1 00:00:00,120 --> 00:00:02,759 Speaker 1: Hey, Dna, Hey Mark. Here we are middle of summer, 2 00:00:03,000 --> 00:00:05,880 Speaker 1: but it seems BENF didn't really get the memo. It 3 00:00:05,880 --> 00:00:09,879 Speaker 1: hasn't really slowed down that much around here, not at all. Actually, 4 00:00:10,039 --> 00:00:12,600 Speaker 1: this week, on the second of August, B and F 5 00:00:12,760 --> 00:00:15,480 Speaker 1: is having our new Delhi Summit. It is one of 6 00:00:15,720 --> 00:00:20,200 Speaker 1: six market gatherings for business and government leaders. We bring 7 00:00:20,239 --> 00:00:23,280 Speaker 1: together people to discuss innovation and the transition to a 8 00:00:23,320 --> 00:00:26,160 Speaker 1: low carbon economy. If you're not lucky enough to attend 9 00:00:26,160 --> 00:00:29,120 Speaker 1: in person, benef clients or BENOF users can still follow 10 00:00:29,120 --> 00:00:30,920 Speaker 1: the action on the BENF mobile app. Just tap on 11 00:00:30,960 --> 00:00:33,000 Speaker 1: the summit. Tap there you can see a full agenda 12 00:00:33,000 --> 00:00:36,320 Speaker 1: with speaker bios and the presentation slides from the BENF talks. 13 00:00:36,400 --> 00:00:38,680 Speaker 1: Those are talks from our BENF analysts. You can also 14 00:00:38,680 --> 00:00:40,800 Speaker 1: see a full list of the attendees. Today, we are 15 00:00:40,800 --> 00:00:43,440 Speaker 1: going to talk with the MC of the Delhi Summit, 16 00:00:43,520 --> 00:00:46,559 Speaker 1: Nathaniel or not Bullard. He is the global head of 17 00:00:46,560 --> 00:00:49,199 Speaker 1: Executive Insights for B and E F. And what does 18 00:00:49,240 --> 00:00:52,120 Speaker 1: that title mean. Well, he wears many hats for us 19 00:00:52,120 --> 00:00:54,840 Speaker 1: over here, and we'll hear all about that in the interview. 20 00:00:55,200 --> 00:00:57,920 Speaker 1: One of those is writing a weekly op ed called 21 00:00:58,000 --> 00:01:01,000 Speaker 1: spark Lines. It is published through Bomberg Opinion and you 22 00:01:01,000 --> 00:01:03,280 Speaker 1: can find it on the terminal under Ni Bullard b 23 00:01:03,520 --> 00:01:06,480 Speaker 1: U L L A R D or on Bloomberg dot 24 00:01:06,520 --> 00:01:10,720 Speaker 1: com under spark Lines, or search for Bullard. In either location. 25 00:01:10,800 --> 00:01:13,840 Speaker 1: You can sign up for a weekly distribution, which I 26 00:01:13,959 --> 00:01:16,640 Speaker 1: must say I am a happy receiver of because his 27 00:01:16,920 --> 00:01:20,800 Speaker 1: pieces are short and pithy and all around interesting. Today 28 00:01:20,840 --> 00:01:22,839 Speaker 1: we're going to talk to him about two spark lines, 29 00:01:22,880 --> 00:01:25,720 Speaker 1: among other things. And just as a quick reminder, B 30 00:01:25,800 --> 00:01:28,319 Speaker 1: and the F does not provide investment or strategy advice. 31 00:01:28,440 --> 00:01:30,080 Speaker 1: You can hear a full disclaimer at the end of 32 00:01:30,080 --> 00:01:34,520 Speaker 1: the show. And right now let's jump in. Hi Na, 33 00:01:34,640 --> 00:01:36,960 Speaker 1: thank you for joining us today. Hi Danna, him Mark, 34 00:01:36,959 --> 00:01:40,679 Speaker 1: How are you guys doing well? So not Bullard, how 35 00:01:40,720 --> 00:01:45,560 Speaker 1: would you describe your role within So? My role is 36 00:01:46,240 --> 00:01:49,480 Speaker 1: a veteran analyst, and I say that very seriously, and 37 00:01:49,480 --> 00:01:51,840 Speaker 1: that I've been doing this now for twelve years, since 38 00:01:51,880 --> 00:01:54,400 Speaker 1: before we were required in a number of different sectors 39 00:01:54,400 --> 00:01:57,320 Speaker 1: and a number of different markets. There are probably not 40 00:01:57,440 --> 00:01:59,680 Speaker 1: that many people that have had that kind of great 41 00:01:59,720 --> 00:02:02,240 Speaker 1: rotation through a lot of the things we do, and 42 00:02:02,320 --> 00:02:05,920 Speaker 1: also are not currently running a big team. So years 43 00:02:05,920 --> 00:02:07,960 Speaker 1: ago in television, we used to have a colleague who 44 00:02:08,040 --> 00:02:10,679 Speaker 1: is described as an editor at large. This is a 45 00:02:10,720 --> 00:02:13,160 Speaker 1: sort of an equivalent analyst at large position, and what 46 00:02:13,280 --> 00:02:19,640 Speaker 1: that actually entails is about even thirds split between doing 47 00:02:19,680 --> 00:02:22,239 Speaker 1: things with our own management committee, like with the two 48 00:02:22,240 --> 00:02:24,160 Speaker 1: of you and with John morre CEO and with our 49 00:02:24,200 --> 00:02:28,720 Speaker 1: other colleagues. Another third is doing public presentations, so the 50 00:02:28,800 --> 00:02:31,240 Speaker 1: sort of classic I talk and travel kind of work 51 00:02:31,400 --> 00:02:34,120 Speaker 1: that a lot of our analysts already do, but with 52 00:02:34,200 --> 00:02:37,679 Speaker 1: a with a particular angle on it. Generally speaking, it's 53 00:02:37,680 --> 00:02:40,680 Speaker 1: either very broadcast so it's something for like three four, 54 00:02:40,880 --> 00:02:44,359 Speaker 1: five hundred or a thousand people, or very narrow cast 55 00:02:44,520 --> 00:02:47,639 Speaker 1: to let's say a corporate board a lot of times 56 00:02:47,880 --> 00:02:51,280 Speaker 1: asking about similar ideas but with a very different set 57 00:02:51,320 --> 00:02:54,679 Speaker 1: of vectors for delivery. And then finally, I write every 58 00:02:54,720 --> 00:02:56,600 Speaker 1: week I have a project that I started five years 59 00:02:56,600 --> 00:03:00,520 Speaker 1: ago as an email essentially for friends and Emily of 60 00:03:01,200 --> 00:03:03,600 Speaker 1: be in the f of the time, that was just 61 00:03:03,720 --> 00:03:06,639 Speaker 1: published by us through our marketing capabilities and now is 62 00:03:06,639 --> 00:03:11,680 Speaker 1: published by Bloomberg Opinion, which publishes well Opinion by Bloomberg authors. 63 00:03:12,240 --> 00:03:15,000 Speaker 1: And it goes out as an email, which is how 64 00:03:15,000 --> 00:03:17,000 Speaker 1: it originated, it goes out on the web, and it 65 00:03:17,040 --> 00:03:20,560 Speaker 1: goes out on the Bloomberg terminal, usually on Friday's maybe 66 00:03:20,639 --> 00:03:23,400 Speaker 1: sometimes with some flexibility depending on the timing of what 67 00:03:23,400 --> 00:03:26,919 Speaker 1: I'm writing about. So you sent us a couple uh 68 00:03:27,120 --> 00:03:29,560 Speaker 1: different pieces today to say, hey, guys, study up a 69 00:03:29,600 --> 00:03:32,200 Speaker 1: little bit before we have a chat um. We can 70 00:03:32,240 --> 00:03:34,200 Speaker 1: dive into those, but I think one that we were 71 00:03:34,240 --> 00:03:36,520 Speaker 1: talking about that was pretty well received, just one called 72 00:03:36,800 --> 00:03:39,800 Speaker 1: climate change is all most of us have ever known. 73 00:03:40,000 --> 00:03:42,480 Speaker 1: That's right, So tell us a little bit about what 74 00:03:42,520 --> 00:03:45,320 Speaker 1: you wrote there and what it means and really the 75 00:03:45,320 --> 00:03:47,560 Speaker 1: message that you were trying to send with that. Certainly. 76 00:03:47,560 --> 00:03:50,920 Speaker 1: So there's another contributor to Bloomberg in Singapore who was 77 00:03:51,160 --> 00:03:54,240 Speaker 1: a former trader. His name is Mark Cutmore, and he 78 00:03:54,320 --> 00:03:56,680 Speaker 1: did the ODDNS podcast a couple of years ago that 79 00:03:57,080 --> 00:03:59,600 Speaker 1: Joe Wisenhal and Tracy All the Way Run, and he 80 00:03:59,720 --> 00:04:01,760 Speaker 1: said something that is stuck with me and is a 81 00:04:01,800 --> 00:04:03,600 Speaker 1: sort of guiding principle for a lot of this work, 82 00:04:03,640 --> 00:04:06,800 Speaker 1: which is markets think in narratives. So we're often looking 83 00:04:06,800 --> 00:04:09,240 Speaker 1: at things from either an intensely analytical or a very 84 00:04:09,280 --> 00:04:12,680 Speaker 1: factual basis, but at the broadest sense of markets with 85 00:04:12,680 --> 00:04:15,400 Speaker 1: the capital m They think in narratives and in stories. 86 00:04:15,880 --> 00:04:17,720 Speaker 1: And one of the challenges that I find in dealing 87 00:04:17,800 --> 00:04:21,520 Speaker 1: with a discussion about climate change in particular is that 88 00:04:21,760 --> 00:04:24,960 Speaker 1: it is quite experiential for a lot of people. And 89 00:04:25,000 --> 00:04:27,240 Speaker 1: I mean experience in a couple of ways. One how 90 00:04:27,240 --> 00:04:29,280 Speaker 1: old you are, like, what you what you knew as 91 00:04:29,320 --> 00:04:33,039 Speaker 1: a child, what informs your expectation based on what you 92 00:04:33,080 --> 00:04:37,279 Speaker 1: knew when you were young? And also your experience within 93 00:04:37,600 --> 00:04:41,640 Speaker 1: the corporate world. Are you nearer to retirement than you 94 00:04:41,680 --> 00:04:45,279 Speaker 1: are to initiating your job, let's say, And in fact, 95 00:04:45,320 --> 00:04:47,000 Speaker 1: if you are the kind of senior people that I'm 96 00:04:47,000 --> 00:04:50,479 Speaker 1: engaging with most of the time, that's almost axiomatic. They're 97 00:04:50,480 --> 00:04:52,960 Speaker 1: almost all that way. Very rare is it that you 98 00:04:53,040 --> 00:04:55,200 Speaker 1: go to, say, a board of directors and somebody's like, yeah, 99 00:04:55,200 --> 00:04:58,280 Speaker 1: I'm twenty four, and more likely they're double that or 100 00:04:58,320 --> 00:05:01,200 Speaker 1: even triple that age, right, And so their their job 101 00:05:01,320 --> 00:05:04,040 Speaker 1: is to sort of traffic in and build off of 102 00:05:04,240 --> 00:05:06,960 Speaker 1: their years and decades of experience. But I think that 103 00:05:06,960 --> 00:05:09,000 Speaker 1: has a way of conquering the ability to look at 104 00:05:09,080 --> 00:05:12,800 Speaker 1: sort of forward narratives. And so my frame for this 105 00:05:12,880 --> 00:05:15,359 Speaker 1: and thinking about climate change was a couple of the 106 00:05:15,360 --> 00:05:18,040 Speaker 1: publications that had come out in from third parties, one 107 00:05:18,040 --> 00:05:21,799 Speaker 1: of them was a precipitation chart in the United States. 108 00:05:21,800 --> 00:05:25,600 Speaker 1: This is from Noah So, one of our research institutes 109 00:05:25,640 --> 00:05:28,800 Speaker 1: in the US that it published that the trailing twelve 110 00:05:28,800 --> 00:05:32,400 Speaker 1: months was the wettest twelve months in the United States 111 00:05:32,400 --> 00:05:36,480 Speaker 1: since and probably forever. There's really no way of knowing before, 112 00:05:38,240 --> 00:05:41,320 Speaker 1: and extremely wet, like much wetter than it's ever been. Now, 113 00:05:41,440 --> 00:05:43,240 Speaker 1: that's a very noisy kind of signal, but if you 114 00:05:43,279 --> 00:05:45,960 Speaker 1: smooth it out, you can see that it's like about 115 00:05:45,960 --> 00:05:48,640 Speaker 1: ten percent wetter than the long term average has ever been. 116 00:05:49,400 --> 00:05:51,839 Speaker 1: Um I also realized that if you if you fit 117 00:05:51,920 --> 00:05:55,200 Speaker 1: these things against the average across the twentieth century, that 118 00:05:55,320 --> 00:05:59,240 Speaker 1: it's been above average for about forty something years, right, 119 00:05:59,240 --> 00:06:02,120 Speaker 1: so we loss the average on the way up, and 120 00:06:02,320 --> 00:06:06,919 Speaker 1: we're still there and actually mean surface temperatures a global 121 00:06:07,080 --> 00:06:09,920 Speaker 1: surface temperatures around the world have fallen on almost exactly 122 00:06:10,000 --> 00:06:12,920 Speaker 1: the same kind of a pattern. There's a thirty year 123 00:06:12,960 --> 00:06:16,880 Speaker 1: interval in which averages are determined and the average temperatures 124 00:06:17,000 --> 00:06:21,479 Speaker 1: the benchmark is nineteen fifty one to night and in 125 00:06:21,640 --> 00:06:25,120 Speaker 1: the mid nineteen seventies, the global surface temperature went above 126 00:06:25,160 --> 00:06:27,599 Speaker 1: that mean and has never been below it. And so 127 00:06:27,680 --> 00:06:29,920 Speaker 1: the reason that I thought that was useful was because 128 00:06:30,080 --> 00:06:33,200 Speaker 1: we might be dealing with a business executive who's at 129 00:06:33,240 --> 00:06:35,760 Speaker 1: the tail end of a long and illustrious career in 130 00:06:35,960 --> 00:06:40,000 Speaker 1: his or her domain, and is mostly embedded in their 131 00:06:40,040 --> 00:06:43,560 Speaker 1: own business. It may not necessarily be thinking on a 132 00:06:43,600 --> 00:06:47,359 Speaker 1: thirty forty year time went ahead, but that interval of 133 00:06:47,600 --> 00:06:50,960 Speaker 1: climate change and that interval of precipitation matches up very 134 00:06:51,000 --> 00:06:54,400 Speaker 1: nicely with the global median age, which is about thirty 135 00:06:54,480 --> 00:06:57,880 Speaker 1: seven which means that actually the median person on Earth 136 00:06:57,920 --> 00:07:02,159 Speaker 1: has only known something that was hotter and wetter than 137 00:07:02,400 --> 00:07:05,919 Speaker 1: it was before. And if you look at places that 138 00:07:05,920 --> 00:07:08,040 Speaker 1: are not you know, the global average, and that's saying 139 00:07:08,120 --> 00:07:10,920 Speaker 1: least developed countries. By the UN standard, the median age 140 00:07:10,960 --> 00:07:15,120 Speaker 1: is nineteen point four years. So most people have had 141 00:07:15,640 --> 00:07:19,960 Speaker 1: the entirety of their lifetimes within a system that is 142 00:07:20,360 --> 00:07:24,679 Speaker 1: not variable and not fluctuating, or rather not just variable 143 00:07:24,680 --> 00:07:28,160 Speaker 1: and fluctuating, but has a vector. And so if you're 144 00:07:29,120 --> 00:07:33,240 Speaker 1: twenty and entering the workforce, your expectations are probably about 145 00:07:33,280 --> 00:07:36,720 Speaker 1: always going to be more automation. It's also if you're 146 00:07:36,760 --> 00:07:39,000 Speaker 1: looking at your macro environment. It's always going to be 147 00:07:39,040 --> 00:07:42,280 Speaker 1: hotter and it feels like it, right, And this is 148 00:07:42,320 --> 00:07:45,280 Speaker 1: a narrative, is something that helps to shape and drive 149 00:07:46,080 --> 00:07:48,640 Speaker 1: the way that people construct their long term vision of 150 00:07:48,640 --> 00:07:51,720 Speaker 1: the future. Companies do this in the form of scenario planning. 151 00:07:52,720 --> 00:07:55,240 Speaker 1: I try to do it in six or seven hundred 152 00:07:55,280 --> 00:07:58,240 Speaker 1: words in an email that people received with a few charts, 153 00:07:58,840 --> 00:08:00,600 Speaker 1: but I think it's part of the same kind of idea. 154 00:08:00,640 --> 00:08:02,960 Speaker 1: And I realized that the only the only way to 155 00:08:03,040 --> 00:08:05,560 Speaker 1: sort of convince people about that that they are carrying 156 00:08:05,600 --> 00:08:08,680 Speaker 1: their own stories with them is to tell another story. 157 00:08:09,040 --> 00:08:11,480 Speaker 1: And it's a useful framework. I think we guess, for 158 00:08:11,520 --> 00:08:14,800 Speaker 1: one thing, the numbers around it are inarguable. I mean, 159 00:08:14,840 --> 00:08:17,760 Speaker 1: you can you can argue about mean surface temperature, but 160 00:08:17,800 --> 00:08:20,120 Speaker 1: you're not really arguing with me, would be any of 161 00:08:20,160 --> 00:08:24,400 Speaker 1: analysts you're arguing with, you know, laboratories and research institutes. 162 00:08:24,960 --> 00:08:27,480 Speaker 1: So you mentioned the piece that sentiment is changing around 163 00:08:27,520 --> 00:08:30,320 Speaker 1: these things. Can you describe kind of how some of 164 00:08:30,320 --> 00:08:34,560 Speaker 1: the sentiments are changing. So very fewer and fewer people 165 00:08:34,880 --> 00:08:39,199 Speaker 1: who do not believe in climate change, particularly people that 166 00:08:39,240 --> 00:08:42,640 Speaker 1: are younger. More and more people believe that not only 167 00:08:42,679 --> 00:08:45,120 Speaker 1: is it occurring, but it is anthropogenic, so it's caused 168 00:08:45,160 --> 00:08:48,040 Speaker 1: by people, and there there is a reason to sort 169 00:08:48,040 --> 00:08:51,439 Speaker 1: of disaggregate those those two beliefs, right well, giving that 170 00:08:51,520 --> 00:08:54,000 Speaker 1: it happens means well, you know, we go through these 171 00:08:54,000 --> 00:08:57,200 Speaker 1: periods once every million years or whatever, so what and 172 00:08:57,200 --> 00:09:01,120 Speaker 1: and in truth that does happen globally or in the 173 00:09:01,120 --> 00:09:04,679 Speaker 1: long geneologic timeline. It usually coincides with what we call 174 00:09:04,760 --> 00:09:09,320 Speaker 1: greatest extinctions, but it does occur on its own. Pleasant pleasant, 175 00:09:09,360 --> 00:09:11,839 Speaker 1: isn't it. But the next aspect, though, is that it's 176 00:09:11,880 --> 00:09:13,719 Speaker 1: being caused by people, meaning that there is something to 177 00:09:13,800 --> 00:09:17,559 Speaker 1: be There's both blame, but I would say more importantly, 178 00:09:17,559 --> 00:09:20,480 Speaker 1: there's something to be done as opposed to nothing to 179 00:09:20,480 --> 00:09:23,280 Speaker 1: be done. And I think that that's that's the sort 180 00:09:23,320 --> 00:09:25,600 Speaker 1: of thing that we start to see show up in 181 00:09:25,600 --> 00:09:28,640 Speaker 1: a business context, partly as imperative, you know, we have 182 00:09:28,760 --> 00:09:31,680 Speaker 1: to do this, but depending on the company, partly as 183 00:09:31,720 --> 00:09:34,800 Speaker 1: opportunity as well, Like if doing doing this, it might 184 00:09:34,840 --> 00:09:38,400 Speaker 1: be a way to first of all, cap your downsides 185 00:09:38,440 --> 00:09:40,280 Speaker 1: as much as possible, Right so the sort of sort 186 00:09:40,280 --> 00:09:43,680 Speaker 1: of resilience dividend or robustness, and the other part is 187 00:09:43,720 --> 00:09:47,120 Speaker 1: to capture some upside from it. We're we're better prepared 188 00:09:47,120 --> 00:09:50,480 Speaker 1: and are therefore in a better position to provide for 189 00:09:51,240 --> 00:09:54,920 Speaker 1: be meaningful in a future that is whether or more volatile. 190 00:09:54,960 --> 00:09:59,360 Speaker 1: More everything you're writing specifically for business audience. You are, 191 00:09:59,480 --> 00:10:01,960 Speaker 1: you are on the Bloomberg terminal and also have a 192 00:10:02,040 --> 00:10:04,600 Speaker 1: newsletter to the wider world, but there there is a 193 00:10:04,600 --> 00:10:07,720 Speaker 1: specific audience here. There are two other pieces that you wrote, 194 00:10:08,200 --> 00:10:11,240 Speaker 1: the one called climate Change puts Insurers to the test 195 00:10:11,400 --> 00:10:14,920 Speaker 1: and the other how far will Insurers go to detach 196 00:10:15,040 --> 00:10:18,640 Speaker 1: from coal? Now, I'm really glad you brought up scenarios. 197 00:10:18,679 --> 00:10:21,400 Speaker 1: Scenario planning is something that is kind of at the 198 00:10:21,520 --> 00:10:26,360 Speaker 1: core of the TCFD Task Force for Climate related Financial disclosures. Additionally, 199 00:10:26,720 --> 00:10:28,760 Speaker 1: it seems to be getting to be at the core 200 00:10:29,080 --> 00:10:33,840 Speaker 1: for a lot of businesses, both corporates and finance UM 201 00:10:33,880 --> 00:10:36,600 Speaker 1: and not just relegated to this insurance space. Whether they're 202 00:10:36,600 --> 00:10:39,280 Speaker 1: constantly trying to come up with probabilities, but these probabilities 203 00:10:39,320 --> 00:10:42,880 Speaker 1: of likelihood around these climate change scenarios seem to be 204 00:10:42,920 --> 00:10:45,440 Speaker 1: going more mainstream. Do you see any evidence of that 205 00:10:45,520 --> 00:10:48,960 Speaker 1: coming about UM or maybe that's illustrated in these two pieces. 206 00:10:49,080 --> 00:10:51,959 Speaker 1: There's an interesting thing always about watching insurance because it's 207 00:10:52,040 --> 00:10:54,600 Speaker 1: it's like a market of other markets, almost right, and 208 00:10:54,679 --> 00:10:58,160 Speaker 1: it in turn has its own risk market called reinsurance. 209 00:10:58,640 --> 00:11:00,319 Speaker 1: But the reason I think that it's very warden to 210 00:11:00,360 --> 00:11:04,120 Speaker 1: watch is because it is both obviously the the arbiter 211 00:11:04,280 --> 00:11:06,840 Speaker 1: and the underwriter of risk, but also it is a 212 00:11:06,880 --> 00:11:11,240 Speaker 1: major investor in assets of all kinds of classes. So 213 00:11:11,280 --> 00:11:15,920 Speaker 1: it has this this unusual exposure to basically anything. So 214 00:11:16,040 --> 00:11:18,400 Speaker 1: let's say that you are you are a you're an 215 00:11:18,400 --> 00:11:21,680 Speaker 1: orige insure and you underwrite the risks around a coal 216 00:11:22,080 --> 00:11:25,480 Speaker 1: coal plant, qual fired power plant. You are exposed to 217 00:11:25,520 --> 00:11:28,400 Speaker 1: anything that you have underwritten on the asset itself, but 218 00:11:28,480 --> 00:11:31,520 Speaker 1: you also might have you might own equity in the 219 00:11:31,600 --> 00:11:34,160 Speaker 1: company that in turn neither provides fuel to that or 220 00:11:34,240 --> 00:11:36,400 Speaker 1: owns the company that owns the coal plant, or something 221 00:11:36,440 --> 00:11:39,240 Speaker 1: like that, and so you're exposed to whatever business dynamics 222 00:11:39,280 --> 00:11:41,680 Speaker 1: happen as well, both the physical risks and the financial 223 00:11:41,760 --> 00:11:43,720 Speaker 1: risk that are associated with one of these assets. So 224 00:11:44,240 --> 00:11:48,000 Speaker 1: insurance is a sort of a uniquely multifaceted way of 225 00:11:48,040 --> 00:11:51,520 Speaker 1: looking at any kind of macro risk. That's generally why 226 00:11:51,559 --> 00:11:55,000 Speaker 1: they're fairly risk averse. Um they're also really highly regulated, 227 00:11:55,040 --> 00:11:57,520 Speaker 1: and that's the key part that I looked at in 228 00:11:57,840 --> 00:12:01,240 Speaker 1: my piece, which was that the Bank of England's Prudential 229 00:12:01,280 --> 00:12:06,760 Speaker 1: Regulation Authority, the regulator for in fiduciary institutions, puts out 230 00:12:06,760 --> 00:12:09,760 Speaker 1: a stress test that it sends to all general insurers 231 00:12:09,800 --> 00:12:11,199 Speaker 1: and I think they do them for banks as well, 232 00:12:11,880 --> 00:12:13,880 Speaker 1: and a lot of it is usual stuff, tell us 233 00:12:13,920 --> 00:12:16,640 Speaker 1: your capital ratios, tell us whatever, whatever kind of things, 234 00:12:17,280 --> 00:12:19,360 Speaker 1: and then they like to and this is a good thing, 235 00:12:19,400 --> 00:12:21,400 Speaker 1: sort of throw something else new in there each time, 236 00:12:21,679 --> 00:12:25,120 Speaker 1: and they're they're sort of less official than the kind 237 00:12:25,160 --> 00:12:26,839 Speaker 1: of standard stuff that always happens. But in the most 238 00:12:26,880 --> 00:12:29,720 Speaker 1: recent one a few months ago, the Bank of England 239 00:12:29,800 --> 00:12:34,320 Speaker 1: p r A says, tell us about your exposure to 240 00:12:34,400 --> 00:12:38,720 Speaker 1: cyber security and to climate risk, and they do it 241 00:12:38,760 --> 00:12:44,360 Speaker 1: by having you lot a spreadsheet that says I have 242 00:12:44,600 --> 00:12:47,400 Speaker 1: X many assets and these these asset classes and in 243 00:12:47,440 --> 00:12:49,679 Speaker 1: these scenarios, I'm going to write their book value down 244 00:12:49,760 --> 00:12:52,240 Speaker 1: by this. So it's it's very it's very blunt. I mean, 245 00:12:52,280 --> 00:12:54,199 Speaker 1: if I can figure it out, it can't be that complicated, 246 00:12:54,240 --> 00:12:58,120 Speaker 1: So it's it's fairly simple. Uh, it's coming from a 247 00:12:58,240 --> 00:13:01,600 Speaker 1: very serious regulatory institutions. You more or less have to 248 00:13:01,640 --> 00:13:03,400 Speaker 1: do it. I don't think you running to punt on it. 249 00:13:04,200 --> 00:13:07,560 Speaker 1: And it's it's got some very clear directives around it. 250 00:13:07,600 --> 00:13:09,320 Speaker 1: So I looked at that as a way of saying, Okay, well, 251 00:13:09,360 --> 00:13:11,319 Speaker 1: this is like what the regulator of the people who 252 00:13:11,400 --> 00:13:16,120 Speaker 1: underwrite an assess risk thinks. The risks might be very 253 00:13:16,160 --> 00:13:18,360 Speaker 1: a very interesting way for us to be to be 254 00:13:18,400 --> 00:13:22,480 Speaker 1: approaching what might be happening and how companies might think 255 00:13:22,480 --> 00:13:26,559 Speaker 1: about it. And it's they're not small numbers in terms 256 00:13:26,640 --> 00:13:28,880 Speaker 1: of what a write down of asset classes would look like. 257 00:13:28,920 --> 00:13:31,000 Speaker 1: I can one of the transition scenarios of climate change. 258 00:13:31,040 --> 00:13:33,400 Speaker 1: They say, you write your cold book off by more 259 00:13:33,440 --> 00:13:36,679 Speaker 1: than which ouch if you're you know, if you're an investor, 260 00:13:36,720 --> 00:13:38,880 Speaker 1: that that's pretty that's pretty severe. And in fact they 261 00:13:38,880 --> 00:13:41,880 Speaker 1: actually call it disorderly like it's not it's not a 262 00:13:41,920 --> 00:13:44,520 Speaker 1: sort of like, well, we can smoothly transition out of this. 263 00:13:44,640 --> 00:13:47,880 Speaker 1: It's more like things have changed so significantly that these 264 00:13:47,920 --> 00:13:51,840 Speaker 1: assets are trending towards worthless, or they're they're so heavily 265 00:13:51,880 --> 00:13:54,360 Speaker 1: impaired that there's something that you you have to get 266 00:13:54,400 --> 00:13:56,800 Speaker 1: out of, no matter what that no matter what's happening. 267 00:13:57,160 --> 00:13:58,920 Speaker 1: So when I think it is actually very useful that 268 00:13:59,000 --> 00:14:02,320 Speaker 1: when looking at the two scenarios the Bank of eng 269 00:14:02,400 --> 00:14:05,679 Speaker 1: And is asking for, is they on the surface of 270 00:14:05,760 --> 00:14:08,280 Speaker 1: nothing in common with each other cybersecurity and climate risk. 271 00:14:08,320 --> 00:14:09,679 Speaker 1: But the more I thought about it, they actually have 272 00:14:09,840 --> 00:14:13,680 Speaker 1: quite a bit in common. They're both pervasive, very large. 273 00:14:13,920 --> 00:14:16,400 Speaker 1: I guess mark what we would call an attack surface 274 00:14:17,040 --> 00:14:19,640 Speaker 1: in which things can happen. Right in cybersecurity, it's everything 275 00:14:19,680 --> 00:14:24,840 Speaker 1: from your connected doorbell or the you know, the connected 276 00:14:25,160 --> 00:14:27,360 Speaker 1: pump in your fish tank can be used as a 277 00:14:27,440 --> 00:14:31,480 Speaker 1: point of entry to somebody's CRM and you now stolen 278 00:14:31,480 --> 00:14:34,880 Speaker 1: everybody's credit card information. So these think this bloomberg business. 279 00:14:34,920 --> 00:14:37,520 Speaker 1: We actually wrote about this and I thought climate is 280 00:14:37,520 --> 00:14:39,880 Speaker 1: actually kind of similar. Is that like, basically everything ends 281 00:14:39,920 --> 00:14:42,560 Speaker 1: up affected by this. It's not just that it's hotter, 282 00:14:42,720 --> 00:14:45,680 Speaker 1: it's also that things are more volatile. Most of our 283 00:14:45,760 --> 00:14:49,320 Speaker 1: built environment was designed around some sort of standard that 284 00:14:49,360 --> 00:14:51,440 Speaker 1: if it's no longer the standard, things just don't work 285 00:14:51,480 --> 00:14:56,200 Speaker 1: as well. It creates brittleness throughout the system. Uh paradox, 286 00:14:56,200 --> 00:14:58,240 Speaker 1: And it was actually easier to measure what might be 287 00:14:58,520 --> 00:15:01,480 Speaker 1: problematic from climate change that was from cybersecurity, even though 288 00:15:01,520 --> 00:15:03,880 Speaker 1: it's a really long term thing. But I like that. 289 00:15:03,960 --> 00:15:06,560 Speaker 1: I think that that that construct that the Bank of 290 00:15:06,600 --> 00:15:09,960 Speaker 1: England has helpfully put together is one that I would 291 00:15:10,000 --> 00:15:14,240 Speaker 1: imagine comes into the scenario planning and the scenario thinking 292 00:15:14,440 --> 00:15:16,600 Speaker 1: of a lot of the institutions that we deal with. 293 00:15:16,720 --> 00:15:19,160 Speaker 1: Is it like, well, if you went to a company 294 00:15:19,240 --> 00:15:22,960 Speaker 1: you said do you have a cybersecurity strategy and they 295 00:15:22,960 --> 00:15:26,720 Speaker 1: said nah, we'd be a bit surprised. I would imagine 296 00:15:26,720 --> 00:15:29,680 Speaker 1: that for pretty much any big institution we would have 297 00:15:29,680 --> 00:15:31,600 Speaker 1: the same reaction if in five years time they said 298 00:15:31,680 --> 00:15:35,520 Speaker 1: I don't have a climate change scenario policy or risk 299 00:15:35,520 --> 00:15:37,840 Speaker 1: assessment or way of thinking about it. So do you 300 00:15:37,840 --> 00:15:40,200 Speaker 1: think these things are things that happened in as curve, 301 00:15:40,240 --> 00:15:42,200 Speaker 1: that just happened all of a sudden Very much so. 302 00:15:42,400 --> 00:15:44,120 Speaker 1: I mean, if you if you look at them, if 303 00:15:44,120 --> 00:15:46,680 Speaker 1: you look at these things again, thinking in stories, very 304 00:15:46,760 --> 00:15:49,080 Speaker 1: few institutions want to be the first to do something, 305 00:15:50,120 --> 00:15:52,840 Speaker 1: even fewer, very few institutions want to be the last 306 00:15:53,000 --> 00:15:56,280 Speaker 1: to do something. So, particularly when you're talking about risk, 307 00:15:56,320 --> 00:15:59,440 Speaker 1: when you're talking about standards and things like that, they 308 00:15:59,480 --> 00:16:03,400 Speaker 1: tend to go slowly and then suddenly and then especially 309 00:16:03,400 --> 00:16:05,640 Speaker 1: once you if you think about it, is a group 310 00:16:05,640 --> 00:16:08,040 Speaker 1: of peers, right, they all want to be doing it. 311 00:16:08,480 --> 00:16:11,240 Speaker 1: Who wants to be who wants to be the last 312 00:16:11,320 --> 00:16:14,720 Speaker 1: insurance company that does not have a policy about thermal 313 00:16:14,760 --> 00:16:19,120 Speaker 1: coal you don't write or you've relegated yourself to essentially 314 00:16:19,120 --> 00:16:22,040 Speaker 1: a very specialty part of the business. Who wants to 315 00:16:22,080 --> 00:16:25,880 Speaker 1: be the auto company that has zero electric vehicle strategy 316 00:16:26,120 --> 00:16:30,000 Speaker 1: would be another analogy. I read Bob Dudley's talk at 317 00:16:30,080 --> 00:16:31,720 Speaker 1: Chatham House a couple of weeks ago and scoring them 318 00:16:31,720 --> 00:16:35,560 Speaker 1: to train in and it really seemed like vp IS 319 00:16:35,560 --> 00:16:37,440 Speaker 1: is on its way right, not maybe not the first, 320 00:16:37,440 --> 00:16:40,320 Speaker 1: but maybe the first oil major to really just go 321 00:16:40,400 --> 00:16:43,320 Speaker 1: up the curve. And but they were the first for 322 00:16:43,360 --> 00:16:45,240 Speaker 1: a while for a while and then backed out. But 323 00:16:45,960 --> 00:16:48,440 Speaker 1: it looks like they're they're backing back in. But but 324 00:16:48,440 --> 00:16:51,800 Speaker 1: so you know, Bob Doney, the CEO of BP and 325 00:16:52,200 --> 00:16:54,920 Speaker 1: his colleague who is his counterpart rather at Shell Bend 326 00:16:54,960 --> 00:16:57,680 Speaker 1: and Britain, they they are both quite vocal about these 327 00:16:57,720 --> 00:17:00,280 Speaker 1: sorts of things. By the time that they've each that 328 00:17:00,400 --> 00:17:04,760 Speaker 1: point of public discussion, it's probably relatively well considered within 329 00:17:04,800 --> 00:17:07,520 Speaker 1: the rest of the organization there. Let's put it this, 330 00:17:07,600 --> 00:17:10,960 Speaker 1: or they're probably not winging it it's it's going, it's 331 00:17:10,960 --> 00:17:14,720 Speaker 1: going through a very thoughtful apparatus, especially for institutions that 332 00:17:14,800 --> 00:17:18,119 Speaker 1: really do plan to So I but I, but I 333 00:17:18,240 --> 00:17:21,040 Speaker 1: what I don't know yet and what is probably in 334 00:17:21,080 --> 00:17:24,400 Speaker 1: a neutral statement unclear for quite some time as exactly 335 00:17:24,400 --> 00:17:26,679 Speaker 1: what that means, you know, is for a company, is 336 00:17:26,680 --> 00:17:29,520 Speaker 1: it primarily rated towards risk? Is is it primarily rated 337 00:17:29,560 --> 00:17:32,920 Speaker 1: towards opportunity? If you think about it from a strategic 338 00:17:32,960 --> 00:17:35,760 Speaker 1: planning perspective, do you think that there's an average time 339 00:17:35,840 --> 00:17:39,320 Speaker 1: from announcement of change in a company to actual implementation. 340 00:17:39,520 --> 00:17:41,920 Speaker 1: It's a fantastic question that I think depends much more 341 00:17:42,000 --> 00:17:44,600 Speaker 1: upon the nature of the business and its own cultures, 342 00:17:44,720 --> 00:17:50,320 Speaker 1: embrace of speed, openness to change, and where where it 343 00:17:50,359 --> 00:17:52,919 Speaker 1: probably is along its own journey with its own from 344 00:17:52,960 --> 00:17:56,199 Speaker 1: lack of a better word, stuff. So, companies that have 345 00:17:56,400 --> 00:17:59,760 Speaker 1: lots of resources of various types, and I would put 346 00:17:59,760 --> 00:18:02,479 Speaker 1: in this in this context, could say a diversified metals 347 00:18:02,480 --> 00:18:07,560 Speaker 1: and mining company has upside scenarios and not upside scenarios 348 00:18:07,600 --> 00:18:12,200 Speaker 1: within its portfolio of assets. In an electric vehicle high 349 00:18:12,240 --> 00:18:16,200 Speaker 1: electric vehicle penetration future, in a very climate change the 350 00:18:16,280 --> 00:18:18,920 Speaker 1: future and whatever there there's there's there's pluses and minuses. 351 00:18:19,240 --> 00:18:22,280 Speaker 1: A lot of times those organizations tend to move sometimes 352 00:18:22,280 --> 00:18:25,480 Speaker 1: actually more supp only because they can. It's Pewer play. 353 00:18:25,560 --> 00:18:29,680 Speaker 1: Companies that have essentially no upside from a transition away 354 00:18:29,680 --> 00:18:32,800 Speaker 1: from one resource towards another. That and I say this 355 00:18:33,240 --> 00:18:38,000 Speaker 1: neutral e are fairly naturally less enthusiastic about such things. 356 00:18:37,840 --> 00:18:40,760 Speaker 1: It's the more active fight rather than adapt. I think 357 00:18:40,760 --> 00:18:42,200 Speaker 1: that's I think that's a way to say it, because 358 00:18:42,240 --> 00:18:46,840 Speaker 1: adapt adaptation is it's not necessarily not in the d 359 00:18:46,960 --> 00:18:49,560 Speaker 1: n A. It's more like not in the capability of 360 00:18:49,760 --> 00:18:52,399 Speaker 1: the resources that are given. It would require doing something 361 00:18:52,400 --> 00:18:57,119 Speaker 1: completely different, especially for institutions for which you know, a 362 00:18:57,160 --> 00:18:59,000 Speaker 1: lot of the value and the way in which they 363 00:18:59,000 --> 00:19:01,560 Speaker 1: are valued is in assets that they own, you know, 364 00:19:02,000 --> 00:19:06,000 Speaker 1: years of future reserves and things like that. Those those 365 00:19:06,000 --> 00:19:10,919 Speaker 1: are not a particularly resilient resource when it comes to 366 00:19:11,880 --> 00:19:13,639 Speaker 1: when it comes to a future that might not be 367 00:19:13,800 --> 00:19:16,359 Speaker 1: using so much. You had another piece, Actually they said, 368 00:19:16,359 --> 00:19:19,800 Speaker 1: like they're those numbers becoming increasingly meaningless. Isn't that right? 369 00:19:20,359 --> 00:19:23,080 Speaker 1: Was that not you? That was Liam Denning? Sorry, I wish, 370 00:19:23,119 --> 00:19:26,000 Speaker 1: I wish I wrote something that good. Yeah, it was. 371 00:19:26,359 --> 00:19:28,959 Speaker 1: It was great, so good in fact that it couldn't 372 00:19:28,960 --> 00:19:32,480 Speaker 1: have been written by That's definitely on the Mdenning piece. 373 00:19:34,600 --> 00:19:38,280 Speaker 1: When you're looking at the change curve, people do resist change, 374 00:19:38,359 --> 00:19:42,400 Speaker 1: whether that be groups of people in a company or individuals. 375 00:19:43,359 --> 00:19:46,240 Speaker 1: And I'm actually thinking, as you're talking about these company 376 00:19:46,320 --> 00:19:51,560 Speaker 1: dynamics and change and opportunity and how you sipeon through that, 377 00:19:51,920 --> 00:19:54,280 Speaker 1: on this very micro level, individuals are doing that. So 378 00:19:54,359 --> 00:19:56,360 Speaker 1: I am actually going to pivot us to two other notes. 379 00:19:57,280 --> 00:20:00,320 Speaker 1: So one is self driving fixed for a population problem, 380 00:20:00,359 --> 00:20:02,919 Speaker 1: and the other is Hong Kong's taxi fleet pages in 381 00:20:03,040 --> 00:20:06,399 Speaker 1: real time. Uh. Now, by Hong Kong's taxi fleet, you're 382 00:20:06,400 --> 00:20:09,399 Speaker 1: talking about people. And I must say that we spend 383 00:20:09,400 --> 00:20:12,280 Speaker 1: a lot of time talking about AI and self driving 384 00:20:12,320 --> 00:20:14,119 Speaker 1: and whether or not this is going to replace physical 385 00:20:14,160 --> 00:20:16,960 Speaker 1: drivers and then Uber indeedy and who those physical drivers 386 00:20:17,000 --> 00:20:21,200 Speaker 1: are and those physical drivers, Yeah, they're They're real people 387 00:20:21,280 --> 00:20:25,119 Speaker 1: who have adapted in many regards, or maybe in Hong 388 00:20:25,200 --> 00:20:30,720 Speaker 1: Kong's case, not adapted to this rapid implementation of change 389 00:20:31,119 --> 00:20:34,399 Speaker 1: in how we move people and things around and in 390 00:20:34,560 --> 00:20:39,199 Speaker 1: what and how it all comes together. So as this 391 00:20:39,280 --> 00:20:42,400 Speaker 1: change is happening to people around the world in real time, 392 00:20:42,640 --> 00:20:44,800 Speaker 1: talk a little bit about those notes, because I think 393 00:20:44,800 --> 00:20:46,440 Speaker 1: one of the fun things that you get to do 394 00:20:46,560 --> 00:20:50,000 Speaker 1: is not just talk about implications for companies and opportunities, 395 00:20:50,080 --> 00:20:53,439 Speaker 1: but actually how it's going to affect everyone's lives. Thank you, 396 00:20:53,480 --> 00:20:54,960 Speaker 1: I I yeah, I had a lot of fun with 397 00:20:55,000 --> 00:20:57,040 Speaker 1: that one. I didn't give in Hong Kong for four years, 398 00:20:57,040 --> 00:20:59,000 Speaker 1: so it's close to heart. And actually marketing into this 399 00:20:59,080 --> 00:21:00,480 Speaker 1: a bit light on how to you come up with 400 00:21:00,480 --> 00:21:04,320 Speaker 1: an idea for something. A lot of them are actually experiential, 401 00:21:04,440 --> 00:21:06,920 Speaker 1: even if it sounds kind of lame to talk about 402 00:21:06,960 --> 00:21:10,040 Speaker 1: experiential in the context of like reading business reports, but 403 00:21:10,359 --> 00:21:13,840 Speaker 1: it's experiential. There's an aha moment, and this was reading 404 00:21:13,880 --> 00:21:16,520 Speaker 1: something in in the Hong Kong English language newspaper the 405 00:21:16,520 --> 00:21:19,320 Speaker 1: South China Morning Post that just said something about Hong 406 00:21:19,359 --> 00:21:22,719 Speaker 1: Kong's taxi drivers are like a record average old age 407 00:21:22,800 --> 00:21:30,200 Speaker 1: and it is quite venerable, like unexpectedly old mid sixties. 408 00:21:30,400 --> 00:21:32,720 Speaker 1: Mid sixties is a sort of median age for a 409 00:21:32,880 --> 00:21:34,600 Speaker 1: for a taxi driver in Hong Kong, but there are 410 00:21:34,600 --> 00:21:36,840 Speaker 1: actually a fair number that are significantly older than that 411 00:21:37,920 --> 00:21:40,800 Speaker 1: are older than seventy yes eight percent of Hong Kong 412 00:21:40,840 --> 00:21:43,240 Speaker 1: taxi drivers are older than seventy. And remember this is 413 00:21:43,280 --> 00:21:47,560 Speaker 1: the this is the locality with the highest average average 414 00:21:47,600 --> 00:21:51,359 Speaker 1: age population on Earth or sorry, average knife expectancy in 415 00:21:51,440 --> 00:21:53,560 Speaker 1: the eighties. So there are plenty of people who are 416 00:21:54,760 --> 00:21:58,159 Speaker 1: over seventy and if they're in good health, have potentially 417 00:21:58,200 --> 00:22:01,320 Speaker 1: another fifteen or twenty years of working if ahead of them. 418 00:22:01,359 --> 00:22:03,600 Speaker 1: And yeah, it's an it's an interesting sort of microcosm 419 00:22:03,680 --> 00:22:07,679 Speaker 1: of many different aspects of transportation in the demographics and 420 00:22:07,680 --> 00:22:12,479 Speaker 1: of society. But I thought about it particularly as like 421 00:22:12,640 --> 00:22:15,200 Speaker 1: as something that is aging in real time and will 422 00:22:15,200 --> 00:22:17,639 Speaker 1: not be replaced. And I used it, and this is 423 00:22:17,960 --> 00:22:20,160 Speaker 1: not characteristic of my work all the time, to use 424 00:22:20,160 --> 00:22:22,159 Speaker 1: it as a sort of metaphor for the rest of 425 00:22:22,200 --> 00:22:25,240 Speaker 1: Hong Kong's economy that's also aging in real time and 426 00:22:25,440 --> 00:22:30,280 Speaker 1: predominantly services, does not have an above replacement birth rate, 427 00:22:30,720 --> 00:22:35,320 Speaker 1: and so is facing things that While we worry in 428 00:22:35,600 --> 00:22:38,800 Speaker 1: a lot of economies that automation and AI and things 429 00:22:38,800 --> 00:22:41,399 Speaker 1: like that will be putting people out of work, I 430 00:22:41,440 --> 00:22:43,600 Speaker 1: sort of imagined in the context here, if they will 431 00:22:43,640 --> 00:22:46,080 Speaker 1: be doing the work that needs to be done, because 432 00:22:46,119 --> 00:22:48,720 Speaker 1: who else will be doing it? I don't know about it. 433 00:22:48,720 --> 00:22:50,760 Speaker 1: If we're gonna have self driving cars in Hong Kong. 434 00:22:50,800 --> 00:22:54,120 Speaker 1: The traffic is traffic, and most important to that, topography 435 00:22:54,240 --> 00:22:58,240 Speaker 1: is incredibly complex, and so it's it's not the same 436 00:22:58,280 --> 00:23:02,720 Speaker 1: thing as driving on an empty, prepared highway somewhere, but 437 00:23:03,040 --> 00:23:05,639 Speaker 1: some something won't have to give in the way that 438 00:23:05,680 --> 00:23:09,760 Speaker 1: people move around or the expectations of how one gets 439 00:23:09,760 --> 00:23:13,800 Speaker 1: from place to place. Maybe in what or with whom 440 00:23:13,840 --> 00:23:16,879 Speaker 1: If you continue to have the Hong Kong taxi drivers 441 00:23:16,920 --> 00:23:20,199 Speaker 1: become older and older and there is no sort of 442 00:23:20,359 --> 00:23:23,360 Speaker 1: replacement to go with it, I want to know more 443 00:23:23,400 --> 00:23:27,639 Speaker 1: about the complex topography. So another city that you also 444 00:23:27,720 --> 00:23:31,600 Speaker 1: lived in, San Francisco, has a lot of hills and 445 00:23:31,960 --> 00:23:35,199 Speaker 1: a lot of technology implementation in this driving space, and 446 00:23:35,280 --> 00:23:38,560 Speaker 1: I keep thinking it wouldn't exactly physically be where I 447 00:23:38,560 --> 00:23:40,560 Speaker 1: would start, but it is where it is all kind 448 00:23:40,560 --> 00:23:44,160 Speaker 1: of coming from. Um, how does what are the barriers 449 00:23:44,160 --> 00:23:49,119 Speaker 1: that Hong Kong has so ongoing? Hong Kong is very dense, Uh, 450 00:23:49,400 --> 00:23:52,560 Speaker 1: it has a very rich visual landscape if you will. 451 00:23:53,000 --> 00:23:55,000 Speaker 1: There's often a lot of things going on, So there 452 00:23:55,000 --> 00:23:57,720 Speaker 1: would be a really really really high amount of signal 453 00:23:58,200 --> 00:24:00,560 Speaker 1: if you think about it, especially through through some kind 454 00:24:00,600 --> 00:24:04,679 Speaker 1: of machine or computer vision, and that's so that's a 455 00:24:04,720 --> 00:24:06,959 Speaker 1: sort of like the vision part of it. The driving 456 00:24:07,000 --> 00:24:09,840 Speaker 1: part is that there's all kinds of like like narrow 457 00:24:10,000 --> 00:24:13,960 Speaker 1: one way roads that wind through the mountains. UH signages 458 00:24:14,000 --> 00:24:17,960 Speaker 1: and two languages. So you might find that the more 459 00:24:18,040 --> 00:24:22,120 Speaker 1: prominent sign would be in Chinese characters, and you'd better 460 00:24:22,160 --> 00:24:25,240 Speaker 1: make sure that your computer vision can read that if 461 00:24:25,240 --> 00:24:28,320 Speaker 1: you need to be reading a sign. There's also lots 462 00:24:28,359 --> 00:24:32,440 Speaker 1: of other traffic going on, everything from motorbikes to buses 463 00:24:32,880 --> 00:24:37,359 Speaker 1: to billionaires going to play ma jong in a Bentley 464 00:24:37,720 --> 00:24:41,560 Speaker 1: h two people darting in and out of traffic with stuff, 465 00:24:41,880 --> 00:24:44,440 Speaker 1: either moving things or just commuting home or whatever it 466 00:24:44,520 --> 00:24:47,199 Speaker 1: might be. So yeah, it's it's very complicated. I think 467 00:24:47,200 --> 00:24:49,720 Speaker 1: about it's as it's like all edge cases all the 468 00:24:49,760 --> 00:24:51,639 Speaker 1: way down. And it's funny when you said about San 469 00:24:51,640 --> 00:24:55,600 Speaker 1: Francisco is good because as an engineer and Chris Rmson, 470 00:24:56,119 --> 00:24:58,760 Speaker 1: who was part of the early days of Google self 471 00:24:58,800 --> 00:25:01,679 Speaker 1: driving auto prob him and he said, yeah, we were 472 00:25:01,680 --> 00:25:04,600 Speaker 1: doing this in pongo Alto or sorry, in Mountain View rather, 473 00:25:04,720 --> 00:25:07,720 Speaker 1: which is a lower context environment, we might say. And 474 00:25:07,720 --> 00:25:09,520 Speaker 1: he said, but one of the things that our cars 475 00:25:09,560 --> 00:25:12,480 Speaker 1: encountered was a woman in a wheelchair chasing ducks across 476 00:25:12,560 --> 00:25:15,400 Speaker 1: the street with a broom, And he said, no, obviously, 477 00:25:15,440 --> 00:25:18,160 Speaker 1: this isn't something that we've programmed in. We didn't say 478 00:25:18,280 --> 00:25:20,359 Speaker 1: let's sit down and have that Nadie in the wheelchair 479 00:25:20,400 --> 00:25:22,960 Speaker 1: with the broom chasing ducks module. So that doesn't go 480 00:25:23,040 --> 00:25:25,639 Speaker 1: in there. But you need to train train the machine 481 00:25:25,680 --> 00:25:27,119 Speaker 1: on how to respond to it. But I feel like 482 00:25:27,160 --> 00:25:30,080 Speaker 1: Hong Kong in particular would be nothing but that like 483 00:25:30,119 --> 00:25:31,960 Speaker 1: it would it would be. It would be that pretty 484 00:25:32,040 --> 00:25:35,240 Speaker 1: much straight through. And that's probably milder version than let's 485 00:25:35,240 --> 00:25:42,360 Speaker 1: say Jakarta traffic or Negos or Bangkok or Manila. So 486 00:25:43,200 --> 00:25:45,679 Speaker 1: I think about it's like, that's why this is so complicated, 487 00:25:45,760 --> 00:25:49,760 Speaker 1: self driving self driving service automobiles to transfer people around. 488 00:25:49,960 --> 00:25:53,120 Speaker 1: You already see them in early phases in retirement communities 489 00:25:53,160 --> 00:25:55,280 Speaker 1: in the United States, where they make perfect sense. They're 490 00:25:55,359 --> 00:25:59,440 Speaker 1: essentially an automation of a job that already exists, which 491 00:25:59,480 --> 00:26:03,280 Speaker 1: is getting an electric golf cart and go from bingo 492 00:26:03,480 --> 00:26:07,879 Speaker 1: to bed. But Hong Kong will be replacing this full 493 00:26:07,920 --> 00:26:14,840 Speaker 1: stack of very rich and dense signals and possibilities and 494 00:26:14,960 --> 00:26:19,400 Speaker 1: scenarios to be played through Sonat's got to jump off 495 00:26:19,400 --> 00:26:21,040 Speaker 1: for a flight because he's just visiting us right now. 496 00:26:21,040 --> 00:26:22,639 Speaker 1: So I'm going to catch him before he leaves, and 497 00:26:22,640 --> 00:26:25,680 Speaker 1: I'm gonna ask him, as somebody who's trying to create 498 00:26:25,720 --> 00:26:29,480 Speaker 1: a successful podcast, how do you create a successful storyboard 499 00:26:29,520 --> 00:26:33,040 Speaker 1: of original ideas every single week? I can ask this 500 00:26:33,119 --> 00:26:37,840 Speaker 1: question by our more recently arrived colleagues pretty much every week, 501 00:26:37,880 --> 00:26:40,880 Speaker 1: and I say, well, you know, it takes. When they asked, 502 00:26:40,960 --> 00:26:42,680 Speaker 1: usually how long has it taken? I said, well, it takes, 503 00:26:42,720 --> 00:26:45,640 Speaker 1: you know, four or five hours plus a decade. Uh, 504 00:26:45,680 --> 00:26:48,360 Speaker 1: you know, it's the it's the decade part of sort 505 00:26:48,359 --> 00:26:55,320 Speaker 1: of a fairly rich repertory of stuff that you've seen before, 506 00:26:55,920 --> 00:26:58,520 Speaker 1: and essentially doing an interrogation when you see something new, 507 00:26:58,640 --> 00:27:02,280 Speaker 1: is this different enough? Is this different enough to be meaningful? 508 00:27:02,400 --> 00:27:05,240 Speaker 1: Is it also different in a way that's useful? And 509 00:27:05,359 --> 00:27:06,960 Speaker 1: let me see what I can do with it. I 510 00:27:07,000 --> 00:27:09,199 Speaker 1: actually find it very helpful to have the imperative of 511 00:27:09,240 --> 00:27:12,320 Speaker 1: doing something every week, right, And I actually I think 512 00:27:12,320 --> 00:27:13,879 Speaker 1: that that's distinct in a lot of ways from the 513 00:27:13,920 --> 00:27:17,800 Speaker 1: general research process. I have to do something, so that 514 00:27:17,880 --> 00:27:21,040 Speaker 1: means find something that's interesting. A lot of times I 515 00:27:21,080 --> 00:27:23,320 Speaker 1: have a sort of a bad catalog of data sets 516 00:27:23,400 --> 00:27:26,320 Speaker 1: that I know will be useful and they're best when 517 00:27:26,359 --> 00:27:28,760 Speaker 1: they're scarce, their best when they're not things that people 518 00:27:28,760 --> 00:27:30,919 Speaker 1: have seen. This thing I mentioned from the Bank of 519 00:27:30,960 --> 00:27:36,120 Speaker 1: England Credential Regulation Authority, I sincerely doubt that anyone outside 520 00:27:36,119 --> 00:27:39,040 Speaker 1: of the world of insurance or other banking regulators or 521 00:27:39,240 --> 00:27:43,160 Speaker 1: reporters on banking regulation would have looked at and even 522 00:27:43,200 --> 00:27:44,760 Speaker 1: then I don't know that they would have taken the 523 00:27:44,800 --> 00:27:47,639 Speaker 1: angle on it than I did. So the storyboarding for 524 00:27:47,680 --> 00:27:51,440 Speaker 1: me is try to figure out what's first of all, 525 00:27:51,520 --> 00:27:54,520 Speaker 1: what is new, and then is it new enough to 526 00:27:54,640 --> 00:27:58,800 Speaker 1: be useful? Uh? And is it useful enough to be 527 00:27:58,960 --> 00:28:01,560 Speaker 1: sort of durable? When worth telling a story about the 528 00:28:01,680 --> 00:28:06,000 Speaker 1: definition of a patentable good in the United States, something 529 00:28:06,040 --> 00:28:07,520 Speaker 1: for which you can get a patent is it has 530 00:28:07,560 --> 00:28:11,439 Speaker 1: to be novel and non obvious. And I think of 531 00:28:11,480 --> 00:28:13,960 Speaker 1: that as like essentially a pretty good, pretty good background. 532 00:28:13,960 --> 00:28:15,280 Speaker 1: And I don't say that just because Mark and I 533 00:28:15,359 --> 00:28:18,040 Speaker 1: used to work right down the street from the PTO 534 00:28:18,119 --> 00:28:20,560 Speaker 1: of the Trade Office, but no, but that that that's 535 00:28:20,560 --> 00:28:23,159 Speaker 1: actually it for me. And sometimes I have, like I 536 00:28:23,200 --> 00:28:26,000 Speaker 1: do right now, about four or five of them not 537 00:28:26,119 --> 00:28:28,280 Speaker 1: quite in the can, as they say, but more or 538 00:28:28,359 --> 00:28:31,000 Speaker 1: less ready to go. Things that I can load up 539 00:28:31,040 --> 00:28:34,760 Speaker 1: and write while i'm while I'm traveling. Sometimes it's a 540 00:28:34,800 --> 00:28:36,920 Speaker 1: Wednesday night and I have no idea what I'm gonna 541 00:28:36,920 --> 00:28:39,440 Speaker 1: be doing by Thursday morning. But that's that's that's common. 542 00:28:39,560 --> 00:28:42,000 Speaker 1: So you're writing one in the plane today this time, 543 00:28:42,000 --> 00:28:43,720 Speaker 1: I already wrote it, but I'll probably be editing. I'll 544 00:28:43,720 --> 00:28:46,280 Speaker 1: be I'll be editing it. So I'm I'm editing something 545 00:28:46,280 --> 00:28:50,200 Speaker 1: that that That originated from driving to the pool with 546 00:28:50,240 --> 00:28:54,520 Speaker 1: my daughter through one of the worst intersections in the 547 00:28:54,520 --> 00:28:58,400 Speaker 1: world in Washington, d C. Which is the original boundary 548 00:28:58,440 --> 00:29:02,360 Speaker 1: line of Lanfrance City Plan, where it intersects with the 549 00:29:02,360 --> 00:29:05,360 Speaker 1: Windy's and New York Avenue Florida Avenue. A bunch of 550 00:29:05,360 --> 00:29:08,240 Speaker 1: the streets. Mark knows this one. It's dire, it's really awful, 551 00:29:08,280 --> 00:29:09,560 Speaker 1: And there was a there was a man driving a 552 00:29:09,560 --> 00:29:11,440 Speaker 1: convertible stuck in the middle of this traffic, and I 553 00:29:11,480 --> 00:29:16,120 Speaker 1: was wondering, what's a convertible these days? And I thought 554 00:29:16,120 --> 00:29:19,440 Speaker 1: that that's like, this looks really unpleasant, and so that 555 00:29:19,600 --> 00:29:22,040 Speaker 1: was like, hmm, instead of just like leaving that there, 556 00:29:22,960 --> 00:29:25,080 Speaker 1: actually then went into the research was like, how how 557 00:29:25,080 --> 00:29:27,120 Speaker 1: are convertible sales doing in the US? It turns out 558 00:29:27,360 --> 00:29:30,160 Speaker 1: rather poorly. They're shrinking as a percentage of total sales. 559 00:29:30,200 --> 00:29:32,120 Speaker 1: I mean they were never like a lot of total 560 00:29:32,160 --> 00:29:35,240 Speaker 1: sales of cars, but down from just under a percent 561 00:29:35,280 --> 00:29:37,840 Speaker 1: of sales a few years ago to about half a 562 00:29:37,840 --> 00:29:41,640 Speaker 1: percent right now. It's similar diminution in the number of 563 00:29:41,680 --> 00:29:45,160 Speaker 1: models of cars that are being sold. And at the 564 00:29:45,160 --> 00:29:47,320 Speaker 1: same time, ftuvs are are pretty much everything. And then 565 00:29:47,360 --> 00:29:50,440 Speaker 1: the real hook for this was that Volkswagen announced, uh 566 00:29:51,400 --> 00:29:54,160 Speaker 1: two days ago that for the first time since nineteen 567 00:29:54,160 --> 00:29:56,880 Speaker 1: sixty six, it will not be selling station wagons in 568 00:29:56,920 --> 00:29:59,800 Speaker 1: the United States. It just won't be selling them. So 569 00:29:59,840 --> 00:30:03,080 Speaker 1: it's stop the Beetle nen station. The Beetle's gone, the 570 00:30:03,080 --> 00:30:07,440 Speaker 1: the the golf sports wagon, and the all track are gone. 571 00:30:07,600 --> 00:30:09,920 Speaker 1: So the base model b W is gonna be a 572 00:30:09,960 --> 00:30:12,320 Speaker 1: t one. It'll be a tigue. And in fact, they 573 00:30:12,360 --> 00:30:15,400 Speaker 1: it says in the press release it's an SUV world now. 574 00:30:15,560 --> 00:30:18,200 Speaker 1: It sure is right, And I thought, okay, great, but 575 00:30:19,280 --> 00:30:21,280 Speaker 1: you know, that just sort of confirms a prior so 576 00:30:21,400 --> 00:30:23,560 Speaker 1: that we already know that. So I thought about it 577 00:30:23,560 --> 00:30:25,440 Speaker 1: a little bit differently as well. There's all kinds of 578 00:30:25,440 --> 00:30:28,640 Speaker 1: other things that people are now imputing to the car, 579 00:30:29,080 --> 00:30:32,680 Speaker 1: including this fascinating study from Japan by NTT DoCoMo, which 580 00:30:32,760 --> 00:30:35,520 Speaker 1: runs a car sharing service, that people in Japan, because 581 00:30:35,600 --> 00:30:37,720 Speaker 1: cars are actually quite cheap to rent by the hour, 582 00:30:38,120 --> 00:30:40,800 Speaker 1: are renting them to do things like take a nap, 583 00:30:41,840 --> 00:30:45,000 Speaker 1: or practice their English, or change into a Halloween costume, 584 00:30:46,080 --> 00:30:48,840 Speaker 1: or practice a speech or a talk or something like that. 585 00:30:49,680 --> 00:30:51,960 Speaker 1: And this study ends with a great line sid like, 586 00:30:52,040 --> 00:30:54,120 Speaker 1: the car is a private space. And I thought about 587 00:30:54,160 --> 00:30:56,719 Speaker 1: that more. It's like, well, an suv is a private car, 588 00:30:56,800 --> 00:30:59,000 Speaker 1: but it's not a great private space. And in the future, 589 00:30:59,040 --> 00:31:00,880 Speaker 1: if these cars are going to be driving themselves, let's 590 00:31:00,880 --> 00:31:02,920 Speaker 1: say twenty years from now, I don't know that the 591 00:31:03,000 --> 00:31:04,840 Speaker 1: form factor of an suv is what you want. You 592 00:31:04,960 --> 00:31:08,640 Speaker 1: probably want something more like giving room or the original 593 00:31:09,400 --> 00:31:11,960 Speaker 1: Volkswagen camper van. Do you think that's why we see 594 00:31:11,960 --> 00:31:16,560 Speaker 1: all those, you know, the prototype self driving cars. I do. Yeah, 595 00:31:16,600 --> 00:31:20,560 Speaker 1: they yeah, they're they're boxing because you they have another 596 00:31:20,600 --> 00:31:22,320 Speaker 1: element in them which they may not be owned by 597 00:31:22,360 --> 00:31:25,520 Speaker 1: the drivers, so you're less attached to the form factor. 598 00:31:25,640 --> 00:31:28,200 Speaker 1: But it also reminds me of a number of my 599 00:31:28,760 --> 00:31:32,600 Speaker 1: friends in the United States, who mentioned with some chagrin 600 00:31:32,680 --> 00:31:36,240 Speaker 1: at first and then amazement, I bought a Christco Pacifica. 601 00:31:36,600 --> 00:31:38,160 Speaker 1: I bought a real many them. And though like it's 602 00:31:38,240 --> 00:31:42,840 Speaker 1: kind of great like that, actually like the sound system 603 00:31:42,920 --> 00:31:45,040 Speaker 1: is good, I can pack a lot of children in here. 604 00:31:45,480 --> 00:31:47,920 Speaker 1: Like it's not the it's definitely not the most awesome car. 605 00:31:48,080 --> 00:31:51,400 Speaker 1: But I'm a boring named dad anyways. So so there 606 00:31:51,440 --> 00:31:55,080 Speaker 1: you go. For those that want to do more than 607 00:31:55,200 --> 00:31:57,360 Speaker 1: just listen to your interesting stories and would like to 608 00:31:57,640 --> 00:32:00,480 Speaker 1: read them, which actually takes substantially less time investment and 609 00:32:00,600 --> 00:32:04,080 Speaker 1: listening to a podcast it does. Where can people subscribe 610 00:32:04,120 --> 00:32:07,480 Speaker 1: to receive your goodness once a week? So on the 611 00:32:07,600 --> 00:32:09,360 Speaker 1: web you can go to Bloomberg Opinion and there will 612 00:32:09,360 --> 00:32:11,720 Speaker 1: be a list of contributors that I'm there. Go to 613 00:32:11,760 --> 00:32:13,320 Speaker 1: any one of those stories, click on it, and at 614 00:32:13,360 --> 00:32:15,680 Speaker 1: the bottom there will be a link to subscribe, and 615 00:32:15,760 --> 00:32:18,120 Speaker 1: that way you can get it just through whatever email 616 00:32:18,120 --> 00:32:20,400 Speaker 1: and address you would like. And then if you are 617 00:32:20,440 --> 00:32:23,680 Speaker 1: a Bloomberg Professional Service user, then you can go on 618 00:32:23,760 --> 00:32:26,760 Speaker 1: the terminal and I which is the news code, and 619 00:32:26,920 --> 00:32:29,800 Speaker 1: I my surname the U L L A R D. 620 00:32:30,480 --> 00:32:33,000 Speaker 1: You'll see all the stuff I write and then you 621 00:32:33,160 --> 00:32:37,040 Speaker 1: can click on a subscribe button. You may occasionally get 622 00:32:37,040 --> 00:32:40,520 Speaker 1: an update about the President of the St. Louis Federal Reserve, 623 00:32:40,720 --> 00:32:43,560 Speaker 1: James Bullard, in there. You can ignore that that's not me. 624 00:32:44,480 --> 00:32:46,800 Speaker 1: I do find myself all of the time looking at headline. 625 00:32:46,800 --> 00:32:49,920 Speaker 1: It says Bullard says two rate cuts might be within range, 626 00:32:50,200 --> 00:32:53,440 Speaker 1: And I think I don't remember saying that, but I 627 00:32:53,520 --> 00:32:55,520 Speaker 1: agree with that. Yeah, I'm not saying it's wrong. I'm 628 00:32:55,560 --> 00:32:59,640 Speaker 1: just saying I don't remember thinking that. Nat. Thank you 629 00:32:59,800 --> 00:33:05,120 Speaker 1: very much for joining us today. Like folks, bloombergin e 630 00:33:05,200 --> 00:33:07,480 Speaker 1: F is a service provided by Bloomberg Finance LP and 631 00:33:07,520 --> 00:33:10,360 Speaker 1: its affiliates. This recording does not constitute, nor it should 632 00:33:10,360 --> 00:33:13,680 Speaker 1: it be construed as investment advice, investment recommendations, or a 633 00:33:13,760 --> 00:33:17,040 Speaker 1: recommendation as to an investment or other strategy. Bloomberguin e 634 00:33:17,120 --> 00:33:19,800 Speaker 1: F should not be considered as information sufficient upon which 635 00:33:19,880 --> 00:33:23,280 Speaker 1: to base an investment decision. Neither Bloomberg Finance LP nor 636 00:33:23,400 --> 00:33:26,479 Speaker 1: any of its affiliates makes any representation or warranty as 637 00:33:26,560 --> 00:33:29,360 Speaker 1: to the accuracy or completeness of the information contained in 638 00:33:29,400 --> 00:33:31,760 Speaker 1: this recording, and any liability as a result of this 639 00:33:31,840 --> 00:33:33,360 Speaker 1: recording is expressly disclaimed