1 00:00:10,080 --> 00:00:13,440 Speaker 1: Hello, and welcome to another episode of the All Thoughts Podcast. 2 00:00:13,520 --> 00:00:17,000 Speaker 1: I'm Tracy Alloway and I'm Joe. Do you know what 3 00:00:17,079 --> 00:00:20,880 Speaker 1: day it is? It's a very special day, like literally 4 00:00:20,920 --> 00:00:24,720 Speaker 1: the day. What do you just tell me? It's novemb okay, 5 00:00:24,760 --> 00:00:29,240 Speaker 1: do you know what novemb go on. By the time 6 00:00:29,280 --> 00:00:32,080 Speaker 1: this episode comes out, it will not be November, but 7 00:00:32,120 --> 00:00:33,920 Speaker 1: we are recording it at the end of the month, 8 00:00:34,400 --> 00:00:38,280 Speaker 1: and it is the end of hurricane season. Oh, I 9 00:00:38,320 --> 00:00:41,320 Speaker 1: did it right, So this is officially when this season 10 00:00:41,400 --> 00:00:43,600 Speaker 1: comes to an end. That's right. It's so starts on 11 00:00:43,720 --> 00:00:46,760 Speaker 1: June one and it ends at the end of November. 12 00:00:47,280 --> 00:00:51,680 Speaker 1: And it has been an unusual season for hurricanes. I 13 00:00:51,720 --> 00:00:56,000 Speaker 1: think it was really quiet right through August, and I 14 00:00:56,040 --> 00:00:58,520 Speaker 1: actually tweeted something about this, so maybe I jinxed it. 15 00:00:58,800 --> 00:01:02,160 Speaker 1: But then in September we had a whole bunch of hurricanes, 16 00:01:02,240 --> 00:01:05,440 Speaker 1: I think four major ones, including Hurricane Ian, which was 17 00:01:05,480 --> 00:01:09,440 Speaker 1: the deadliest hurricane to hit the US in two decades. Yeah, 18 00:01:09,480 --> 00:01:11,600 Speaker 1: this is always kind of I mean, it's kind of random. 19 00:01:11,640 --> 00:01:14,240 Speaker 1: It's interesting because I think of Florida as being like 20 00:01:14,280 --> 00:01:17,520 Speaker 1: an hurricane Alliott, right and right there, but it hadn't 21 00:01:17,520 --> 00:01:19,720 Speaker 1: actually been hit by a hurricane in a long time, 22 00:01:20,040 --> 00:01:22,399 Speaker 1: but this was a really big one. I'm seeing something 23 00:01:22,440 --> 00:01:26,640 Speaker 1: that at least over fifty billion dollars in damage. And 24 00:01:26,680 --> 00:01:30,600 Speaker 1: then beyond hurricanes, and we'll talk about them, obviously, like 25 00:01:30,880 --> 00:01:34,000 Speaker 1: weather and extreme weather events seems to come up a 26 00:01:34,000 --> 00:01:36,639 Speaker 1: lot for us in terms of things we talked about 27 00:01:37,000 --> 00:01:43,040 Speaker 1: climate risk, drought, the heat of rivers and lakes. Weather 28 00:01:43,120 --> 00:01:45,119 Speaker 1: seems to be popping up a lot, but we haven't 29 00:01:45,160 --> 00:01:47,920 Speaker 1: actually really like talked about that as a consistent thing. No, 30 00:01:48,120 --> 00:01:50,680 Speaker 1: So we had this erratic hurricane season, but we also 31 00:01:50,720 --> 00:01:54,000 Speaker 1: had major droughts around the world. As you mentioned, there 32 00:01:54,080 --> 00:01:57,000 Speaker 1: was a drought even in in the Northeast in places 33 00:01:57,000 --> 00:02:01,480 Speaker 1: like Connecticut, which is kind of unusual. Made your extreme 34 00:02:01,640 --> 00:02:05,800 Speaker 1: weather events seem to be happening more often, and this 35 00:02:05,880 --> 00:02:09,359 Speaker 1: kind of begs the question of how the financial industry 36 00:02:09,520 --> 00:02:11,720 Speaker 1: is thinking about this, because of course there is a 37 00:02:11,720 --> 00:02:16,040 Speaker 1: lot of money that is related to things like the weather, right, 38 00:02:16,080 --> 00:02:19,320 Speaker 1: and so we think of, you know, obviously, when there 39 00:02:19,400 --> 00:02:23,160 Speaker 1: is a major hurricane with pupils, homes and infrastructure being destroyed, 40 00:02:23,160 --> 00:02:28,840 Speaker 1: the sort of straightforward insurance reinsurance cost associated with that, 41 00:02:29,480 --> 00:02:32,000 Speaker 1: and then of course all these other things that create 42 00:02:32,160 --> 00:02:36,360 Speaker 1: business disruptions of various swords. Again, going back to the drought, 43 00:02:36,400 --> 00:02:40,200 Speaker 1: we recently talked about affecting the corn market on the 44 00:02:40,200 --> 00:02:46,200 Speaker 1: Mississippi River, and so yes, financial implications abound from unpredictable 45 00:02:46,280 --> 00:02:49,359 Speaker 1: variations in the weather absolutely, And today I am very 46 00:02:49,360 --> 00:02:51,560 Speaker 1: pleased to say we are going to be discussing something 47 00:02:51,600 --> 00:02:54,200 Speaker 1: that we've been meaning to for a long time, which 48 00:02:54,240 --> 00:02:58,720 Speaker 1: is how the insurance industry is basically handling extreme weather 49 00:02:58,840 --> 00:03:03,040 Speaker 1: events and what the implications of extreme weather events are 50 00:03:03,160 --> 00:03:09,280 Speaker 1: for the vast ecosystem of insurance links, securities and products 51 00:03:09,400 --> 00:03:13,160 Speaker 1: and reinsurance. There's this whole massive pool of money that 52 00:03:13,320 --> 00:03:16,720 Speaker 1: is basically set up for these events, but it feels 53 00:03:16,760 --> 00:03:19,560 Speaker 1: like we don't talk about it often enough. So we're 54 00:03:19,600 --> 00:03:22,080 Speaker 1: going to rectify that today with someone who talks about 55 00:03:22,080 --> 00:03:24,440 Speaker 1: it all the time. We're going to be speaking with 56 00:03:24,480 --> 00:03:27,840 Speaker 1: Steve Evans. He is, of course the owner of Artemis, 57 00:03:27,880 --> 00:03:32,000 Speaker 1: which is a publication covering the insurance linked securities market, 58 00:03:32,480 --> 00:03:36,240 Speaker 1: and he is also the owner of Reinsurance News, So 59 00:03:36,600 --> 00:03:40,360 Speaker 1: really the perfect person. Yeah, all right, Steve, thank you 60 00:03:40,400 --> 00:03:43,120 Speaker 1: so much for coming on. Ad thoughts. Thank you, Tracy, 61 00:03:43,200 --> 00:03:45,000 Speaker 1: thank you Joe. It's a pleasure to be here and 62 00:03:45,040 --> 00:03:46,840 Speaker 1: I've I've been looking forward to being one of the 63 00:03:46,880 --> 00:03:53,760 Speaker 1: perfect guests as an avid listener. Thank you. So, maybe 64 00:03:53,800 --> 00:03:57,000 Speaker 1: just to begin with, can you talk about, like from 65 00:03:57,040 --> 00:04:02,360 Speaker 1: your perspective, from the insurance industry perspective, does it seem 66 00:04:02,440 --> 00:04:06,520 Speaker 1: like extreme weather is becoming more of an issue? Is 67 00:04:06,560 --> 00:04:09,120 Speaker 1: this a topic that is cropping up more for you? 68 00:04:10,920 --> 00:04:14,600 Speaker 1: And absolutely it's an area that's cropping up even more 69 00:04:14,720 --> 00:04:18,120 Speaker 1: these days. I mean, extreme weather has been something that 70 00:04:18,160 --> 00:04:22,799 Speaker 1: the insurance industry has provided capital to support for hundreds 71 00:04:22,839 --> 00:04:24,680 Speaker 1: of years now. I mean it's one of the major 72 00:04:24,760 --> 00:04:28,000 Speaker 1: risks that the marine insurance market covered. When you were 73 00:04:28,040 --> 00:04:31,080 Speaker 1: heading off across the Atlantic to go and gather your 74 00:04:31,279 --> 00:04:34,280 Speaker 1: commodities from overseas, you'd you'd want to make sure that 75 00:04:34,320 --> 00:04:36,280 Speaker 1: your boat was going to make it back on in 76 00:04:36,360 --> 00:04:38,719 Speaker 1: one piece, and storms were one of the things that 77 00:04:38,760 --> 00:04:42,200 Speaker 1: you wanted financial protection against. So the insurance industry has 78 00:04:42,240 --> 00:04:45,719 Speaker 1: been in this space for forever, really since the industry began, 79 00:04:46,600 --> 00:04:49,120 Speaker 1: but I guess over the last sort of two decades 80 00:04:49,320 --> 00:04:55,040 Speaker 1: it's become an increasingly important focus point. Obviously with the 81 00:04:55,080 --> 00:04:59,120 Speaker 1: climate change discussion alongside that as well. Now I guess 82 00:04:59,160 --> 00:05:03,560 Speaker 1: insurance in range Duras are hedging weather within many of 83 00:05:03,600 --> 00:05:06,880 Speaker 1: their product sets. But then you have the specific area 84 00:05:06,920 --> 00:05:10,080 Speaker 1: of the market that really interests me, which is around catastrophe, 85 00:05:10,120 --> 00:05:12,920 Speaker 1: severe weather, and all of the areas you you mentioned 86 00:05:12,920 --> 00:05:15,960 Speaker 1: in your opener there, and this is an area that's 87 00:05:16,320 --> 00:05:19,640 Speaker 1: just become much more sophisticated. I guess it's probably three 88 00:05:19,680 --> 00:05:23,800 Speaker 1: decades now since the first major catastrophe models came along, 89 00:05:23,880 --> 00:05:29,520 Speaker 1: which were software designed to really help people not predict 90 00:05:29,600 --> 00:05:33,120 Speaker 1: when whether it's going to happen, but understand the magnitude 91 00:05:33,200 --> 00:05:35,760 Speaker 1: of the potential impacts it could have and how that 92 00:05:35,760 --> 00:05:40,400 Speaker 1: would affect portfolios, whether that's portfolios of insurance, rare score, 93 00:05:40,400 --> 00:05:44,000 Speaker 1: portfolios of property. And I guess the the advent of 94 00:05:44,000 --> 00:05:47,279 Speaker 1: the cat model, which really they pretty much came out 95 00:05:47,320 --> 00:05:50,679 Speaker 1: of places like universities in the States and even Silicon Valley, 96 00:05:50,680 --> 00:05:53,120 Speaker 1: one of the main cat modeling firms came out of. 97 00:05:53,680 --> 00:05:56,040 Speaker 1: That's really helped the industry to get a better hand 98 00:05:56,040 --> 00:05:59,920 Speaker 1: along catastrophe risk and help to develop the whole catastrophe 99 00:06:00,040 --> 00:06:03,919 Speaker 1: insurance market into something that's a really meaningful piece of 100 00:06:04,000 --> 00:06:08,320 Speaker 1: overall insurance capital today. And alongside that, we also have 101 00:06:08,520 --> 00:06:13,520 Speaker 1: everything from weather derivatives to swaps between companies, and what's 102 00:06:13,560 --> 00:06:16,560 Speaker 1: called parametric insurance, which is another area of the market 103 00:06:16,600 --> 00:06:20,560 Speaker 1: that's particularly interesting right now and moving forwards very rapidly, 104 00:06:20,920 --> 00:06:24,400 Speaker 1: particularly with what we always refer to as the insure 105 00:06:24,440 --> 00:06:29,960 Speaker 1: tech trend, where tech advancements are coming into insurance carriers. Finally, 106 00:06:30,720 --> 00:06:34,679 Speaker 1: it's taken a while, but now companies are increasingly looking 107 00:06:34,720 --> 00:06:38,200 Speaker 1: at new ways to construct products to help their customers 108 00:06:38,240 --> 00:06:42,240 Speaker 1: hedge risk as well, just on the modeling points. So 109 00:06:42,560 --> 00:06:47,920 Speaker 1: my my impression of the insurance links securities industry is 110 00:06:47,960 --> 00:06:50,200 Speaker 1: that one of the reasons it became so big was 111 00:06:50,279 --> 00:06:55,240 Speaker 1: because of improvements in weather modeling, and it gave investors 112 00:06:55,279 --> 00:07:00,440 Speaker 1: maybe some reassurance that they were gauging and pricing weather 113 00:07:00,480 --> 00:07:04,320 Speaker 1: related risks more accurately. Has that been a major factor 114 00:07:04,600 --> 00:07:09,320 Speaker 1: in the growth and development of this market. Absolutely. I mean, 115 00:07:09,560 --> 00:07:12,640 Speaker 1: I guess there's there's two types of technology that really 116 00:07:12,680 --> 00:07:16,760 Speaker 1: helped the insurance lon securities market come about. There's the 117 00:07:16,760 --> 00:07:19,360 Speaker 1: the advent of the cat model. Then the sort of 118 00:07:19,400 --> 00:07:23,200 Speaker 1: advancement of the cat model into the two main peak perils, 119 00:07:23,200 --> 00:07:26,840 Speaker 1: which are really predominantly US hurricane risk. That's really the 120 00:07:27,400 --> 00:07:31,240 Speaker 1: peak exposure in the whole world, but then other cyclone 121 00:07:31,280 --> 00:07:34,160 Speaker 1: and storm risks around the world, and then earthquake risk 122 00:07:34,280 --> 00:07:37,200 Speaker 1: being the other one. When the cat models came around, 123 00:07:37,240 --> 00:07:40,680 Speaker 1: it helped companies to really understand what exposure they were 124 00:07:40,720 --> 00:07:43,680 Speaker 1: taking on. So I'm thinking about the insurance and reinsurance 125 00:07:43,680 --> 00:07:47,840 Speaker 1: companies of the world there, and they realized that really 126 00:07:47,880 --> 00:07:52,080 Speaker 1: that the capacity within the insurance market itself was probably 127 00:07:52,120 --> 00:07:54,640 Speaker 1: not sufficient for the really peak events if you think 128 00:07:54,680 --> 00:07:58,720 Speaker 1: about a Cat five hurricane barreling into Miami one day, 129 00:07:58,840 --> 00:08:03,400 Speaker 1: or San Francisco having a really serious earthquake event, or 130 00:08:03,440 --> 00:08:05,800 Speaker 1: Tokyo or any of the other big cities of the world. 131 00:08:06,440 --> 00:08:10,440 Speaker 1: And there was a sort of a recognition that tapping 132 00:08:10,480 --> 00:08:14,040 Speaker 1: into the deepest, most liquid pool of capital available would 133 00:08:14,040 --> 00:08:16,720 Speaker 1: be a beneficial thing for the insurance and reinsurance market. 134 00:08:16,760 --> 00:08:20,600 Speaker 1: It's already funded by institutional investors, obviously on the shareholder side, 135 00:08:20,960 --> 00:08:25,520 Speaker 1: but this was seen whether there could be the development 136 00:08:25,560 --> 00:08:29,040 Speaker 1: of almost a companion source of risk capital that the 137 00:08:29,120 --> 00:08:32,640 Speaker 1: companies in the insurance space could tap into. And so 138 00:08:33,720 --> 00:08:36,600 Speaker 1: really the next bit of technology alongside the cat models 139 00:08:36,679 --> 00:08:40,119 Speaker 1: was actually financial technology. So the plumbing of the financial 140 00:08:40,160 --> 00:08:44,800 Speaker 1: world and predominantly the fund structure and securitization as well. 141 00:08:45,200 --> 00:08:49,200 Speaker 1: That helped very bright people in the early days and 142 00:08:49,360 --> 00:08:52,920 Speaker 1: very small companies that are sometimes span out of existing 143 00:08:52,920 --> 00:08:56,480 Speaker 1: reinsurers or sometimes set up as like individual hedge fund 144 00:08:56,520 --> 00:09:01,479 Speaker 1: type managers, and they started to construct financial all instruments 145 00:09:01,520 --> 00:09:05,560 Speaker 1: that would allow catastrophe risk to be contained within them, 146 00:09:05,600 --> 00:09:08,800 Speaker 1: modeling to be put against that, to develop the understanding 147 00:09:08,880 --> 00:09:11,040 Speaker 1: for that risk, and to enable a price to be 148 00:09:11,080 --> 00:09:14,079 Speaker 1: put on it as well, and then that was issued 149 00:09:14,120 --> 00:09:17,400 Speaker 1: out in a form that was investable. And so these 150 00:09:17,440 --> 00:09:20,480 Speaker 1: sort of niche little hedge funds that set themselves up 151 00:09:20,520 --> 00:09:23,320 Speaker 1: and started to target the space could build portfolios for 152 00:09:23,360 --> 00:09:26,080 Speaker 1: their third party investor base. So I think without the 153 00:09:26,080 --> 00:09:28,480 Speaker 1: cap models, it would have been very hard to see 154 00:09:28,840 --> 00:09:30,880 Speaker 1: the I l S market, as we call it development. 155 00:09:47,960 --> 00:09:50,840 Speaker 1: So I have a short quotion first, but how big 156 00:09:50,920 --> 00:09:54,199 Speaker 1: is this? Are these markets that we're talking about so 157 00:09:54,600 --> 00:09:58,280 Speaker 1: very difficult to give an accurate number. It's changing all 158 00:09:58,320 --> 00:10:00,480 Speaker 1: the time with events and thing as a land and 159 00:10:00,559 --> 00:10:03,920 Speaker 1: within flows and outflows. But it's been estimated that global 160 00:10:04,080 --> 00:10:08,240 Speaker 1: sort of reinsurance capital has been somewhere around the six 161 00:10:08,320 --> 00:10:12,040 Speaker 1: hundred billion ish mark for a few years. The I 162 00:10:12,320 --> 00:10:15,520 Speaker 1: L S capital within that is anywhere between eighty to 163 00:10:15,600 --> 00:10:18,840 Speaker 1: a hundred billion, depending on which type of structures and 164 00:10:19,760 --> 00:10:22,840 Speaker 1: funds and things like that you include within it. So 165 00:10:23,080 --> 00:10:25,800 Speaker 1: the thing that I maybe her once or that my 166 00:10:25,920 --> 00:10:30,760 Speaker 1: understanding is that part of the appeal of investments that 167 00:10:31,120 --> 00:10:34,559 Speaker 1: essentially lose money when there's a big catastrophe is that, 168 00:10:34,720 --> 00:10:38,040 Speaker 1: you know, people are always seeking uncorrelated returns, and so 169 00:10:38,120 --> 00:10:40,600 Speaker 1: much of the economy is correlated because when there's a 170 00:10:40,600 --> 00:10:44,000 Speaker 1: recession and everything is hit all at once, and that 171 00:10:44,200 --> 00:10:48,560 Speaker 1: the physical catastrophes, whether they be hurricanes or earthquakes or 172 00:10:48,600 --> 00:10:51,320 Speaker 1: other storms, are at a type of risk that is 173 00:10:51,360 --> 00:10:54,280 Speaker 1: not going to be cyclical related to the economy, because 174 00:10:54,360 --> 00:10:58,760 Speaker 1: hurricanes can happen in recessions or booms. And so does 175 00:10:58,800 --> 00:11:02,000 Speaker 1: it work out like that in practice and theory? I 176 00:11:02,080 --> 00:11:05,880 Speaker 1: get that that makes total sense. In practice. Do securities 177 00:11:06,040 --> 00:11:09,880 Speaker 1: that are linked to extreme events properly exhibit these sort 178 00:11:09,920 --> 00:11:14,920 Speaker 1: of uncorrelated payout structures. It's a very good question. Definitely. 179 00:11:15,160 --> 00:11:18,840 Speaker 1: The lack of correlation is an important aspect that attracts 180 00:11:18,880 --> 00:11:21,760 Speaker 1: investors to the space. Now, I say lack of correlation 181 00:11:21,880 --> 00:11:26,080 Speaker 1: because I don't think anything is ever fully uncorrelated when 182 00:11:26,080 --> 00:11:29,800 Speaker 1: you're talking about potentially world changing events. So a good 183 00:11:29,800 --> 00:11:33,800 Speaker 1: example actually is the Tohoku earthquake consumed army in Japan. 184 00:11:34,760 --> 00:11:38,280 Speaker 1: Now that was a very major insurance market event. It 185 00:11:38,360 --> 00:11:41,600 Speaker 1: had some impact to the I L S market, including 186 00:11:41,760 --> 00:11:46,680 Speaker 1: to a number of catastrophe bonds, mostly in marketer market loss. 187 00:11:46,720 --> 00:11:48,640 Speaker 1: It's for the cap on market that there were some 188 00:11:48,880 --> 00:11:52,920 Speaker 1: drawdowns of principle as well. And when that event occurred, 189 00:11:52,960 --> 00:11:56,600 Speaker 1: there was a decline in Japanese equities, there was a 190 00:11:56,600 --> 00:11:59,520 Speaker 1: decline in the Japanese economy and things like that, but 191 00:12:00,120 --> 00:12:04,240 Speaker 1: that will bounced back quite quickly. So I think predominantly 192 00:12:04,559 --> 00:12:09,760 Speaker 1: natural catastrophe and weather risk are diversifying. I would never 193 00:12:09,800 --> 00:12:13,120 Speaker 1: say totally uncorrelated, because I think when the biggest sort 194 00:12:13,160 --> 00:12:16,360 Speaker 1: of market moving events occur in the KNAT CAT space, 195 00:12:16,800 --> 00:12:21,880 Speaker 1: they're still going to move some indices, but the recovery 196 00:12:21,960 --> 00:12:24,360 Speaker 1: from the event should be far far quicker, and so 197 00:12:24,880 --> 00:12:28,200 Speaker 1: it's really a very very far tail risk correlation. I 198 00:12:28,200 --> 00:12:30,319 Speaker 1: would say a lot of people talk about I L 199 00:12:30,440 --> 00:12:34,319 Speaker 1: S as being lightly correlated or loosely correlated rather than 200 00:12:34,320 --> 00:12:38,320 Speaker 1: being completely uncorrelated, and I think investors should really be 201 00:12:38,440 --> 00:12:41,680 Speaker 1: educated to the degree that a correlation could occur but 202 00:12:41,720 --> 00:12:44,120 Speaker 1: it's probably not going to be something that you really 203 00:12:44,120 --> 00:12:47,199 Speaker 1: need to worry about in the overall scheme of your portfolio. 204 00:12:47,840 --> 00:12:50,240 Speaker 1: I remember this was something that came up when I 205 00:12:50,280 --> 00:12:54,400 Speaker 1: was writing about the World Bank's pandemic which failed to trigger, 206 00:12:54,520 --> 00:12:57,120 Speaker 1: and you know, one of the selling points for those was, well, 207 00:12:57,160 --> 00:13:01,920 Speaker 1: by pandemic exposure going to be uncoorrelated. But then you 208 00:13:02,000 --> 00:13:07,040 Speaker 1: have this massive global pandemic and the market's absolutely dropped, 209 00:13:07,040 --> 00:13:10,320 Speaker 1: and it turns out that you know, it was rather correlated. 210 00:13:10,400 --> 00:13:14,000 Speaker 1: But okay, Steve, a related question, can you talk a 211 00:13:14,000 --> 00:13:17,080 Speaker 1: little bit about the pricing of cat bonds or other 212 00:13:17,120 --> 00:13:20,880 Speaker 1: insurance linked securities and products, because this is also kind 213 00:13:20,880 --> 00:13:24,880 Speaker 1: of a sensitive point, which is you want it priced 214 00:13:25,120 --> 00:13:28,760 Speaker 1: enough that investors are going to come in and buy 215 00:13:28,840 --> 00:13:32,360 Speaker 1: these things because they feel they're being accurately compensated for 216 00:13:32,520 --> 00:13:35,160 Speaker 1: the risk that the bonds are potentially going to get 217 00:13:35,200 --> 00:13:37,320 Speaker 1: written down to zero or something like that if there 218 00:13:37,400 --> 00:13:41,440 Speaker 1: is a major catastrophe. But at the same time, you 219 00:13:41,600 --> 00:13:45,679 Speaker 1: don't want the payout to be so rich that it 220 00:13:45,720 --> 00:13:49,280 Speaker 1: becomes uneconomical for the insurers or the governments who are 221 00:13:49,280 --> 00:13:52,480 Speaker 1: actually issuing these things. So how are people thinking about 222 00:13:53,040 --> 00:13:58,679 Speaker 1: that pricing aspect, especially as we get more extreme weather events, 223 00:13:58,720 --> 00:14:02,920 Speaker 1: our investors demanding more of a return for taking on 224 00:14:02,960 --> 00:14:08,120 Speaker 1: this risk. Sure, very timely question, because right at this 225 00:14:08,200 --> 00:14:11,800 Speaker 1: point in time, certainly investors are demanding more return. There's 226 00:14:11,800 --> 00:14:15,920 Speaker 1: been a particularly difficult number of years for the global 227 00:14:16,000 --> 00:14:19,280 Speaker 1: reinsurance market as a whole. And whenever the reinsurance market 228 00:14:19,320 --> 00:14:23,000 Speaker 1: has significant losses from severe weather or catastrophes, than the 229 00:14:23,040 --> 00:14:25,160 Speaker 1: I L S market will take a share because it 230 00:14:25,320 --> 00:14:29,440 Speaker 1: is providing a significant proportion of the capital these days. 231 00:14:29,600 --> 00:14:33,600 Speaker 1: So since obviously we had a severe hurricane season that year, 232 00:14:33,640 --> 00:14:39,440 Speaker 1: we've had wildfires, floods, more hurricanes, some earthquakes, a number 233 00:14:39,480 --> 00:14:42,840 Speaker 1: of other other events, and there have been losses. And 234 00:14:42,840 --> 00:14:47,240 Speaker 1: now the losses haven't been enough to significantly damp and 235 00:14:47,360 --> 00:14:52,280 Speaker 1: investor demand until you start to get repeat years. And 236 00:14:52,280 --> 00:14:55,160 Speaker 1: and actually we have seen a decline in investor demand 237 00:14:55,320 --> 00:14:58,800 Speaker 1: through this year, but that's also happened at exactly the 238 00:14:58,840 --> 00:15:02,240 Speaker 1: same time as we've had had some financial market pressures. 239 00:15:02,280 --> 00:15:05,840 Speaker 1: Obviously there's the war Russia's war in Ukraine going on, 240 00:15:06,080 --> 00:15:09,120 Speaker 1: and then you've got inflation as well, and all of 241 00:15:09,160 --> 00:15:11,480 Speaker 1: this has kind of come home to roost in one 242 00:15:11,600 --> 00:15:14,480 Speaker 1: single year for the insurance market, and as a result, 243 00:15:14,600 --> 00:15:19,200 Speaker 1: we see reinsurance rates and pricing going up, and in tandem, 244 00:15:19,400 --> 00:15:22,120 Speaker 1: rates for insurance link securities are going up as well, 245 00:15:22,480 --> 00:15:27,480 Speaker 1: because insurance line securities are essentially largely providing capital either 246 00:15:27,520 --> 00:15:31,040 Speaker 1: to an insurance or reinsurance arrangement, and so the pricing 247 00:15:31,440 --> 00:15:34,240 Speaker 1: kind of follows the pricing of the traditional insurance and 248 00:15:34,280 --> 00:15:38,560 Speaker 1: reinsurance market to a degree. Now, there are some capital 249 00:15:38,560 --> 00:15:42,840 Speaker 1: efficiencies in terms of being able to tap diversifying sources, 250 00:15:43,160 --> 00:15:47,440 Speaker 1: being able to distribute risk into an enormous market such 251 00:15:47,480 --> 00:15:49,520 Speaker 1: as the capital markets as well, which can give some 252 00:15:49,880 --> 00:15:52,960 Speaker 1: sort of capital efficiencies as well. But then there are 253 00:15:52,960 --> 00:15:57,040 Speaker 1: additional costs sometimes with issuing insurance lin securities because they 254 00:15:57,040 --> 00:16:01,640 Speaker 1: are financial securitization structures and so they do have additional 255 00:16:01,680 --> 00:16:04,640 Speaker 1: cost attached to them sometimes as well. But the pricing 256 00:16:04,680 --> 00:16:08,760 Speaker 1: does sort of tend to follow traditional reinsurance and I 257 00:16:08,800 --> 00:16:12,200 Speaker 1: guess the one thing that everybody in the insurance industry 258 00:16:12,200 --> 00:16:14,640 Speaker 1: will always point to when it is particularly when it 259 00:16:14,680 --> 00:16:17,800 Speaker 1: comes to climate sort of variability and climate change and 260 00:16:17,920 --> 00:16:21,080 Speaker 1: how the risk might be changing over time, is that 261 00:16:21,360 --> 00:16:26,200 Speaker 1: typically these are transactions on the traditional reinsurance side, they 262 00:16:26,240 --> 00:16:28,880 Speaker 1: might be one year to three year. On the insurance 263 00:16:28,920 --> 00:16:31,520 Speaker 1: link security side, they might be sort of two to 264 00:16:31,640 --> 00:16:34,680 Speaker 1: five years and tenure, So you are getting a chance 265 00:16:34,720 --> 00:16:39,400 Speaker 1: to reprice that risk now. Within an insurance link securities transaction, 266 00:16:39,440 --> 00:16:43,160 Speaker 1: there's also what's called an annual reset as well, where 267 00:16:43,240 --> 00:16:47,440 Speaker 1: a sponsor can adjust the profile of risk that's covered 268 00:16:47,440 --> 00:16:51,040 Speaker 1: in the transaction. But at the same time, the metrics 269 00:16:51,120 --> 00:16:53,560 Speaker 1: that are used to calculate the coupon payment for the 270 00:16:53,600 --> 00:16:57,760 Speaker 1: investors also get adjusted as well, So as the risk changes, 271 00:16:58,360 --> 00:17:01,040 Speaker 1: you get a chance to reprice the risk when you 272 00:17:01,080 --> 00:17:04,560 Speaker 1: either renew a contract or you reset a contract. And 273 00:17:04,640 --> 00:17:08,640 Speaker 1: so the idea is, in an ideal world, the pricing 274 00:17:08,680 --> 00:17:12,040 Speaker 1: would keep up with the changes. Now when the whole 275 00:17:12,080 --> 00:17:17,760 Speaker 1: industry feels like perhaps it's been sort of underpricing for 276 00:17:17,800 --> 00:17:20,360 Speaker 1: a little while, which I think is something that most 277 00:17:20,400 --> 00:17:23,720 Speaker 1: of the industry would recognize that we had some particularly 278 00:17:23,760 --> 00:17:26,959 Speaker 1: big sort of inflows of capital. We also had some 279 00:17:27,040 --> 00:17:32,320 Speaker 1: particularly benine years in terms of catastrophes through the tens, 280 00:17:32,920 --> 00:17:37,000 Speaker 1: right up to seventeen when suddenly the hurricane season exploded 281 00:17:37,040 --> 00:17:39,320 Speaker 1: and we had three major storms all in a row. 282 00:17:40,160 --> 00:17:43,159 Speaker 1: And I think now it's taken a few years for 283 00:17:43,200 --> 00:17:46,320 Speaker 1: it to sort of sink in that there really is 284 00:17:46,359 --> 00:17:51,800 Speaker 1: a need for for higher pricing. Alongside that, without a doubt, 285 00:17:51,840 --> 00:17:55,760 Speaker 1: there appears to be changes in sort of frequency of 286 00:17:55,800 --> 00:18:00,280 Speaker 1: events and potentially severity as well. But also some climate 287 00:18:00,359 --> 00:18:03,480 Speaker 1: scientists would say that the the overall sort of the 288 00:18:03,520 --> 00:18:08,000 Speaker 1: way a hurricane exhibits its damage might have changed or 289 00:18:08,119 --> 00:18:10,960 Speaker 1: might be set to change with climate change as well, 290 00:18:11,000 --> 00:18:15,800 Speaker 1: in terms of potentially carrying more water, potentially storms getting bigger, 291 00:18:15,840 --> 00:18:18,399 Speaker 1: that sort of thing. So there's a lot of money 292 00:18:18,480 --> 00:18:22,960 Speaker 1: spent on both the traditional cap catastrophe models that the 293 00:18:22,960 --> 00:18:25,320 Speaker 1: industry is used now for about thirty years or so, 294 00:18:25,640 --> 00:18:29,440 Speaker 1: but also increasingly on climate models and climate simulations as well, 295 00:18:29,480 --> 00:18:32,359 Speaker 1: where people are trying to look ahead twenty to forty 296 00:18:32,440 --> 00:18:36,639 Speaker 1: years to try and see how the impact of storms 297 00:18:36,720 --> 00:18:39,879 Speaker 1: such as hurricanes might change over us a broader period 298 00:18:39,920 --> 00:18:42,600 Speaker 1: of time. And really there's there's just a lot more 299 00:18:42,680 --> 00:18:46,760 Speaker 1: research nowadays with better technology being available as well, to 300 00:18:46,800 --> 00:18:50,159 Speaker 1: try and help people to price risk better but also 301 00:18:50,280 --> 00:18:53,600 Speaker 1: to perhaps ensure that the pricing is more sustainable over 302 00:18:53,640 --> 00:18:56,040 Speaker 1: a longer period of time as well. Yeah, I want 303 00:18:56,040 --> 00:18:59,200 Speaker 1: to just talk further about that because I guess, like 304 00:18:59,240 --> 00:19:01,760 Speaker 1: you know, part of the appeal of investing in this 305 00:19:01,840 --> 00:19:04,359 Speaker 1: space is that there's just gonna be some randomness. We 306 00:19:04,440 --> 00:19:07,720 Speaker 1: talked about this sort of lightly correlated market, and you 307 00:19:07,800 --> 00:19:10,760 Speaker 1: might have a year or two a very extreme hurricane, 308 00:19:11,240 --> 00:19:13,720 Speaker 1: and then you might have years and years where Florida 309 00:19:13,760 --> 00:19:17,640 Speaker 1: and other major property areas really don't get hit much 310 00:19:17,640 --> 00:19:21,040 Speaker 1: at all. But I would imagine that if there is 311 00:19:21,080 --> 00:19:25,520 Speaker 1: a sort of significant climate change element to this, that 312 00:19:25,640 --> 00:19:28,520 Speaker 1: perhaps some of this randomness could go away, or that 313 00:19:28,560 --> 00:19:30,960 Speaker 1: you know, could get worse and worse in some sort 314 00:19:30,960 --> 00:19:34,920 Speaker 1: of maybe predictable trajectory. Can you talk a little bit 315 00:19:34,960 --> 00:19:37,720 Speaker 1: more about the sort of intersection of sort of extreme 316 00:19:37,760 --> 00:19:41,080 Speaker 1: weather risk with the climate modeling that you're talking about 317 00:19:41,080 --> 00:19:44,439 Speaker 1: and how it changes the industry If there's a perception 318 00:19:45,200 --> 00:19:47,719 Speaker 1: that some of these things aren't random and that there 319 00:19:47,720 --> 00:19:50,360 Speaker 1: are trends that are going to sustain themselves for years 320 00:19:50,400 --> 00:19:54,000 Speaker 1: to come, that's that's actually quite a difficult question to answer, 321 00:19:54,040 --> 00:19:55,800 Speaker 1: to be honest with you, without talking to the to 322 00:19:55,840 --> 00:19:58,480 Speaker 1: the people with the money or the underwriters on the ground. 323 00:19:58,480 --> 00:20:01,200 Speaker 1: But I guess mors months to that would be that 324 00:20:01,240 --> 00:20:06,640 Speaker 1: the industry is certainly looking far ahead now in terms 325 00:20:06,640 --> 00:20:09,840 Speaker 1: of the research and analysis that they're doing, and they're 326 00:20:09,840 --> 00:20:13,119 Speaker 1: really trying to understand where the trajectory of events is going, 327 00:20:13,560 --> 00:20:16,800 Speaker 1: but it can be very difficult to pinpoint that in 328 00:20:16,840 --> 00:20:20,280 Speaker 1: any exact way. And Tracy began this by saying that 329 00:20:20,320 --> 00:20:23,520 Speaker 1: this year's hurricane season was a little strange. Now, some 330 00:20:23,640 --> 00:20:26,320 Speaker 1: of the forecasts in advance of the hurricane season from 331 00:20:26,320 --> 00:20:30,800 Speaker 1: the main meteorological agencies were predicting huge numbers of storms, 332 00:20:30,840 --> 00:20:34,119 Speaker 1: and we just didn't see that. So you really can't 333 00:20:34,280 --> 00:20:37,560 Speaker 1: go out and buy your protection based on a forecast. 334 00:20:37,680 --> 00:20:41,080 Speaker 1: You've got to look at sort of recent history plus 335 00:20:41,119 --> 00:20:44,439 Speaker 1: factor in your forward looking climate science and try and 336 00:20:44,480 --> 00:20:47,760 Speaker 1: come up with something reasonable for the next season or 337 00:20:47,800 --> 00:20:51,159 Speaker 1: two seasons or three seasons. Now, I'm sure at a 338 00:20:51,240 --> 00:20:54,080 Speaker 1: the CFO level of the big insurance companies they're thinking 339 00:20:54,160 --> 00:20:57,040 Speaker 1: much further ahead and wondering how they're going to adjust 340 00:20:57,119 --> 00:21:01,400 Speaker 1: their pricing to accommodate the ential climate of the future. 341 00:21:01,840 --> 00:21:04,679 Speaker 1: But I think on the sort of underwriting side, the 342 00:21:04,720 --> 00:21:08,920 Speaker 1: people who are sort of analyzing underwriting and then pricing 343 00:21:08,960 --> 00:21:12,080 Speaker 1: these risks, they're thinking about the duration of the contract 344 00:21:12,119 --> 00:21:15,280 Speaker 1: and what could happen within that period of time, and 345 00:21:15,359 --> 00:21:18,879 Speaker 1: there's other factors out there that have really been as 346 00:21:19,040 --> 00:21:22,520 Speaker 1: damaging in some ways in terms of losses as the 347 00:21:22,600 --> 00:21:25,679 Speaker 1: events themselves in some cases, and I'm thinking here about 348 00:21:26,240 --> 00:21:32,440 Speaker 1: elements like social inflation litigation alongside inflated prices and how 349 00:21:32,480 --> 00:21:37,560 Speaker 1: that that is affecting property, sort of rebuild costs and 350 00:21:37,600 --> 00:21:40,000 Speaker 1: things like that. There's a lot been going on over 351 00:21:40,040 --> 00:21:43,199 Speaker 1: the last five years, which is all sort of coincided 352 00:21:43,240 --> 00:21:47,479 Speaker 1: with a particularly challenging period of catastrophe activity as well, 353 00:21:47,840 --> 00:21:51,439 Speaker 1: and when hurricanes have hit Florida and the industry has 354 00:21:51,480 --> 00:21:54,199 Speaker 1: been hit by what we tend to call loss creep, 355 00:21:54,760 --> 00:21:56,760 Speaker 1: A lot of that lost creep has ended up to 356 00:21:56,800 --> 00:21:59,960 Speaker 1: be down to litigation. There's a lot of people who 357 00:22:00,040 --> 00:22:03,520 Speaker 1: would call some of that lidication at least to be 358 00:22:03,680 --> 00:22:07,199 Speaker 1: driven by fraud, and that really has inflated some of 359 00:22:07,240 --> 00:22:10,879 Speaker 1: the claims payments that insurers make, which results in insurers 360 00:22:10,920 --> 00:22:15,240 Speaker 1: claiming more back from their reinsurers and would even result 361 00:22:15,280 --> 00:22:18,800 Speaker 1: in some insurance link securities potentially paying out in return 362 00:22:18,880 --> 00:22:39,920 Speaker 1: for inflated loss costs that come through. Maybe this is 363 00:22:39,960 --> 00:22:43,360 Speaker 1: a good time to ask you about parametric insurance as well, 364 00:22:43,400 --> 00:22:45,680 Speaker 1: because this is something you know, I've written a little 365 00:22:45,720 --> 00:22:48,560 Speaker 1: bit about cat bonds in the past, and the World 366 00:22:48,640 --> 00:22:52,200 Speaker 1: banks pandemic bonds. But parametric insurance is something that I've 367 00:22:52,240 --> 00:22:56,080 Speaker 1: seen come up increasingly in recent years, but I don't 368 00:22:56,119 --> 00:22:59,399 Speaker 1: actually have any idea what it means. So what is 369 00:22:59,400 --> 00:23:04,840 Speaker 1: that exactly? Sure? So essentially, insurance is usually what we 370 00:23:04,960 --> 00:23:08,600 Speaker 1: call an indemnity based product, where it's it's a it's 371 00:23:08,600 --> 00:23:11,240 Speaker 1: a it's a promise to make somebody whole again when 372 00:23:11,359 --> 00:23:14,440 Speaker 1: something happens that meets the terms of the contract, and 373 00:23:14,680 --> 00:23:19,080 Speaker 1: the making whole is subject to certain certain exclusions and 374 00:23:19,119 --> 00:23:22,520 Speaker 1: things like that, as with any insurance contract. Might be 375 00:23:22,960 --> 00:23:25,920 Speaker 1: that that works really well obviously for for your average 376 00:23:26,200 --> 00:23:31,000 Speaker 1: insurance consumer. It also works well for insurers buying reinsurance 377 00:23:31,000 --> 00:23:33,199 Speaker 1: as well, and they will do that on an indemnity 378 00:23:33,240 --> 00:23:38,480 Speaker 1: basis as well. Parametrics really came into the industry as 379 00:23:38,520 --> 00:23:41,080 Speaker 1: well over two decades ago when we first saw saw 380 00:23:41,160 --> 00:23:44,199 Speaker 1: them come come into the marketplace, and they're basically an 381 00:23:44,240 --> 00:23:47,320 Speaker 1: insurance contract that will trigger based on the parameter of 382 00:23:47,400 --> 00:23:50,840 Speaker 1: an event. So it's some kind of data input, be 383 00:23:51,000 --> 00:23:58,200 Speaker 1: that windspeed, earthquake intensity, ground movement from an earthquake, flood depth, 384 00:23:58,800 --> 00:24:02,760 Speaker 1: temperature that there's so many different triggers out there now 385 00:24:02,800 --> 00:24:07,240 Speaker 1: in the parametric world. These are much more applicable in 386 00:24:07,640 --> 00:24:13,200 Speaker 1: developing economies because there's often a lack of ensurable interest 387 00:24:13,280 --> 00:24:15,400 Speaker 1: on the ground, so there may not be very much 388 00:24:15,400 --> 00:24:20,280 Speaker 1: insurance in force. But a sovereign government, for example, could 389 00:24:20,280 --> 00:24:24,240 Speaker 1: buy drought protection that pays out based on a parametric 390 00:24:24,280 --> 00:24:27,800 Speaker 1: index of how much moisture has fallen in that year 391 00:24:27,840 --> 00:24:30,760 Speaker 1: in that country, and that that's now quite a popular 392 00:24:30,760 --> 00:24:35,560 Speaker 1: product in places like Africa. But there's people in Florida, 393 00:24:35,640 --> 00:24:39,520 Speaker 1: Florida on the coast who will buy parametric protection to 394 00:24:40,000 --> 00:24:43,639 Speaker 1: cover their condos or their hotels or golf courses or 395 00:24:43,680 --> 00:24:46,040 Speaker 1: whatever they may be against a hurricane of a certain 396 00:24:46,080 --> 00:24:49,880 Speaker 1: windspeed moving through a specific area of the coastline that's 397 00:24:49,880 --> 00:24:52,320 Speaker 1: going to be close to where they're based. For me, 398 00:24:52,480 --> 00:24:56,320 Speaker 1: parametrics are something that i'd love to see continue to 399 00:24:56,359 --> 00:24:59,000 Speaker 1: develop at the pace they're now beginning to, because it's 400 00:24:59,080 --> 00:25:02,159 Speaker 1: really accelerat did over the last few years. There's some 401 00:25:02,200 --> 00:25:04,840 Speaker 1: really good technology companies come into the space trying to 402 00:25:04,880 --> 00:25:07,840 Speaker 1: build better parametric triggers, trying to build software for it, 403 00:25:07,920 --> 00:25:11,600 Speaker 1: trying to automate claims payments to some degree as well. 404 00:25:11,680 --> 00:25:14,320 Speaker 1: Because that's the other beauty of a parametric trigger that 405 00:25:14,840 --> 00:25:18,320 Speaker 1: there's no need for a lengthy claims assessment. You don't 406 00:25:18,320 --> 00:25:20,840 Speaker 1: have to send an adjuster out to look at a property, 407 00:25:21,280 --> 00:25:24,120 Speaker 1: for example, to assess how much damage has been done. 408 00:25:24,520 --> 00:25:27,680 Speaker 1: You can just see from the data inputs that it's 409 00:25:27,720 --> 00:25:31,000 Speaker 1: above the level that is required to trigger the contract 410 00:25:31,040 --> 00:25:33,439 Speaker 1: and trigger a pay out, and then there's usually a 411 00:25:33,480 --> 00:25:36,840 Speaker 1: third party will validate that in some way, so claims 412 00:25:36,840 --> 00:25:40,120 Speaker 1: payments can be as quick as I mean they're they're 413 00:25:40,200 --> 00:25:42,359 Speaker 1: usually in the sort of two to four week range, 414 00:25:42,359 --> 00:25:44,919 Speaker 1: but I've seen them made in twenty four hours for 415 00:25:45,000 --> 00:25:48,320 Speaker 1: certain parametric contracts, which is really fantastic because it means 416 00:25:48,359 --> 00:25:51,320 Speaker 1: you can make somebody not whole because they're buying a 417 00:25:51,400 --> 00:25:54,399 Speaker 1: certain amount of protection, but you can certainly deliver the 418 00:25:54,440 --> 00:25:56,960 Speaker 1: capital they may need to help them recover far far 419 00:25:57,040 --> 00:26:02,480 Speaker 1: more quickly. It does seem like the triggers for the 420 00:26:02,480 --> 00:26:06,720 Speaker 1: payouts on parametric insurance products. So I understand you're trying 421 00:26:06,760 --> 00:26:10,800 Speaker 1: to make specific parameters or data points that get that 422 00:26:10,920 --> 00:26:13,480 Speaker 1: get hit by an event so that you have these 423 00:26:13,520 --> 00:26:17,120 Speaker 1: automatic payouts, but it does seem like getting the triggers 424 00:26:17,560 --> 00:26:21,040 Speaker 1: right like would still be an issue. Right, because the 425 00:26:21,119 --> 00:26:24,639 Speaker 1: investors would want to see something that they think isn't 426 00:26:24,760 --> 00:26:27,560 Speaker 1: likely to happen, and then the people who are actually 427 00:26:27,800 --> 00:26:32,360 Speaker 1: selling those products would want to have them set so 428 00:26:32,400 --> 00:26:36,119 Speaker 1: that there is a realistic chance that if something happens, 429 00:26:36,400 --> 00:26:39,040 Speaker 1: they would get that additional money. I don't know, it 430 00:26:39,080 --> 00:26:42,000 Speaker 1: just seems like it would like it would be slightly 431 00:26:42,040 --> 00:26:46,560 Speaker 1: complicated to figure those out. It's certainly complicated, and I 432 00:26:46,560 --> 00:26:49,200 Speaker 1: think this is an era that the industry struggled with 433 00:26:49,440 --> 00:26:54,080 Speaker 1: for for a while. When parametrics first came around, they 434 00:26:54,200 --> 00:26:56,760 Speaker 1: tended to be quite simplistic in the way the triggers 435 00:26:56,760 --> 00:27:01,399 Speaker 1: were structured. One of my favorites was took Disneyland the 436 00:27:01,400 --> 00:27:09,080 Speaker 1: theme park water, don't we all. They actually bought a 437 00:27:09,080 --> 00:27:12,760 Speaker 1: catastrophe bond back in the late nineties. I can't remember 438 00:27:12,760 --> 00:27:15,919 Speaker 1: the exact year, but it was called Concentric Limited, and 439 00:27:15,960 --> 00:27:18,320 Speaker 1: the reason it was called concentric was that the people 440 00:27:18,320 --> 00:27:22,040 Speaker 1: who structured the deal drew three circles around the center 441 00:27:22,080 --> 00:27:26,119 Speaker 1: of Tokyo Disneyland, and if an earthquake occurred within those 442 00:27:26,160 --> 00:27:29,879 Speaker 1: three concentric circles that worked out from Disneyland, you'd get 443 00:27:29,920 --> 00:27:33,320 Speaker 1: a different payout depending on which circle it fell in. Now, 444 00:27:33,400 --> 00:27:36,640 Speaker 1: of course, if the earthquake epicenter was outside the furthest 445 00:27:36,680 --> 00:27:39,880 Speaker 1: circle could still be some damage. They may not get 446 00:27:39,880 --> 00:27:42,440 Speaker 1: any pay out at all, of course, but that's really 447 00:27:42,480 --> 00:27:45,240 Speaker 1: something that the buyer of the protection, I guess has 448 00:27:45,280 --> 00:27:49,560 Speaker 1: to has to reconcile with themselves. And really they're buying 449 00:27:49,560 --> 00:27:52,000 Speaker 1: this as kind of a form of just in time 450 00:27:52,119 --> 00:27:54,840 Speaker 1: capital that's going to come in when the worst thing 451 00:27:54,960 --> 00:28:00,240 Speaker 1: possible happens. There's some really sophisticated insurance buyers out they're 452 00:28:00,280 --> 00:28:03,960 Speaker 1: now who buy parametric cover as well, and they'll buy 453 00:28:04,000 --> 00:28:08,240 Speaker 1: their traditional property insurance tower all of their other liability 454 00:28:08,280 --> 00:28:11,720 Speaker 1: and commercial coverages, and then they'll buy some elements of 455 00:28:11,800 --> 00:28:15,760 Speaker 1: parametric cover just really to provide them with capital inflows 456 00:28:15,800 --> 00:28:18,919 Speaker 1: should the really bad events that they don't want to 457 00:28:18,920 --> 00:28:21,720 Speaker 1: see happen occur. There's some good examples of this in 458 00:28:21,840 --> 00:28:26,359 Speaker 1: Japan again, where around earthquake risk retailers and things like 459 00:28:26,440 --> 00:28:30,440 Speaker 1: that will be buying an element of earthquake parametric insurance 460 00:28:30,480 --> 00:28:33,560 Speaker 1: protection so that if there's a bad earthquake anywhere in 461 00:28:33,600 --> 00:28:36,000 Speaker 1: the country, they know it's probably going to mean that 462 00:28:36,080 --> 00:28:39,800 Speaker 1: they either can't get their stock in, they can't open, 463 00:28:39,920 --> 00:28:43,400 Speaker 1: they lose power all these bad things could happen to them, 464 00:28:43,680 --> 00:28:47,760 Speaker 1: but the parametric insurance might pay them million dollars in 465 00:28:47,800 --> 00:28:49,959 Speaker 1: a very quick period of time to help them recover. 466 00:28:50,040 --> 00:28:53,560 Speaker 1: It's also very good in areas such as the developing world, 467 00:28:53,600 --> 00:28:58,080 Speaker 1: where aid inflows can actually be much slower than we 468 00:28:58,160 --> 00:29:00,520 Speaker 1: might think. I mean, when you when you look at 469 00:29:00,960 --> 00:29:04,200 Speaker 1: how fast aid flows into an area that has drought 470 00:29:04,320 --> 00:29:06,960 Speaker 1: or famine, it can take months before there's any real 471 00:29:07,080 --> 00:29:10,240 Speaker 1: build up of capital. If their government can afford to 472 00:29:10,320 --> 00:29:12,840 Speaker 1: buy or can get donors to pay the premiums for 473 00:29:12,960 --> 00:29:16,160 Speaker 1: parametric protection, that can actually flow into the country much 474 00:29:16,160 --> 00:29:20,280 Speaker 1: more quickly. You mentioned drought in Africa. We started talking 475 00:29:20,280 --> 00:29:22,800 Speaker 1: about this conversation that some of the things we've talked 476 00:29:22,840 --> 00:29:26,440 Speaker 1: about drought in the US, particularly with the Mississippi River, 477 00:29:27,040 --> 00:29:30,640 Speaker 1: and then also elevated water levels due to heat waves, 478 00:29:30,640 --> 00:29:32,640 Speaker 1: which are a really big story in Europe over the 479 00:29:32,640 --> 00:29:35,200 Speaker 1: past summer, and we had some episodes where we talked 480 00:29:35,200 --> 00:29:38,240 Speaker 1: about the fact that that is having on say nuclear 481 00:29:38,320 --> 00:29:41,320 Speaker 1: plants that need the cool water from the river so 482 00:29:41,360 --> 00:29:44,760 Speaker 1: that they can dump the hot water safely. Are those 483 00:29:44,960 --> 00:29:48,440 Speaker 1: types of things also insured against in some way, like 484 00:29:48,480 --> 00:29:52,160 Speaker 1: are there products structured around all of these risks or 485 00:29:52,200 --> 00:29:54,600 Speaker 1: would something like that be too niche really to have 486 00:29:55,120 --> 00:30:00,400 Speaker 1: a financial infrastructure around it. Sure the river the one 487 00:30:00,480 --> 00:30:03,080 Speaker 1: is a very good example because there actually have been 488 00:30:03,200 --> 00:30:08,480 Speaker 1: some parametric insurance products covering the River Rhine for specifically 489 00:30:08,560 --> 00:30:12,320 Speaker 1: to for the ability of shipping companies to continue moving 490 00:30:12,400 --> 00:30:15,400 Speaker 1: up and down the river easily and delivering their their goods. 491 00:30:15,840 --> 00:30:17,760 Speaker 1: I don't know whether they triggered or not, but I 492 00:30:17,840 --> 00:30:20,520 Speaker 1: know that the river levels did get very close to 493 00:30:20,600 --> 00:30:23,479 Speaker 1: where I understand the triggers to be last year. I 494 00:30:23,520 --> 00:30:27,120 Speaker 1: don't imagine there's a huge amount of capacity deployed into 495 00:30:27,160 --> 00:30:30,520 Speaker 1: those sorts of risks. They are quite niche, but certainly 496 00:30:30,560 --> 00:30:33,800 Speaker 1: they can now be protected against something can be structured 497 00:30:33,840 --> 00:30:38,920 Speaker 1: to do exactly that. On the nuclear power plants issue, again, 498 00:30:39,000 --> 00:30:41,920 Speaker 1: if it's based on river levels, then there certainly are 499 00:30:41,960 --> 00:30:45,760 Speaker 1: people out there providing insurance on that basis already today. 500 00:30:46,040 --> 00:30:49,360 Speaker 1: I think we're parametrics get really interesting for the future 501 00:30:49,400 --> 00:30:53,480 Speaker 1: for me or around what we call non damage business interruption. 502 00:30:54,000 --> 00:30:58,320 Speaker 1: So this is where something happens that impacts businesses and 503 00:30:58,440 --> 00:31:02,160 Speaker 1: it's not a physical damage incident, but there's something that 504 00:31:02,200 --> 00:31:05,080 Speaker 1: has a knock on effect. If you can start to 505 00:31:05,200 --> 00:31:10,240 Speaker 1: put some understanding around those potential events that could cause 506 00:31:10,280 --> 00:31:13,520 Speaker 1: those effects, then you can possibly start to put parametric 507 00:31:13,520 --> 00:31:15,560 Speaker 1: triggers around them as well. And there are some people 508 00:31:15,560 --> 00:31:18,920 Speaker 1: looking at this quite seriously right now, both around sort 509 00:31:18,960 --> 00:31:22,360 Speaker 1: of financial effects that could affect businesses, but also the 510 00:31:22,440 --> 00:31:25,880 Speaker 1: knock on effects of other events in the world that 511 00:31:25,960 --> 00:31:31,000 Speaker 1: could hurt businesses, so things that cause shipping delays, for example. 512 00:31:31,120 --> 00:31:33,840 Speaker 1: There are certainly companies out there looking at those sorts 513 00:31:33,840 --> 00:31:36,720 Speaker 1: of risks as well. I want to ask a sort 514 00:31:36,760 --> 00:31:43,000 Speaker 1: of existential question about this entire space, which is obviously, 515 00:31:43,040 --> 00:31:48,680 Speaker 1: as we get more extreme weather related events, more natural catastrophes, 516 00:31:49,200 --> 00:31:52,360 Speaker 1: you could see why people would want to have this 517 00:31:52,520 --> 00:31:56,280 Speaker 1: kind of insurance in place. But on the other hand, 518 00:31:56,360 --> 00:31:59,840 Speaker 1: one of the criticisms I've seen of catastrophe bonds, and 519 00:31:59,880 --> 00:32:03,040 Speaker 1: I guess this would extend to parametric insurance as well. 520 00:32:03,640 --> 00:32:07,600 Speaker 1: One of the criticisms is that if you are offering 521 00:32:08,000 --> 00:32:15,240 Speaker 1: more protection against extreme weather, then maybe that will disincentivize 522 00:32:15,360 --> 00:32:21,480 Speaker 1: people from planning effectively for climate change or maybe changing 523 00:32:21,480 --> 00:32:25,040 Speaker 1: their own behavior. The classic example of this is whether 524 00:32:25,120 --> 00:32:27,560 Speaker 1: or not we should be providing insurance for people to 525 00:32:27,680 --> 00:32:31,480 Speaker 1: build beach houses on the coast of Florida, right, or 526 00:32:31,520 --> 00:32:35,480 Speaker 1: whether we should not offer insurance for that risk because 527 00:32:35,520 --> 00:32:38,239 Speaker 1: we know that climate change is going to happen and 528 00:32:38,480 --> 00:32:41,600 Speaker 1: those houses are going to get swept away at some point. 529 00:32:42,160 --> 00:32:48,000 Speaker 1: Is that a valid criticism in your opinion? Um? Is 530 00:32:48,000 --> 00:32:50,920 Speaker 1: it a valid criticism? I mean, the insurance industries provided 531 00:32:51,280 --> 00:32:55,760 Speaker 1: protection to industries that perhaps some of us would certainly 532 00:32:55,760 --> 00:32:58,680 Speaker 1: think nowadays maybe shouldn't have ever had that protection because 533 00:32:58,680 --> 00:33:01,560 Speaker 1: it's enabled their business is to some degree, I suppose, 534 00:33:01,800 --> 00:33:04,080 Speaker 1: and that's really been the way of the insurance industry, 535 00:33:04,120 --> 00:33:06,960 Speaker 1: that they will sell protection to people for the right price. 536 00:33:08,160 --> 00:33:11,400 Speaker 1: But it actually now speaks to a couple of things 537 00:33:11,440 --> 00:33:14,680 Speaker 1: that are happening in the industry which I'm particularly passionate about. 538 00:33:14,720 --> 00:33:18,240 Speaker 1: One is around resilience. So there are a number of 539 00:33:18,240 --> 00:33:21,120 Speaker 1: initiatives around the world. Again, these are largely in developing 540 00:33:21,160 --> 00:33:23,840 Speaker 1: economies at the moment, but I think we'll start to 541 00:33:23,880 --> 00:33:26,440 Speaker 1: see this and actually we are seeing this increasingly in 542 00:33:26,480 --> 00:33:28,800 Speaker 1: developed world as well, but in a slightly different way. 543 00:33:28,960 --> 00:33:32,280 Speaker 1: And this is around the terms of your insurance coverage 544 00:33:32,400 --> 00:33:37,120 Speaker 1: also requiring you to do something that's going to increase 545 00:33:37,200 --> 00:33:40,360 Speaker 1: your resilience to those events as well. So whether that's 546 00:33:40,400 --> 00:33:43,200 Speaker 1: a you need to have a resilience plan in place, 547 00:33:43,320 --> 00:33:45,640 Speaker 1: you need to have a plan for how you're going 548 00:33:45,680 --> 00:33:49,000 Speaker 1: to deploy that money should the insurance pay out, and 549 00:33:49,040 --> 00:33:51,040 Speaker 1: you need to demonstrate that that's going to go to 550 00:33:51,080 --> 00:33:54,480 Speaker 1: the right people, particularly in the case of sovereign risk transfer, 551 00:33:54,520 --> 00:33:57,959 Speaker 1: where a government or country is buying it. But alongside 552 00:33:58,000 --> 00:34:02,719 Speaker 1: that there's also a sort of examples where people are 553 00:34:02,720 --> 00:34:05,840 Speaker 1: being encouraged to put in place things that will help 554 00:34:05,880 --> 00:34:08,640 Speaker 1: them to keep floodwaters out of their property, for example, 555 00:34:08,719 --> 00:34:12,080 Speaker 1: and that can be tied into an insurance sale. Cyber 556 00:34:12,200 --> 00:34:15,960 Speaker 1: risk is another interesting area because the cyber insurance market 557 00:34:16,080 --> 00:34:20,840 Speaker 1: is growing very fast. It has capacity issues because obviously 558 00:34:20,880 --> 00:34:24,240 Speaker 1: it's an enormous risk that's actually quite hard to model 559 00:34:24,280 --> 00:34:26,919 Speaker 1: in a lot of ways, so there's only a certain 560 00:34:27,000 --> 00:34:29,320 Speaker 1: number of people who really want to put capital down 561 00:34:29,360 --> 00:34:32,280 Speaker 1: for that. But most of the sort of the big 562 00:34:32,920 --> 00:34:36,640 Speaker 1: large commercial cyber insurance agreements of the world will have 563 00:34:36,920 --> 00:34:39,640 Speaker 1: an element of cyber risk protection into them as well. 564 00:34:39,680 --> 00:34:44,040 Speaker 1: They'll be cyber software, there'll be cyber security reviews, there 565 00:34:44,040 --> 00:34:47,160 Speaker 1: will be penetration testing, all sorts of things that go 566 00:34:47,280 --> 00:34:50,799 Speaker 1: on as you buy your cyber insurance policy. And some 567 00:34:50,920 --> 00:34:53,280 Speaker 1: of them may be conditional on whether you can actually 568 00:34:53,320 --> 00:34:55,440 Speaker 1: buy that policy or not. If you're not willing to 569 00:34:55,520 --> 00:35:00,040 Speaker 1: demonstrate that you're making some efforts to prevent cyber a 570 00:35:00,360 --> 00:35:03,520 Speaker 1: sort of exploits occur within your business, you may find 571 00:35:03,560 --> 00:35:05,720 Speaker 1: it harder or you may pay more for your cyber 572 00:35:05,760 --> 00:35:09,759 Speaker 1: insurance protection. So I just have one more question, and 573 00:35:09,800 --> 00:35:13,080 Speaker 1: it relates to climate change, and it also sort of 574 00:35:13,080 --> 00:35:16,319 Speaker 1: relates to E. S G and government regulations because you know, 575 00:35:16,360 --> 00:35:22,240 Speaker 1: I feel like, Okay, if I'm thinking about ensuring against 576 00:35:22,320 --> 00:35:24,520 Speaker 1: hurricanes or flood risk in Florida, then I might be 577 00:35:24,560 --> 00:35:28,239 Speaker 1: concerned about climate risk and whether that's going to amplify 578 00:35:28,360 --> 00:35:30,880 Speaker 1: the number of highly destructive hurricanes in the future, and 579 00:35:30,920 --> 00:35:32,920 Speaker 1: I have to model that out. But then the other 580 00:35:33,000 --> 00:35:35,600 Speaker 1: thing I feel like that is always changing is not 581 00:35:35,800 --> 00:35:39,160 Speaker 1: just the hurricanes itself, but how are the laws going 582 00:35:39,200 --> 00:35:43,000 Speaker 1: to change and how are regulations going to change, and 583 00:35:43,080 --> 00:35:47,680 Speaker 1: so essentially the risk of a different legal framework or 584 00:35:47,719 --> 00:35:50,400 Speaker 1: you know, we just had the latest climate conference in 585 00:35:50,440 --> 00:35:53,879 Speaker 1: Egypt and some new rule that comes out of that, 586 00:35:54,040 --> 00:35:56,960 Speaker 1: and so you know, not necessarily the extreme weather itself, 587 00:35:57,400 --> 00:35:59,880 Speaker 1: but that government say to some industry you can't do 588 00:36:00,080 --> 00:36:01,719 Speaker 1: is or you can do that, or you have to 589 00:36:01,760 --> 00:36:03,799 Speaker 1: price this higher, you have to pay this tax, or 590 00:36:03,960 --> 00:36:06,640 Speaker 1: something like that. How much of like the thinking is 591 00:36:06,680 --> 00:36:12,880 Speaker 1: related to the straightforward risk of extreme weather as opposed 592 00:36:12,920 --> 00:36:16,840 Speaker 1: to sort of like various mandates that may change the 593 00:36:16,960 --> 00:36:20,400 Speaker 1: nature of business going forward as a result of government 594 00:36:20,560 --> 00:36:23,839 Speaker 1: trying to take action on climate change. That's a very 595 00:36:23,880 --> 00:36:27,160 Speaker 1: interesting question. Obviously, there's a lot going on in the 596 00:36:27,200 --> 00:36:31,640 Speaker 1: climate sort of legislative arena at the moment, and insurers 597 00:36:31,640 --> 00:36:34,720 Speaker 1: are kind of exposed to that to a degree, I suppose. 598 00:36:34,880 --> 00:36:37,319 Speaker 1: I guess it's another input that really needs to be 599 00:36:37,760 --> 00:36:41,239 Speaker 1: a difficult to model for, but needs to be considered 600 00:36:41,400 --> 00:36:44,920 Speaker 1: when they model in price their their business. And the 601 00:36:44,960 --> 00:36:47,640 Speaker 1: other thing is that the insurance and reinsurance industry are 602 00:36:47,719 --> 00:36:51,279 Speaker 1: incredibly engaged in most of those discussions where they can 603 00:36:51,320 --> 00:36:55,640 Speaker 1: be as well. And and certainly there's some areas that 604 00:36:55,960 --> 00:36:59,760 Speaker 1: the insurance and reinsurance industry might actually see potential future 605 00:36:59,800 --> 00:37:03,680 Speaker 1: rock tunity coming from, such as climate disclosure. So if 606 00:37:03,800 --> 00:37:07,319 Speaker 1: the so for example, the Fortune five companies and the 607 00:37:07,400 --> 00:37:10,279 Speaker 1: largest businesses in the world all have to start to 608 00:37:10,400 --> 00:37:15,400 Speaker 1: disclose their weather exposure on their balance sheets or something, 609 00:37:15,440 --> 00:37:19,359 Speaker 1: because that comes out of a cop conference. Obviously, if 610 00:37:19,360 --> 00:37:21,359 Speaker 1: you start to disclose that kind of thing and your 611 00:37:21,400 --> 00:37:26,200 Speaker 1: shareholders are seeing these potential big negative numbers on your 612 00:37:26,200 --> 00:37:29,840 Speaker 1: balance sheet, even if they don't manifest, it's still something 613 00:37:29,880 --> 00:37:32,760 Speaker 1: that really any sensible business owners should be taking steps 614 00:37:32,760 --> 00:37:35,799 Speaker 1: to protect against. So there's also potentially going to be 615 00:37:35,840 --> 00:37:39,359 Speaker 1: more demand that comes out of climate legislation as well, 616 00:37:39,360 --> 00:37:43,480 Speaker 1: I mean demand for risk transfer and insurance itself. So 617 00:37:43,600 --> 00:37:46,840 Speaker 1: we've been focused on the weather and climate change for 618 00:37:46,960 --> 00:37:51,040 Speaker 1: obvious reasons. But there's another thing happening which has an 619 00:37:51,080 --> 00:37:53,480 Speaker 1: impact on the insurance industry as a whole, and that 620 00:37:53,640 --> 00:37:58,440 Speaker 1: is just higher benchmark interest rates in general. Can you 621 00:37:58,480 --> 00:38:02,560 Speaker 1: maybe talk a little bit about what that means for 622 00:38:02,680 --> 00:38:07,200 Speaker 1: the insurance and the reinsurance market. And I guess the 623 00:38:07,280 --> 00:38:11,520 Speaker 1: other big question would be, given the combination of we 624 00:38:11,600 --> 00:38:15,280 Speaker 1: have this expectation that there will be more extreme natural 625 00:38:15,560 --> 00:38:19,359 Speaker 1: disasters in the future, plus interest rates seem to be 626 00:38:19,480 --> 00:38:23,920 Speaker 1: trending higher for the foreseeable future, does that just inevitably 627 00:38:23,960 --> 00:38:27,160 Speaker 1: mean that insurance rates are going to have to go up? Like? 628 00:38:27,360 --> 00:38:32,239 Speaker 1: Is that our inevitable future? I mean, what while inflation 629 00:38:32,400 --> 00:38:35,799 Speaker 1: remains at ten percent than than just the cost of 630 00:38:35,840 --> 00:38:39,799 Speaker 1: everything that potentially gets damaged is going up significantly from 631 00:38:39,840 --> 00:38:43,800 Speaker 1: property to everything that you own, and as a result, 632 00:38:44,040 --> 00:38:47,600 Speaker 1: insurance costs will go up to cover those those items 633 00:38:47,640 --> 00:38:50,040 Speaker 1: that we all love and want to want to keep. 634 00:38:50,400 --> 00:38:52,560 Speaker 1: But I guess I've going back to the start of 635 00:38:52,560 --> 00:38:56,279 Speaker 1: your question there the interest rate aspect, there's certainly a 636 00:38:56,320 --> 00:39:00,319 Speaker 1: negative initial effect on insurance and reinsurance industry in terms 637 00:39:00,360 --> 00:39:03,000 Speaker 1: of how it affects some of their portfolios of assets 638 00:39:03,000 --> 00:39:07,000 Speaker 1: on the bond side. That has caused some sort of 639 00:39:07,040 --> 00:39:11,120 Speaker 1: decline in in industry capital due to some of the 640 00:39:11,600 --> 00:39:15,040 Speaker 1: volatility we've seen in financial markets so through this year 641 00:39:15,120 --> 00:39:18,040 Speaker 1: so far, but most of that will would be expected 642 00:39:18,080 --> 00:39:21,840 Speaker 1: to be recovered as obviously the instruments all moved towards 643 00:39:21,960 --> 00:39:25,320 Speaker 1: maturity and yields increase on them. Again, in the insurance 644 00:39:25,360 --> 00:39:29,879 Speaker 1: and security space, interest rates are very relevant there as well, 645 00:39:30,000 --> 00:39:34,560 Speaker 1: because a catastrophe bond, the return that investor gets is 646 00:39:34,600 --> 00:39:38,640 Speaker 1: based on the coupon, which is the risk spread, so 647 00:39:38,640 --> 00:39:41,759 Speaker 1: how much they're getting paid for the risk they're taking on. 648 00:39:42,160 --> 00:39:44,640 Speaker 1: But then there's also the return from the collateral because 649 00:39:44,680 --> 00:39:47,880 Speaker 1: these are fully collateralized instruments, so a hundred percent of 650 00:39:47,880 --> 00:39:51,840 Speaker 1: the collateral is usually invested in something like a treasury 651 00:39:51,920 --> 00:39:54,239 Speaker 1: money market bond or something like that, so it's a 652 00:39:54,320 --> 00:39:57,640 Speaker 1: very safe asset. Now all of those assets are floating 653 00:39:57,719 --> 00:40:00,879 Speaker 1: up with rising interest rates, which means the the returns 654 00:40:00,920 --> 00:40:04,399 Speaker 1: from catastrophe bonds rise on top of it. And so 655 00:40:04,440 --> 00:40:07,120 Speaker 1: that's maybe a positive for the investors there and also 656 00:40:07,239 --> 00:40:11,239 Speaker 1: something that keeps the insurance of securities markets are still appealing, 657 00:40:11,400 --> 00:40:14,080 Speaker 1: even while other asset classes around the world are obviously 658 00:40:14,280 --> 00:40:18,400 Speaker 1: inflating their returns as well. The question of does insurance 659 00:40:18,440 --> 00:40:20,160 Speaker 1: have to keep rising, I mean, I think I think 660 00:40:20,200 --> 00:40:23,800 Speaker 1: that's the inflationary factor really there, and it's certainly something 661 00:40:23,920 --> 00:40:28,040 Speaker 1: that right now that's one of the key drivers for rates. 662 00:40:28,120 --> 00:40:32,640 Speaker 1: And we're expecting next year well that the January renewals, 663 00:40:32,680 --> 00:40:36,600 Speaker 1: which is the time of year when sort of global 664 00:40:36,640 --> 00:40:39,880 Speaker 1: reinsurance gets renewed, they're going to see of what we 665 00:40:39,920 --> 00:40:44,600 Speaker 1: would call a hard market, so steeply increasing rates. People 666 00:40:44,600 --> 00:40:49,200 Speaker 1: are projecting sort of anything up to increases, particularly for 667 00:40:49,280 --> 00:40:54,080 Speaker 1: property catastrophe risks. More broadly in areas like liability, there 668 00:40:54,120 --> 00:40:57,080 Speaker 1: will still be increases, it seems like, even though there 669 00:40:57,080 --> 00:41:00,799 Speaker 1: hasn't been the severe loss experience there. But then inflation 670 00:41:00,920 --> 00:41:07,440 Speaker 1: obviously affects things like court judgment payouts and litigation costs, 671 00:41:07,560 --> 00:41:11,360 Speaker 1: and so I would imagine that the more inflation is entrenched, 672 00:41:11,520 --> 00:41:15,920 Speaker 1: the more costs for the insurance industry rise, and therefore 673 00:41:16,000 --> 00:41:18,239 Speaker 1: the more customers would have to pay for it as 674 00:41:18,280 --> 00:41:22,440 Speaker 1: a result. Alright, Steve Evans, thank you so much for 675 00:41:22,520 --> 00:41:24,880 Speaker 1: coming on odd Lots. I'm glad we could finally have 676 00:41:25,000 --> 00:41:28,080 Speaker 1: this conversation. You know, we've covered weather from a real 677 00:41:28,120 --> 00:41:30,759 Speaker 1: economy perspective, but we haven't actually done it from a 678 00:41:30,800 --> 00:41:34,920 Speaker 1: sort of financial industry perspective. So thank you so much. Sure, 679 00:41:34,960 --> 00:41:37,439 Speaker 1: it's my pleasure, really great talking both, and I hope 680 00:41:37,560 --> 00:41:40,080 Speaker 1: that was interesting. Yeah, very much, thank you so much. 681 00:41:40,560 --> 00:41:57,560 Speaker 1: Thanks Jed, Thanks Tracy, so Joe. I found that conversation 682 00:41:57,600 --> 00:42:00,600 Speaker 1: to be fascinating. I do think, like I guess, I 683 00:42:00,680 --> 00:42:03,560 Speaker 1: come out of it with with more questions, because it 684 00:42:04,320 --> 00:42:06,879 Speaker 1: does seem like, you know, there is really this there's 685 00:42:06,880 --> 00:42:12,040 Speaker 1: always this tension in insurance between paying enough that investors 686 00:42:12,200 --> 00:42:15,759 Speaker 1: want to take on this risk without making it sort 687 00:42:15,800 --> 00:42:18,680 Speaker 1: of prohibitive lee expensive. But then also when it comes 688 00:42:18,680 --> 00:42:22,920 Speaker 1: to a lot of the catastrophe bonds and weather related insurance, 689 00:42:22,960 --> 00:42:25,560 Speaker 1: it seems like there is this added factor of should 690 00:42:25,640 --> 00:42:28,759 Speaker 1: we be ensuring some of these risks at all? You know, 691 00:42:29,320 --> 00:42:31,440 Speaker 1: I say, if people want to pay for the insurance, 692 00:42:31,600 --> 00:42:34,359 Speaker 1: let people build on the Florida coast. You know. It's 693 00:42:34,400 --> 00:42:37,800 Speaker 1: like I don't think it should be like subsidized or 694 00:42:37,880 --> 00:42:40,919 Speaker 1: it should be free, but you know, if the people 695 00:42:40,960 --> 00:42:43,120 Speaker 1: want to pay for it, that's great. Well there's also 696 00:42:43,160 --> 00:42:45,560 Speaker 1: the question, and we didn't get into this with Steve, 697 00:42:45,680 --> 00:42:48,800 Speaker 1: but you have seen a lot of governments and states 698 00:42:49,120 --> 00:42:53,360 Speaker 1: issuing catastrophe bonds selling those to private investors, and it 699 00:42:53,400 --> 00:42:55,839 Speaker 1: does cut This is something that I vaguely remember came 700 00:42:55,920 --> 00:42:58,400 Speaker 1: up with the World Bank pandemic bonds as well. But 701 00:42:58,480 --> 00:43:01,319 Speaker 1: it does beg the question of should the government be 702 00:43:01,440 --> 00:43:04,560 Speaker 1: paying investors, you know, like a well, it's not that 703 00:43:04,600 --> 00:43:07,400 Speaker 1: impressive anymore, but three or four years ago it was 704 00:43:07,440 --> 00:43:10,840 Speaker 1: impressive a six percent yield on a bond instead of 705 00:43:10,880 --> 00:43:16,719 Speaker 1: just borrowing themselves directly in the market. Yeah, we need 706 00:43:16,719 --> 00:43:19,000 Speaker 1: to do a whole thing on like municipal finance because 707 00:43:19,000 --> 00:43:20,840 Speaker 1: I have like, once you started getting the question of 708 00:43:20,840 --> 00:43:23,040 Speaker 1: like well why is there like the specific bonds and 709 00:43:23,160 --> 00:43:26,839 Speaker 1: why they then yes, maybe we could do a sort 710 00:43:26,880 --> 00:43:31,480 Speaker 1: of govern a state and local government financing episodes because 711 00:43:31,480 --> 00:43:34,239 Speaker 1: I have a million questions about that. You know, there 712 00:43:34,280 --> 00:43:36,400 Speaker 1: were all kind of you know, in terms of um 713 00:43:36,600 --> 00:43:38,560 Speaker 1: things that st you have talked about. I want to 714 00:43:38,600 --> 00:43:42,480 Speaker 1: do more on like software and just like modeling software, 715 00:43:42,640 --> 00:43:45,760 Speaker 1: and the software comes up in a lot of our conversations. 716 00:43:46,400 --> 00:43:49,400 Speaker 1: There's that also, it comes up in the semiconductor of 717 00:43:49,440 --> 00:43:51,440 Speaker 1: conversations that we have. So I feel like I want 718 00:43:51,480 --> 00:43:53,160 Speaker 1: to learn more about the software side of all this. 719 00:43:53,360 --> 00:43:55,400 Speaker 1: We should talk to A I R, which are the 720 00:43:55,440 --> 00:43:58,400 Speaker 1: big modeling guys a lot of cat bonds, and then 721 00:43:58,400 --> 00:44:01,040 Speaker 1: we should also talk to on a related note, we 722 00:44:01,040 --> 00:44:05,439 Speaker 1: should talk to the third party pricing services for bonds. Yeah, 723 00:44:06,040 --> 00:44:08,200 Speaker 1: no one ever talks about them. Okay, So this is 724 00:44:08,200 --> 00:44:11,160 Speaker 1: an episode in which like we've come away with what 725 00:44:11,360 --> 00:44:13,960 Speaker 1: three more episodes that we need to do at least 726 00:44:14,000 --> 00:44:15,759 Speaker 1: three more, and you know, just on the one thing 727 00:44:15,800 --> 00:44:17,319 Speaker 1: that I keep coming back to is like, Okay, if 728 00:44:17,320 --> 00:44:21,120 Speaker 1: you have like insurance, on some level, you sort of 729 00:44:21,160 --> 00:44:24,479 Speaker 1: expected to be mean reverting. You sort of expect things 730 00:44:24,520 --> 00:44:28,440 Speaker 1: to be random, these sort of like undiversifiable risks that 731 00:44:28,480 --> 00:44:30,480 Speaker 1: you need these big pools of capital out there to 732 00:44:30,560 --> 00:44:32,799 Speaker 1: protect you against. But I do wonder, you know, if 733 00:44:32,840 --> 00:44:36,880 Speaker 1: there if there are certain areas particularly related to climate change, 734 00:44:36,880 --> 00:44:39,520 Speaker 1: in which the expectation is that there is some sort 735 00:44:39,560 --> 00:44:42,200 Speaker 1: of extreme weather event that is going to march steadily 736 00:44:42,280 --> 00:44:46,200 Speaker 1: worse and worse over time, that there's no natural mean reversion, 737 00:44:46,480 --> 00:44:49,640 Speaker 1: that there is less chaos and randomness. It doesn't make 738 00:44:49,680 --> 00:44:51,839 Speaker 1: me wonder like the degree to which some of these 739 00:44:51,880 --> 00:44:54,839 Speaker 1: industries will be up ended totally. And there are all 740 00:44:54,840 --> 00:44:58,000 Speaker 1: sorts of philosophical questions thrown up by this as well, 741 00:44:58,000 --> 00:45:02,120 Speaker 1: which is of course, insurance can be a really effective 742 00:45:02,120 --> 00:45:07,040 Speaker 1: way of actually altering behavior like maybe you shouldn't build 743 00:45:07,239 --> 00:45:10,360 Speaker 1: houses on a beach in Florida, and whether or not 744 00:45:10,400 --> 00:45:15,120 Speaker 1: they're gonna be partnering maybe with governments. Interesting, Yeah, to 745 00:45:15,239 --> 00:45:19,399 Speaker 1: try to, um, you know, affect some of that fascinating conversation. Yeah, 746 00:45:19,440 --> 00:45:21,359 Speaker 1: I'm glad we finally had it. Shall we leave it there? 747 00:45:21,440 --> 00:45:23,760 Speaker 1: Let's leave it there? All right? This has been another 748 00:45:23,800 --> 00:45:26,840 Speaker 1: episode of the All Thoughts podcast. I'm Tracy Alloway. You 749 00:45:26,880 --> 00:45:29,600 Speaker 1: can follow me on Twitter at Tracy Alloway and I'm 750 00:45:29,680 --> 00:45:31,920 Speaker 1: Joe Why Isn't All? You can follow me on Twitter 751 00:45:32,080 --> 00:45:35,200 Speaker 1: at the Stalwart. Follow our guest Steve Evans he's at 752 00:45:35,280 --> 00:45:40,200 Speaker 1: Steve underscore E. Follow our producers Carmen Rodriguez at Kerman 753 00:45:40,360 --> 00:45:44,160 Speaker 1: Armand and Dash Bennett at dashbot. And follow all of 754 00:45:44,160 --> 00:45:49,040 Speaker 1: the Bloomberg podcasts under the handle at podcasts and for 755 00:45:49,120 --> 00:45:51,800 Speaker 1: more odd Lots content, go to Bloomberg dot com slash 756 00:45:51,840 --> 00:45:54,640 Speaker 1: odd Lots, where we post transcripts, Tracy and I blog. 757 00:45:54,719 --> 00:45:57,800 Speaker 1: We also have a weekly newsletter that you can subscribe to. 758 00:45:58,040 --> 00:46:00,560 Speaker 1: And on that note, we're gonna be doing and Ask 759 00:46:00,640 --> 00:46:03,680 Speaker 1: Me Anything episode where you can ask me and Tracy 760 00:46:03,960 --> 00:46:07,440 Speaker 1: questions about anything. You want to record your questions in 761 00:46:07,480 --> 00:46:10,040 Speaker 1: the form of a voice memo, include your name and location, 762 00:46:10,200 --> 00:46:12,319 Speaker 1: and then forward that to odd Lots at bloomberg got 763 00:46:12,320 --> 00:46:14,160 Speaker 1: net and we'll listen to them and we'll try to 764 00:46:14,200 --> 00:46:16,480 Speaker 1: answer a bunch of your questions. Whatever you want to 765 00:46:16,480 --> 00:46:19,720 Speaker 1: know about odd locks, send it it. Thanks for listening.