29.320 companies released why they are shoring out of the market, 0:19:29.480 --> 0:19:33.720 especially like in Florida. So they cited a higher risk 0:19:33.800 --> 0:19:36.960 in California was higher, while fire risk, which guest check, 0:19:37.080 --> 0:19:41.000 we see higher risk of that. They had higher building costs, 0:19:41.119 --> 0:19:45.000 so yeah, you know, spending paying for the cost of 0:19:45.000 --> 0:19:47.399 somebody rebuilding a home that has gone up as well. 0:19:48.000 --> 0:19:52.399 And then they also cited an increase in their own 0:19:52.520 --> 0:19:57.560 insurance policies, meaning insurance companies ensuring with what is called 0:19:57.560 --> 0:20:02.080 a reinsurance company that raid has also gone up for them. 0:20:02.480 --> 0:20:04.560 So they had to make a decision, you know, are 0:20:04.560 --> 0:20:07.480 we going to or can we pass on these higher 0:20:07.520 --> 0:20:11.199 costs that we have and create an insurance product that 0:20:11.359 --> 0:20:14.040 is competitive in the market. So can they then offer 0:20:14.520 --> 0:20:18.280 a insurance premium that people would be willing to pay? 0:20:18.640 --> 0:20:21.320 And obviously they made the decision that they're going to 0:20:21.560 --> 0:20:25.199 pause writing policies. And I think, you know, calling this 0:20:25.280 --> 0:20:27.879 a pause is important because this is not the first 0:20:27.880 --> 0:20:31.960 time that we've seen this happen. Insurance companies have retreated 0:20:32.280 --> 0:20:34.520 for a certain time period and then have come back 0:20:34.520 --> 0:20:37.520 into the market. So we've seen this, for instance, in 0:20:37.560 --> 0:20:41.120 the state of Louisiana when this happened before the same 0:20:41.160 --> 0:20:45.000 happened in Florida. You could also what you didn't see 0:20:45.000 --> 0:20:47.240 in the statement, you could also interpret this. This is 0:20:47.280 --> 0:20:50.520 what I personally interpret this approach as well, is sort 0:20:50.520 --> 0:20:54.679 of a signal to a state government saying maybe we 0:20:54.720 --> 0:20:57.800 need to rethink our partnership or maybe we need to 0:20:57.840 --> 0:21:00.159 engage in a partnership, and maybe they need to be 0:21:00.240 --> 0:21:04.480 legislation that incentivizes us to come back. Because, as you 0:21:04.560 --> 0:21:09.000 mentioned earlier, we do not want people to be without 0:21:09.040 --> 0:21:14.240 insurance because we know research shows that people recover much 0:21:14.480 --> 0:21:18.600 much slower from a disaster if they do not have insurance. 0:21:18.760 --> 0:21:22.120 And it's obvious because you don't have the financial resources. 0:21:22.320 --> 0:21:25.720 Unless you have massive savings, then maybe you don't need insurance. 0:21:26.119 --> 0:21:28.959 But if you're a person like me who doesn't have 0:21:29.000 --> 0:21:31.919 massive savings, I need insurance if I need to recover 0:21:32.080 --> 0:21:35.080 and rebuild my home. And so we want people to 0:21:35.160 --> 0:21:38.520 be insured. So the fewer people we have that have insurance, 0:21:38.920 --> 0:21:42.240 we are really foregoing what we know is a key 0:21:42.359 --> 0:21:43.880 factor to disaster recovery. 0:21:44.560 --> 0:21:47.760 Tracy Melanie said something, there's a lot there, but one 0:21:47.760 --> 0:21:50.160 thing that I just want to or sort of pull out. 0:21:50.680 --> 0:21:53.000 Is that point about higher construction costs because we talk 0:21:53.000 --> 0:21:55.760 about this all the time with inflation and labor costs 0:21:55.760 --> 0:21:58.560 and materials, et cetera. I mean, if it's like significantly 0:21:58.640 --> 0:22:01.720 more expensive in twenty two twenty three to rebuild a 0:22:01.760 --> 0:22:05.679 home than in twenty nineteen, then just not everything else aside, 0:22:05.680 --> 0:22:08.360 like mathematically you'd expect. Yeah, of course, like Insuran's got 0:22:08.400 --> 0:22:10.240 to be a compensated for. 0:22:10.200 --> 0:22:13.240 That, absolutely, Melanie. I want to go back to something 0:22:13.440 --> 0:22:16.040 you just said about, Well, maybe the insurers are sort 0:22:16.080 --> 0:22:21.520 of angling for legislative assistance and no one wants people 0:22:21.560 --> 0:22:25.199 to go uninsured. I mean, another way of looking at 0:22:25.240 --> 0:22:29.840 it is maybe we should be incentivizing people to move 0:22:30.000 --> 0:22:34.800 out of these risk prone areas by not providing them 0:22:34.840 --> 0:22:37.359 insurance and saying like, hey, if you want to live here, 0:22:37.480 --> 0:22:40.480 you're on your own, and if something happens, that's on you. 0:22:41.080 --> 0:22:45.280 I mean, is that a legitimate thought to have about this? 0:22:45.359 --> 0:22:48.639 And is there any evidence that people not having insurance 0:22:48.720 --> 0:22:51.400 actually does encourage them to move elsewhere? 0:22:53.119 --> 0:22:56.399 So what really encourages people to have insurance is having 0:22:56.440 --> 0:22:59.920 gone through a disaster, like we know, a key drive 0:23:00.200 --> 0:23:05.040 force for people to become proactive for instance, with regard 0:23:05.080 --> 0:23:08.520 to maybe thinking about elevating their home, purchasing insurance, maybe 0:23:08.520 --> 0:23:13.720 even moving, sort of really bracing for a future event 0:23:13.800 --> 0:23:16.480 and preparing to have less impacts in the future. The 0:23:16.600 --> 0:23:19.720 key driver for that is having gone through a disaster before, 0:23:20.000 --> 0:23:21.879 so experience is a key factor. 0:23:22.160 --> 0:23:25.160