1 00:00:00,560 --> 00:00:02,759 Speaker 1: This is tomerin ands Reese and you're listening to Switched 2 00:00:02,800 --> 00:00:05,800 Speaker 1: on the podcast brought to you by Bloomberg. Enif nature 3 00:00:05,880 --> 00:00:07,960 Speaker 1: risk is emerging as one of the most complex and 4 00:00:08,080 --> 00:00:12,080 Speaker 1: least understood challenges facing companies today. Unlike climate, which can 5 00:00:12,080 --> 00:00:15,160 Speaker 1: be measured through a single global metric, nature related risks 6 00:00:15,160 --> 00:00:18,439 Speaker 1: span everything from water and biodiversity to waste and pollution, 7 00:00:18,720 --> 00:00:22,280 Speaker 1: and play out very differently across sectors and geographies. Bloomberg's 8 00:00:22,360 --> 00:00:25,119 Speaker 1: new Nature Risk Management Scores attempt to bring structure to 9 00:00:25,160 --> 00:00:28,760 Speaker 1: that complexity, combining company exposure with the actions taken to 10 00:00:28,800 --> 00:00:32,960 Speaker 1: manage those risks. The results reveal a striking disconnect. Firms 11 00:00:32,960 --> 00:00:35,360 Speaker 1: with the highest exposure are not necessarily those doing the 12 00:00:35,400 --> 00:00:37,760 Speaker 1: most to mitigate it. And while progress on climate and 13 00:00:37,760 --> 00:00:42,080 Speaker 1: waste is relatively advanced, engagement on water and biodiversity still lags. 14 00:00:42,520 --> 00:00:44,880 Speaker 1: So how do you measure something as diffuse as nature 15 00:00:44,920 --> 00:00:46,960 Speaker 1: risk and what do those scores tell us about which 16 00:00:47,000 --> 00:00:49,760 Speaker 1: companies are best prepared. On today's show, I'm joined by 17 00:00:49,760 --> 00:00:53,120 Speaker 1: Alistair Purdy, a senior associate from our Nature and Biodiversity team, 18 00:00:53,200 --> 00:00:56,360 Speaker 1: to discuss findings from his note Managing Nature Risk Company 19 00:00:56,440 --> 00:00:59,240 Speaker 1: League Tables be Any of clients can find this note 20 00:00:59,280 --> 00:01:02,440 Speaker 1: and other nature and biodiversity research by heading to BNF 21 00:01:02,480 --> 00:01:05,360 Speaker 1: go on the Bloomberg terminal or BNF dot com. If 22 00:01:05,360 --> 00:01:07,880 Speaker 1: you'd like to learn more about how BNF approaches strategy 23 00:01:07,920 --> 00:01:11,120 Speaker 1: research on the energy transition, including developments in commodity markets, 24 00:01:11,160 --> 00:01:14,080 Speaker 1: trends across different sectors, and the cross cutting technology shaping 25 00:01:14,120 --> 00:01:16,839 Speaker 1: the future, you can find more information on BNF dot com. 26 00:01:16,880 --> 00:01:18,160 Speaker 1: And if you'd like to speak with a member of 27 00:01:18,200 --> 00:01:20,600 Speaker 1: our team about becoming a client, email US at sales 28 00:01:20,640 --> 00:01:23,200 Speaker 1: do BNF at Bloomberg dot net. But for now, let's 29 00:01:23,240 --> 00:01:25,200 Speaker 1: take a closer look at the league tables and how 30 00:01:25,240 --> 00:01:37,440 Speaker 1: the scores come together. Hi Alistair, Welcome to the podcast. 31 00:01:37,640 --> 00:01:39,640 Speaker 2: Hey Tom, nice to be back. Thank you for having me. 32 00:01:40,319 --> 00:01:44,200 Speaker 1: So let's start right at the beginning, because he were 33 00:01:44,240 --> 00:01:47,600 Speaker 1: to talk about nature risk. And when you say those 34 00:01:47,640 --> 00:01:50,880 Speaker 1: words like, all sorts of things come to mind. I mean, 35 00:01:51,080 --> 00:01:54,480 Speaker 1: on one extreme, I have pictures of situations like the 36 00:01:54,560 --> 00:01:57,280 Speaker 1: day of the Triffids where the plants come and take over. 37 00:01:57,920 --> 00:02:01,320 Speaker 1: I'm presuming that's not in scull for the work you've 38 00:02:01,320 --> 00:02:03,880 Speaker 1: been doing. But I also because it is such a 39 00:02:04,560 --> 00:02:07,840 Speaker 1: broad concept, can you talk about what we are talking 40 00:02:07,840 --> 00:02:10,000 Speaker 1: about and in a way like what sits inside and 41 00:02:10,000 --> 00:02:12,400 Speaker 1: outside of nature risk, because I know we've had people 42 00:02:12,400 --> 00:02:14,400 Speaker 1: in the podcast, for example, to amount climate risk as 43 00:02:14,440 --> 00:02:16,320 Speaker 1: climate risk a subset of nature risk, or is it 44 00:02:16,360 --> 00:02:18,800 Speaker 1: something that stands alongside it. They've already trying to try 45 00:02:18,840 --> 00:02:20,880 Speaker 1: and guess what nature risk is. Why can not I 46 00:02:20,880 --> 00:02:22,360 Speaker 1: just let you tell me what nature sure is. 47 00:02:22,360 --> 00:02:23,880 Speaker 2: Sure, of course we've got to cover this at the 48 00:02:23,880 --> 00:02:25,880 Speaker 2: top of the show. And your point on triffids is 49 00:02:25,960 --> 00:02:28,560 Speaker 2: relevant because a part of nature related risk is about 50 00:02:28,560 --> 00:02:31,600 Speaker 2: invasive alien species, but this is less relevant to some 51 00:02:31,639 --> 00:02:33,880 Speaker 2: of the companies that we'll be discussing today. So yeah, 52 00:02:33,960 --> 00:02:36,800 Speaker 2: I'm sure almost the entirety of the audience will be 53 00:02:36,800 --> 00:02:39,520 Speaker 2: familiar with nature as a concept in that it's anything 54 00:02:39,600 --> 00:02:44,040 Speaker 2: non artificial. This comprises living things such as plants, animals, bacteria, 55 00:02:44,200 --> 00:02:46,160 Speaker 2: and so on, as well as non living things. So 56 00:02:46,200 --> 00:02:50,120 Speaker 2: that's materials, water, and the atmosphere. And that atmospheric component 57 00:02:50,240 --> 00:02:52,840 Speaker 2: links closely to what you said about the relationship between 58 00:02:52,840 --> 00:02:55,880 Speaker 2: climate risk and nature risk. Climate risk is a subset 59 00:02:55,960 --> 00:02:59,800 Speaker 2: of broader and nature risk. All economic activity essentially interacts 60 00:02:59,800 --> 00:03:02,560 Speaker 2: with nature to some extent and does so in two 61 00:03:02,560 --> 00:03:06,440 Speaker 2: different ways. Firstly, it depends on natural assets. So natural 62 00:03:06,480 --> 00:03:08,880 Speaker 2: assets are any of these living or non living things 63 00:03:08,960 --> 00:03:12,200 Speaker 2: from which we derive ecosystem services. That's a series of 64 00:03:12,240 --> 00:03:15,200 Speaker 2: benefits just taken from nature. There's a range of different 65 00:03:15,240 --> 00:03:18,240 Speaker 2: dependencies that we may have. For example, a mining company 66 00:03:18,280 --> 00:03:21,200 Speaker 2: extracts materials from the ground. That's known as resource extraction. 67 00:03:21,360 --> 00:03:25,240 Speaker 2: A food company might also extract materials. It requires pollination 68 00:03:25,360 --> 00:03:28,440 Speaker 2: for crops that then become ingredients. It needs water, and 69 00:03:28,480 --> 00:03:31,640 Speaker 2: so on. A financial data services companies such as ours, 70 00:03:31,800 --> 00:03:35,480 Speaker 2: requires energy, water, it requires a stable ground on which 71 00:03:35,520 --> 00:03:38,400 Speaker 2: to build paper, a whole range of different things that 72 00:03:38,480 --> 00:03:41,840 Speaker 2: come from nature. Now, if these underlying natural resources or 73 00:03:41,880 --> 00:03:45,640 Speaker 2: ecosystem services are jeopardized, so too are the company cash 74 00:03:45,680 --> 00:03:49,880 Speaker 2: flows and ultimately the returns of investors and financiers. At 75 00:03:49,920 --> 00:03:53,800 Speaker 2: the same time, however, the companies through their operations impact 76 00:03:54,120 --> 00:03:57,000 Speaker 2: the natural environments and these natural assets that we were 77 00:03:57,040 --> 00:04:00,960 Speaker 2: just talking about. We can also understand this is an 78 00:04:00,960 --> 00:04:05,600 Speaker 2: economy shaped by a variety of different regulations, policies, consumer 79 00:04:05,640 --> 00:04:10,000 Speaker 2: and market expectations, and emerging new technologies. Whenever these things change, 80 00:04:10,120 --> 00:04:14,080 Speaker 2: then we also have a threat presented to company cash flows. Now, 81 00:04:14,120 --> 00:04:16,720 Speaker 2: these two forms of risk, as you know from our 82 00:04:16,760 --> 00:04:19,520 Speaker 2: guests on this podcast talking about climate, are known as 83 00:04:19,560 --> 00:04:22,640 Speaker 2: physical risk where you're dependent on a natural asset that 84 00:04:22,760 --> 00:04:25,880 Speaker 2: might get damaged, and transition risk when the regulations and 85 00:04:25,960 --> 00:04:30,120 Speaker 2: market expectations shift. So nature covering a variety of issues, 86 00:04:30,279 --> 00:04:33,200 Speaker 2: manifests through changes in physical and transition risk. 87 00:04:33,760 --> 00:04:37,440 Speaker 1: So this kind of notion of nature risk, I mean, 88 00:04:37,480 --> 00:04:40,919 Speaker 1: in a certain sense, it has always existed, you know, 89 00:04:41,000 --> 00:04:44,080 Speaker 1: to your point, all the economic activity and I'm assuming 90 00:04:44,080 --> 00:04:48,400 Speaker 1: this goes through the centuries as well, has interacted with nature. 91 00:04:48,720 --> 00:04:51,480 Speaker 1: But I'm pretty sure you know, back in Elizabethan times 92 00:04:51,680 --> 00:04:55,039 Speaker 1: there wasn't an analyst doing nature risk, or maybe there was. 93 00:04:55,120 --> 00:04:57,160 Speaker 1: I mean, is this a new thing or is it 94 00:04:57,240 --> 00:04:59,520 Speaker 1: something that's always been a consideration, But it's kind of 95 00:04:59,520 --> 00:05:01,400 Speaker 1: evol into its current form. 96 00:05:01,839 --> 00:05:04,960 Speaker 2: There would even in a like Victorian times, there would 97 00:05:05,000 --> 00:05:08,160 Speaker 2: have been an analyst assessing say the stag of timber 98 00:05:08,320 --> 00:05:11,920 Speaker 2: that's available for a paper producer. But it's just recently, 99 00:05:11,960 --> 00:05:13,680 Speaker 2: over the last five or six years, we've seen it 100 00:05:13,720 --> 00:05:17,240 Speaker 2: codified differently. And it's when financial institutions start to take 101 00:05:17,360 --> 00:05:20,240 Speaker 2: risk and see this as an actual financial risk both 102 00:05:20,240 --> 00:05:23,320 Speaker 2: to their loan books or equity portfolio. Is that it's 103 00:05:23,400 --> 00:05:26,279 Speaker 2: become much more of a real thing rather than like 104 00:05:26,320 --> 00:05:30,039 Speaker 2: a conceptual tangential thing that people have considered just to 105 00:05:30,160 --> 00:05:33,839 Speaker 2: let's say, look good. Now it's considered as alongside climate 106 00:05:33,880 --> 00:05:34,840 Speaker 2: as classic risk. 107 00:05:35,279 --> 00:05:38,279 Speaker 1: I mean, the reason I asked my question is, you know, 108 00:05:38,320 --> 00:05:39,920 Speaker 1: I was just from to understand I mean. And the 109 00:05:40,760 --> 00:05:43,920 Speaker 1: example use of the sort of the Victorian paper mill 110 00:05:43,960 --> 00:05:47,599 Speaker 1: and the woods is a good one in that there 111 00:05:47,640 --> 00:05:51,239 Speaker 1: there was a very specific dependency to a specific business 112 00:05:51,279 --> 00:05:55,080 Speaker 1: model and their operations, and so of course they were 113 00:05:55,120 --> 00:05:58,000 Speaker 1: considering that. But where I was really coming from is 114 00:05:58,120 --> 00:06:01,359 Speaker 1: our nature risks? Now can spared to say that example? 115 00:06:01,560 --> 00:06:05,600 Speaker 1: Are they recognized as much more universal, impacting a much 116 00:06:05,640 --> 00:06:08,040 Speaker 1: broader range of companies in a lot of ways, less 117 00:06:08,080 --> 00:06:11,360 Speaker 1: directly related to just the local environment, but the broader environment. 118 00:06:11,440 --> 00:06:13,760 Speaker 1: And are they much more severe? And is that why 119 00:06:13,800 --> 00:06:16,000 Speaker 1: it's getting codified in a more serious way. 120 00:06:16,040 --> 00:06:18,520 Speaker 2: Yeah, very much so. So if we look back two 121 00:06:18,560 --> 00:06:20,880 Speaker 2: hundred years or even one hundred years ago, production was 122 00:06:20,960 --> 00:06:24,000 Speaker 2: much more localized. But now that we have global supply chains, 123 00:06:24,080 --> 00:06:26,800 Speaker 2: particularly for the largest of companies, we see a complex 124 00:06:26,880 --> 00:06:30,400 Speaker 2: web of dependencies and indeed impact and these are spread globally, 125 00:06:30,760 --> 00:06:33,320 Speaker 2: So if you're a conglomerate producing a wide range of 126 00:06:33,320 --> 00:06:36,360 Speaker 2: different products, then you source from countries all over the world. 127 00:06:36,640 --> 00:06:38,760 Speaker 2: And as for the extent of that risk or the 128 00:06:38,800 --> 00:06:41,280 Speaker 2: scale of it, it is becoming more severe. We see 129 00:06:41,400 --> 00:06:45,320 Speaker 2: changing climate impacting the stability and availability of many different 130 00:06:45,400 --> 00:06:48,920 Speaker 2: natural resources. I'm sure every audience member here is as 131 00:06:48,960 --> 00:06:52,680 Speaker 2: sort of water stress like difficulties for economic activities that 132 00:06:52,720 --> 00:06:54,920 Speaker 2: depend on some form of fresh water or salt water. 133 00:06:55,839 --> 00:06:59,520 Speaker 2: We've seen an unprecedented decline in the amount of biodiversity, 134 00:06:59,600 --> 00:07:03,480 Speaker 2: which has the stability and resilience of many biophysical systems. 135 00:07:03,760 --> 00:07:07,200 Speaker 2: It's a broad range of issues that are becoming more 136 00:07:07,240 --> 00:07:10,960 Speaker 2: and more at risk that impacts global company operations, and 137 00:07:11,000 --> 00:07:13,000 Speaker 2: so that's why it's become much more of an issue 138 00:07:13,080 --> 00:07:15,440 Speaker 2: for many in the financial sector and as well as 139 00:07:15,440 --> 00:07:16,680 Speaker 2: many large corporates. 140 00:07:17,000 --> 00:07:20,000 Speaker 1: So I hear you on the just that the risks 141 00:07:20,000 --> 00:07:23,360 Speaker 1: are more severe inherently, and then because of the very 142 00:07:23,360 --> 00:07:28,160 Speaker 1: interconnected way global economy works, they are much more wide ranging. 143 00:07:28,520 --> 00:07:31,520 Speaker 1: But to that latter point, I also imagine for you 144 00:07:32,080 --> 00:07:34,840 Speaker 1: as someone who analyzes this stuff, it makes it a 145 00:07:34,840 --> 00:07:38,480 Speaker 1: lot more complicated to analyze which kind of leads me 146 00:07:38,720 --> 00:07:41,400 Speaker 1: to asking you about the work you've been doing. So 147 00:07:41,440 --> 00:07:47,680 Speaker 1: you've published scores rating different organizations on their preparedness for 148 00:07:47,800 --> 00:07:49,680 Speaker 1: nature risks. Can you tell us a little bit more 149 00:07:49,680 --> 00:07:50,360 Speaker 1: about that work. 150 00:07:50,440 --> 00:07:53,320 Speaker 2: Yeah. Absolutely, And one of the things that readers will 151 00:07:53,360 --> 00:07:56,400 Speaker 2: note throughout this report is exactly what you're talking about. 152 00:07:56,520 --> 00:07:59,760 Speaker 2: Nature risk is such a multifaceted threat, so many different 153 00:07:59,760 --> 00:08:02,760 Speaker 2: issues feed into assessment of it. So what we did 154 00:08:02,960 --> 00:08:07,040 Speaker 2: was to firstly, we designed we determined a company universe. 155 00:08:07,400 --> 00:08:10,120 Speaker 2: We chose seven sectors, most GERMANE to B and F 156 00:08:10,200 --> 00:08:14,120 Speaker 2: research and chose the thirty largest companies within them by revenue. 157 00:08:14,280 --> 00:08:17,320 Speaker 2: Then we determined what are the most salient nature related 158 00:08:17,360 --> 00:08:21,040 Speaker 2: issues and we chose four main ones and one supplemental one. 159 00:08:21,200 --> 00:08:24,480 Speaker 2: The four main ones are just done because they conceptually 160 00:08:24,560 --> 00:08:29,280 Speaker 2: make sense. We look at company performance on water, climate change, 161 00:08:29,440 --> 00:08:33,800 Speaker 2: waste and pollution, and biodiversity as a topic. So each 162 00:08:33,840 --> 00:08:37,320 Speaker 2: of those four components that are the high level indicators 163 00:08:37,360 --> 00:08:39,800 Speaker 2: of what companies are doing, and we also supplement it 164 00:08:39,840 --> 00:08:43,280 Speaker 2: with reporting and disclosure. There's a market Lead initiative that 165 00:08:43,360 --> 00:08:47,160 Speaker 2: produces recommendations for companies to report and disclose impacts and 166 00:08:47,200 --> 00:08:50,800 Speaker 2: dependencies as well as analysis of risk and opportunity, and 167 00:08:50,840 --> 00:08:53,960 Speaker 2: the scoring framework breaks down into two main pillars. We've 168 00:08:53,960 --> 00:08:57,000 Speaker 2: got thirty percent of the score coming from exposure, so 169 00:08:57,320 --> 00:09:01,079 Speaker 2: how much revenue is at risk from these and dependencies 170 00:09:01,080 --> 00:09:03,800 Speaker 2: that we talked about earlier. The remaining seventy percent, or 171 00:09:03,840 --> 00:09:07,520 Speaker 2: the majority of the score is company performance and interventions 172 00:09:07,559 --> 00:09:10,440 Speaker 2: relating to these four high level topics. So, based on 173 00:09:10,679 --> 00:09:15,440 Speaker 2: approximately sixty five Bloomberg terminal fields and some additional BNF research, 174 00:09:15,559 --> 00:09:17,920 Speaker 2: we issue level scores that then roll up to a 175 00:09:17,960 --> 00:09:21,040 Speaker 2: single number company score. The ranges from zero to ten, 176 00:09:21,160 --> 00:09:24,240 Speaker 2: with a score of zero meaning you're extraordinarily exposed to 177 00:09:24,800 --> 00:09:27,560 Speaker 2: nature risk and you're doing absolutely nothing to mitigate it, 178 00:09:27,720 --> 00:09:30,760 Speaker 2: whilst your interaction with nature is highly destructive, to ten 179 00:09:30,960 --> 00:09:34,400 Speaker 2: meaning the inverse, you have zero exposure and you're extraordinarily 180 00:09:34,440 --> 00:09:36,800 Speaker 2: brilliant company doing everything to mitigate risk. 181 00:09:37,440 --> 00:09:40,280 Speaker 1: So it's like thirty percent how much of this is 182 00:09:40,280 --> 00:09:43,600 Speaker 1: a problem for you, seventy percent is what you're actually 183 00:09:43,600 --> 00:09:44,200 Speaker 1: doing about it. 184 00:09:44,320 --> 00:09:45,240 Speaker 2: Yes, exactly right. 185 00:09:45,640 --> 00:09:49,360 Speaker 1: And I suppose when you're comparing like two piers in 186 00:09:49,600 --> 00:09:52,640 Speaker 1: the same industry, probably the thirty percent of how much 187 00:09:52,679 --> 00:09:55,080 Speaker 1: of a problem this is for probably quite similar, so 188 00:09:55,120 --> 00:09:58,120 Speaker 1: that seventy percent is the real differentiation. 189 00:09:57,440 --> 00:10:00,520 Speaker 2: Yeah, very much, And we found that across the seven sectors. 190 00:10:00,559 --> 00:10:03,839 Speaker 2: So if, especially if you're a large integrated company, you're 191 00:10:03,960 --> 00:10:06,800 Speaker 2: likely to have exposure across the whole value chain, meaning 192 00:10:06,800 --> 00:10:10,720 Speaker 2: that two such companies in practice will have similar risk exposure. 193 00:10:11,040 --> 00:10:13,280 Speaker 2: So yeah, I think it's best to think of the exposure. 194 00:10:13,280 --> 00:10:16,520 Speaker 2: It's more conceptual thing what kind of industry you're operating, 195 00:10:16,600 --> 00:10:18,800 Speaker 2: what kind of activities are you likely to be doing, 196 00:10:18,840 --> 00:10:21,600 Speaker 2: whereas the interventions a more real world like what's your 197 00:10:21,640 --> 00:10:24,520 Speaker 2: actual performance, what are you committing to? That's where you 198 00:10:24,520 --> 00:10:26,880 Speaker 2: can find much more of a differentiation. Well, so the 199 00:10:26,920 --> 00:10:31,640 Speaker 2: scores are not particularly designed for intersector comparison because there's 200 00:10:31,640 --> 00:10:34,400 Speaker 2: so much peer comparison that feeds into the scores, Like 201 00:10:34,440 --> 00:10:37,319 Speaker 2: it doesn't make too much sense to compare an upstream 202 00:10:37,440 --> 00:10:40,880 Speaker 2: like oil producer with a Tazla, for example, because of 203 00:10:41,080 --> 00:10:44,120 Speaker 2: their waste, their climate impacts will be so different. 204 00:10:44,520 --> 00:10:47,480 Speaker 1: Yeah, I can definitely see that. And just to like 205 00:10:47,640 --> 00:10:51,520 Speaker 1: further understand this because obviously our economy impacts the environment 206 00:10:51,520 --> 00:10:54,520 Speaker 1: and impacts nature and is driving a lot of these risks, 207 00:10:54,520 --> 00:10:57,280 Speaker 1: I think it's fair to say that. And then in turn, 208 00:10:57,440 --> 00:11:01,880 Speaker 1: the economy is exposed to these environmental risks. To what 209 00:11:01,960 --> 00:11:05,920 Speaker 1: extent are we scoring companies on the first part of 210 00:11:05,960 --> 00:11:08,720 Speaker 1: it the degree to which they're contributing to the problem 211 00:11:08,920 --> 00:11:13,760 Speaker 1: versus the degree to which they are exposed versus insulating 212 00:11:13,800 --> 00:11:18,199 Speaker 1: themselves from the resulting challenges. You could, for example, I 213 00:11:18,240 --> 00:11:23,360 Speaker 1: could imagine a company that has a really high emissions 214 00:11:23,400 --> 00:11:29,480 Speaker 1: intensity and is therefore contributing to climate change, but actually 215 00:11:29,720 --> 00:11:32,800 Speaker 1: it is very well protected from all of the physical 216 00:11:32,880 --> 00:11:36,920 Speaker 1: risks it could potentially be exposed to, and so is 217 00:11:37,000 --> 00:11:40,240 Speaker 1: not going to be impacted by climate change in terms 218 00:11:40,240 --> 00:11:42,840 Speaker 1: of its revenues. Like, how would you score a company 219 00:11:42,920 --> 00:11:43,199 Speaker 1: like that? 220 00:11:43,760 --> 00:11:47,280 Speaker 2: So firstly, it's a Muldi stage process. So first it's 221 00:11:47,320 --> 00:11:50,920 Speaker 2: just pure conceptual exposure. How much is the risk likely 222 00:11:51,000 --> 00:11:53,800 Speaker 2: to manifest? Then a secondary tier is what are the 223 00:11:53,920 --> 00:11:56,640 Speaker 2: actual impacts on the company. So we take into account 224 00:11:56,800 --> 00:12:00,440 Speaker 2: the emission's intensity that's a fairly high percis and it 225 00:12:00,480 --> 00:12:03,760 Speaker 2: accounts for about ten percent of the total climate score 226 00:12:03,800 --> 00:12:06,520 Speaker 2: of the company. And then following that there's a range 227 00:12:06,520 --> 00:12:09,720 Speaker 2: of much smaller fields that feed in of secondary importance, 228 00:12:09,800 --> 00:12:12,040 Speaker 2: each of one or two percent each. So we would 229 00:12:12,040 --> 00:12:16,600 Speaker 2: look at say the company pledges for emissions reductions or 230 00:12:16,720 --> 00:12:20,520 Speaker 2: energy efficiency policies, the use of carbon removals and carbon credits. 231 00:12:20,600 --> 00:12:23,040 Speaker 2: Do they have a high level climate change policy? Do 232 00:12:23,120 --> 00:12:27,240 Speaker 2: they assess climate change risks in their state in their filings? 233 00:12:27,320 --> 00:12:30,760 Speaker 2: Do they undertake climate scenario analysis? Do they have Borden 234 00:12:30,880 --> 00:12:34,760 Speaker 2: executive level oversight of climate All of these smaller fields 235 00:12:34,880 --> 00:12:39,720 Speaker 2: are approximately equally weighted collectively to the actual impact of 236 00:12:39,760 --> 00:12:43,960 Speaker 2: the company. And then the separate, slightly lower, lower weighted 237 00:12:44,080 --> 00:12:46,959 Speaker 2: score is the revenue exposure. So all of the things 238 00:12:47,000 --> 00:12:53,880 Speaker 2: feed in and the materiality of each component reflects the impact, 239 00:12:53,960 --> 00:12:56,680 Speaker 2: the actual effect that the company is having through its 240 00:12:56,800 --> 00:12:59,400 Speaker 2: use of this policy or initiative, and to what extent 241 00:12:59,440 --> 00:13:03,559 Speaker 2: it is at damaging the environment I suppose. 242 00:13:03,760 --> 00:13:06,000 Speaker 1: I mean, if I was to simplify what you're saying, 243 00:13:06,080 --> 00:13:07,960 Speaker 1: because I remember at the start you said it, you 244 00:13:08,000 --> 00:13:11,560 Speaker 1: can divide it into sort of physical risk and transition risk, 245 00:13:11,640 --> 00:13:14,160 Speaker 1: which is the sort of changing of regulations. If you 246 00:13:14,200 --> 00:13:16,920 Speaker 1: are damaging the environment, then you're highly at risk of 247 00:13:17,360 --> 00:13:21,280 Speaker 1: regulations coming in and not being prepared for that change. 248 00:13:21,559 --> 00:13:24,760 Speaker 2: Yeah, if you're a highly destructive company, then you're exposed 249 00:13:24,760 --> 00:13:28,400 Speaker 2: to both physical and transition risk. I would contend So 250 00:13:28,640 --> 00:13:31,319 Speaker 2: in order to be highly destructive, you have to interact 251 00:13:31,520 --> 00:13:35,120 Speaker 2: extensively with the natural environment. So by extension, you will 252 00:13:35,120 --> 00:13:38,319 Speaker 2: have big dependencies. But it's also these impacts that will 253 00:13:38,360 --> 00:13:40,960 Speaker 2: put you at risk, will leave you open to transition risk. 254 00:13:41,280 --> 00:13:43,360 Speaker 1: Got it. So I'm going to ask you about your 255 00:13:43,400 --> 00:13:46,480 Speaker 1: findings before we dive into it. Just I think you 256 00:13:46,559 --> 00:13:49,360 Speaker 1: mentioned that you looked at the sectors that were I 257 00:13:49,360 --> 00:13:51,800 Speaker 1: believe the word to us was jermaine great word. You 258 00:13:51,880 --> 00:13:53,559 Speaker 1: were most Germane to be any if I'm going to 259 00:13:53,600 --> 00:13:55,360 Speaker 1: try and find excuses to use that stay. 260 00:13:56,760 --> 00:14:00,559 Speaker 2: So what were those sectors? So, yeah, we looked primarily 261 00:14:01,000 --> 00:14:04,400 Speaker 2: at sectors where we have deep expertise at BNF, as 262 00:14:04,400 --> 00:14:07,520 Speaker 2: well as the most destructive sectors because they're the ones 263 00:14:07,559 --> 00:14:11,040 Speaker 2: that present the greatest threat to the financial component of 264 00:14:11,040 --> 00:14:13,360 Speaker 2: the economy, as well as the places where you can 265 00:14:13,360 --> 00:14:16,280 Speaker 2: find the biggest opportunity for change. There's more to be done, 266 00:14:16,360 --> 00:14:19,280 Speaker 2: So we looked at oil and gas, both upstream and downstream. 267 00:14:19,360 --> 00:14:21,680 Speaker 2: We looked at the biggest metals and mining firms as 268 00:14:21,680 --> 00:14:25,080 Speaker 2: well as chemical firms. We looked at automakers covering both 269 00:14:25,120 --> 00:14:28,720 Speaker 2: traditional ice vehicles and evs. We looked at big technology 270 00:14:28,760 --> 00:14:33,080 Speaker 2: firms spanning chip manufacturers, data centers and other things, BNF 271 00:14:33,160 --> 00:14:36,600 Speaker 2: Classic power utilities, and then one of BNF's new teams, 272 00:14:36,800 --> 00:14:39,720 Speaker 2: the food and agriculture sector. So we've got a broad 273 00:14:39,800 --> 00:14:43,760 Speaker 2: range of coverage to reflect the diversity of activities, and 274 00:14:43,800 --> 00:14:46,400 Speaker 2: there's also pretty broad geographical coverage here as well. 275 00:14:46,800 --> 00:14:49,040 Speaker 1: So let's go on to your findings. I'm going to 276 00:14:49,440 --> 00:14:53,200 Speaker 1: kind of preempt your answer by just making an observation 277 00:14:53,920 --> 00:14:57,560 Speaker 1: that you condensed everything you're saying down into a score 278 00:14:57,600 --> 00:15:00,000 Speaker 1: out of ten, and nobody got higher than a ste 279 00:15:02,080 --> 00:15:05,120 Speaker 1: So I don't know if you're like the Simon Cowell 280 00:15:05,200 --> 00:15:08,520 Speaker 1: of nature risk or what, but just tell us a 281 00:15:08,520 --> 00:15:10,200 Speaker 1: little bit about that to start with. 282 00:15:10,440 --> 00:15:13,720 Speaker 2: Sure, so we alluded to this like briefly before, it's 283 00:15:13,760 --> 00:15:16,800 Speaker 2: almost impossible for a company to get an extremely high score, 284 00:15:16,880 --> 00:15:19,040 Speaker 2: especially in the kind of sectors that we were looking at, 285 00:15:19,120 --> 00:15:21,240 Speaker 2: because if you remember, thirty percent of the score is 286 00:15:21,320 --> 00:15:26,120 Speaker 2: revenue exposure to the most impactful or that highest dependency 287 00:15:26,920 --> 00:15:30,840 Speaker 2: related activities. So regardless of what you do as say 288 00:15:31,000 --> 00:15:33,400 Speaker 2: an upstream oil producer, and no matter how brilliant your 289 00:15:33,400 --> 00:15:37,520 Speaker 2: climate policy, no matter how extraordinary your biodiversity risk mitigation 290 00:15:37,680 --> 00:15:40,000 Speaker 2: you're still going to have revenue exposure, and that's going 291 00:15:40,000 --> 00:15:42,280 Speaker 2: to bring down your score at least one or two points. 292 00:15:42,520 --> 00:15:45,960 Speaker 2: So we would say an upper bound for all of 293 00:15:45,960 --> 00:15:48,440 Speaker 2: these companies is likely going to be a seven. If 294 00:15:48,480 --> 00:15:51,160 Speaker 2: you hit everything perfectly and outperform your peers on your 295 00:15:51,200 --> 00:15:55,160 Speaker 2: actual impact, then seven's the best we found. Their Spanish 296 00:15:55,280 --> 00:15:58,920 Speaker 2: electric utility Abatrolla, was the sole company among the two 297 00:15:59,000 --> 00:16:01,440 Speaker 2: hundred and ten to it a score of six or above, 298 00:16:01,560 --> 00:16:04,040 Speaker 2: and it did so by in our in our judgment, 299 00:16:04,320 --> 00:16:07,560 Speaker 2: very strong performance across all four of those main issues 300 00:16:07,560 --> 00:16:10,880 Speaker 2: that we discussed, as well as commitment to and publishing 301 00:16:10,920 --> 00:16:14,520 Speaker 2: of a Task Force on Nature Aid Financial Disclosures Report. 302 00:16:14,840 --> 00:16:17,600 Speaker 2: So six in this context extraordinarily high. 303 00:16:18,000 --> 00:16:20,520 Speaker 1: So to get higher than that, really you'd have to 304 00:16:20,560 --> 00:16:22,360 Speaker 1: be I don't know. Maybe if you were doing this 305 00:16:22,520 --> 00:16:26,640 Speaker 1: for finance, if we're talking about big industries, then perhaps 306 00:16:26,640 --> 00:16:29,040 Speaker 1: it would be possible to get higher. It would if 307 00:16:29,040 --> 00:16:31,600 Speaker 1: you had a particular investment strategy, because what we're doing 308 00:16:31,720 --> 00:16:34,320 Speaker 1: is so flexible in finance in terms of what. 309 00:16:34,240 --> 00:16:37,120 Speaker 2: Industries are exposed to very much and the direct the 310 00:16:37,240 --> 00:16:40,200 Speaker 2: direct operations of the financial sector will be much less. 311 00:16:40,680 --> 00:16:44,000 Speaker 2: The impacts and dependencies, So you have like tangential or 312 00:16:44,040 --> 00:16:49,320 Speaker 2: indirect dependencies versus like the primary economic activities of many 313 00:16:49,360 --> 00:16:51,920 Speaker 2: of these sectors with much higher impacts and dependencies. 314 00:16:52,200 --> 00:16:56,480 Speaker 1: Got it. So, whilst it's striking that nobody got better 315 00:16:56,480 --> 00:16:58,440 Speaker 1: than a six in this report, it's maybe just a 316 00:16:58,440 --> 00:17:01,560 Speaker 1: reflection of the real truly half glass full about this, 317 00:17:01,680 --> 00:17:04,520 Speaker 1: because six out of ten is six out of ten, 318 00:17:04,880 --> 00:17:07,919 Speaker 1: But it's just a real reflection of the challenges that 319 00:17:07,960 --> 00:17:08,800 Speaker 1: these sectors face. 320 00:17:08,880 --> 00:17:11,840 Speaker 2: Absolutely, and that's part of the intention behind the scores. 321 00:17:12,040 --> 00:17:15,280 Speaker 2: We want to capture that these companies, regardless of what 322 00:17:15,320 --> 00:17:17,760 Speaker 2: they do, still have very high exposure and a score 323 00:17:17,800 --> 00:17:20,000 Speaker 2: above five, say, just means they're doing a good job 324 00:17:20,160 --> 00:17:23,000 Speaker 2: managing those very risks. For Abadola to do better, it 325 00:17:23,040 --> 00:17:26,399 Speaker 2: would have to implement policies that are not connected or 326 00:17:26,400 --> 00:17:29,159 Speaker 2: not material to the areas of operations that it's in, 327 00:17:29,359 --> 00:17:32,200 Speaker 2: Like why would Abigolla have a commitment to reduce pesticides, 328 00:17:32,240 --> 00:17:34,800 Speaker 2: for example? But that does that does that kind of 329 00:17:34,800 --> 00:17:37,800 Speaker 2: feel does feed into this generalized score, got it. 330 00:17:37,840 --> 00:17:40,200 Speaker 1: So it's kind of like for some of these companies 331 00:17:40,200 --> 00:17:42,159 Speaker 1: to get a higher score, they would have to just 332 00:17:42,200 --> 00:17:45,080 Speaker 1: become a different company exactly. That's why we're going to 333 00:17:45,200 --> 00:17:46,679 Speaker 1: have to start doing something different. 334 00:17:46,760 --> 00:17:49,760 Speaker 2: Yeah. For for example, for BP to excel, it would 335 00:17:49,840 --> 00:17:51,840 Speaker 2: just have to leave the oil and gas industry, which 336 00:17:51,880 --> 00:17:54,119 Speaker 2: is obviously not going to happen. So it's it's just 337 00:17:54,480 --> 00:17:57,680 Speaker 2: the absolute value of the score is not necessarily important. 338 00:17:57,720 --> 00:18:00,360 Speaker 2: So a company shouldn't be disheartened if it's going five 339 00:18:00,359 --> 00:18:03,280 Speaker 2: point five. Rather, it should look at its efforts be 340 00:18:03,400 --> 00:18:05,800 Speaker 2: and feel good that it's well ahead of peers who 341 00:18:05,840 --> 00:18:07,680 Speaker 2: scored say two or two point five. 342 00:18:08,200 --> 00:18:10,280 Speaker 1: Was there anyone who came out with zero in all 343 00:18:10,320 --> 00:18:12,160 Speaker 1: of this, Is it possible to get a score that low? 344 00:18:12,359 --> 00:18:15,280 Speaker 2: It's it's unlikely because a big component of the scores 345 00:18:15,359 --> 00:18:19,560 Speaker 2: is relative performance to peers. So if you're significantly more 346 00:18:19,600 --> 00:18:22,960 Speaker 2: destructive in terms of emissions, the amount of waste that 347 00:18:23,000 --> 00:18:25,320 Speaker 2: you generate, the amount of water that you use, and 348 00:18:25,400 --> 00:18:28,520 Speaker 2: you also have zero policies to mitigate, yes you could 349 00:18:28,560 --> 00:18:31,320 Speaker 2: get a zero. But within these sectors, there's always going 350 00:18:31,400 --> 00:18:34,080 Speaker 2: to be one company that does much worse in terms 351 00:18:34,119 --> 00:18:37,280 Speaker 2: of its relative emissions or relative waste, and that's going 352 00:18:37,359 --> 00:18:40,080 Speaker 2: to make you look relatively good. I think if we 353 00:18:40,160 --> 00:18:43,199 Speaker 2: feed all of these attributes into the algorithm, then it 354 00:18:43,240 --> 00:18:45,480 Speaker 2: will output like the lowest possible score of one. 355 00:18:46,520 --> 00:18:48,879 Speaker 1: I'm kind of curious to know. I mean, I mean, 356 00:18:48,960 --> 00:18:50,959 Speaker 1: a simple question I could ask you is, you know, 357 00:18:51,000 --> 00:18:54,359 Speaker 1: how do the sectors that we looked at compared to 358 00:18:54,440 --> 00:18:57,159 Speaker 1: each other? You know, but to all of the previous conversations, 359 00:18:57,240 --> 00:18:59,879 Speaker 1: some of the score is kind of the nature of 360 00:18:59,880 --> 00:19:02,240 Speaker 1: the particular sector itself. So I know, you say, like, 361 00:19:02,280 --> 00:19:05,080 Speaker 1: all of these companies will find it challenging, but I'm 362 00:19:05,119 --> 00:19:08,480 Speaker 1: guessing it's different for like an oil and gas company 363 00:19:08,560 --> 00:19:10,720 Speaker 1: versus a utility, you know, in terms of what you 364 00:19:10,760 --> 00:19:13,520 Speaker 1: can realistically expect them to score. So I mean, maybe 365 00:19:13,520 --> 00:19:15,240 Speaker 1: I am going to ask that question, But I would 366 00:19:15,240 --> 00:19:17,480 Speaker 1: also just like to add maybe a bit of a twist. 367 00:19:18,160 --> 00:19:22,520 Speaker 1: Were there any sectors that stood out for overall doing 368 00:19:23,280 --> 00:19:26,440 Speaker 1: more with the cards they've been Dell, if you see 369 00:19:26,440 --> 00:19:29,320 Speaker 1: what I mean where you're saying, sing, maybe more proactive 370 00:19:30,119 --> 00:19:33,240 Speaker 1: activities to mitigate the risk maybe compared to what you 371 00:19:33,280 --> 00:19:36,480 Speaker 1: would expect if you're just looking at inherently what they're doing. 372 00:19:36,720 --> 00:19:39,240 Speaker 2: Yeah, yeah, it does make sense. So there are still 373 00:19:39,320 --> 00:19:42,280 Speaker 2: some components that we can score. When we average out 374 00:19:42,320 --> 00:19:45,280 Speaker 2: the differences in peer comparison, we're still left with the 375 00:19:45,359 --> 00:19:49,119 Speaker 2: absolute binaries of do you have a commitment to reduce 376 00:19:49,119 --> 00:19:52,000 Speaker 2: emissions for example. So looking at that we can see 377 00:19:52,000 --> 00:19:55,760 Speaker 2: some sectors slightly further ahead, and bearing in mind exposure 378 00:19:55,800 --> 00:19:58,640 Speaker 2: to the natural aid impacts and dependencies too, we see 379 00:19:58,640 --> 00:20:02,320 Speaker 2: that automakers are a slightly ahead on average in terms 380 00:20:02,359 --> 00:20:05,400 Speaker 2: of score relative to the other sectors. The lowest performing 381 00:20:05,400 --> 00:20:08,080 Speaker 2: sectors were power utilities and metals and mining. They have 382 00:20:08,119 --> 00:20:11,440 Speaker 2: extraordinarily high exposure to the risks and tend to do 383 00:20:11,600 --> 00:20:14,600 Speaker 2: less than the other industries, especially on thems such as 384 00:20:14,680 --> 00:20:17,600 Speaker 2: water and biodiversity. That being said, the mouths and mining 385 00:20:17,600 --> 00:20:20,480 Speaker 2: industry is a bit ahead in terms of its disclosure. 386 00:20:20,720 --> 00:20:24,320 Speaker 2: An industry initiative came together and encouraged and worked with 387 00:20:24,560 --> 00:20:28,000 Speaker 2: the members to do TNFT related reporting, so it is 388 00:20:28,040 --> 00:20:30,760 Speaker 2: doing some good stuff, which is unfortunately, on average a 389 00:20:30,800 --> 00:20:34,080 Speaker 2: company is less likely to have a water reuse and 390 00:20:34,160 --> 00:20:37,399 Speaker 2: recycling program than it might in the water making sector. 391 00:20:37,960 --> 00:20:40,840 Speaker 1: I think the thing that's really fascinating to me is 392 00:20:40,920 --> 00:20:45,320 Speaker 1: that you power utilities are, in the kind of the 393 00:20:45,359 --> 00:20:47,919 Speaker 1: framing of this question, are doing less than oil and 394 00:20:47,960 --> 00:20:50,840 Speaker 1: gas companies because oil and gas is at least in 395 00:20:50,920 --> 00:20:57,000 Speaker 1: terms of climate exposure, A inherently more polluting industry, and also, 396 00:20:57,119 --> 00:20:59,159 Speaker 1: if you think about it in just in terms of 397 00:20:59,200 --> 00:21:01,760 Speaker 1: the sort of the now, narratives, may be culturally more 398 00:21:01,800 --> 00:21:04,160 Speaker 1: resistant to accepting that some of these things are an issue. 399 00:21:04,200 --> 00:21:07,800 Speaker 1: Whereas power utilities are both rooted in fossil fuels but 400 00:21:07,960 --> 00:21:11,720 Speaker 1: also have the opportunity to be the driving force behind 401 00:21:11,920 --> 00:21:15,399 Speaker 1: the reduction of emissions across the economy. So they have 402 00:21:15,760 --> 00:21:18,760 Speaker 1: a lot more rope to work with, if you see 403 00:21:18,800 --> 00:21:21,800 Speaker 1: what I mean, and more opportunity to score better. So 404 00:21:21,920 --> 00:21:25,240 Speaker 1: why is it that they are doing worse than oil 405 00:21:25,240 --> 00:21:27,080 Speaker 1: and gas companies? According to this. 406 00:21:27,119 --> 00:21:31,959 Speaker 2: Scoring, it's primarily due to investor pressure or The largest 407 00:21:32,000 --> 00:21:35,240 Speaker 2: oil and gas companies are extremely well known public companies 408 00:21:35,280 --> 00:21:38,160 Speaker 2: with big brand images. Everyone has heard of the top 409 00:21:38,200 --> 00:21:41,000 Speaker 2: fifteen or twenty oil and gas companies globally, so they've 410 00:21:41,040 --> 00:21:45,000 Speaker 2: faced years of pressure on their biodiversity impact, their climate impact, 411 00:21:45,119 --> 00:21:47,560 Speaker 2: how much water they're using, and as a result they've 412 00:21:47,840 --> 00:21:51,480 Speaker 2: marginally improved. They've got policies now covering all of these 413 00:21:51,520 --> 00:21:55,000 Speaker 2: things and include them in their annual disclosures. That has 414 00:21:55,040 --> 00:21:57,720 Speaker 2: accounted for an increase in their overall scorer. Is a 415 00:21:57,760 --> 00:22:01,439 Speaker 2: group power utilities, however, on apridge are less familiar to 416 00:22:01,480 --> 00:22:04,080 Speaker 2: the average consumer and face less pressure. If you look 417 00:22:04,119 --> 00:22:06,560 Speaker 2: through the list of the thirty largest power utilities that 418 00:22:06,600 --> 00:22:09,520 Speaker 2: we've covered, they haven't come under this sustained pressure that 419 00:22:09,560 --> 00:22:11,800 Speaker 2: the oil and gas majors have and therefore have done 420 00:22:11,840 --> 00:22:15,000 Speaker 2: slightly less. Of course, among that, there are still individual 421 00:22:15,080 --> 00:22:18,119 Speaker 2: utilities that are doing extremely well, such as Abadrola that 422 00:22:18,160 --> 00:22:20,919 Speaker 2: we mentioned earlier, But on average it's as a sector 423 00:22:21,119 --> 00:22:22,760 Speaker 2: behind that's interesting. 424 00:22:22,880 --> 00:22:26,120 Speaker 1: So, I mean, a lot of utilities are regulated monopolies, 425 00:22:26,480 --> 00:22:30,800 Speaker 1: so they don't face any consumer pressure and they don't 426 00:22:30,840 --> 00:22:34,680 Speaker 1: accept they're not exposed to the same financial pressure as 427 00:22:34,680 --> 00:22:36,840 Speaker 1: all of these oil and gas gas companies that are 428 00:22:36,960 --> 00:22:39,000 Speaker 1: out in the world having to compete with each other 429 00:22:39,240 --> 00:22:43,720 Speaker 1: both for capital and for customers. Now it's debatable to 430 00:22:43,760 --> 00:22:47,200 Speaker 1: the degrees to which customers choose one brand of gasoline 431 00:22:47,240 --> 00:22:50,040 Speaker 1: over another based on the green credentials of a company. 432 00:22:50,160 --> 00:22:53,480 Speaker 1: But still it seems like what I'm hearing here is 433 00:22:53,600 --> 00:22:59,960 Speaker 1: that being exposed to other industries and their priorities forces change. 434 00:23:00,280 --> 00:23:04,320 Speaker 1: Maybe where perhaps power utilities, a lot of them I'm 435 00:23:04,320 --> 00:23:07,200 Speaker 1: not I mean the power utilities. They're all regulated monopolies, 436 00:23:07,480 --> 00:23:09,879 Speaker 1: of course, but there may be a little bit more 437 00:23:10,320 --> 00:23:13,879 Speaker 1: protected from the pressure to change. 438 00:23:13,920 --> 00:23:17,560 Speaker 2: Absolutely, if you're a regulated monopoly, what your incentive to 439 00:23:17,640 --> 00:23:20,960 Speaker 2: do better, Your pursuit of capital is far less dependent 440 00:23:21,000 --> 00:23:23,879 Speaker 2: on showing what good you do versus how entrensed you 441 00:23:23,920 --> 00:23:24,560 Speaker 2: are in the market. 442 00:23:24,920 --> 00:23:28,240 Speaker 1: Yeah, I mean, the only thing that will really make 443 00:23:28,240 --> 00:23:29,399 Speaker 1: you change is the regulator. 444 00:23:29,600 --> 00:23:33,240 Speaker 2: And you know, regulators have got different concerns right now 445 00:23:33,240 --> 00:23:35,679 Speaker 2: than water use. Although the contention of us is that 446 00:23:35,760 --> 00:23:37,800 Speaker 2: will become a much more material thing in the next 447 00:23:38,080 --> 00:23:39,240 Speaker 2: ten to twenty years. 448 00:23:39,400 --> 00:23:41,159 Speaker 1: So actually that kind of leads me on to the 449 00:23:42,080 --> 00:23:44,960 Speaker 1: sort of the next kind of maybe angle I want 450 00:23:44,960 --> 00:23:46,480 Speaker 1: to tackle this from, because we've talked a little bit 451 00:23:46,480 --> 00:23:49,800 Speaker 1: about how different industries compare. But there were these fundamental 452 00:23:49,920 --> 00:23:54,440 Speaker 1: risk brackets buimets, water and biodiverse. 453 00:23:53,880 --> 00:23:55,800 Speaker 2: And that right, and the fourth is waste and pollution. 454 00:23:56,040 --> 00:23:59,560 Speaker 1: Waste and pollution. So can you just talk talk us 455 00:23:59,560 --> 00:24:01,920 Speaker 1: through a little little bit about what your findings really 456 00:24:01,960 --> 00:24:05,719 Speaker 1: revealed on the risk exposure to those four different types 457 00:24:05,760 --> 00:24:06,560 Speaker 1: of nature risk. 458 00:24:07,000 --> 00:24:10,440 Speaker 2: Yeah. So on the exposure side, we found that all 459 00:24:11,000 --> 00:24:15,159 Speaker 2: of these companies, across all of these sectors are extremely 460 00:24:15,280 --> 00:24:19,840 Speaker 2: dependent on something called energy provisioning ecosystem services, and that essentially, 461 00:24:20,119 --> 00:24:21,200 Speaker 2: if you're in let's. 462 00:24:21,080 --> 00:24:25,280 Speaker 1: Say that again slo energy provisioning ecosystem services. 463 00:24:25,359 --> 00:24:26,160 Speaker 2: Yeah, that's right. 464 00:24:26,400 --> 00:24:28,680 Speaker 1: So that just means that trying to bring that, I'm 465 00:24:28,720 --> 00:24:30,760 Speaker 1: just trying to use that in a sentence today as 466 00:24:31,320 --> 00:24:32,560 Speaker 1: along with remain. 467 00:24:32,320 --> 00:24:34,880 Speaker 2: It's yeah, all of these, all of these sectors are 468 00:24:35,280 --> 00:24:40,320 Speaker 2: highly exposed to energy provisioning ecosystem services. That essentially means 469 00:24:40,440 --> 00:24:43,760 Speaker 2: nature gives energy that companies harness and used to power 470 00:24:43,800 --> 00:24:47,000 Speaker 2: their operations. That's very unsurprising. But we also find that 471 00:24:47,280 --> 00:24:50,800 Speaker 2: water use exposure is very high as well. And for example, 472 00:24:50,840 --> 00:24:54,199 Speaker 2: in metals and mining, water is essential essential part of 473 00:24:54,240 --> 00:24:57,840 Speaker 2: the production process in the upstream mining. It's also key 474 00:24:57,880 --> 00:25:01,720 Speaker 2: in oil and gas production. These use extraordinary volumes of 475 00:25:01,760 --> 00:25:04,440 Speaker 2: water in the production, and this is true downstream as well. 476 00:25:04,520 --> 00:25:06,520 Speaker 2: The refining uses a large amount of water for a 477 00:25:06,640 --> 00:25:12,200 Speaker 2: variety of different processes. These dependencies then translate into how 478 00:25:12,280 --> 00:25:15,280 Speaker 2: much water are the companies actually using, and we can 479 00:25:15,320 --> 00:25:18,680 Speaker 2: see that typically in each industry, one or two companies 480 00:25:18,720 --> 00:25:21,280 Speaker 2: are using far more than others, and that again is 481 00:25:21,320 --> 00:25:24,520 Speaker 2: for a variety of different reasons. The same is also 482 00:25:24,560 --> 00:25:27,480 Speaker 2: true on emissions. We see one or two companies that 483 00:25:27,520 --> 00:25:30,720 Speaker 2: are far far ahead on their relative emissions intensity. So 484 00:25:30,920 --> 00:25:33,639 Speaker 2: in short, all of these industries are very highly exposed 485 00:25:33,720 --> 00:25:36,600 Speaker 2: to all of these issues. But it's the performance of 486 00:25:36,600 --> 00:25:39,679 Speaker 2: one or two companies that is significantly behind the others 487 00:25:39,760 --> 00:25:42,200 Speaker 2: that leads to overall average score changes. 488 00:25:43,200 --> 00:25:45,560 Speaker 1: So let me just make sure I've understood what you've 489 00:25:45,600 --> 00:25:50,840 Speaker 1: just said. So across climber, water, biodiversity, and waste, they're 490 00:25:50,880 --> 00:25:54,080 Speaker 1: all exposed, and that's why you chose those pillars, I guess. 491 00:25:54,240 --> 00:25:57,080 Speaker 1: But it's you mentioned that there's some that are doing 492 00:25:57,359 --> 00:26:00,960 Speaker 1: significantly better and some are doing significantly worse, and in particular, 493 00:26:01,040 --> 00:26:03,080 Speaker 1: water seems to be an area of differentiation. 494 00:26:03,560 --> 00:26:08,879 Speaker 2: Yeah, this relatively fewer fields feed into the overall water score. 495 00:26:09,200 --> 00:26:11,960 Speaker 2: One of the primary things that we found was a 496 00:26:12,040 --> 00:26:15,200 Speaker 2: lack of disclosure on water use from many companies. Generally, 497 00:26:15,520 --> 00:26:19,040 Speaker 2: the larger European companies from all of these seven sectors 498 00:26:19,040 --> 00:26:21,880 Speaker 2: were quite good at disclosing their water use. This includes 499 00:26:21,920 --> 00:26:24,240 Speaker 2: both the amount of water that they take out and 500 00:26:24,400 --> 00:26:26,520 Speaker 2: the amount of water that they consume, so that's the 501 00:26:26,560 --> 00:26:29,560 Speaker 2: amount of water you take out versus minus the amount 502 00:26:29,600 --> 00:26:34,520 Speaker 2: that you return and water consumption. However, many East and 503 00:26:34,640 --> 00:26:39,160 Speaker 2: South Asian economies were much less successful in their disclosure, 504 00:26:39,240 --> 00:26:42,680 Speaker 2: much less comprehensive. Many firms from China or India had 505 00:26:42,760 --> 00:26:46,840 Speaker 2: almost no disclosures on anything water related. They would typically 506 00:26:46,880 --> 00:26:50,040 Speaker 2: have a high level water policy where they mentioned water 507 00:26:50,280 --> 00:26:53,000 Speaker 2: in their filings, but they don't go beyond this. They 508 00:26:53,000 --> 00:26:55,840 Speaker 2: don't discuss a water use and protection plan. They don't 509 00:26:55,840 --> 00:26:59,439 Speaker 2: disclose the amount of emissions to water, essentially water pollution 510 00:26:59,520 --> 00:27:02,920 Speaker 2: that they have. We also examine them percentage of assets 511 00:27:02,960 --> 00:27:05,760 Speaker 2: and areas of high or very high water stress, and 512 00:27:05,800 --> 00:27:09,160 Speaker 2: typically we found the companies with more assets and aario 513 00:27:09,440 --> 00:27:12,000 Speaker 2: areas of high stress, we're doing less in terms of 514 00:27:12,080 --> 00:27:15,119 Speaker 2: the policies and interventions that they have to mitigate risks 515 00:27:15,160 --> 00:27:15,919 Speaker 2: that result. 516 00:27:16,320 --> 00:27:19,960 Speaker 1: This is so interesting that we're talking about these four 517 00:27:20,000 --> 00:27:23,440 Speaker 1: pillars kind of equally, because I mean a b EF 518 00:27:23,880 --> 00:27:28,520 Speaker 1: being an energy analysis company in particular, one whose starting 519 00:27:28,560 --> 00:27:31,280 Speaker 1: point was thinking about clean energy and the issue of 520 00:27:31,320 --> 00:27:35,200 Speaker 1: climate change. We've always been very focused on greenhouse gas 521 00:27:35,240 --> 00:27:38,320 Speaker 1: emissions and the impact of climate and I think that 522 00:27:38,320 --> 00:27:40,520 Speaker 1: that is fair to say that that is in most 523 00:27:40,600 --> 00:27:45,840 Speaker 1: people's perception of the challenges we're facing environmentally. That's the 524 00:27:46,000 --> 00:27:48,800 Speaker 1: thing that it comes kind of front of mind, and 525 00:27:49,280 --> 00:27:54,800 Speaker 1: stuff like water biodiversity are waste management maybe been, and 526 00:27:54,920 --> 00:27:59,000 Speaker 1: I might just be my biases here sort of secondary concerns, 527 00:27:59,080 --> 00:28:02,200 Speaker 1: like the real alarm has been around climate, Like COP 528 00:28:02,400 --> 00:28:03,920 Speaker 1: is all about climate. I don't know if there's something 529 00:28:03,920 --> 00:28:06,840 Speaker 1: equivalent for water. I know that there's a biodiversity COP, 530 00:28:06,920 --> 00:28:10,320 Speaker 1: but those other forms of nature risks seem to have 531 00:28:10,440 --> 00:28:13,760 Speaker 1: been rising up the agenda and rising up the consciousness. 532 00:28:14,080 --> 00:28:15,840 Speaker 1: It's I mean, firstly, do you think that, like what 533 00:28:15,960 --> 00:28:19,720 Speaker 1: I'm saying, my perception is kind of mirrors what you're 534 00:28:19,760 --> 00:28:22,720 Speaker 1: observing more generally, And if it is, why is it changing? 535 00:28:23,119 --> 00:28:25,760 Speaker 2: Yeah? Absolutely, That's what I first thought when I joined 536 00:28:25,840 --> 00:28:28,399 Speaker 2: bn F and this this this role was created to 537 00:28:28,400 --> 00:28:31,120 Speaker 2: look more at nature, but it's a parallel to what's 538 00:28:31,119 --> 00:28:33,800 Speaker 2: going on in climates. BNF has got very strong team 539 00:28:33,880 --> 00:28:36,679 Speaker 2: looking at climate the risks and opportunities both in the 540 00:28:36,680 --> 00:28:40,080 Speaker 2: real economy and financial sector, and the same risks and 541 00:28:40,120 --> 00:28:42,840 Speaker 2: opportunities are there just through a nature lens. But as 542 00:28:42,840 --> 00:28:45,480 Speaker 2: we discussed earlier, it's much more of an emergent risk. 543 00:28:45,640 --> 00:28:48,320 Speaker 2: Both academia and the business world are finally starting to 544 00:28:48,360 --> 00:28:50,760 Speaker 2: get their heads around what exactly this risk is and 545 00:28:50,800 --> 00:28:53,239 Speaker 2: how it manifests. And it's because of a lack of 546 00:28:53,360 --> 00:28:56,239 Speaker 2: understanding on how to manage these risks or even what 547 00:28:56,320 --> 00:28:59,280 Speaker 2: these risks are, that they've been secondary. But I would 548 00:28:59,280 --> 00:29:02,640 Speaker 2: contend that even at BNF we do have sectors looking 549 00:29:02,720 --> 00:29:05,440 Speaker 2: at these things. We've got the Technology and Innovation team 550 00:29:05,480 --> 00:29:09,040 Speaker 2: looks at emerging technologies to handle waste or look at water, 551 00:29:09,320 --> 00:29:12,560 Speaker 2: and we've got an incredible circular economy team looking at 552 00:29:12,560 --> 00:29:15,840 Speaker 2: these things. It's perhaps among these four different issues that 553 00:29:15,880 --> 00:29:19,280 Speaker 2: we've discussed biodiversity that's the most emergent, and you did 554 00:29:19,280 --> 00:29:24,840 Speaker 2: mention COP and how both policy makers and the business 555 00:29:24,880 --> 00:29:28,720 Speaker 2: world is considering this set of issues. But while climate 556 00:29:28,760 --> 00:29:31,320 Speaker 2: COP is the most famous, and there is biodiversity COP, 557 00:29:31,400 --> 00:29:34,680 Speaker 2: there's a third one called the CCD, which is the 558 00:29:34,680 --> 00:29:39,200 Speaker 2: Cup for Desertification, reflecting our understanding of changing land use 559 00:29:39,240 --> 00:29:41,920 Speaker 2: and decreasing water. And earlier this year they announced the 560 00:29:41,960 --> 00:29:45,400 Speaker 2: creation of a fourth COP which is the Cup for Oceans, 561 00:29:45,560 --> 00:29:48,040 Speaker 2: and the first one is which is slated to begin 562 00:29:48,400 --> 00:29:51,920 Speaker 2: next year. So these are attracting the attention of all 563 00:29:52,000 --> 00:29:58,080 Speaker 2: stakeholders across business policy, academia everywhere, and as they're emerging, 564 00:29:58,400 --> 00:30:02,600 Speaker 2: they're little understood. But if you look at how for example, 565 00:30:02,640 --> 00:30:07,080 Speaker 2: the financial sector is treating nature. Every major financial institution 566 00:30:07,200 --> 00:30:10,000 Speaker 2: now will have a nature team that is assessing these risks, 567 00:30:10,120 --> 00:30:13,040 Speaker 2: seeing how material they are and discussing internally what they 568 00:30:13,080 --> 00:30:15,400 Speaker 2: can do to mitigate, as well as partnering with the 569 00:30:15,400 --> 00:30:16,520 Speaker 2: stewardship teams. 570 00:30:16,760 --> 00:30:19,840 Speaker 1: Another interesting kind of thought here, and I'd be interested 571 00:30:19,840 --> 00:30:21,800 Speaker 1: to hear your sort of reflections on this, as we're 572 00:30:21,880 --> 00:30:25,160 Speaker 1: kind of comparing climate risk and the issue of climate 573 00:30:25,200 --> 00:30:28,680 Speaker 1: to these other sectors. Is and far from saying that 574 00:30:28,760 --> 00:30:31,800 Speaker 1: it's easy to think about climate, but it can be 575 00:30:31,880 --> 00:30:35,840 Speaker 1: condensed down into like a single problem. There's too many 576 00:30:35,840 --> 00:30:39,160 Speaker 1: greenhouse gases in the atmosphere, it's causing climate to change, 577 00:30:39,320 --> 00:30:40,959 Speaker 1: and so you can distill it down. I mean, I 578 00:30:41,000 --> 00:30:43,560 Speaker 1: know that it's not just carbon dioxide, but like other 579 00:30:43,680 --> 00:30:47,720 Speaker 1: greenhouse gases, we can translate it into carbon dioxide equivalent. 580 00:30:47,920 --> 00:30:50,160 Speaker 1: And so there's a very sort of simple metric on 581 00:30:50,440 --> 00:30:53,920 Speaker 1: how collectively we're doing. We can kind of characterize different 582 00:30:54,040 --> 00:30:56,520 Speaker 1: forms of mitigation. We can kind of compare the cost 583 00:30:56,600 --> 00:30:59,520 Speaker 1: on a dollars per ton of CO two omitted. I 584 00:30:59,520 --> 00:31:02,880 Speaker 1: guess what I'm saying is it naturally leads itself to 585 00:31:03,480 --> 00:31:06,880 Speaker 1: being measured and progress being measured, and you know in 586 00:31:06,920 --> 00:31:09,480 Speaker 1: a lot of cases lack of progress being measured. But 587 00:31:09,600 --> 00:31:12,520 Speaker 1: these other areas, I have the sense that there's not 588 00:31:13,560 --> 00:31:18,000 Speaker 1: a single way of kind of simplifying the issue and 589 00:31:18,080 --> 00:31:21,560 Speaker 1: kind of communicating how we're progressing, how we're doing. Do 590 00:31:21,600 --> 00:31:23,920 Speaker 1: you think that that holds back those when we're thinking 591 00:31:23,960 --> 00:31:26,480 Speaker 1: about making the comparisons around nature risk. 592 00:31:27,040 --> 00:31:29,880 Speaker 2: Yeah, absolutely, and this is a very common comparison that 593 00:31:29,920 --> 00:31:32,920 Speaker 2: we see the difference between climate and nature. Climate is 594 00:31:32,960 --> 00:31:35,000 Speaker 2: much easier for two reason. It's not only just the 595 00:31:35,040 --> 00:31:37,800 Speaker 2: single metric of CO two e, which in itself can 596 00:31:37,880 --> 00:31:40,280 Speaker 2: be quite difficult when you look across the different scopes. 597 00:31:40,480 --> 00:31:42,840 Speaker 2: But more than that, it's that CO two e is 598 00:31:43,200 --> 00:31:46,280 Speaker 2: a universal metric. It doesn't matter where you sit. If 599 00:31:46,320 --> 00:31:49,240 Speaker 2: you release a ton of carbon dioxide equivalent into the 600 00:31:49,240 --> 00:31:52,800 Speaker 2: atmosphere in Japan versus in Madagascar, you calculate it in 601 00:31:52,840 --> 00:31:55,800 Speaker 2: the same way. But for nature it's far more localized. 602 00:31:55,960 --> 00:31:59,200 Speaker 2: Everything depends on how much of the natural resource is 603 00:31:59,240 --> 00:32:02,440 Speaker 2: currently there or to what extent in this locality you're 604 00:32:02,480 --> 00:32:06,560 Speaker 2: impacting those ecosystem services. That makes it extremely challenging, So 605 00:32:06,600 --> 00:32:10,000 Speaker 2: we need an enormous volume of data to accurately assess, 606 00:32:10,200 --> 00:32:15,000 Speaker 2: and we need a very stringent and complex, multifaceted framework 607 00:32:15,080 --> 00:32:19,840 Speaker 2: for calculating exactly what the risk is, what the value 608 00:32:19,840 --> 00:32:22,120 Speaker 2: at risk is, and what should be done about that, 609 00:32:22,240 --> 00:32:25,400 Speaker 2: how to manage it. You've got to consider companies direct 610 00:32:25,440 --> 00:32:28,440 Speaker 2: operations as well as supply chains, and often companies might 611 00:32:28,480 --> 00:32:31,040 Speaker 2: not even know where the primary assets are located. So 612 00:32:31,080 --> 00:32:34,880 Speaker 2: how do we manage risk and say deforestation? These things 613 00:32:34,960 --> 00:32:38,520 Speaker 2: are changing. Data is available, like Bloomberg itself has got 614 00:32:38,560 --> 00:32:42,400 Speaker 2: an enormous amount, but a lot of other providers. When 615 00:32:42,400 --> 00:32:45,880 Speaker 2: I say providers, I mean research organizations NGOs are doing 616 00:32:45,920 --> 00:32:48,680 Speaker 2: a lot to map and understand these risks. One of 617 00:32:48,720 --> 00:32:51,960 Speaker 2: our advantages is we've got very good asset level data 618 00:32:52,040 --> 00:32:54,840 Speaker 2: and we can work with these companies, for example the 619 00:32:54,960 --> 00:32:58,720 Speaker 2: Natural History Museum and its Biodiversity INTACTNUS index to combine 620 00:32:58,800 --> 00:33:01,600 Speaker 2: these two data sets stand better where the risk is. 621 00:33:01,760 --> 00:33:04,400 Speaker 2: Understanding where the risk is is just obviously step number one. 622 00:33:04,440 --> 00:33:07,680 Speaker 2: Managing that risk is step number two, and then once 623 00:33:07,720 --> 00:33:10,800 Speaker 2: you've decided how to manage, implementing that is another step. 624 00:33:11,040 --> 00:33:15,480 Speaker 2: The multifasted characteristics of nature mean that it's extraordinary complex, 625 00:33:15,720 --> 00:33:19,600 Speaker 2: and as it becomes more understood and more material to companies, 626 00:33:19,720 --> 00:33:23,240 Speaker 2: there will be more options to manage. One of the 627 00:33:23,240 --> 00:33:26,680 Speaker 2: objectives of these nature risk management scores is essentially a 628 00:33:26,760 --> 00:33:30,880 Speaker 2: preliminary exploration to assess how companies are doing. As this 629 00:33:31,000 --> 00:33:33,479 Speaker 2: becomes more nuanced and advanced, will be able to produce 630 00:33:33,640 --> 00:33:37,320 Speaker 2: different frameworks specific to each sector, they'll be able to 631 00:33:37,600 --> 00:33:41,640 Speaker 2: accurately rank companies, perhaps a bit more reflecting what's really 632 00:33:41,680 --> 00:33:44,200 Speaker 2: going on than in this initial research offering. 633 00:33:44,760 --> 00:33:48,360 Speaker 1: I mean, as these risks become more and more prevalent, 634 00:33:48,640 --> 00:33:54,120 Speaker 1: this nature based lens is really very germane. And I 635 00:33:54,120 --> 00:33:56,920 Speaker 1: shouldn't even be joking. This is, you know, serious stuff, 636 00:33:56,920 --> 00:34:00,400 Speaker 1: but joking aside. It's kind of like I mean, bringing 637 00:34:00,440 --> 00:34:02,520 Speaker 1: me right back to the start of the podcast, I 638 00:34:02,560 --> 00:34:07,120 Speaker 1: mean outlining this kind of increasingly complex picture, trying to 639 00:34:07,200 --> 00:34:10,040 Speaker 1: simplify so that we can all make sense of it 640 00:34:10,280 --> 00:34:12,840 Speaker 1: in maybe the way same way that you know, simplifying 641 00:34:12,840 --> 00:34:15,640 Speaker 1: all these different greenhouse gases into a CO two E 642 00:34:16,280 --> 00:34:19,600 Speaker 1: helps simplify how we think about the problem. That is 643 00:34:19,640 --> 00:34:22,640 Speaker 1: why the work you're doing right now is really important. 644 00:34:22,680 --> 00:34:25,600 Speaker 1: I'm guessing and having a framework like yours. I mean, 645 00:34:25,640 --> 00:34:28,600 Speaker 1: I know it sounds very you know, giving all of 646 00:34:28,640 --> 00:34:31,359 Speaker 1: these companies a score out of ten across such a 647 00:34:31,440 --> 00:34:35,959 Speaker 1: kind of complex and diverse set of considerations. It's really 648 00:34:36,000 --> 00:34:39,359 Speaker 1: important work you're doing, so I really appreciate you coming 649 00:34:39,640 --> 00:34:43,359 Speaker 1: and explaining it to us today. And yeah, looking forward 650 00:34:43,400 --> 00:34:45,200 Speaker 1: to seeing more of the work you do on this 651 00:34:45,239 --> 00:34:47,080 Speaker 1: topic because it's been a fascinating conversation. 652 00:34:47,320 --> 00:34:48,839 Speaker 2: Yep, thank you very much, Tom, I enjoyed this. 653 00:34:57,600 --> 00:35:00,719 Speaker 1: Today's episode of Switched On was produced by Cam Gray 654 00:35:00,920 --> 00:35:04,640 Speaker 1: with production assistance from Kamalas Shelling. Bloomberg NIF is a 655 00:35:04,680 --> 00:35:07,840 Speaker 1: service provided by Bloomberg Finance LP and its affiliates. This 656 00:35:07,920 --> 00:35:10,600 Speaker 1: recording does not constitute, nor should it be construed as 657 00:35:10,640 --> 00:35:14,560 Speaker 1: investment advice, investment recommendations, or a recommendation as to an 658 00:35:14,600 --> 00:35:15,920 Speaker 1: investment or other strategy. 659 00:35:15,960 --> 00:35:19,359 Speaker 2: Bloomberg ANIF should not be considered as information sufficient upon 660 00:35:19,400 --> 00:35:22,560 Speaker 2: which to base an investment decision. Neither Bloomberg Finance Lp 661 00:35:22,800 --> 00:35:26,000 Speaker 2: Nor any of its affiliates makes any representation or warranty 662 00:35:26,080 --> 00:35:29,120 Speaker 2: as to the accuracy or completeness of the information contained 663 00:35:29,160 --> 00:35:31,680 Speaker 2: in this recording, and any liability as a result of 664 00:35:31,719 --> 00:35:33,680 Speaker 2: this recording is expressly disclaimed.