1 00:00:02,720 --> 00:00:10,560 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,560 --> 00:00:14,520 Speaker 1: Bloomberg Intelligence podcast. Catch us live weekdays at ten am 3 00:00:14,560 --> 00:00:18,479 Speaker 1: Eastern on Applecarplay and Android Auto with the Bloomberg Business app. 4 00:00:18,600 --> 00:00:21,799 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:21,920 --> 00:00:23,040 Speaker 1: us live on YouTube. 6 00:00:23,560 --> 00:00:25,640 Speaker 2: One of the big stories on the Bloomberg terminal today 7 00:00:25,840 --> 00:00:29,720 Speaker 2: and how US banks finance their own competition to the 8 00:00:29,720 --> 00:00:32,560 Speaker 2: tune of one trillion dollars. I'm talking about financing, priving, 9 00:00:32,600 --> 00:00:36,120 Speaker 2: some financing to non financial kind of institutions, thinking private equity, 10 00:00:36,159 --> 00:00:37,480 Speaker 2: private credit, that kind of thing. 11 00:00:38,400 --> 00:00:40,800 Speaker 3: Herman Chan joins us here. He is Bloomberg Intelligence. She 12 00:00:40,800 --> 00:00:41,640 Speaker 3: covers all the banks. 13 00:00:41,880 --> 00:00:44,760 Speaker 2: Herman, what are the what are the banks, the US 14 00:00:44,880 --> 00:00:48,040 Speaker 2: banks doing in terms of, you know, lending to maybe 15 00:00:48,080 --> 00:00:51,840 Speaker 2: some non traditional financial institutions like private equity, like hedge funds. 16 00:00:52,360 --> 00:00:53,519 Speaker 3: How big of a business is that? 17 00:00:53,840 --> 00:00:57,920 Speaker 4: Yeah, it's It's really interesting because the Federal Reserve has 18 00:00:58,240 --> 00:01:02,720 Speaker 4: just recently require hired banks to disclose more on lending 19 00:01:02,760 --> 00:01:07,360 Speaker 4: to these non bank, non bank financial intermediaries. And what 20 00:01:07,440 --> 00:01:11,080 Speaker 4: we've seen is that some banks that we cover, like 21 00:01:11,240 --> 00:01:15,800 Speaker 4: Bank OZK, Western Alliance, that could basically mean over fifty 22 00:01:15,840 --> 00:01:19,400 Speaker 4: percent of their commercial loan portfolio is to the shadow banks. 23 00:01:19,840 --> 00:01:23,280 Speaker 4: So it's an area that is growing where you see 24 00:01:23,440 --> 00:01:27,240 Speaker 4: traditional businesses are a bit wary in this current macro 25 00:01:27,360 --> 00:01:30,480 Speaker 4: environment which still elevated interest rates, a lot of uncertainty 26 00:01:30,959 --> 00:01:36,200 Speaker 4: with the economy. But lending to non bank financial institutions 27 00:01:36,319 --> 00:01:37,680 Speaker 4: is an area of course. 28 00:01:38,080 --> 00:01:39,320 Speaker 5: So explain shadow banks. 29 00:01:39,360 --> 00:01:40,240 Speaker 3: What is that topic? 30 00:01:40,600 --> 00:01:46,520 Speaker 4: So it's interesting the regulators have broken out shadow banks 31 00:01:46,840 --> 00:01:53,440 Speaker 4: non bank financial institutions as institutions like mortgage lenders, private equity, 32 00:01:53,680 --> 00:01:59,040 Speaker 4: private credits, financial institutions that lend but don't have the 33 00:01:59,120 --> 00:02:03,680 Speaker 4: depository component to their operations. 34 00:02:04,640 --> 00:02:07,800 Speaker 2: So I kind of view these what do you call 35 00:02:07,840 --> 00:02:11,640 Speaker 2: them nd fi's, so non depositive and institutions. Aren't they 36 00:02:12,080 --> 00:02:14,560 Speaker 2: competitors to the banks themselves, So why am I lending 37 00:02:14,560 --> 00:02:14,960 Speaker 2: the money? 38 00:02:15,040 --> 00:02:21,160 Speaker 4: They are increasingly competitors. What we have noticed is that 39 00:02:21,880 --> 00:02:27,720 Speaker 4: the participants that are borrowing from these non pick financial 40 00:02:27,720 --> 00:02:31,760 Speaker 4: competitors are are a bit more riskier, and so they 41 00:02:32,919 --> 00:02:35,760 Speaker 4: are viewed as more high yield. And these are areas 42 00:02:35,800 --> 00:02:40,000 Speaker 4: that the traditional banking institutions don't want to lend money to. 43 00:02:40,560 --> 00:02:42,760 Speaker 4: So a way to get around at is to lend 44 00:02:42,800 --> 00:02:47,320 Speaker 4: it to the sponsors, and that's something that's happening. What's 45 00:02:47,360 --> 00:02:51,480 Speaker 4: interesting is that the banks themselves will say they're not 46 00:02:51,520 --> 00:02:56,240 Speaker 4: competing with the private credit operators head the head, but 47 00:02:57,760 --> 00:02:59,440 Speaker 4: we do see a bit of a hallowing out of 48 00:02:59,480 --> 00:03:02,920 Speaker 4: the tradition business borrowers. Because if you have private acway 49 00:03:02,960 --> 00:03:05,720 Speaker 4: coming in and leveraging the balance sheets of the companies 50 00:03:05,800 --> 00:03:09,120 Speaker 4: they borrow, inherently these companies are not going to be 51 00:03:10,680 --> 00:03:15,320 Speaker 4: good customers for a traditional bank, So a lot of 52 00:03:15,320 --> 00:03:17,239 Speaker 4: these customers continue to go away. 53 00:03:17,840 --> 00:03:21,040 Speaker 5: So I'm hearing the industry watched our dogs are worried 54 00:03:21,040 --> 00:03:25,399 Speaker 5: about the increase in bank loans to these DFIs. They're 55 00:03:25,440 --> 00:03:27,800 Speaker 5: thinking that it can make banks more vulnerable to liquidity 56 00:03:27,960 --> 00:03:31,200 Speaker 5: or credit shocks. What are the developments there. 57 00:03:31,200 --> 00:03:33,919 Speaker 4: Yeah, well, it remains to be seen, right, So it's 58 00:03:34,000 --> 00:03:38,120 Speaker 4: continuing to be a larger and larger portion of the 59 00:03:39,240 --> 00:03:42,400 Speaker 4: loan portfolio for these banks, but it's still in the 60 00:03:42,440 --> 00:03:44,880 Speaker 4: grand scheme of things. A lot of the banks remain 61 00:03:45,040 --> 00:03:49,720 Speaker 4: very diversified, but we haven't seen a downturn with such 62 00:03:49,800 --> 00:03:52,440 Speaker 4: a fragmented market where a lot of the lending is 63 00:03:52,560 --> 00:03:56,840 Speaker 4: going outside of the traditional banking system. So it's something 64 00:03:56,880 --> 00:04:00,640 Speaker 4: that continues to be monitored and something that we're assessing 65 00:04:00,760 --> 00:04:01,520 Speaker 4: quarter by quarter. 66 00:04:02,240 --> 00:04:04,080 Speaker 3: Do you like this business as an analysts? Do you think 67 00:04:04,080 --> 00:04:07,040 Speaker 3: it's a good business for some of these banks right now? 68 00:04:07,200 --> 00:04:11,880 Speaker 4: It's it's a way to demonstrate some better growth. We 69 00:04:12,040 --> 00:04:15,680 Speaker 4: just looked at the numbers before joining and traditional commercial 70 00:04:15,760 --> 00:04:18,920 Speaker 4: and industrial lending, it's about in the first quarter, it's 71 00:04:18,960 --> 00:04:22,680 Speaker 4: about half a percentage point growth. If you look at 72 00:04:22,760 --> 00:04:25,480 Speaker 4: the lending to non big financial institutions, that's up five 73 00:04:25,520 --> 00:04:28,520 Speaker 4: point seven percent in the quarter. So if you have 74 00:04:28,640 --> 00:04:32,279 Speaker 4: a bit more exposure to that, you can juice your growth, 75 00:04:32,360 --> 00:04:35,280 Speaker 4: which in this current environment you're not seeing a lot 76 00:04:35,279 --> 00:04:40,359 Speaker 4: of activity there. But again you need to have a 77 00:04:40,520 --> 00:04:42,360 Speaker 4: very diversified portfolio. 78 00:04:42,600 --> 00:04:45,200 Speaker 3: All right, Herman chen, you're the expert here. We're going 79 00:04:45,279 --> 00:04:45,640 Speaker 3: to go with you. 80 00:04:45,640 --> 00:04:48,920 Speaker 2: Herman Chinn, Senior analyst for US regional banks. We usually 81 00:04:48,960 --> 00:04:50,920 Speaker 2: talk to Herman when something's blowing up, but we want 82 00:04:50,920 --> 00:04:54,040 Speaker 2: to talk it's crazy, something's gulpin' right. Here's a new 83 00:04:54,080 --> 00:04:56,000 Speaker 2: source of potential long growth for some of these banks 84 00:04:56,000 --> 00:04:58,280 Speaker 2: out there. Herman Chann, senior analysts covers the regional banks 85 00:04:58,279 --> 00:05:00,599 Speaker 2: for Bloomberg Intelligence, Joining the heres joining us here in 86 00:05:00,600 --> 00:05:03,000 Speaker 2: our Bloomberg Interactive Broker Studio. 87 00:05:05,080 --> 00:05:08,800 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 88 00:05:08,880 --> 00:05:12,279 Speaker 1: weekdays at ten am Eastern on Applecarplay and Android Auto 89 00:05:12,360 --> 00:05:15,440 Speaker 1: with the Bloomberg Business App. Listen on demand wherever you 90 00:05:15,480 --> 00:05:18,680 Speaker 1: get your podcasts, or watch us live on YouTube. 91 00:05:19,400 --> 00:05:21,599 Speaker 3: It's got a Steve Man. He's a Global autos and 92 00:05:21,720 --> 00:05:22,120 Speaker 3: I'll Steve. 93 00:05:22,160 --> 00:05:24,080 Speaker 2: I know you've got earnings models out there for a 94 00:05:24,080 --> 00:05:27,400 Speaker 2: lot of these big auto companies. Are you adjusting your 95 00:05:27,400 --> 00:05:30,039 Speaker 2: earnings models for tariffs? Here? 96 00:05:30,080 --> 00:05:32,760 Speaker 3: How's that can impact some of these big global automakers. 97 00:05:33,640 --> 00:05:37,000 Speaker 6: Yeah, we are actually going through that right now. One 98 00:05:37,040 --> 00:05:39,159 Speaker 6: of the things we did publish this morning was the 99 00:05:39,240 --> 00:05:42,680 Speaker 6: auto sales forecast for the US. You know, we were 100 00:05:42,880 --> 00:05:46,240 Speaker 6: initially looking at down half a percent. We're looking at 101 00:05:46,360 --> 00:05:49,680 Speaker 6: being down at least three percent now for the year. 102 00:05:50,680 --> 00:05:53,120 Speaker 6: But you know, we are going through the model. One 103 00:05:53,440 --> 00:05:56,760 Speaker 6: thing that really stood out for us was really Ford. 104 00:05:58,120 --> 00:05:58,560 Speaker 3: Ford. 105 00:05:58,600 --> 00:06:02,159 Speaker 6: Look, you know they they're losing Armin and le like 106 00:06:02,360 --> 00:06:05,880 Speaker 6: on on ev sales. Uh. The the popular Mochi is 107 00:06:05,880 --> 00:06:09,000 Speaker 6: actually made in Mexico, So like for us, if you 108 00:06:09,080 --> 00:06:13,479 Speaker 6: tack on another ten ten grand on the price and 109 00:06:13,520 --> 00:06:15,719 Speaker 6: it goes through the bottom line. You know, it could 110 00:06:15,839 --> 00:06:20,320 Speaker 6: hit another you could hit five hundred million dollars on earnings. 111 00:06:20,320 --> 00:06:23,080 Speaker 6: That's ten percent of their earnings. So those are some 112 00:06:23,120 --> 00:06:24,760 Speaker 6: of the things we're looking at. 113 00:06:24,600 --> 00:06:27,120 Speaker 5: Steve, What are the names that you're seeing are most 114 00:06:27,160 --> 00:06:27,920 Speaker 5: exposed here? 115 00:06:29,279 --> 00:06:33,400 Speaker 6: Well, I think on the downside, are definitely the legacy 116 00:06:33,600 --> 00:06:36,720 Speaker 6: you know, the big three autos, plus the the foreign 117 00:06:37,480 --> 00:06:40,880 Speaker 6: legacy auto makers. You know, they do have a lot 118 00:06:40,880 --> 00:06:46,240 Speaker 6: of production outside of the US. As you can see, 119 00:06:46,520 --> 00:06:49,880 Speaker 6: you know, the peer plays, not just Tesla, Rivian and Lucid, 120 00:06:50,200 --> 00:06:56,360 Speaker 6: are actually relatively performing relatively better because there's a possibility 121 00:06:56,400 --> 00:06:59,760 Speaker 6: that the peer plays could take marketshare ev market share 122 00:06:59,800 --> 00:07:03,160 Speaker 6: from legacy automakers if they have to increase prices on 123 00:07:03,240 --> 00:07:07,560 Speaker 6: those ev imports that they make in Mexico. The other 124 00:07:07,680 --> 00:07:10,720 Speaker 6: thing that's interesting too that we're keeping an eye on 125 00:07:11,280 --> 00:07:17,760 Speaker 6: is really on the retail auto parts companies like O'Reilly, AutoZone, 126 00:07:17,800 --> 00:07:20,880 Speaker 6: Advanced Auto Parts. You know, they're actually bucking the trend. 127 00:07:20,960 --> 00:07:24,440 Speaker 6: They're up and simply the reason is that you know, 128 00:07:24,520 --> 00:07:28,240 Speaker 6: if people are not buying new cars, they're gonna have 129 00:07:28,320 --> 00:07:33,000 Speaker 6: to maintain existing ones, and so you know, those DIY 130 00:07:33,600 --> 00:07:36,280 Speaker 6: parts stores are are are actually doing well today. 131 00:07:36,320 --> 00:07:38,400 Speaker 2: Yeah, I'm looking at those stocks. I mean AutoZone for examples, 132 00:07:38,480 --> 00:07:41,360 Speaker 2: up two point seven percent today, fifty two week Hi, 133 00:07:41,680 --> 00:07:43,600 Speaker 2: A lot of the other names are two three four percent. 134 00:07:43,640 --> 00:07:46,640 Speaker 3: And Steve, I'll have you know I did buy a 135 00:07:46,720 --> 00:07:47,600 Speaker 3: new or at least a. 136 00:07:47,560 --> 00:07:50,240 Speaker 2: New vehicle this past weekend, a Condon but I got 137 00:07:50,240 --> 00:07:51,400 Speaker 2: a hybrid. 138 00:07:51,720 --> 00:07:54,240 Speaker 3: So how about which hon does this? Okay? 139 00:07:54,400 --> 00:07:58,200 Speaker 2: Okay, so I've got, I've got, I've got in front 140 00:07:58,200 --> 00:07:59,320 Speaker 2: of the tariffs. 141 00:07:59,360 --> 00:08:00,880 Speaker 3: There are some set to go there. 142 00:08:00,960 --> 00:08:02,480 Speaker 6: Oh, you're on your way there. 143 00:08:02,720 --> 00:08:05,480 Speaker 2: So Stee, what are you hearing from the Hondas of 144 00:08:05,480 --> 00:08:08,600 Speaker 2: the world, the Volkswagons, the Toyotas of the world. 145 00:08:08,640 --> 00:08:10,400 Speaker 3: How are they viewing this environment? 146 00:08:10,680 --> 00:08:13,280 Speaker 6: Yeah, you know, I think they're gonna face some cost 147 00:08:13,320 --> 00:08:16,040 Speaker 6: pressures as well. You know, they do have a big chunk. Actually, 148 00:08:16,040 --> 00:08:18,840 Speaker 6: the CRV is actually made in Canada, by the way, 149 00:08:19,720 --> 00:08:21,440 Speaker 6: So yeah, so they're gonna. 150 00:08:21,440 --> 00:08:23,120 Speaker 3: I don't know what the big dealers. 151 00:08:23,280 --> 00:08:24,040 Speaker 5: See for Canada. 152 00:08:24,440 --> 00:08:24,680 Speaker 3: Yep. 153 00:08:24,960 --> 00:08:27,240 Speaker 6: So you know they're gonna they're gonna get hit. But 154 00:08:27,600 --> 00:08:30,840 Speaker 6: the difference is that Honda and Toyota in the US, 155 00:08:30,960 --> 00:08:34,199 Speaker 6: and I think globally they do have a much lower 156 00:08:34,320 --> 00:08:38,240 Speaker 6: dealer inventory so you know, there's there's still a lot 157 00:08:38,240 --> 00:08:40,880 Speaker 6: of demand for their cars because they're you know, known 158 00:08:40,920 --> 00:08:44,600 Speaker 6: to be more reliable, so you know, you know, they're 159 00:08:44,600 --> 00:08:47,640 Speaker 6: may be able to pass on some of the higher costs, 160 00:08:48,160 --> 00:08:51,880 Speaker 6: the higher pricing. The price increases the consumers, so they 161 00:08:52,080 --> 00:08:57,360 Speaker 6: they would probably fare better within the legacy automaker, but 162 00:08:57,400 --> 00:09:01,319 Speaker 6: the European will probably get hit pretty bad, especially like 163 00:09:02,000 --> 00:09:05,800 Speaker 6: the luxury brand bm BMW, Mercedes and Audi. You know, 164 00:09:05,880 --> 00:09:09,040 Speaker 6: they have a different strategy. You know, they don't they 165 00:09:09,040 --> 00:09:11,800 Speaker 6: don't have multiple plants for certain models. They do have 166 00:09:11,920 --> 00:09:15,560 Speaker 6: they have a global plant for for for their models. 167 00:09:15,600 --> 00:09:19,480 Speaker 6: So so for example, BMW and Mercedes mix SUVs in 168 00:09:19,600 --> 00:09:22,559 Speaker 6: the US, so it's going to be hard for them 169 00:09:22,600 --> 00:09:26,200 Speaker 6: to shift footprint. But the other way to think about 170 00:09:26,240 --> 00:09:28,520 Speaker 6: it is, you know, if someone is able to afford 171 00:09:28,800 --> 00:09:32,640 Speaker 6: a more expensive vehicle like a Mercedes and BMW, they 172 00:09:32,679 --> 00:09:35,720 Speaker 6: may be able to stomach the higher prices. 173 00:09:36,200 --> 00:09:36,719 Speaker 3: Yeah, I don't know. 174 00:09:36,840 --> 00:09:40,440 Speaker 2: Coming through my BMW X three, I guess it's South Carolina. 175 00:09:40,679 --> 00:09:42,440 Speaker 2: I don't know where it was built, but it wasn't 176 00:09:42,440 --> 00:09:43,800 Speaker 2: in Stuttgart with the rest of them. 177 00:09:43,920 --> 00:09:45,400 Speaker 3: Steve Man, thanks so much, appreciate it. 178 00:09:45,679 --> 00:09:48,760 Speaker 2: Steve Ban Global Autos and industrials research channels for Bloomberg 179 00:09:48,760 --> 00:09:53,360 Speaker 2: Intelligencies down there in a Bloomberg Princeton office. The office 180 00:09:53,400 --> 00:09:55,560 Speaker 2: probably some of the best food in all of Global 181 00:09:55,600 --> 00:09:58,960 Speaker 2: Bloomberg will laid out there for you right now. 182 00:10:00,120 --> 00:10:04,040 Speaker 1: Listening to the Bloomberg Intelligence Podcast. Catch us live weekdays 183 00:10:04,040 --> 00:10:06,920 Speaker 1: at ten am Eastern on Apple Cocklay and Android Auto 184 00:10:07,040 --> 00:10:10,120 Speaker 1: with the Bloomberg Business App. Listen on demand wherever you 185 00:10:10,160 --> 00:10:15,319 Speaker 1: get your podcasts, or watch us live on YouTube. 186 00:10:17,800 --> 00:10:21,520 Speaker 2: Talking about the AI trade for two years, it's been listening. 187 00:10:21,559 --> 00:10:23,120 Speaker 2: It's not just been a tech thing, it's been a 188 00:10:23,160 --> 00:10:26,000 Speaker 2: market thing. It's every company in the SP five round 189 00:10:26,080 --> 00:10:27,840 Speaker 2: and their conference calls they talk about AI. It's been 190 00:10:27,840 --> 00:10:29,200 Speaker 2: going on for a couple of years. One of the 191 00:10:29,200 --> 00:10:32,760 Speaker 2: ways to think about it is from the real estate perspective. Definitely, 192 00:10:32,840 --> 00:10:34,160 Speaker 2: you can do that. John Lynn, he does that. He 193 00:10:34,240 --> 00:10:37,840 Speaker 2: joins us. He's a chief business officer for Equinox, joining 194 00:10:37,920 --> 00:10:39,559 Speaker 2: us here in our Bloomberg Interactive Broker studio. 195 00:10:39,640 --> 00:10:41,080 Speaker 3: John to us, what you guys do at Equinics. 196 00:10:41,080 --> 00:10:44,480 Speaker 7: Thanks so much for having me. We're really the fundamental 197 00:10:44,480 --> 00:10:47,319 Speaker 7: digital infrastructure provider of the world. Building two hundred and 198 00:10:47,360 --> 00:10:49,640 Speaker 7: sixty eight data centers across seventy four market. 199 00:10:49,760 --> 00:10:50,240 Speaker 3: You're the guys. 200 00:10:50,520 --> 00:10:52,880 Speaker 7: We are the guys building and connecting all of these 201 00:10:53,160 --> 00:10:56,440 Speaker 7: cloud providers and enterprises making all of that data available 202 00:10:56,440 --> 00:10:56,880 Speaker 7: for AI. 203 00:10:57,440 --> 00:10:59,480 Speaker 5: And it's really interesting because I was just speaking with 204 00:10:59,559 --> 00:11:02,839 Speaker 5: him during the break saying that I cover US real 205 00:11:02,960 --> 00:11:05,400 Speaker 5: estate stocks, I cover real estate investment trust, and that's 206 00:11:05,440 --> 00:11:08,240 Speaker 5: exactly what ethics falls in that patch. This is my guy, 207 00:11:09,520 --> 00:11:12,120 Speaker 5: So wonderful to have this conversation. But I think that 208 00:11:12,120 --> 00:11:14,800 Speaker 5: there's often people don't really when you think about data centers, 209 00:11:14,840 --> 00:11:17,240 Speaker 5: they don't often think about the people that are actually 210 00:11:17,400 --> 00:11:19,640 Speaker 5: providing the real estate forward data center. So can you 211 00:11:19,679 --> 00:11:22,920 Speaker 5: talk a little bit about how Equinis differs from maybe 212 00:11:22,960 --> 00:11:24,800 Speaker 5: for thinking about a data center itself, but more or 213 00:11:24,880 --> 00:11:27,080 Speaker 5: less the fact that you guys are acquiring properties and 214 00:11:27,120 --> 00:11:27,920 Speaker 5: doing it that way. 215 00:11:28,120 --> 00:11:30,240 Speaker 7: Yeah, you can think about it as full scope development, 216 00:11:30,240 --> 00:11:32,440 Speaker 7: where I mean we're going from raw land getting their 217 00:11:32,559 --> 00:11:35,040 Speaker 7: entitlements and then building the entire data center and then 218 00:11:35,200 --> 00:11:39,040 Speaker 7: operating that for perpetuity essentially, and our focus is around 219 00:11:39,080 --> 00:11:41,880 Speaker 7: making sure we're getting as many customers as possible into 220 00:11:41,880 --> 00:11:45,120 Speaker 7: the facilities and really interconnecting their data flows together, which 221 00:11:45,160 --> 00:11:47,760 Speaker 7: is pretty unique. In the data center space, which has 222 00:11:47,880 --> 00:11:49,920 Speaker 7: also been a great opportunity for us to participate in 223 00:11:49,960 --> 00:11:50,720 Speaker 7: the AI growth. 224 00:11:51,360 --> 00:11:52,319 Speaker 3: What are you guys seeing here? 225 00:11:52,360 --> 00:11:54,880 Speaker 2: What are you seeing from your clients, the people you 226 00:11:54,960 --> 00:11:58,360 Speaker 2: talk to about kind of their needs going forward? Because 227 00:11:58,440 --> 00:12:00,280 Speaker 2: right now, I think in the marketplace you look, it's 228 00:12:00,320 --> 00:12:02,200 Speaker 2: like Invidious Stock and some of the other stocks that 229 00:12:02,240 --> 00:12:03,760 Speaker 2: trade around the AI theme. 230 00:12:04,120 --> 00:12:05,640 Speaker 3: Twenty twenty five has not been a good year. 231 00:12:05,679 --> 00:12:08,679 Speaker 2: After obviously phenomenal extraordinary growth in twenty three twenty four, 232 00:12:08,679 --> 00:12:12,719 Speaker 2: maybe before that. How are you viewing the growth here 233 00:12:12,880 --> 00:12:14,520 Speaker 2: in AI and from your end of the business, the 234 00:12:14,559 --> 00:12:15,280 Speaker 2: real estate side. 235 00:12:15,400 --> 00:12:17,360 Speaker 7: Yeah, First, I'd just say, you know, AI is a 236 00:12:17,400 --> 00:12:19,920 Speaker 7: portion of the demand for data centers, but data center 237 00:12:19,920 --> 00:12:22,400 Speaker 7: as a whole are powering everything that everybody is doing 238 00:12:22,480 --> 00:12:25,240 Speaker 7: right like listening to this broadcast, you know, ordering food 239 00:12:25,280 --> 00:12:28,880 Speaker 7: for lunch, you know, trading, trading on the exchange, et cetera. 240 00:12:28,960 --> 00:12:31,760 Speaker 7: I mean, you need computers for everything nowadays, and that's 241 00:12:31,760 --> 00:12:34,480 Speaker 7: still continuing. I think, you know, digital transformation is not 242 00:12:34,520 --> 00:12:36,960 Speaker 7: in the early stages anymore, but we're far from done, 243 00:12:37,000 --> 00:12:39,719 Speaker 7: and so that is just the secular driver that will continue. 244 00:12:40,360 --> 00:12:43,280 Speaker 7: From the eye landscape, I'd say, obviously, a huge amount 245 00:12:43,320 --> 00:12:45,720 Speaker 7: of interest and excitement, and I think the it caught 246 00:12:45,760 --> 00:12:49,040 Speaker 7: the imagination of everyone, and I'd say, right now, what 247 00:12:49,080 --> 00:12:53,000 Speaker 7: we're seeing is like exciting use cases that are really 248 00:12:53,040 --> 00:12:55,839 Speaker 7: providing durable value, right. And I think it's still early 249 00:12:55,880 --> 00:12:58,880 Speaker 7: stages for many of that across the general business landscape, 250 00:12:59,000 --> 00:13:01,040 Speaker 7: but that's what gets me fund mentally excited. You look 251 00:13:01,040 --> 00:13:03,640 Speaker 7: at a company like Bristol Myers squib a customer of ours. 252 00:13:03,760 --> 00:13:08,559 Speaker 7: They're doing drug discovery using nvidiagpus and being able to 253 00:13:08,679 --> 00:13:12,360 Speaker 7: increase and accelerate their time to therapeutics. That's fundamentally going 254 00:13:12,400 --> 00:13:14,320 Speaker 7: to improve like human life, right, And I think that 255 00:13:14,320 --> 00:13:16,960 Speaker 7: there's so many different aspects that AI can improve based 256 00:13:17,000 --> 00:13:17,280 Speaker 7: on that. 257 00:13:17,480 --> 00:13:19,520 Speaker 5: So run us through some of your biggest customers. Who 258 00:13:19,559 --> 00:13:20,200 Speaker 5: do you all work with? 259 00:13:20,600 --> 00:13:23,000 Speaker 7: Certainly the cloud providers are some of our top customers. 260 00:13:23,120 --> 00:13:25,800 Speaker 7: We've got over two thousand different network providers as well. 261 00:13:25,920 --> 00:13:28,680 Speaker 7: The genesis of the company was really around how do 262 00:13:28,720 --> 00:13:31,120 Speaker 7: we help the Internet scale? And that ended up being well, 263 00:13:31,160 --> 00:13:35,280 Speaker 7: how do we help the globes telecommunications and data flows scale? 264 00:13:35,520 --> 00:13:37,600 Speaker 7: And so when you think about all of the cloud providers, 265 00:13:37,679 --> 00:13:40,360 Speaker 7: how do they connect to the end customers that's through 266 00:13:40,360 --> 00:13:43,880 Speaker 7: our facilities. And then as we've built that landscape, we've 267 00:13:43,920 --> 00:13:47,480 Speaker 7: ended up basically becoming the place where enterprises put their 268 00:13:47,480 --> 00:13:50,439 Speaker 7: most trusted assets. When you think about then, whether they 269 00:13:50,440 --> 00:13:52,719 Speaker 7: have some workloads that are in the public cloud, well, 270 00:13:52,720 --> 00:13:54,160 Speaker 7: they're going to have some that they're going to have 271 00:13:54,240 --> 00:13:56,800 Speaker 7: ownership and control of themselves. When they put those in 272 00:13:56,840 --> 00:14:00,120 Speaker 7: our facilities, it lets them glue that infrastructure together and 273 00:14:00,160 --> 00:14:03,320 Speaker 7: become like one super powerful environment. 274 00:14:03,640 --> 00:14:08,040 Speaker 2: And folks, Equinics is a publicly traded company. Eqix is 275 00:14:08,320 --> 00:14:10,520 Speaker 2: the ticker. It's got a market cap of eighty one 276 00:14:10,800 --> 00:14:14,200 Speaker 2: billion dollars. And if you want some research on it 277 00:14:14,240 --> 00:14:16,400 Speaker 2: and you're on the Bloomberg terminal, Jeffrey Langbaum was my 278 00:14:16,559 --> 00:14:19,480 Speaker 2: reat analyst. He covers eqix, you can go big and 279 00:14:19,520 --> 00:14:23,880 Speaker 2: that's where you find the research on Equinox. John talk 280 00:14:23,880 --> 00:14:25,440 Speaker 2: to us about the global form front, and we know 281 00:14:25,440 --> 00:14:28,920 Speaker 2: you guys are global here. Where are you seeing growth, 282 00:14:29,720 --> 00:14:31,320 Speaker 2: stronger growth versus weaker growth? 283 00:14:31,880 --> 00:14:34,720 Speaker 7: Yeah, I'd say across the landscape, there's still quite a 284 00:14:34,760 --> 00:14:37,440 Speaker 7: bit of demand for data center activity. You know, we're 285 00:14:37,440 --> 00:14:40,360 Speaker 7: particularly excited about some of the emerging markets Southeast Asia, 286 00:14:40,360 --> 00:14:43,640 Speaker 7: for instance, it's certainly growing quite a bit, but you know, 287 00:14:43,960 --> 00:14:46,200 Speaker 7: based off of a lot of the recent Surgeon AI 288 00:14:46,400 --> 00:14:48,200 Speaker 7: and kind of the use cases set up for that, 289 00:14:48,560 --> 00:14:50,640 Speaker 7: just a tremendous amount of growth in the US over 290 00:14:50,680 --> 00:14:51,880 Speaker 7: the course of the last two years. 291 00:14:52,360 --> 00:14:54,240 Speaker 5: So, I mean, when we think about your competitors in 292 00:14:54,280 --> 00:14:57,040 Speaker 5: this broader landscape, there is obviously digital realty trust when 293 00:14:57,040 --> 00:14:59,360 Speaker 5: we're thinking about publicly traded routs here in the data 294 00:14:59,360 --> 00:15:02,400 Speaker 5: center space. And if you look over the past five years, 295 00:15:02,600 --> 00:15:05,840 Speaker 5: we have equinic shares that have risen forty percent, but 296 00:15:05,840 --> 00:15:08,480 Speaker 5: that's compared to digital realty that's risen about eleven percent. 297 00:15:08,760 --> 00:15:10,360 Speaker 5: What do you think that you all are doing differently 298 00:15:10,400 --> 00:15:11,480 Speaker 5: than your competitors. 299 00:15:12,480 --> 00:15:16,960 Speaker 7: I think one, it's our focus around really driving diversity 300 00:15:16,960 --> 00:15:20,240 Speaker 7: of customer and like kind of having an ecosystem that 301 00:15:20,240 --> 00:15:22,400 Speaker 7: we've built around the value that we're doing. And so 302 00:15:22,520 --> 00:15:25,080 Speaker 7: that's incredibly important for us. Like for the AI trade, 303 00:15:25,080 --> 00:15:27,840 Speaker 7: for instance, we're focusing not just on capturing some of 304 00:15:27,880 --> 00:15:30,400 Speaker 7: these large training footprints, but really how do we make 305 00:15:30,400 --> 00:15:32,680 Speaker 7: sure we're getting all of these AI players and exposing 306 00:15:32,720 --> 00:15:34,600 Speaker 7: them to the rest of our customer base and really 307 00:15:34,640 --> 00:15:39,560 Speaker 7: again that fuel becomes additional growth across our entire portfolio. 308 00:15:40,440 --> 00:15:43,560 Speaker 2: Do you develop and build data centers or do you 309 00:15:43,600 --> 00:15:44,960 Speaker 2: just buy existing. 310 00:15:44,760 --> 00:15:46,000 Speaker 7: We develop and build? 311 00:15:46,240 --> 00:15:49,080 Speaker 3: Where are you developing and building these days? And if 312 00:15:49,080 --> 00:15:50,280 Speaker 3: you say Texas. 313 00:15:49,960 --> 00:15:53,200 Speaker 7: Or Florida, Well, we're building all around the world. I 314 00:15:53,200 --> 00:15:56,280 Speaker 7: think we've got sixty eight current like major construction projects 315 00:15:56,280 --> 00:15:58,720 Speaker 7: across it. Yeah, so we're very active. 316 00:15:59,400 --> 00:16:01,760 Speaker 3: Wow, come up to it's. 317 00:16:01,680 --> 00:16:03,280 Speaker 5: Really it's big company in this. 318 00:16:03,560 --> 00:16:07,520 Speaker 3: I mean, yeah, you guys have to come to my path. 319 00:16:08,720 --> 00:16:09,680 Speaker 7: It's a beautiful space. 320 00:16:10,720 --> 00:16:12,240 Speaker 5: So what is your you know, what are your thoughts 321 00:16:12,280 --> 00:16:14,160 Speaker 5: for people who are saying that, you know, the tech 322 00:16:14,280 --> 00:16:16,640 Speaker 5: rally has run too far, you know, maybe we have 323 00:16:16,760 --> 00:16:19,120 Speaker 5: capex spend that's just you know, bloated. There's so much 324 00:16:19,120 --> 00:16:21,560 Speaker 5: spending in this space. Is this a place to be 325 00:16:21,600 --> 00:16:23,840 Speaker 5: investing right now? When we think about AI and in 326 00:16:23,840 --> 00:16:24,400 Speaker 5: places of. 327 00:16:24,360 --> 00:16:28,480 Speaker 7: That regard, I think the long term trend around this 328 00:16:28,560 --> 00:16:30,360 Speaker 7: is going to be inevitable, right. I think it's certainly 329 00:16:30,440 --> 00:16:33,080 Speaker 7: we're creating durable value not just for you know, kind 330 00:16:33,080 --> 00:16:35,040 Speaker 7: of the planet and all of our customers, but but 331 00:16:35,120 --> 00:16:37,720 Speaker 7: for shareholders. I think the uh, the amount of investment 332 00:16:37,760 --> 00:16:39,960 Speaker 7: in the space, and like the numbers are candidly like 333 00:16:40,040 --> 00:16:42,040 Speaker 7: eye watering right now, and so but a lot of 334 00:16:42,040 --> 00:16:44,760 Speaker 7: that I think is just capital accumulation rather than deployment. 335 00:16:45,440 --> 00:16:47,560 Speaker 7: And you know, compared to a lot of other markets 336 00:16:47,720 --> 00:16:50,000 Speaker 7: in the real estate side, it's actually a little hard 337 00:16:50,040 --> 00:16:53,520 Speaker 7: to kind of overbuild just because there's so many natural 338 00:16:53,880 --> 00:16:55,960 Speaker 7: h like limters in terms of the way we want 339 00:16:55,960 --> 00:16:59,400 Speaker 7: to scale, from utility power availability, to supply chain to 340 00:17:00,240 --> 00:17:02,160 Speaker 7: you know, kind of just the amount of trades you 341 00:17:02,200 --> 00:17:04,920 Speaker 7: need to be able to build and operate these facilities. 342 00:17:05,119 --> 00:17:07,480 Speaker 7: And so I think that that helps kind of provide 343 00:17:07,480 --> 00:17:09,800 Speaker 7: more rationality than you know, in some some real estate 344 00:17:09,800 --> 00:17:11,400 Speaker 7: markets where you know, you can throw up a shell 345 00:17:11,440 --> 00:17:13,280 Speaker 7: pretty easily, you can you can kind of just like 346 00:17:13,320 --> 00:17:16,600 Speaker 7: convert and overbuild. In this case, it's a very long 347 00:17:16,640 --> 00:17:19,040 Speaker 7: development cycle, and so I think you'll you'll see kind 348 00:17:19,040 --> 00:17:20,200 Speaker 7: of some self metering there. 349 00:17:20,680 --> 00:17:22,760 Speaker 3: John, thanks very much for joining us. Really appreciate you 350 00:17:22,800 --> 00:17:23,119 Speaker 3: coming in. 351 00:17:23,400 --> 00:17:26,760 Speaker 2: John Lynn, he's a chief business officer of Equinox, joining 352 00:17:26,840 --> 00:17:29,520 Speaker 2: us live here in our Bloomberg Interactive Broker studio. Again, 353 00:17:29,840 --> 00:17:32,520 Speaker 2: another company walking into my door here in my studio. 354 00:17:32,960 --> 00:17:35,520 Speaker 3: I had no idea existed. Happens every day now, you know, 355 00:17:35,640 --> 00:17:36,560 Speaker 3: eighty billion. 356 00:17:36,320 --> 00:17:38,359 Speaker 2: Dollars in market cap and of course I missed it, 357 00:17:38,880 --> 00:17:41,359 Speaker 2: but a big real estate investment trust. And I know 358 00:17:42,119 --> 00:17:44,520 Speaker 2: our bi Anlyst Jeff Langbaum, he's all over here. He's 359 00:17:44,520 --> 00:17:46,960 Speaker 2: got research on this company as well. 360 00:17:47,840 --> 00:17:52,520 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 361 00:17:52,720 --> 00:17:56,160 Speaker 1: and anywhere else you get your podcasts. Listen live each 362 00:17:56,280 --> 00:17:59,800 Speaker 1: me day ten am to noon Eastern on Bloomberg dot com, 363 00:18:00,119 --> 00:18:03,639 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 364 00:18:04,040 --> 00:18:06,960 Speaker 1: You can also watch us live every weekday on YouTube 365 00:18:07,359 --> 00:18:09,600 Speaker 1: and always on the Bloomberg terminal