1 00:00:02,960 --> 00:00:10,840 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. You're listening to the 2 00:00:10,880 --> 00:00:15,040 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am 3 00:00:15,080 --> 00:00:18,079 Speaker 1: Eastern on Apple Car playing Android Otto with the Bloomberg 4 00:00:18,120 --> 00:00:21,440 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:21,640 --> 00:00:24,040 Speaker 1: or watch us live on YouTube. 6 00:00:25,079 --> 00:00:28,680 Speaker 2: Let's get back to John Tucker in our New York studio. John, 7 00:00:28,720 --> 00:00:31,520 Speaker 2: Supreme Court. We got some rulings today, the notable on 8 00:00:31,560 --> 00:00:34,320 Speaker 2: the crossing the tape. Supreme Court backs White House on 9 00:00:34,400 --> 00:00:36,800 Speaker 2: social media post removal. What do we know about that? 10 00:00:36,920 --> 00:00:40,879 Speaker 3: Yeah, the Court issuing several major decisions this week. They 11 00:00:40,880 --> 00:00:44,320 Speaker 3: could also extend into next week. In fact, twelve opinions 12 00:00:44,720 --> 00:00:48,279 Speaker 3: left in in this term. Paul on Alex Paper opinions 13 00:00:48,320 --> 00:00:50,640 Speaker 3: released to the courthouse in Washington just a few minutes 14 00:00:50,680 --> 00:00:54,640 Speaker 3: before they're posted online. June Grosso, the host of Bloomberg Law, 15 00:00:55,040 --> 00:00:57,160 Speaker 3: joining me now to go over some of these decisions 16 00:00:57,440 --> 00:01:01,680 Speaker 3: with respect to the Biden administration. They're social media contexts. 17 00:01:01,840 --> 00:01:02,880 Speaker 3: What was the decision? 18 00:01:03,280 --> 00:01:06,920 Speaker 4: So the decision, the complaint by a few Republican states 19 00:01:06,920 --> 00:01:09,760 Speaker 4: and people was that the Biden administration, and this was 20 00:01:09,840 --> 00:01:14,319 Speaker 4: during COVID was contacting the social media platforms and getting 21 00:01:14,319 --> 00:01:18,240 Speaker 4: them to change information. That was the charge. So here 22 00:01:18,280 --> 00:01:20,240 Speaker 4: in a six to three case, and both the cases 23 00:01:20,280 --> 00:01:23,640 Speaker 4: today are six to three, which is indicative of how 24 00:01:23,680 --> 00:01:24,759 Speaker 4: this term might end. 25 00:01:24,840 --> 00:01:25,480 Speaker 5: Six to three. 26 00:01:25,959 --> 00:01:31,759 Speaker 4: So the court went off on a standing issue, which 27 00:01:32,040 --> 00:01:35,080 Speaker 4: is procedural, and I know I've discussed this before, but 28 00:01:35,720 --> 00:01:38,039 Speaker 4: it's a way for the court not to reach the 29 00:01:38,040 --> 00:01:41,319 Speaker 4: main issue, but to say the people who are suing 30 00:01:41,360 --> 00:01:44,080 Speaker 4: here don't have standing to sue because they weren't injured 31 00:01:44,080 --> 00:01:46,959 Speaker 4: in any way. But also in doing that, just as 32 00:01:47,040 --> 00:01:49,920 Speaker 4: Amy Cony Barrett, who wrote the majority, said that the 33 00:01:49,960 --> 00:01:53,560 Speaker 4: Fifth Circuit here was wrong in some of the analysis 34 00:01:53,560 --> 00:01:56,240 Speaker 4: that it made and that they couldn't really show that 35 00:01:56,280 --> 00:01:59,760 Speaker 4: it was the government that injured the plaintiffs at all 36 00:01:59,760 --> 00:02:02,280 Speaker 4: these points. So you know, the question is and also 37 00:02:02,320 --> 00:02:04,000 Speaker 4: it's sixty three in the. 38 00:02:04,560 --> 00:02:07,880 Speaker 3: Three, So it sets up how this is going to 39 00:02:07,880 --> 00:02:10,880 Speaker 3: play out before the election in terms of misinformation on 40 00:02:10,919 --> 00:02:11,639 Speaker 3: social media. 41 00:02:11,800 --> 00:02:12,040 Speaker 1: Right. 42 00:02:12,080 --> 00:02:15,400 Speaker 4: Also, there are two other cases that are sort of 43 00:02:15,520 --> 00:02:18,919 Speaker 4: joined that are more important as far as social media 44 00:02:18,960 --> 00:02:21,920 Speaker 4: is concerned, and those are the cases concerning the Texas 45 00:02:22,360 --> 00:02:27,639 Speaker 4: and Florida laws where they're trying to curtail the platforms 46 00:02:27,680 --> 00:02:31,640 Speaker 4: into doing you know, into into and it's another thing 47 00:02:31,680 --> 00:02:34,680 Speaker 4: like a conservative saying that you know they're being unfair 48 00:02:34,720 --> 00:02:37,600 Speaker 4: to us, and it's a question of free speech. So 49 00:02:37,840 --> 00:02:43,240 Speaker 4: the dissent here was the three most conservative justices, Alito, Gorsicic, 50 00:02:43,360 --> 00:02:44,160 Speaker 4: and Thomas. 51 00:02:44,720 --> 00:02:46,520 Speaker 3: How many more cases are going to be? Is that 52 00:02:46,600 --> 00:02:47,239 Speaker 3: it for today? 53 00:02:47,560 --> 00:02:49,960 Speaker 4: There's one other case on public corruption, something that we 54 00:02:50,000 --> 00:02:53,720 Speaker 4: haven't been following, but it continues the Supreme Court's skepticism 55 00:02:53,760 --> 00:02:55,200 Speaker 4: of these public corruption laws. 56 00:02:55,280 --> 00:02:58,040 Speaker 3: All right, June Grasso, the host of Bloomberg Law, with 57 00:02:58,200 --> 00:03:00,480 Speaker 3: me to break down some of these cases. The Supreme 58 00:03:00,480 --> 00:03:04,560 Speaker 3: Court again backing the Biden administration on the social post 59 00:03:04,960 --> 00:03:11,720 Speaker 3: media removal in terms of cases that go against the arguments. 60 00:03:13,400 --> 00:03:17,320 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 61 00:03:17,400 --> 00:03:20,880 Speaker 1: weekdays at ten am Eastern on applecar Play and Android 62 00:03:20,919 --> 00:03:24,120 Speaker 1: Auto with the Bloomberg Business. You can also listen live 63 00:03:24,200 --> 00:03:27,360 Speaker 1: on Amazon Alexa from our flagship New York station, Just 64 00:03:27,440 --> 00:03:31,000 Speaker 1: say Alexa Play Bloomberg eleven thirty. 65 00:03:31,560 --> 00:03:32,760 Speaker 5: Let's get back to FedEx. 66 00:03:33,120 --> 00:03:36,480 Speaker 6: Thomas black is the Bloomberg opinion columnists covering logistics, manufacturing, 67 00:03:36,560 --> 00:03:38,080 Speaker 6: and aerospace, joining us. 68 00:03:38,120 --> 00:03:40,360 Speaker 5: Now, So what did you make of that news? In particular? 69 00:03:41,600 --> 00:03:44,839 Speaker 6: A strategic spinoff maybe, or strategic options, I should say 70 00:03:44,880 --> 00:03:45,920 Speaker 6: for its freight unit. 71 00:03:45,960 --> 00:03:47,960 Speaker 5: That pretty much surprised a lot of analysts. What did 72 00:03:47,960 --> 00:03:48,440 Speaker 5: you make of that? 73 00:03:49,880 --> 00:03:53,680 Speaker 7: It was surprising. It potentially could unlock a lot of value, 74 00:03:53,720 --> 00:03:55,720 Speaker 7: and I think that's why the stock price is up 75 00:03:56,240 --> 00:04:00,920 Speaker 7: around fifteen percent today. Investors see that as kind of 76 00:04:00,920 --> 00:04:04,280 Speaker 7: a little gold nugget that's been hidden in FedEx. It's 77 00:04:04,320 --> 00:04:10,640 Speaker 7: the largest less than truckload carrier, and those trucking companies 78 00:04:10,720 --> 00:04:14,520 Speaker 7: tend to have pretty high valuations right now, so they 79 00:04:14,640 --> 00:04:16,920 Speaker 7: could definitely unlock some value. 80 00:04:17,960 --> 00:04:21,200 Speaker 2: So is the expectation that they will spin that out 81 00:04:21,520 --> 00:04:24,200 Speaker 2: or ipo it. What mechanism were they discussing? 82 00:04:24,200 --> 00:04:27,800 Speaker 7: Do you think they didn't want to talk about it? 83 00:04:27,880 --> 00:04:30,720 Speaker 7: They were asked several questions about that on the conference call, 84 00:04:30,760 --> 00:04:33,400 Speaker 7: and they batted them all away. They're going to review it. 85 00:04:33,880 --> 00:04:37,799 Speaker 7: Spin out would be would be easier to do, probably 86 00:04:37,839 --> 00:04:42,080 Speaker 7: more tax friendly as well. They could sell it, sure 87 00:04:42,080 --> 00:04:44,480 Speaker 7: there would be some interested buyers in there. It's a 88 00:04:44,520 --> 00:04:47,600 Speaker 7: pretty high margin business for the trucking company, for trucking 89 00:04:47,640 --> 00:04:52,360 Speaker 7: industry IPO. I presume they could do that as well. 90 00:04:52,640 --> 00:04:55,719 Speaker 7: A spin would probably be the better way to get it, 91 00:04:56,000 --> 00:04:57,080 Speaker 7: you know, trading. 92 00:04:57,480 --> 00:05:01,120 Speaker 2: Yep, you know, just looking at this just the most 93 00:05:01,120 --> 00:05:03,440 Speaker 2: recent results. You know, they're talking about their forecast revenue 94 00:05:03,440 --> 00:05:05,600 Speaker 2: will grow in the load a mid single digit percentage 95 00:05:06,240 --> 00:05:09,200 Speaker 2: in the upcoming period. But boy, they're talking about a 96 00:05:09,200 --> 00:05:13,400 Speaker 2: big gain in EPs net profitability. What are they doing 97 00:05:13,480 --> 00:05:15,280 Speaker 2: on the cost side that's kind of bringing a lot 98 00:05:15,320 --> 00:05:16,000 Speaker 2: more dollars down? 99 00:05:16,960 --> 00:05:20,240 Speaker 7: Yeah, the FedEx story is all about cost cutting. The 100 00:05:20,279 --> 00:05:22,880 Speaker 7: parcel market is a little soft right now. It's been 101 00:05:22,960 --> 00:05:27,120 Speaker 7: that way for a few quarters. As people the revenge 102 00:05:27,160 --> 00:05:32,599 Speaker 7: traveling and all the revenge experiences that people are buying, 103 00:05:32,600 --> 00:05:36,480 Speaker 7: they're not buying as much stuff, so e commerce in 104 00:05:36,520 --> 00:05:40,159 Speaker 7: the package delivery market's a little flat. So FedEx is 105 00:05:40,279 --> 00:05:43,800 Speaker 7: cutting costs hard. That the new CEO, Rod Supermanium, came 106 00:05:43,800 --> 00:05:45,880 Speaker 7: in a couple of years ago and announced this big 107 00:05:45,920 --> 00:05:48,800 Speaker 7: transformation of FedEx, and he's doing it. There was some 108 00:05:49,160 --> 00:05:52,800 Speaker 7: skepticism about how this would work, but he's winning over 109 00:05:52,880 --> 00:05:57,240 Speaker 7: investors now because they've had several quarters in which they 110 00:05:57,279 --> 00:06:00,520 Speaker 7: have increased margins even though their revenue has been on 111 00:06:00,600 --> 00:06:05,120 Speaker 7: the decline because of the market pressure. So so far, 112 00:06:05,240 --> 00:06:08,000 Speaker 7: so good for mister SUPERMANI. 113 00:06:09,360 --> 00:06:11,920 Speaker 6: So you had a great opinion piece out about FedEx 114 00:06:12,120 --> 00:06:14,560 Speaker 6: and you sort of broke down this logistics business and 115 00:06:14,560 --> 00:06:18,200 Speaker 6: then what would be left afterwards, and how FedEx would 116 00:06:18,200 --> 00:06:21,200 Speaker 6: be then a pure play small packaged delivery company, and 117 00:06:21,240 --> 00:06:23,600 Speaker 6: then you'd have this behemoth logistics company. And is how 118 00:06:23,680 --> 00:06:26,200 Speaker 6: much market share they really own? Can you talk us 119 00:06:26,200 --> 00:06:28,080 Speaker 6: through some of those numbers, because I think of what's 120 00:06:28,120 --> 00:06:30,080 Speaker 6: left of FedEx will be quite interesting in how to 121 00:06:30,160 --> 00:06:30,640 Speaker 6: value it. 122 00:06:31,960 --> 00:06:35,520 Speaker 7: Right, So what they would spin out would be there 123 00:06:36,040 --> 00:06:40,000 Speaker 7: less than truckbload UH trucking company. And these are these 124 00:06:40,000 --> 00:06:44,400 Speaker 7: are companies that have a network of warehouses and they 125 00:06:44,400 --> 00:06:48,400 Speaker 7: bring in customers goods and they consolidate them so that 126 00:06:48,440 --> 00:06:51,240 Speaker 7: they can fill a full trailer instead of just taking 127 00:06:51,320 --> 00:06:54,440 Speaker 7: a partial trailer. So they're essentially a trucking It's a 128 00:06:54,480 --> 00:06:57,000 Speaker 7: trucking company. So FedEx is going to keep all of 129 00:06:57,040 --> 00:07:00,440 Speaker 7: its UH if it did spin that, it would keep 130 00:07:00,480 --> 00:07:03,640 Speaker 7: all of its package delivery business. It also has some 131 00:07:03,920 --> 00:07:08,760 Speaker 7: logistics business in which it helps customers move freight around 132 00:07:08,760 --> 00:07:12,960 Speaker 7: the world. They do custom stuff and freight forwarding and 133 00:07:12,960 --> 00:07:15,480 Speaker 7: so forth, so they would keep that as well with 134 00:07:15,920 --> 00:07:18,440 Speaker 7: the main company. So this would be a trucking company. 135 00:07:19,240 --> 00:07:26,200 Speaker 7: They've tried in the past to help to merge these 136 00:07:26,200 --> 00:07:29,080 Speaker 7: companies a little bit more, in other words, having the 137 00:07:29,120 --> 00:07:32,760 Speaker 7: trucking company do some of the package delivery and so forth, 138 00:07:32,880 --> 00:07:36,360 Speaker 7: especially some of the large packages. I'm not sure it 139 00:07:36,400 --> 00:07:38,840 Speaker 7: worked out that well, So maybe that's why they're pivoting 140 00:07:38,880 --> 00:07:41,560 Speaker 7: and saying, well, maybe we could unlock more value instead 141 00:07:41,560 --> 00:07:43,720 Speaker 7: of trying to integrate it more into our system, let's 142 00:07:43,760 --> 00:07:45,000 Speaker 7: just go ahead and carve it out. 143 00:07:47,160 --> 00:07:49,120 Speaker 2: You know, when we talk cost custs in this business, 144 00:07:49,160 --> 00:07:51,400 Speaker 2: a lot of times it means headcount. What have they 145 00:07:51,440 --> 00:07:53,200 Speaker 2: done on the headcount front, because it just seems like 146 00:07:53,240 --> 00:07:54,600 Speaker 2: a labor intensive business. 147 00:07:56,240 --> 00:07:59,440 Speaker 7: They've definitely have lowered some headcount. I don't have the 148 00:07:59,520 --> 00:08:01,560 Speaker 7: numbers off the top of my head, but that's that's 149 00:08:01,600 --> 00:08:04,960 Speaker 7: one of the things. The other is they're trying to 150 00:08:04,960 --> 00:08:09,880 Speaker 7: consolidate their networks. And if they're in the past, if 151 00:08:09,880 --> 00:08:13,480 Speaker 7: there was an express facility and a ground facility in 152 00:08:13,520 --> 00:08:17,440 Speaker 7: the same vicinity, they would just continue to operate those 153 00:08:17,480 --> 00:08:22,400 Speaker 7: and the trucks sometimes would arrive at your house. One 154 00:08:22,440 --> 00:08:24,960 Speaker 7: would be an express truck, one would be a ground truck. 155 00:08:25,080 --> 00:08:28,280 Speaker 7: They're trying to eliminate a lot of that duplication so 156 00:08:28,760 --> 00:08:32,679 Speaker 7: in some cases they're consolidating facilities, they're handing off packages 157 00:08:33,040 --> 00:08:36,720 Speaker 7: so that only one driver comes to your door or 158 00:08:36,760 --> 00:08:40,520 Speaker 7: your business. So that's another way in which they're cutting costs. 159 00:08:41,000 --> 00:08:43,600 Speaker 7: It's not all just head counted operational. 160 00:08:44,240 --> 00:08:47,320 Speaker 6: Yeah, and clearly also, you know, spinning on the logistic 161 00:08:47,360 --> 00:08:49,720 Speaker 6: business will help them cash flow there real quick before 162 00:08:49,720 --> 00:08:52,400 Speaker 6: you let you go. If the spinoff of logistic business 163 00:08:52,400 --> 00:08:54,160 Speaker 6: went the way of M and A, who might be 164 00:08:54,200 --> 00:08:55,080 Speaker 6: potential buyers? 165 00:08:55,320 --> 00:08:56,000 Speaker 2: Oh, good question. 166 00:08:57,720 --> 00:09:00,400 Speaker 7: That's a little bit of shaky ground. But there are 167 00:09:00,400 --> 00:09:04,520 Speaker 7: some large LTL players out there. I'd have to say 168 00:09:04,679 --> 00:09:10,240 Speaker 7: XBO would come to mind, maybe because they have their chairman, 169 00:09:10,480 --> 00:09:13,640 Speaker 7: Brad Jacobs has made a living by acquiring companies, so 170 00:09:14,000 --> 00:09:17,000 Speaker 7: I wouldn't put them. I would put them on the list. 171 00:09:17,640 --> 00:09:22,680 Speaker 7: In fact, when Yellow, which is another LTL carrier, went bankrupt, 172 00:09:23,280 --> 00:09:26,480 Speaker 7: XBO bought the most of the assets. The assets were 173 00:09:26,480 --> 00:09:29,840 Speaker 7: all divided up and sold and XBO came out with 174 00:09:29,920 --> 00:09:33,840 Speaker 7: the lion's share of those. So it's it's it's willing 175 00:09:33,840 --> 00:09:36,360 Speaker 7: to expand through acquisition, So I would put them on 176 00:09:36,400 --> 00:09:36,720 Speaker 7: the list. 177 00:09:38,520 --> 00:09:40,480 Speaker 2: All right, Very good, Thomas Black, Thank you very much 178 00:09:40,480 --> 00:09:43,400 Speaker 2: for joining us. Really appreciate Thomas Black, Bloomberg opinion columnists, 179 00:09:43,440 --> 00:09:45,600 Speaker 2: just giving us the latest on FedEx better and expect 180 00:09:45,600 --> 00:09:48,360 Speaker 2: the results. Taking guidance up stock moving up here about 181 00:09:48,360 --> 00:09:51,000 Speaker 2: about thirteen fourteen percent fifty two week high. About that 182 00:09:51,080 --> 00:09:52,720 Speaker 2: for our friends at FedEx. 183 00:09:54,160 --> 00:09:58,040 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 184 00:09:58,120 --> 00:10:01,480 Speaker 1: weekdays at ten am Eastern car playing and broud Otto 185 00:10:01,559 --> 00:10:04,520 Speaker 1: with the Bloomberg Business app. Listening on demand wherever you 186 00:10:04,520 --> 00:10:08,240 Speaker 1: get your podcasts, or watch us live on YouTube. 187 00:10:09,280 --> 00:10:12,840 Speaker 2: We're live here at the very loud Bloomberg invest Conference 188 00:10:12,840 --> 00:10:15,120 Speaker 2: in Lower Manhattan. It's called the World Financial Center for 189 00:10:15,120 --> 00:10:16,839 Speaker 2: those of us that were actually here back in the 190 00:10:16,920 --> 00:10:19,199 Speaker 2: day down in Lower Manhattan, which by the way, is 191 00:10:19,240 --> 00:10:21,400 Speaker 2: a great place. I'm gonna plug it yet again. Come 192 00:10:21,440 --> 00:10:23,240 Speaker 2: down here in warm weather with the kids and stuff. 193 00:10:23,280 --> 00:10:24,960 Speaker 2: There's you know, you're right on the river. Lots of 194 00:10:24,960 --> 00:10:26,600 Speaker 2: cool restaurants, a lot of fun places for the kids 195 00:10:26,600 --> 00:10:29,120 Speaker 2: are run around, big yachts there to look at. So 196 00:10:29,160 --> 00:10:30,520 Speaker 2: it's a great part of the city that I think 197 00:10:30,559 --> 00:10:33,240 Speaker 2: a lot of people kind of miss here. So in video, 198 00:10:33,320 --> 00:10:35,199 Speaker 2: is that our drawdown the last few you know, that 199 00:10:35,320 --> 00:10:37,200 Speaker 2: was it? That was it? Okay, now we're back up 200 00:10:37,240 --> 00:10:40,199 Speaker 2: at it all right in videos up taking up the 201 00:10:40,280 --> 00:10:42,120 Speaker 2: nastac so so so there you go. Let's talk about 202 00:10:42,120 --> 00:10:44,240 Speaker 2: these markets here and where we go. Clark Chang, CEO 203 00:10:44,280 --> 00:10:48,480 Speaker 2: and Chief investment Officer Merrimack Corporation. Clark is a Fuqua 204 00:10:48,840 --> 00:10:52,160 Speaker 2: graduate at Duke University, so he's he's much younger than 205 00:10:52,160 --> 00:10:55,320 Speaker 2: I am, but we will both went to the business exactly. 206 00:10:55,480 --> 00:10:58,640 Speaker 2: Hey Clark, what do you feel about these markets here? 207 00:10:58,720 --> 00:11:01,440 Speaker 2: What's kind of how are you approaching them right here? 208 00:11:01,480 --> 00:11:04,160 Speaker 2: Because we've got a FED that presumably is going to 209 00:11:04,160 --> 00:11:06,600 Speaker 2: be cutting raged at some time, I guess later rather 210 00:11:06,600 --> 00:11:10,200 Speaker 2: than that, the sooner we've got decent earnings, how are 211 00:11:10,200 --> 00:11:11,000 Speaker 2: you guys approaching it? 212 00:11:11,160 --> 00:11:13,240 Speaker 8: I think the FED is thinking they're going to start 213 00:11:13,240 --> 00:11:15,439 Speaker 8: cutting rage, So that's what people think in September and stuff. 214 00:11:15,440 --> 00:11:17,760 Speaker 8: I think every time we talk about this it keeps 215 00:11:17,760 --> 00:11:21,000 Speaker 8: getting delayed more and more, and I don't I think 216 00:11:21,040 --> 00:11:23,640 Speaker 8: this market is very dependent on what the FED does, 217 00:11:23,679 --> 00:11:26,360 Speaker 8: and they're timing of it. So growth is slowing down, 218 00:11:26,520 --> 00:11:29,680 Speaker 8: unemployment is slowly starting to increase, things are heading in 219 00:11:29,679 --> 00:11:32,160 Speaker 8: the right direction, Inflation is coming down, and it just 220 00:11:32,160 --> 00:11:35,400 Speaker 8: depends on how the FED reacts. If they react too quickly. 221 00:11:35,920 --> 00:11:38,200 Speaker 8: I think we could go the wrong direction. May they 222 00:11:38,360 --> 00:11:40,040 Speaker 8: react to slow they go the other direction. So I 223 00:11:40,080 --> 00:11:42,080 Speaker 8: think it's very conditional on how the FED, on how 224 00:11:42,080 --> 00:11:43,240 Speaker 8: the FED basically performs. 225 00:11:43,360 --> 00:11:46,360 Speaker 6: What I was struck with over the last day listening 226 00:11:46,400 --> 00:11:48,520 Speaker 6: to a lot of the Bloomberg in Best Panels is 227 00:11:48,559 --> 00:11:50,680 Speaker 6: how little the FED was really talked about, Like it 228 00:11:50,720 --> 00:11:52,280 Speaker 6: was a little bit here and there, but it was 229 00:11:52,320 --> 00:11:55,400 Speaker 6: mostly about AI, how to invest, what the potentials are, 230 00:11:55,440 --> 00:11:57,480 Speaker 6: and private credit and sort of what do you do 231 00:11:58,080 --> 00:11:59,920 Speaker 6: in that sector as part of the family off of 232 00:12:00,480 --> 00:12:02,760 Speaker 6: how do you guys look at the best investment thesis 233 00:12:02,760 --> 00:12:03,160 Speaker 6: for AI. 234 00:12:04,520 --> 00:12:07,320 Speaker 8: AI is moving so fast that I don't think anyone 235 00:12:07,400 --> 00:12:09,240 Speaker 8: has any idea what's going to happen with it. But 236 00:12:09,600 --> 00:12:12,200 Speaker 8: it's going at an exponential pace. So you know, we 237 00:12:12,240 --> 00:12:15,240 Speaker 8: went from like PCs to the internet, to mobile to 238 00:12:15,679 --> 00:12:18,120 Speaker 8: the cloud, and I think AI is going to be 239 00:12:18,200 --> 00:12:20,120 Speaker 8: much faster. But I think the things that are gonna 240 00:12:20,240 --> 00:12:22,560 Speaker 8: change AI for this next generation, I don't think people 241 00:12:22,600 --> 00:12:25,520 Speaker 8: can even comprehend, like even terms of making like entertainment 242 00:12:25,520 --> 00:12:29,120 Speaker 8: and stuff like that, the like we don't need actors 243 00:12:29,120 --> 00:12:32,439 Speaker 8: and actresses. Sora from Open AI can generate a video live, 244 00:12:32,920 --> 00:12:34,800 Speaker 8: and I think this magic and secret is just in 245 00:12:34,880 --> 00:12:36,200 Speaker 8: terms of how you prompt it. 246 00:12:36,320 --> 00:12:41,440 Speaker 5: I think my artist soul is slowly dying, yes, but. 247 00:12:41,960 --> 00:12:43,400 Speaker 8: It really is changing the world that I don't think 248 00:12:43,440 --> 00:12:45,599 Speaker 8: people even understand. I think the danger of it is 249 00:12:45,600 --> 00:12:48,960 Speaker 8: always going to be the deep fakes, the cybersecurity, all 250 00:12:49,000 --> 00:12:52,480 Speaker 8: that stuff, because I think the hackers are much more 251 00:12:52,480 --> 00:12:54,880 Speaker 8: innovative than the people defending against it, and they only 252 00:12:54,920 --> 00:12:57,040 Speaker 8: have to win once. So I think that's the danger 253 00:12:57,120 --> 00:12:59,720 Speaker 8: of it. I think people are starting to understand this. 254 00:12:59,720 --> 00:13:02,360 Speaker 8: So I think we're starting to see dedicated AI models 255 00:13:02,400 --> 00:13:05,719 Speaker 8: for specific countries. So I think Japan just invested in 256 00:13:05,840 --> 00:13:08,120 Speaker 8: one for their country. I think India is looking at 257 00:13:08,160 --> 00:13:10,360 Speaker 8: it too, because no one wants to be using the 258 00:13:10,559 --> 00:13:14,520 Speaker 8: US LM model. Basically, it's using US data and as 259 00:13:14,559 --> 00:13:17,480 Speaker 8: a result, it reflects more of the US population, the 260 00:13:17,520 --> 00:13:19,559 Speaker 8: Western society and stuff like that. To do that and 261 00:13:19,600 --> 00:13:22,480 Speaker 8: to run that in China is useless because the Chinese 262 00:13:22,520 --> 00:13:25,640 Speaker 8: population they have so many restrictions on jaywalking or chewing 263 00:13:25,640 --> 00:13:27,760 Speaker 8: gum or whatever that it just may not work over there. 264 00:13:28,080 --> 00:13:29,800 Speaker 8: So I think AA is gonna be It's gonna be 265 00:13:29,880 --> 00:13:32,000 Speaker 8: fascinating in terms of how impacts the world. 266 00:13:32,080 --> 00:13:33,040 Speaker 2: The energy usage is. 267 00:13:32,960 --> 00:13:36,280 Speaker 8: Going to be a huge issue. And I mean I 268 00:13:36,120 --> 00:13:37,760 Speaker 8: was I was out in Las Vegas last week and 269 00:13:38,360 --> 00:13:41,560 Speaker 8: William Jensen was actually speaking at an energy conference and 270 00:13:41,600 --> 00:13:43,520 Speaker 8: he's you know, he's a tech guy and he's at 271 00:13:43,520 --> 00:13:44,360 Speaker 8: an energy conference. 272 00:13:44,400 --> 00:13:46,840 Speaker 6: But he was speaking with Edison International, which is the 273 00:13:46,840 --> 00:13:49,240 Speaker 6: CEO that I've spoken to about power usage. 274 00:13:49,240 --> 00:13:50,360 Speaker 5: They're based in California. 275 00:13:51,080 --> 00:13:54,480 Speaker 6: So to that point, do you invest though in this thesis, 276 00:13:54,480 --> 00:13:57,000 Speaker 6: like you're absolutely right, like everything you said makes complete sense. 277 00:13:57,320 --> 00:13:58,360 Speaker 5: Do you make money off of that? 278 00:13:59,040 --> 00:14:00,800 Speaker 8: No, we could definitely make money off I think it's 279 00:14:00,880 --> 00:14:03,439 Speaker 8: changing so quickly. I think the problem is knowing who 280 00:14:03,480 --> 00:14:06,559 Speaker 8: the winner is going to be, no matter what Navidia 281 00:14:06,640 --> 00:14:10,040 Speaker 8: is doing for now, because everything they produce is sold 282 00:14:10,040 --> 00:14:12,839 Speaker 8: out and everyone's trying to get ahead. And if you're 283 00:14:12,840 --> 00:14:14,280 Speaker 8: not buying the chips, you're not going to be on 284 00:14:14,320 --> 00:14:17,400 Speaker 8: the forefront of this technology. So I mean, if they 285 00:14:17,400 --> 00:14:19,520 Speaker 8: can keep the market share that it's fantastic. I think 286 00:14:19,520 --> 00:14:21,320 Speaker 8: they have a mode around them with the software and 287 00:14:21,360 --> 00:14:24,160 Speaker 8: the chip, but I think it's just a home run 288 00:14:24,240 --> 00:14:24,520 Speaker 8: right now. 289 00:14:24,560 --> 00:14:27,360 Speaker 2: And what seems a little bit different AI versus say 290 00:14:27,360 --> 00:14:29,800 Speaker 2: the Internet, for example, is the Internet was a whole 291 00:14:29,800 --> 00:14:34,040 Speaker 2: bunch of new companies, disruptors, whether it's Google or Facebook, 292 00:14:34,520 --> 00:14:37,920 Speaker 2: disrupting the existing business models. Here doesn't seem to be 293 00:14:37,960 --> 00:14:40,120 Speaker 2: that way. It seems to be in Nvidia is the 294 00:14:40,200 --> 00:14:44,240 Speaker 2: chip play. Maybe Microsoft's a software play, you know, and 295 00:14:44,480 --> 00:14:48,520 Speaker 2: it's these existing incumbents that are investing in and building 296 00:14:48,600 --> 00:14:51,440 Speaker 2: up AI capabilities. I guess that's the way to play it. 297 00:14:51,440 --> 00:14:53,720 Speaker 8: It's all it's all in the data. The data is oil. 298 00:14:53,760 --> 00:14:57,320 Speaker 8: The data is what trains these models. The investments that 299 00:14:57,360 --> 00:14:59,680 Speaker 8: you need in the infrastructure in terms of these data 300 00:14:59,720 --> 00:15:02,400 Speaker 8: centers can only come from the largest companies, like say Microsoft. 301 00:15:02,440 --> 00:15:04,880 Speaker 8: I think Microsoft and open ai have a project that 302 00:15:04,880 --> 00:15:07,560 Speaker 8: we working to build the biggest you know, data center 303 00:15:07,560 --> 00:15:10,440 Speaker 8: of the world to basically run AI. So I think 304 00:15:10,480 --> 00:15:12,920 Speaker 8: it is gonna be with those big winners that are 305 00:15:12,960 --> 00:15:15,200 Speaker 8: out there. But if you're a small company, we see 306 00:15:15,200 --> 00:15:17,560 Speaker 8: this a lot on the venture side. You develop something new, 307 00:15:17,640 --> 00:15:20,680 Speaker 8: like say mid Junior, some of these you know videotype 308 00:15:20,680 --> 00:15:24,080 Speaker 8: of creation models, you're you're basically out innovated within six 309 00:15:24,120 --> 00:15:27,760 Speaker 8: months when open I released Sora. So like it's happening 310 00:15:27,800 --> 00:15:29,520 Speaker 8: at such a fast pace set if you're a startup 311 00:15:29,560 --> 00:15:31,720 Speaker 8: and you don't have the capital and the resources and 312 00:15:31,760 --> 00:15:35,040 Speaker 8: the talent to innovate faster than the big guys. Your 313 00:15:35,040 --> 00:15:38,160 Speaker 8: basic business model, business models is basically gone in six months. 314 00:15:38,360 --> 00:15:40,520 Speaker 6: So you were on a panel that was titled meeting 315 00:15:40,640 --> 00:15:42,600 Speaker 6: the Needs of the Rising Generation. 316 00:15:43,280 --> 00:15:44,040 Speaker 5: What does that mean? 317 00:15:44,560 --> 00:15:46,400 Speaker 6: Is that like, we don't have enough kids and everyone 318 00:15:46,520 --> 00:15:48,640 Speaker 6: is gonna get old and there's a big fiscal deficit. 319 00:15:48,720 --> 00:15:51,040 Speaker 6: Does that mean that it's gonna be super isolationist? What 320 00:15:51,080 --> 00:15:51,640 Speaker 6: does that mean? 321 00:15:51,920 --> 00:15:54,800 Speaker 8: I mean we do have a demographic problem. I think 322 00:15:54,840 --> 00:15:56,360 Speaker 8: in the in the modern world where I think the 323 00:15:56,400 --> 00:15:59,080 Speaker 8: population is declining, I think the people are getting older. Well, 324 00:15:59,120 --> 00:16:01,320 Speaker 8: we were talking about earlier is more. There's an eighty 325 00:16:01,360 --> 00:16:03,360 Speaker 8: four trillion dollars of a wealth that's going to be 326 00:16:03,360 --> 00:16:05,960 Speaker 8: transferred from the baby boomers towards the next two generations. 327 00:16:06,000 --> 00:16:08,680 Speaker 8: It's going to happen over the next twenty years. And 328 00:16:10,000 --> 00:16:12,680 Speaker 8: the question is how does it happen? What is this 329 00:16:12,760 --> 00:16:13,360 Speaker 8: next generation? 330 00:16:13,600 --> 00:16:14,240 Speaker 7: Like, what are they? 331 00:16:14,280 --> 00:16:17,040 Speaker 8: What are the what are their intentions? I think I 332 00:16:17,080 --> 00:16:20,680 Speaker 8: think the the generation that generated the wealth after World 333 00:16:20,720 --> 00:16:24,120 Speaker 8: War two, through through housing and through the stock market. 334 00:16:24,480 --> 00:16:27,560 Speaker 8: I mean, their their intention was clear. They were trying 335 00:16:27,600 --> 00:16:29,560 Speaker 8: to generate wealth and have a good cost of living 336 00:16:29,600 --> 00:16:31,360 Speaker 8: and stuff like that. I think the next generation, I 337 00:16:31,360 --> 00:16:33,360 Speaker 8: think is more idealistic, and they do want to help 338 00:16:33,840 --> 00:16:38,680 Speaker 8: solve income inequality, they want to help solve climate impact ESG. Stuff. 339 00:16:39,200 --> 00:16:41,080 Speaker 8: I think the danger with that is the fact that 340 00:16:41,120 --> 00:16:43,640 Speaker 8: if you're not focused on one goal and you have 341 00:16:43,720 --> 00:16:47,120 Speaker 8: conditional goals where this is the best investment relative to climate, 342 00:16:47,480 --> 00:16:49,880 Speaker 8: it's it gets hard to measure how you're actually performing. 343 00:16:49,960 --> 00:16:52,440 Speaker 8: And as a psychologist, we really wanted to make keep 344 00:16:52,480 --> 00:16:54,560 Speaker 8: things simple. We want to have one goal. You can 345 00:16:54,640 --> 00:16:56,400 Speaker 8: have another goal for a different part of your business, 346 00:16:56,480 --> 00:16:58,440 Speaker 8: like say at the foundation, but to combine the two 347 00:16:58,480 --> 00:17:01,200 Speaker 8: into one, I think you really never know how you're doing. 348 00:17:01,960 --> 00:17:05,080 Speaker 2: So from an investment perspective, do you have that in 349 00:17:05,119 --> 00:17:06,240 Speaker 2: your back in your mind? 350 00:17:06,640 --> 00:17:06,880 Speaker 7: ESG. 351 00:17:07,200 --> 00:17:09,840 Speaker 2: And let's not even use those letters because they become toxic. 352 00:17:09,880 --> 00:17:12,600 Speaker 2: I guess it's just just is that part of your 353 00:17:12,640 --> 00:17:15,600 Speaker 2: investment outlook, or you're just there focus on generating the 354 00:17:15,640 --> 00:17:17,000 Speaker 2: best returns for your client. 355 00:17:17,840 --> 00:17:20,080 Speaker 8: We're here to generate returns. And then we have another side, 356 00:17:20,160 --> 00:17:22,600 Speaker 8: the foundation side that does all the charitable stuff. So 357 00:17:22,680 --> 00:17:24,600 Speaker 8: we have two distinct goals and two separate parts of 358 00:17:24,640 --> 00:17:26,600 Speaker 8: our businesses, but we try not to combine the two 359 00:17:26,680 --> 00:17:27,160 Speaker 8: into one. 360 00:17:28,680 --> 00:17:31,879 Speaker 6: Then I guess the question then becomes, how do you 361 00:17:31,920 --> 00:17:34,840 Speaker 6: think of, say the deglobalization part, because you get the 362 00:17:34,880 --> 00:17:37,440 Speaker 6: transfer of wealth. Yes, and we're also going to be 363 00:17:37,480 --> 00:17:40,400 Speaker 6: in an entirely different few decades now as we were 364 00:17:40,440 --> 00:17:42,760 Speaker 6: since like the Industrial revolution, kind of how do you 365 00:17:42,760 --> 00:17:43,360 Speaker 6: think about that? 366 00:17:44,119 --> 00:17:47,360 Speaker 8: I think the world is going in a very bad direction. 367 00:17:47,440 --> 00:17:50,040 Speaker 8: I think if you read Destined for War, you're talking 368 00:17:50,040 --> 00:17:52,520 Speaker 8: about the changes of economic powers. Every time one and 369 00:17:52,560 --> 00:17:55,160 Speaker 8: two changes powered, there is some kind of war, whether 370 00:17:55,200 --> 00:17:56,680 Speaker 8: it be a kinetic war or not. I don't think 371 00:17:56,680 --> 00:17:59,359 Speaker 8: it's going to be the I think we are in 372 00:17:59,400 --> 00:18:01,679 Speaker 8: a cyber war. We are in a tech war. I 373 00:18:01,680 --> 00:18:04,800 Speaker 8: think between China and Russia, North Korea and Iran, they're 374 00:18:04,800 --> 00:18:06,480 Speaker 8: gonna have their own tech stack and the US is 375 00:18:06,520 --> 00:18:08,240 Speaker 8: gonna have our own tech stack with our own allies. 376 00:18:08,280 --> 00:18:11,040 Speaker 8: So there's gonna be two distinct tech stacks are gonna 377 00:18:11,040 --> 00:18:14,879 Speaker 8: be generated from each of these groups of nations. But 378 00:18:14,920 --> 00:18:16,479 Speaker 8: I don't think we're going to share stuff. If you're 379 00:18:16,520 --> 00:18:18,840 Speaker 8: reading the book of How the World Ends, they talk 380 00:18:18,880 --> 00:18:21,439 Speaker 8: about all the cyber stuff, but it is scary the 381 00:18:21,440 --> 00:18:24,120 Speaker 8: stuff that they can do. So I think ultimately that's 382 00:18:24,160 --> 00:18:25,879 Speaker 8: where we're going. And as a result, I think the 383 00:18:26,000 --> 00:18:29,080 Speaker 8: globalization is going to happen. That is going to be inflationary. However, 384 00:18:29,080 --> 00:18:31,639 Speaker 8: that's going to go against AI, which is going to 385 00:18:31,720 --> 00:18:32,919 Speaker 8: be very disinflationary too. 386 00:18:33,080 --> 00:18:34,840 Speaker 2: Because we grew up in a general I'm gonna say 387 00:18:34,840 --> 00:18:38,480 Speaker 2: the last at least a generation was all about globalization 388 00:18:38,680 --> 00:18:44,320 Speaker 2: bringing barriers down out sign and then I know that 389 00:18:44,400 --> 00:18:48,040 Speaker 2: turned maybe four or five, six, seven years ago. Is 390 00:18:48,080 --> 00:18:48,960 Speaker 2: globalization dead? 391 00:18:49,000 --> 00:18:49,360 Speaker 5: Do you think? 392 00:18:49,600 --> 00:18:51,679 Speaker 8: I don't know if it's dead. It just made me 393 00:18:51,720 --> 00:18:55,080 Speaker 8: more compartmentalized within each country's allies and stuff like that. 394 00:18:55,119 --> 00:18:56,680 Speaker 8: It's just but I don't think it's going to be 395 00:18:56,680 --> 00:18:59,560 Speaker 8: as global as it was before because China wasn't a threat, 396 00:18:59,640 --> 00:19:02,639 Speaker 8: nor were the power economic power we were trying to 397 00:19:02,720 --> 00:19:05,240 Speaker 8: I can convince him to come towards the US type 398 00:19:05,240 --> 00:19:07,879 Speaker 8: of you know, type big Colombian market, but they're not 399 00:19:07,920 --> 00:19:09,840 Speaker 8: going to head in that direction. So I think the 400 00:19:09,880 --> 00:19:12,160 Speaker 8: world is changing right now and it's gonna be really 401 00:19:12,160 --> 00:19:13,480 Speaker 8: interesting for this next generation. 402 00:19:13,920 --> 00:19:16,679 Speaker 6: All right, Clark, we really appreciate Clark Chang's CEO and 403 00:19:16,760 --> 00:19:21,560 Speaker 6: CIO of Marymac Corporation joining us here at Bloomberg invest 404 00:19:21,840 --> 00:19:24,200 Speaker 6: I have to say, I don't envy having to think 405 00:19:24,240 --> 00:19:26,800 Speaker 6: about these themes in the next few decades when literally 406 00:19:26,840 --> 00:19:29,439 Speaker 6: nobody knows what it's going to be, whether it's AI 407 00:19:29,720 --> 00:19:32,680 Speaker 6: and how that cyclical nature of that industry works, whether 408 00:19:32,760 --> 00:19:35,280 Speaker 6: it's deglobilization and what that winds up looking like. 409 00:19:35,800 --> 00:19:37,760 Speaker 5: It is very confusing. 410 00:19:39,359 --> 00:19:43,280 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 411 00:19:43,359 --> 00:19:46,880 Speaker 1: weekdays at ten am Eastern on applecar Play and Android 412 00:19:46,920 --> 00:19:49,680 Speaker 1: Auto with the Bloomberg Business app. You can also listen 413 00:19:49,800 --> 00:19:52,880 Speaker 1: live on Amazon Alexa from our flagship New York station 414 00:19:53,240 --> 00:19:56,280 Speaker 1: Just Say Alexa Play Bloomberg eleven thirty. 415 00:19:57,640 --> 00:19:59,000 Speaker 5: Alex you alongside Paul Sweeny. 416 00:19:59,119 --> 00:20:02,040 Speaker 6: We are live from the Bloomberg and Best Conference in Manhattan, 417 00:20:02,160 --> 00:20:03,800 Speaker 6: Lawer Manhattan, a beautiful. 418 00:20:03,400 --> 00:20:04,840 Speaker 5: Two two five a Liberty Street. 419 00:20:04,960 --> 00:20:08,800 Speaker 6: We're bringing together leaders from asset management, banking and private markets. 420 00:20:08,840 --> 00:20:10,840 Speaker 6: Well here on set, I have a special guest for you. 421 00:20:10,880 --> 00:20:13,560 Speaker 6: Rebecca Lynn is co founder and general partner of Canvas 422 00:20:13,680 --> 00:20:17,159 Speaker 6: Ventures now. Canvas Ventures was founded in twenty thirteen and 423 00:20:17,160 --> 00:20:22,160 Speaker 6: focuses on leading Series A and Series B investments around AI, say, fintech, 424 00:20:22,600 --> 00:20:25,080 Speaker 6: digital health, A lot of stuff going on in that space, 425 00:20:25,080 --> 00:20:25,959 Speaker 6: and Rebecca joins us. 426 00:20:25,960 --> 00:20:27,920 Speaker 5: Now, Rebecca, thank you so much for joining us. 427 00:20:28,080 --> 00:20:28,960 Speaker 9: Thank you for having me. 428 00:20:29,280 --> 00:20:31,920 Speaker 6: So what do you like right now? Like, what's interesting 429 00:20:32,000 --> 00:20:35,080 Speaker 6: to you? What's the market like? Give us some perspective 430 00:20:35,119 --> 00:20:36,920 Speaker 6: of how you're thinking about things. 431 00:20:37,440 --> 00:20:39,800 Speaker 9: Yeah, there's a lot that's happening right now in the 432 00:20:39,800 --> 00:20:42,920 Speaker 9: market overall. I think AI is creating a real catalyst. 433 00:20:42,960 --> 00:20:44,920 Speaker 9: We're hearing a lot about, you know, jen Ai with 434 00:20:45,040 --> 00:20:47,720 Speaker 9: the launch of chat JPT just a year and a 435 00:20:47,760 --> 00:20:50,879 Speaker 9: half ago. And the interesting thing is is this has 436 00:20:50,920 --> 00:20:53,160 Speaker 9: been evolving for some time. I mean, we've been tracking 437 00:20:53,160 --> 00:20:55,400 Speaker 9: the LLLM and the AI space for many years. We've 438 00:20:55,400 --> 00:20:57,320 Speaker 9: had a number of exits in this space, you know, 439 00:20:57,400 --> 00:20:59,800 Speaker 9: way dating back to Siri, you know, in my prior 440 00:21:00,880 --> 00:21:03,560 Speaker 9: and most recently case text. And so what we're seeing 441 00:21:03,760 --> 00:21:07,920 Speaker 9: is that Jenai can really supercharge many of the theses 442 00:21:07,960 --> 00:21:10,440 Speaker 9: we've had for a very long time in both fintech 443 00:21:10,640 --> 00:21:15,000 Speaker 9: and in digital health. One example is the ability to 444 00:21:15,440 --> 00:21:18,040 Speaker 9: actually take all the call volume, for example, off of 445 00:21:18,080 --> 00:21:21,760 Speaker 9: a physician practice is an incredible opportunity. Wealth Management is 446 00:21:21,760 --> 00:21:25,399 Speaker 9: another company that we recently recently let an investment in 447 00:21:25,480 --> 00:21:30,240 Speaker 9: where the company can actually perform all of the back 448 00:21:30,280 --> 00:21:33,199 Speaker 9: office functionality that a wealth manager would typically do and 449 00:21:33,280 --> 00:21:35,840 Speaker 9: quite frankly doesn't really want to do, right, all of 450 00:21:35,880 --> 00:21:39,480 Speaker 9: the back office compliance, the emails, the reporting, the generation 451 00:21:39,560 --> 00:21:41,920 Speaker 9: of reports, things that would take them ten to fifteen 452 00:21:41,920 --> 00:21:45,280 Speaker 9: hours on average a week. JENAI can now lift off 453 00:21:45,280 --> 00:21:47,440 Speaker 9: their shoulders and let them do what they do best, 454 00:21:47,480 --> 00:21:49,280 Speaker 9: which is really interface with the clients. 455 00:21:49,440 --> 00:21:52,199 Speaker 2: Right. So one of the things as I talked to 456 00:21:52,320 --> 00:21:57,359 Speaker 2: just investors, they're saying, where's that AHA moment for AI? 457 00:21:57,440 --> 00:21:59,920 Speaker 2: From an IPO perspective? So for example, for search we had, 458 00:22:00,480 --> 00:22:05,120 Speaker 2: for social we had Facebook. Should we be anticipating an 459 00:22:05,160 --> 00:22:07,359 Speaker 2: Aha ipel to come out of Sandhill Road and just 460 00:22:07,400 --> 00:22:08,359 Speaker 2: blow the market away? 461 00:22:10,080 --> 00:22:13,520 Speaker 9: You know, as an investor in early stage or early growth, right, 462 00:22:14,040 --> 00:22:17,520 Speaker 9: we actually think the Aha moment is M and A OK. 463 00:22:17,720 --> 00:22:20,400 Speaker 9: And so what's going to happen is all of these 464 00:22:20,440 --> 00:22:24,520 Speaker 9: companies that are focused on solving real world problems with 465 00:22:24,560 --> 00:22:28,080 Speaker 9: AI are going to be acquired by these very large 466 00:22:28,119 --> 00:22:30,600 Speaker 9: tech companies that have consumer bases they can sell into. 467 00:22:30,840 --> 00:22:33,160 Speaker 9: And that's what happened with case Text, right. Case Text 468 00:22:33,200 --> 00:22:36,240 Speaker 9: had ten thousand of its own users, but their AI 469 00:22:36,280 --> 00:22:39,920 Speaker 9: product was fundamentally disrupting all of Thompson Router's Oh and 470 00:22:39,960 --> 00:22:43,440 Speaker 9: so Thompson Reuters had said publicly that they were going 471 00:22:43,520 --> 00:22:46,919 Speaker 9: to invest a billion dollars in AI technology because they 472 00:22:46,960 --> 00:22:51,080 Speaker 9: saw it disruptive to their entire business, right, and instead 473 00:22:51,080 --> 00:22:53,520 Speaker 9: they bought case text, which they could plug right into 474 00:22:53,560 --> 00:22:55,440 Speaker 9: their existing customer base. 475 00:22:55,560 --> 00:22:57,800 Speaker 6: Do you feel like the regulatory environment is going to 476 00:22:57,800 --> 00:22:59,840 Speaker 6: allow for stuff like that? Because I feel like, if, 477 00:23:00,000 --> 00:23:05,000 Speaker 6: if anything, big tech making making big deals based on 478 00:23:05,119 --> 00:23:07,480 Speaker 6: things that they need and don't want to compete against, 479 00:23:07,600 --> 00:23:08,119 Speaker 6: it's not going to. 480 00:23:08,119 --> 00:23:08,640 Speaker 5: Go so well. 481 00:23:09,000 --> 00:23:11,440 Speaker 9: I mean, if they if they truly have a monopoly, right, 482 00:23:11,480 --> 00:23:13,600 Speaker 9: But I think regulatory right now has bigger fish to 483 00:23:13,680 --> 00:23:14,400 Speaker 9: fry personally. 484 00:23:14,560 --> 00:23:17,800 Speaker 2: Okay, how about just fundraising in general? If I have 485 00:23:17,800 --> 00:23:20,200 Speaker 2: an idea, I go to Sandhill Road and I try 486 00:23:20,200 --> 00:23:23,280 Speaker 2: to get some capital. What's it like these days in 487 00:23:23,400 --> 00:23:25,600 Speaker 2: raising capital? If I do I have to have an 488 00:23:25,640 --> 00:23:28,520 Speaker 2: AI angle, can I get something done? Otherwise? What's it 489 00:23:28,680 --> 00:23:29,800 Speaker 2: like raising money these days? 490 00:23:30,280 --> 00:23:32,520 Speaker 9: You know what it's like raising money? I think it's 491 00:23:32,760 --> 00:23:36,280 Speaker 9: very like the general the ecosystem. I first came into 492 00:23:36,320 --> 00:23:38,760 Speaker 9: venture in in that O eight O nine time period 493 00:23:39,680 --> 00:23:43,000 Speaker 9: where you know, the markets were a little bit frozen. 494 00:23:43,160 --> 00:23:45,439 Speaker 9: In terms of early stage, we're seeing a decrease in 495 00:23:45,480 --> 00:23:48,159 Speaker 9: like the seed and the A funding. Definitely seeing a 496 00:23:48,160 --> 00:23:51,399 Speaker 9: lot more down rounds in the later stage. However, that 497 00:23:51,600 --> 00:23:53,399 Speaker 9: was the biggest fund I've been involved in. That was 498 00:23:53,440 --> 00:23:56,919 Speaker 9: a monster fund, right because what's happening right now is 499 00:23:56,960 --> 00:23:59,439 Speaker 9: the same thing that happened back then. Where you know, 500 00:23:59,560 --> 00:24:02,520 Speaker 9: venture capital firms have record amounts of cash, but because 501 00:24:02,520 --> 00:24:06,000 Speaker 9: their valuations of their current companies got so over their skis, 502 00:24:06,400 --> 00:24:08,840 Speaker 9: they're having to put their money and their current companies 503 00:24:08,880 --> 00:24:11,359 Speaker 9: and not invest as much in new companies. And so 504 00:24:11,440 --> 00:24:13,840 Speaker 9: if you kept sort of, if you kept sort of 505 00:24:13,840 --> 00:24:15,960 Speaker 9: in a steady pace like we did, you're able to 506 00:24:16,040 --> 00:24:18,960 Speaker 9: still invest in all of those new y early stage companies. 507 00:24:18,960 --> 00:24:21,000 Speaker 9: But for the early stage company, it's nice because you 508 00:24:21,040 --> 00:24:24,800 Speaker 9: don't have fifty other competitors being also backed, so you 509 00:24:24,880 --> 00:24:26,480 Speaker 9: have some runway to move. 510 00:24:27,000 --> 00:24:28,920 Speaker 6: In terms of exit strategies. I know you said M 511 00:24:28,960 --> 00:24:30,560 Speaker 6: and A, is you think how it's going to go? 512 00:24:30,960 --> 00:24:32,880 Speaker 6: What do you think the IPO market does, like when 513 00:24:32,920 --> 00:24:33,680 Speaker 6: does that open up? 514 00:24:33,920 --> 00:24:34,120 Speaker 7: When? 515 00:24:34,359 --> 00:24:37,560 Speaker 9: So my crystal ball is not here with me today, However, 516 00:24:38,200 --> 00:24:41,159 Speaker 9: you know, I think it's incredible what we've seen in 517 00:24:41,200 --> 00:24:45,160 Speaker 9: the pipeline for IPOs. Right when we took Doximity public, 518 00:24:45,600 --> 00:24:48,639 Speaker 9: the rule of thumb back then was, you know, one 519 00:24:48,720 --> 00:24:51,840 Speaker 9: hundred million plus in revenue, you know, thirty percent to 520 00:24:51,920 --> 00:24:55,040 Speaker 9: fifty percent growth year over year, you know, profitability. And 521 00:24:55,080 --> 00:24:57,200 Speaker 9: they were profitable and they went out, which I think 522 00:24:57,240 --> 00:24:58,359 Speaker 9: is very important. 523 00:24:58,640 --> 00:24:59,879 Speaker 5: In the hopper we have. 524 00:25:00,000 --> 00:25:03,680 Speaker 9: We have companies that have a billion dollars of revenue 525 00:25:03,880 --> 00:25:07,360 Speaker 9: and are profitable, and so I think, what as soon 526 00:25:07,400 --> 00:25:10,000 Speaker 9: as they're still private and they're still private, and we 527 00:25:10,000 --> 00:25:12,200 Speaker 9: can talk about maybe why they're still private, but they're 528 00:25:12,240 --> 00:25:14,239 Speaker 9: still private. And so when those go out and they 529 00:25:14,240 --> 00:25:17,000 Speaker 9: go public and they have already proven their ability quarter 530 00:25:17,119 --> 00:25:19,520 Speaker 9: over quarter to hit their plan and to hit their 531 00:25:19,520 --> 00:25:21,840 Speaker 9: benchmarks and to be able to predict it. It's the 532 00:25:21,920 --> 00:25:24,560 Speaker 9: number one recipe for success is to be able to 533 00:25:24,560 --> 00:25:27,199 Speaker 9: being able to forecast and predict accurately. It's what we found. 534 00:25:27,880 --> 00:25:30,000 Speaker 9: I think that's going to bolster the market overall and 535 00:25:30,080 --> 00:25:33,399 Speaker 9: really open the gates for other companies when that happens real. 536 00:25:33,320 --> 00:25:35,240 Speaker 2: Quick thirty seconds. What's it like for you to raise 537 00:25:35,320 --> 00:25:37,240 Speaker 2: venture capital money? Are people still looking to put money 538 00:25:37,240 --> 00:25:37,919 Speaker 2: and venture. 539 00:25:38,200 --> 00:25:40,439 Speaker 9: You know they are looking to put money. Investor but 540 00:25:40,680 --> 00:25:43,480 Speaker 9: in venture. But it's tough because they are really people 541 00:25:43,480 --> 00:25:45,760 Speaker 9: are for some reason are focused on these multi billion 542 00:25:45,800 --> 00:25:47,879 Speaker 9: dollar funds which probably aren't going to return more than 543 00:25:47,880 --> 00:25:50,680 Speaker 9: the public markets. Okay, and so yeah, for an early 544 00:25:50,720 --> 00:25:52,440 Speaker 9: stage fund, I think we have a lot of opportunity. 545 00:25:52,840 --> 00:25:54,919 Speaker 2: Great stuff, Rebecca, thank you so much for joining us. 546 00:25:54,960 --> 00:25:57,399 Speaker 2: Rebecca Lynn, she's a co founder and general partner of 547 00:25:57,440 --> 00:25:59,840 Speaker 2: Canvas Ventures based in San Francisco, but she found her 548 00:25:59,840 --> 00:26:01,800 Speaker 2: way here to Lower man and to be at the 549 00:26:01,800 --> 00:26:05,160 Speaker 2: Bloomberg invest conference here in Lower Manhattan. I always wonder 550 00:26:05,200 --> 00:26:06,879 Speaker 2: what it's like if it's gonna be M and A 551 00:26:07,040 --> 00:26:09,280 Speaker 2: because it just doesn't seem like the IPO market is 552 00:26:09,600 --> 00:26:12,840 Speaker 2: as as I thought it would be up fifteen percent 553 00:26:12,880 --> 00:26:14,760 Speaker 2: this year up, you know, thirty forty percent off that 554 00:26:14,800 --> 00:26:16,080 Speaker 2: October twenty three. 555 00:26:16,160 --> 00:26:16,360 Speaker 6: Low. 556 00:26:16,560 --> 00:26:17,960 Speaker 2: I mean, back in the day, I could get these 557 00:26:18,000 --> 00:26:19,840 Speaker 2: companies out the door. Right, I don't know what's going on. 558 00:26:19,880 --> 00:26:21,320 Speaker 6: I mean, but back in the day, would the M 559 00:26:21,359 --> 00:26:23,280 Speaker 6: and A market have been as robust as maybe it 560 00:26:23,320 --> 00:26:23,840 Speaker 6: could be now? 561 00:26:23,960 --> 00:26:26,439 Speaker 2: Yeah, I don't know. I'm just thinking this younger generation 562 00:26:26,600 --> 00:26:30,440 Speaker 2: just not as Oh, Paul, exactly right. 563 00:26:32,680 --> 00:26:36,560 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 564 00:26:36,640 --> 00:26:40,160 Speaker 1: weekdays at ten am Eastern on applecar Play and Android 565 00:26:40,200 --> 00:26:42,960 Speaker 1: Auto with the Bloomberg Business app. You can also listen 566 00:26:43,080 --> 00:26:46,200 Speaker 1: live on Amazon Alexa from our flagship New York station, 567 00:26:46,560 --> 00:26:50,280 Speaker 1: Just Say Alexa playing Bloomberg eleven thirty. 568 00:26:51,200 --> 00:26:53,200 Speaker 2: Alex Steel Paul Sweeney were live here in a Bloomberg 569 00:26:53,280 --> 00:26:57,320 Speaker 2: Interactor Roker Studio actually downtown at the Bloomberg invest Conference. 570 00:26:57,440 --> 00:27:00,520 Speaker 2: We've moved it downtown to the World Financial ud Bloomberg 571 00:27:00,560 --> 00:27:03,320 Speaker 2: Invest Conference. A lot of good stuff going on down here. 572 00:27:03,760 --> 00:27:05,560 Speaker 2: You know, there's one of the great stories in global 573 00:27:05,560 --> 00:27:08,840 Speaker 2: financial services and wealth management is this supposed transfer of wealth, 574 00:27:08,840 --> 00:27:11,400 Speaker 2: like a jillion dollars of wealth from baby boomers, which 575 00:27:11,400 --> 00:27:14,080 Speaker 2: I qualify by like a year to like the Gen 576 00:27:14,280 --> 00:27:16,120 Speaker 2: X and gen Z. Well, I'll tell you what I've 577 00:27:16,119 --> 00:27:19,159 Speaker 2: told my kids, four of them. The last check I 578 00:27:19,160 --> 00:27:21,320 Speaker 2: write is going to bounce, So don't wait on me, 579 00:27:21,680 --> 00:27:24,320 Speaker 2: get the work and start saving. But I understand it's 580 00:27:24,359 --> 00:27:27,480 Speaker 2: a thing. Emily Green Joints is ahead of wealth management 581 00:27:27,520 --> 00:27:30,880 Speaker 2: at Elvest. Emily, can you frame out what this opportunity 582 00:27:31,040 --> 00:27:34,240 Speaker 2: is in wealth management? Because people are telling me there's 583 00:27:34,280 --> 00:27:36,320 Speaker 2: gonna be a pretty big wealth transfer over the next 584 00:27:36,359 --> 00:27:36,879 Speaker 2: generation or. 585 00:27:36,880 --> 00:27:40,000 Speaker 10: So, Yeah, definitely, and it's already started. Okay, So the 586 00:27:40,520 --> 00:27:44,120 Speaker 10: numbers vary depending on what people say, but it's looking 587 00:27:44,160 --> 00:27:46,879 Speaker 10: at anywhere from eighty four trillion to one hundred and 588 00:27:46,880 --> 00:27:50,399 Speaker 10: twenty nine trillion have been named to actually move to 589 00:27:50,480 --> 00:27:53,000 Speaker 10: the next generations. There's been a lot of talk millennials, 590 00:27:53,040 --> 00:27:55,000 Speaker 10: but to your point, actually Gen X and Gen Z 591 00:27:55,119 --> 00:27:57,879 Speaker 10: have been talked about a lot more more recently as well. 592 00:27:59,119 --> 00:28:01,760 Speaker 10: And what people have really forgotten is actually the first 593 00:28:01,760 --> 00:28:04,560 Speaker 10: transfer is going to go from the husbands to the 594 00:28:04,600 --> 00:28:06,720 Speaker 10: wives within there. And so we talk a lot about 595 00:28:06,760 --> 00:28:09,920 Speaker 10: those millennials, but the wives are actually getting the money already, 596 00:28:09,960 --> 00:28:11,760 Speaker 10: and so this is something that's already ocurring. And so 597 00:28:11,800 --> 00:28:15,520 Speaker 10: you look at thirty trillion dollars by twenty thirty should 598 00:28:15,520 --> 00:28:16,440 Speaker 10: have transferred to women. 599 00:28:16,640 --> 00:28:19,880 Speaker 6: Oh wow, which is really where labs comes in your 600 00:28:19,920 --> 00:28:22,359 Speaker 6: CEO of Sally crowcheck yep. And this is all about 601 00:28:22,440 --> 00:28:25,640 Speaker 6: sort of helping investing in wealth management company that's built 602 00:28:25,680 --> 00:28:28,920 Speaker 6: by women and for women. How does this differ from 603 00:28:29,240 --> 00:28:30,320 Speaker 6: another wealth manager? 604 00:28:30,359 --> 00:28:32,800 Speaker 10: For example, Yeah, I worked at a traditional wealth manager, 605 00:28:32,800 --> 00:28:35,920 Speaker 10: one of the biggest wealth manager for a long time, 606 00:28:36,720 --> 00:28:39,320 Speaker 10: and people often ask us this, and you know number one, 607 00:28:39,520 --> 00:28:41,840 Speaker 10: just the numbers of financial advisors. I think what people 608 00:28:41,840 --> 00:28:44,800 Speaker 10: also forget in this great wealth transfer is that over 609 00:28:44,840 --> 00:28:47,080 Speaker 10: fifty percent of advisors are over the age of fifty five. 610 00:28:47,360 --> 00:28:50,200 Speaker 10: There's going to be an enormous transfer of advisors as well. 611 00:28:50,240 --> 00:28:52,000 Speaker 10: We're starting to see it a lot of people coming 612 00:28:52,040 --> 00:28:54,920 Speaker 10: to us and saying, advisors, my advisor retired, what do 613 00:28:54,960 --> 00:28:55,360 Speaker 10: I do? 614 00:28:56,200 --> 00:28:56,480 Speaker 5: And so? 615 00:28:57,280 --> 00:28:59,080 Speaker 10: And you sit in a lot of rooms. In seventy 616 00:28:59,080 --> 00:29:00,840 Speaker 10: percent of advisors, there's a lot of time or over 617 00:29:00,880 --> 00:29:03,080 Speaker 10: the age of seventy and not below the age of thirty. 618 00:29:03,200 --> 00:29:05,360 Speaker 10: So what's going to happen within here? And so what 619 00:29:05,400 --> 00:29:09,040 Speaker 10: all of us eighty three percent of our team is women. Overall, 620 00:29:09,280 --> 00:29:12,520 Speaker 10: all of our advisors are women. It's very rare within here. 621 00:29:13,000 --> 00:29:16,440 Speaker 10: And so just that we are her within there and 622 00:29:16,480 --> 00:29:18,800 Speaker 10: so that we hear her. And so when people when 623 00:29:18,840 --> 00:29:22,560 Speaker 10: women are going through divorce, widowhood, inheritance, all these things 624 00:29:22,560 --> 00:29:25,880 Speaker 10: that are occurring that our team actually reflects. That has 625 00:29:25,920 --> 00:29:29,360 Speaker 10: been an enormous way for us to actually gather clients 626 00:29:29,400 --> 00:29:31,600 Speaker 10: within here. And then the other thing that we really 627 00:29:31,600 --> 00:29:34,480 Speaker 10: see is these women, this next generation has been looking 628 00:29:34,480 --> 00:29:37,400 Speaker 10: for more impact ESG investing, impact, whatever we want to 629 00:29:37,400 --> 00:29:39,320 Speaker 10: call it. We can throw a lot of labels at this, 630 00:29:39,720 --> 00:29:42,600 Speaker 10: but how do we actually align their values to their money? 631 00:29:43,200 --> 00:29:45,920 Speaker 2: So on the first point there, where do you get 632 00:29:45,920 --> 00:29:49,160 Speaker 2: these young women to be advisors? Where do you get them? 633 00:29:49,200 --> 00:29:51,360 Speaker 2: Because I know even the traditional investment banks have a 634 00:29:51,440 --> 00:29:51,800 Speaker 2: hard time. 635 00:29:51,920 --> 00:29:54,240 Speaker 6: Yeah, No, we just went we just went to an 636 00:29:54,280 --> 00:29:56,520 Speaker 6: event in Nashville. Yeah, and we're just you know. 637 00:29:56,560 --> 00:29:58,640 Speaker 10: It's not easy. And I'll tell you that I spent 638 00:29:58,720 --> 00:30:00,320 Speaker 10: a lot of time looking at it, a lot of 639 00:30:00,360 --> 00:30:02,800 Speaker 10: resumes of people who apply and such. It's not all 640 00:30:02,840 --> 00:30:05,480 Speaker 10: young women, you know. I have some advisors. I one 641 00:30:05,480 --> 00:30:07,920 Speaker 10: of the top advisors on my team a woman in 642 00:30:07,920 --> 00:30:12,080 Speaker 10: her mid fifties. She was a large advisor at Wells 643 00:30:12,160 --> 00:30:14,280 Speaker 10: Fargo for a long time. She went through something that 644 00:30:14,320 --> 00:30:17,800 Speaker 10: was really soul searching for her. She had breast cancer 645 00:30:18,080 --> 00:30:20,040 Speaker 10: and it made her really realize she needed to do 646 00:30:20,080 --> 00:30:22,720 Speaker 10: something more meaningful in her life. And so finding advisors 647 00:30:22,760 --> 00:30:24,720 Speaker 10: like that where she was making a ton of money, 648 00:30:24,760 --> 00:30:26,520 Speaker 10: she was good, she had a huge book of business. 649 00:30:26,720 --> 00:30:28,880 Speaker 10: She didn't need to leave Wells Fargo. You know, these advisors, 650 00:30:28,920 --> 00:30:32,080 Speaker 10: they don't need to make that transition. But she decided 651 00:30:32,080 --> 00:30:34,520 Speaker 10: she'd need to do something more meaningful, and that a 652 00:30:34,560 --> 00:30:37,240 Speaker 10: lot of advisors I find that are in their you know, 653 00:30:37,280 --> 00:30:38,920 Speaker 10: mid thirties and trying to figure out, like how do 654 00:30:39,000 --> 00:30:43,320 Speaker 10: I make something for myself? And really those advisors who 655 00:30:43,600 --> 00:30:46,320 Speaker 10: may be at that point where they're going to have children, 656 00:30:46,600 --> 00:30:48,480 Speaker 10: they're thinking about what their career is going to look 657 00:30:48,520 --> 00:30:50,800 Speaker 10: like at these big banks, at these large broker dealers, 658 00:30:51,160 --> 00:30:53,200 Speaker 10: and they start to reflect and say, I'd rather be 659 00:30:53,280 --> 00:30:56,160 Speaker 10: somewhere like Elevest. And so we've recruited a lot from 660 00:30:56,200 --> 00:30:57,440 Speaker 10: these large broker dealers. 661 00:30:57,480 --> 00:31:00,120 Speaker 6: Well, I was gonna say, what is your recruitment process? 662 00:31:00,160 --> 00:31:02,280 Speaker 6: Like how easy is it to pitch? Like what's the 663 00:31:02,440 --> 00:31:03,360 Speaker 6: what's the track record? 664 00:31:03,520 --> 00:31:07,200 Speaker 10: It's pretty good. We get a lot of applications. I 665 00:31:07,280 --> 00:31:09,000 Speaker 10: always joke to people, people be like, did you see 666 00:31:09,000 --> 00:31:11,000 Speaker 10: my friend's application? Because I do get the emails. I 667 00:31:11,280 --> 00:31:13,800 Speaker 10: don't read everyone's application every single day. We get a 668 00:31:13,840 --> 00:31:17,000 Speaker 10: lot of them. That's so great, it's wonderful in a 669 00:31:17,000 --> 00:31:18,920 Speaker 10: lot of So what do you look for them? It's 670 00:31:19,120 --> 00:31:21,560 Speaker 10: it really varies within here. So I always tell people 671 00:31:21,600 --> 00:31:24,600 Speaker 10: I need a couple of different things. And actually, my 672 00:31:24,680 --> 00:31:28,360 Speaker 10: biggest problem of hiring advisors, especially from the big broker dealers, 673 00:31:28,360 --> 00:31:30,480 Speaker 10: and I come from I worked at JPMorgan where they 674 00:31:30,480 --> 00:31:32,479 Speaker 10: tell you what to say every day. You know you're 675 00:31:32,840 --> 00:31:37,480 Speaker 10: very trained, and is really finding people who can have 676 00:31:37,560 --> 00:31:42,400 Speaker 10: that ability to think for themselves and to learn and 677 00:31:42,440 --> 00:31:44,840 Speaker 10: to realize that our business six months ago was different 678 00:31:44,840 --> 00:31:46,240 Speaker 10: than it is six months from now, and it will 679 00:31:46,280 --> 00:31:48,560 Speaker 10: be different twelve months from now. And so how are 680 00:31:48,640 --> 00:31:52,200 Speaker 10: you actually building with us within there and then really 681 00:31:52,240 --> 00:31:54,720 Speaker 10: thinking about that person who was passionate to our mission. 682 00:31:55,160 --> 00:31:57,400 Speaker 10: I can feel from an advisor if they're just trying 683 00:31:57,400 --> 00:31:59,480 Speaker 10: to come work for Sally Crotcheck or if they really 684 00:31:59,560 --> 00:32:02,520 Speaker 10: want to we want to do and it is always amazing. 685 00:32:02,560 --> 00:32:04,600 Speaker 10: Like I work with Sally very closely. I forget that 686 00:32:04,800 --> 00:32:07,720 Speaker 10: she's Sally, and people you know, they want to meet her, 687 00:32:07,800 --> 00:32:09,320 Speaker 10: they want to go through it, they want to do that. 688 00:32:09,360 --> 00:32:11,160 Speaker 10: And so we do get a good amount of that 689 00:32:11,200 --> 00:32:11,959 Speaker 10: within the process. 690 00:32:12,000 --> 00:32:14,640 Speaker 5: Start with people have oh wow, Sally. 691 00:32:14,640 --> 00:32:16,000 Speaker 10: And so you have to work through the people who 692 00:32:16,040 --> 00:32:17,400 Speaker 10: are going to be able to sit in a room, 693 00:32:17,720 --> 00:32:20,400 Speaker 10: hold their own and show that they actually care about 694 00:32:20,400 --> 00:32:22,840 Speaker 10: the last mission and that they're going to be able 695 00:32:22,920 --> 00:32:23,800 Speaker 10: to relate to women. 696 00:32:24,640 --> 00:32:28,880 Speaker 2: What's a typical Elvest client look like? So and what 697 00:32:28,920 --> 00:32:29,440 Speaker 2: do they need? 698 00:32:29,640 --> 00:32:32,840 Speaker 10: We have clients Elevest overall, we have clients from zero 699 00:32:33,280 --> 00:32:36,240 Speaker 10: to tens of millions. Within there, I run our wealth 700 00:32:36,280 --> 00:32:38,640 Speaker 10: management business and so that has kind of two parts 701 00:32:38,640 --> 00:32:40,480 Speaker 10: within it. We have a mass affluent business and a 702 00:32:40,520 --> 00:32:44,160 Speaker 10: traditional more high ultra high network business. Our average client 703 00:32:44,160 --> 00:32:47,720 Speaker 10: sets between two and ten million of investable assets. We 704 00:32:47,800 --> 00:32:50,400 Speaker 10: do have family offices who come in and we do 705 00:32:50,440 --> 00:32:53,360 Speaker 10: a lot of more private investing within there, and so 706 00:32:53,680 --> 00:32:57,480 Speaker 10: they're typically people who need a financial plan, need that guidance, 707 00:32:57,960 --> 00:33:01,600 Speaker 10: need some decision making in order to think about what 708 00:33:01,640 --> 00:33:04,320 Speaker 10: does retirement look like. I would tell you none of 709 00:33:04,320 --> 00:33:07,600 Speaker 10: our clients. I have one client where retirement means golf 710 00:33:07,760 --> 00:33:09,640 Speaker 10: every day. Most of them it means I want to 711 00:33:09,680 --> 00:33:14,080 Speaker 10: leave my huge mag seven job and go do something different. 712 00:33:14,120 --> 00:33:15,840 Speaker 10: I need to do something meaningful, I want to start 713 00:33:15,840 --> 00:33:18,520 Speaker 10: a business. Whatever that means in us helping guide them 714 00:33:18,520 --> 00:33:22,160 Speaker 10: through that. And then we invest across all ASCID classes. 715 00:33:22,240 --> 00:33:24,880 Speaker 10: So we do stocks, bonds, and alternative investing, and that's 716 00:33:24,880 --> 00:33:27,240 Speaker 10: where we've gathered or a lot of clients. Actually is 717 00:33:27,280 --> 00:33:30,840 Speaker 10: the differentiated alternative investing that we really do, which is 718 00:33:30,880 --> 00:33:32,680 Speaker 10: not the big guys, It's not the names that we 719 00:33:32,720 --> 00:33:35,360 Speaker 10: all know. It's not the places that all the large 720 00:33:35,800 --> 00:33:38,640 Speaker 10: broker dealers put on their platform. These are like bespoke 721 00:33:38,720 --> 00:33:42,240 Speaker 10: managers that could be fifty to a couple hundred million 722 00:33:42,320 --> 00:33:45,760 Speaker 10: in AUM managers, and people really leave some of these 723 00:33:45,800 --> 00:33:50,720 Speaker 10: big broker dealers to have some of these very opportunistic ideas. 724 00:33:50,760 --> 00:33:52,480 Speaker 5: So interesting, really cool. 725 00:33:52,520 --> 00:33:54,240 Speaker 6: I'm the women who come to you, are they also 726 00:33:54,320 --> 00:33:55,800 Speaker 6: tend to be married or is it more just like 727 00:33:55,800 --> 00:33:57,400 Speaker 6: you really focus on the women's side. 728 00:33:57,440 --> 00:34:00,480 Speaker 10: Great question. People ask me this all the time. Yes, 729 00:34:01,200 --> 00:34:03,600 Speaker 10: forty percent of our clients are actually meant in wealth 730 00:34:03,640 --> 00:34:07,880 Speaker 10: management because sometimes women marry men. It happens, and so 731 00:34:08,040 --> 00:34:10,280 Speaker 10: most of them are married. Actually, And what you find 732 00:34:10,360 --> 00:34:12,520 Speaker 10: is a lot of times the woman has to have 733 00:34:12,560 --> 00:34:15,319 Speaker 10: some authority over the money. So she made it, she 734 00:34:15,400 --> 00:34:19,279 Speaker 10: inherited it, she's the one who controls it in some way, 735 00:34:19,520 --> 00:34:22,319 Speaker 10: and she comes and we have clients who maybe for 736 00:34:22,360 --> 00:34:25,040 Speaker 10: a little while they manage their money separately, and then 737 00:34:25,239 --> 00:34:28,920 Speaker 10: a year later he comes overtly, Yeah, comes across the corner, 738 00:34:29,040 --> 00:34:31,120 Speaker 10: you know, comes to that zoom meeting and it's like 739 00:34:31,280 --> 00:34:32,080 Speaker 10: I don't like me. 740 00:34:32,400 --> 00:34:35,160 Speaker 6: Yeah, really amazing, This is such great stuff. I learned 741 00:34:35,200 --> 00:34:36,680 Speaker 6: a lot on the Green Thank you so very much. 742 00:34:36,680 --> 00:34:38,120 Speaker 6: Head of Wealth Management at. 743 00:34:37,960 --> 00:34:40,480 Speaker 5: Elves CEO, of course, is Sally Crocheck. 744 00:34:40,560 --> 00:34:40,759 Speaker 10: There. 745 00:34:42,360 --> 00:34:46,240 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 746 00:34:46,320 --> 00:34:49,840 Speaker 1: weekdays at ten am Eastern on applecar Play and Android 747 00:34:49,880 --> 00:34:52,640 Speaker 1: Auto with the Bloomberg Business at You can also listen 748 00:34:52,760 --> 00:34:55,839 Speaker 1: live on Amazon Alexa from our flagship New York station 749 00:34:56,239 --> 00:35:00,080 Speaker 1: just say Alexa playing Bloomberg eleven thirty. 750 00:35:00,520 --> 00:35:01,960 Speaker 5: All right, malex, you alongside pause. 751 00:35:01,960 --> 00:35:03,920 Speaker 6: We need this at Bloomberg Intelligence Radio and we are 752 00:35:03,960 --> 00:35:07,800 Speaker 6: broadcasting to you live from the Bloomberg invest Write Conference 753 00:35:07,880 --> 00:35:10,719 Speaker 6: right here in Lawer Manhattan, bringing together the leaders from 754 00:35:10,800 --> 00:35:13,320 Speaker 6: asset management, banking in private markets. It's wrapping up in 755 00:35:13,360 --> 00:35:14,959 Speaker 6: just a few hours, but it's been a really fun 756 00:35:15,440 --> 00:35:17,080 Speaker 6: day and a half. We also keep you updated on 757 00:35:17,080 --> 00:35:19,480 Speaker 6: all the fun, juicy Wall Street stories, and for that 758 00:35:19,520 --> 00:35:21,760 Speaker 6: we're going to go back to seven thirty one legs 759 00:35:22,080 --> 00:35:25,600 Speaker 6: to shrin Anarajan in the Bloomberg Interactive Broker Studio. A. Shri, 760 00:35:25,719 --> 00:35:28,400 Speaker 6: you have an amazing big take story that you co 761 00:35:28,480 --> 00:35:30,880 Speaker 6: authored and it's called the last seventy two hours of 762 00:35:30,920 --> 00:35:33,680 Speaker 6: our kegos. I can't imagine what reporting this story out 763 00:35:33,960 --> 00:35:36,480 Speaker 6: must have been like, can you walk us through can 764 00:35:36,520 --> 00:35:39,080 Speaker 6: you give us the cliff notes to the seventy two hours. 765 00:35:39,480 --> 00:35:41,680 Speaker 11: Look, this is a story that's fascinated Wall Street for 766 00:35:41,760 --> 00:35:45,160 Speaker 11: much of the last three years. Right Billhong out of nowhere, 767 00:35:45,800 --> 00:35:50,400 Speaker 11: had built up such enormous wealth, had a family office, 768 00:35:50,440 --> 00:35:53,440 Speaker 11: and yet hid wealth had gone from a billion to 769 00:35:53,520 --> 00:35:56,120 Speaker 11: four billion, from four billion to thirty six billion in 770 00:35:56,160 --> 00:35:59,880 Speaker 11: a span of six months. That all collapsed very publicly 771 00:36:00,080 --> 00:36:02,320 Speaker 11: in March twenty twenty one, when in a matter of 772 00:36:02,440 --> 00:36:06,320 Speaker 11: days he lost his entire fortune. Everyone on Wall Street 773 00:36:06,360 --> 00:36:09,160 Speaker 11: has been trying to figure out what happened, how it happened, 774 00:36:09,200 --> 00:36:11,000 Speaker 11: and a lot of the details have been dribbling out 775 00:36:11,000 --> 00:36:13,520 Speaker 11: for the last few years. But over the last few 776 00:36:13,600 --> 00:36:17,520 Speaker 11: weeks any court room in downtown Manhattan, Bill Huong is 777 00:36:17,600 --> 00:36:22,719 Speaker 11: on trial. Prosecutors accused him of manipulating markets, of defrauding lenders. 778 00:36:23,280 --> 00:36:26,080 Speaker 11: But after having spent a lot of time in the courtroom, 779 00:36:26,239 --> 00:36:29,600 Speaker 11: another key takeaway from it all has been that Wall 780 00:36:29,640 --> 00:36:33,720 Speaker 11: Street doesn't look all that great. Here was someone whose 781 00:36:33,760 --> 00:36:35,960 Speaker 11: personal wealth might have been thirty six billion dollars, but 782 00:36:36,040 --> 00:36:38,840 Speaker 11: he had another one hundred and twenty five billion dollars 783 00:36:38,840 --> 00:36:41,719 Speaker 11: in borrowed money. He had a gross portfolio size of 784 00:36:41,719 --> 00:36:45,680 Speaker 11: one hundred and sixty billion dollars, making concentrated bets on 785 00:36:45,840 --> 00:36:48,839 Speaker 11: much of the same names, and all the banks were 786 00:36:48,920 --> 00:36:55,040 Speaker 11: largely caught unawares. Yes, they got vague answers, evasive answers, 787 00:36:55,200 --> 00:36:58,799 Speaker 11: but they also relied on pinky promises effectively to give 788 00:36:58,880 --> 00:37:01,400 Speaker 11: him so much fire for his bets. And in the 789 00:37:01,520 --> 00:37:04,320 Speaker 11: end the banks were burnt badly, lost over ten billion dollars, 790 00:37:04,440 --> 00:37:06,920 Speaker 11: and one of those banks, the most badly hit credit Squeeze, 791 00:37:07,200 --> 00:37:09,760 Speaker 11: doesn't even exist anymore, and you could argue Bill Hung's 792 00:37:09,800 --> 00:37:12,120 Speaker 11: firm played a key role in that. 793 00:37:14,239 --> 00:37:16,279 Speaker 2: So Shree, what I found fascionating about this article, and 794 00:37:16,320 --> 00:37:19,160 Speaker 2: it's a great minute by minute walk through a seventy 795 00:37:19,160 --> 00:37:21,200 Speaker 2: two hour period when it all kind of came to 796 00:37:21,239 --> 00:37:24,360 Speaker 2: an end for everyone involved, was that the banks did 797 00:37:24,480 --> 00:37:27,879 Speaker 2: not know that Bilhuang and his firm was layering on 798 00:37:28,480 --> 00:37:31,960 Speaker 2: such concentrated bets across various firms. One bank didn't know 799 00:37:32,000 --> 00:37:33,719 Speaker 2: what the other bank was doing. Therefore they didn't know 800 00:37:33,760 --> 00:37:36,920 Speaker 2: the magnitude of the exposure. How did that happen? 801 00:37:37,040 --> 00:37:39,480 Speaker 11: And look in all the conversations we have, they will 802 00:37:39,480 --> 00:37:41,719 Speaker 11: tell you we're not allowed to ask. If you're in 803 00:37:41,760 --> 00:37:43,600 Speaker 11: the prime brokerage business, if you're in the business of 804 00:37:43,640 --> 00:37:47,880 Speaker 11: extending leverage to your client, the client doesn't necessarily have 805 00:37:47,960 --> 00:37:50,839 Speaker 11: to tell you or show you their exact portfolio. They 806 00:37:50,880 --> 00:37:54,960 Speaker 11: will claim secrecy, they will claim proprietary information. But at 807 00:37:55,000 --> 00:37:57,239 Speaker 11: the end of the day, banks can also say, if 808 00:37:57,280 --> 00:38:00,480 Speaker 11: you don't give me as many disclosures as possible, I 809 00:38:00,520 --> 00:38:01,920 Speaker 11: will not give you that money. 810 00:38:02,120 --> 00:38:03,080 Speaker 2: That never happened. 811 00:38:03,400 --> 00:38:05,600 Speaker 11: These guys would come in and say, yes, we have 812 00:38:05,640 --> 00:38:08,520 Speaker 11: a diversified portfolio, and yes, don't worry, we have all 813 00:38:08,560 --> 00:38:11,760 Speaker 11: the controls in place, and it's across a mix of names, 814 00:38:11,920 --> 00:38:15,560 Speaker 11: and the banks would believe that, Yes, they expect honesty 815 00:38:15,640 --> 00:38:18,440 Speaker 11: and truthful answers. And if they didn't get that, and 816 00:38:18,480 --> 00:38:20,319 Speaker 11: you can see why the DOJ wants to go after 817 00:38:20,320 --> 00:38:22,600 Speaker 11: Billhong and Archie goes. But just think about it for 818 00:38:22,600 --> 00:38:24,759 Speaker 11: a moment. You walk into a bank today as a 819 00:38:24,840 --> 00:38:28,560 Speaker 11: retail customer and want a ten thousand dollars loan or 820 00:38:28,640 --> 00:38:31,160 Speaker 11: a mortgage, or you are trying to get into a 821 00:38:31,160 --> 00:38:34,479 Speaker 11: co op. The hoops that one has to jump through, 822 00:38:34,520 --> 00:38:36,799 Speaker 11: the signatures you have to get I mean to get 823 00:38:36,800 --> 00:38:40,600 Speaker 11: into a co op. You will need three witnesses, three friends, 824 00:38:40,640 --> 00:38:43,640 Speaker 11: your high school teacher, your college professor, and so many other. 825 00:38:43,480 --> 00:38:45,839 Speaker 5: People when you're first born man, and if you're getting 826 00:38:45,880 --> 00:38:46,720 Speaker 5: into a co op. 827 00:38:46,680 --> 00:38:49,920 Speaker 11: Pretty much and in this case, he as someone who 828 00:38:49,960 --> 00:38:52,720 Speaker 11: said I would like five billion dollars in capacity, Actually, 829 00:38:52,800 --> 00:38:55,320 Speaker 11: can we increase it ten billion now? Because my portfolio 830 00:38:55,320 --> 00:38:58,640 Speaker 11: sizes increase and all the banks are doing you're sure 831 00:38:58,480 --> 00:39:01,080 Speaker 11: you're you're good for that right and we can trust 832 00:39:01,120 --> 00:39:03,520 Speaker 11: you that you're investing well and you're doing this responsibility. 833 00:39:03,600 --> 00:39:04,120 Speaker 10: Yep, yep. 834 00:39:04,239 --> 00:39:07,560 Speaker 11: Great not They didn't even require written declarations about what 835 00:39:07,600 --> 00:39:10,279 Speaker 11: the portfolio looks like. These were phone conversations and that 836 00:39:10,440 --> 00:39:13,120 Speaker 11: was convincing enough for them to extend this kind of money. 837 00:39:13,239 --> 00:39:16,920 Speaker 11: And that's why for us it's yes, the legal process 838 00:39:16,960 --> 00:39:19,520 Speaker 11: will follow its own path, and the jury of twelve 839 00:39:19,520 --> 00:39:22,400 Speaker 11: New York because will decide whether Bill Hoong his CFO 840 00:39:22,480 --> 00:39:24,200 Speaker 11: if they are guilty or not on the charges that 841 00:39:24,280 --> 00:39:28,600 Speaker 11: have been brought against them. But it's not a great 842 00:39:28,600 --> 00:39:29,319 Speaker 11: look for Wall three. 843 00:39:31,080 --> 00:39:33,640 Speaker 6: So in terms of Wall Street, could this happen again 844 00:39:34,239 --> 00:39:37,640 Speaker 6: or do you think now things will be rethought? Those 845 00:39:37,680 --> 00:39:41,880 Speaker 6: pinky pinky swears will be by the wayside. 846 00:39:41,360 --> 00:39:42,640 Speaker 11: By the way, I was told by one of the 847 00:39:42,719 --> 00:39:47,360 Speaker 11: editors that pinky swears are the highest grade of promises 848 00:39:47,360 --> 00:39:49,239 Speaker 11: out there. So if you can't rely on that, what 849 00:39:49,280 --> 00:39:52,640 Speaker 11: do you rely on. I will make the point though, 850 00:39:52,760 --> 00:39:56,560 Speaker 11: that the lack of copycats before our kid goes or 851 00:39:56,600 --> 00:40:01,600 Speaker 11: even after our k goes, isn't necessarily reflection of a 852 00:40:01,680 --> 00:40:05,640 Speaker 11: new regime of banking, of strengthen controls of great oversight. 853 00:40:06,120 --> 00:40:09,200 Speaker 11: As much as in the case of our gecos there 854 00:40:09,320 --> 00:40:13,160 Speaker 11: was one man who was willing to take a pliant 855 00:40:13,560 --> 00:40:16,480 Speaker 11: system to the extremes. There was a lot of noise 856 00:40:16,520 --> 00:40:19,319 Speaker 11: about bringing in rules. Family officers don't face the same 857 00:40:19,400 --> 00:40:21,359 Speaker 11: kind of oversight as hatch funds, and they will talk 858 00:40:21,520 --> 00:40:25,040 Speaker 11: about what can be changed, how the rules need to 859 00:40:25,080 --> 00:40:27,799 Speaker 11: be modified. Some have been put in place, but for 860 00:40:27,800 --> 00:40:29,719 Speaker 11: the most part it's been a lot of talk, and 861 00:40:29,800 --> 00:40:34,720 Speaker 11: these things take time. The worry still remains. And look, 862 00:40:34,880 --> 00:40:37,200 Speaker 11: this happened recently, so the banks are perhaps shry of 863 00:40:37,239 --> 00:40:40,160 Speaker 11: doing this with someone else, but it's not entirely clear 864 00:40:40,200 --> 00:40:44,800 Speaker 11: to me how they avoid a repeat of this situation. 865 00:40:44,920 --> 00:40:48,880 Speaker 11: If someone else comes along and follows this, you know, 866 00:40:48,880 --> 00:40:50,759 Speaker 11: you may want to call it what might have looked 867 00:40:50,800 --> 00:40:53,200 Speaker 11: like genius investing to start with, but really at the 868 00:40:53,320 --> 00:40:56,640 Speaker 11: end of it reckless investing. If they follow the same pattern, 869 00:40:57,000 --> 00:40:59,240 Speaker 11: can we be guaranteed that they won't be a repeat? 870 00:41:00,480 --> 00:41:03,840 Speaker 11: I don't know, and Credit Swiss will tell you it 871 00:41:03,840 --> 00:41:06,840 Speaker 11: doesn't even matter, because they don't. They don't exist anymore 872 00:41:06,880 --> 00:41:08,160 Speaker 11: to be able to tell you if there will be 873 00:41:08,160 --> 00:41:10,120 Speaker 11: a repeat or not. That was the kind of consequence 874 00:41:10,160 --> 00:41:11,640 Speaker 11: we saw from the collapse of this one film. 875 00:41:13,760 --> 00:41:17,759 Speaker 2: Any says how this trial is gonna gorocery, Well, it's 876 00:41:17,960 --> 00:41:18,759 Speaker 2: it's fascinating. 877 00:41:19,200 --> 00:41:21,080 Speaker 11: It's happening in the court room of a nineteen year 878 00:41:21,120 --> 00:41:25,040 Speaker 11: old judge, right, and you have you have a jury 879 00:41:26,360 --> 00:41:28,600 Speaker 11: most of them, well all of them had never heard 880 00:41:28,600 --> 00:41:30,880 Speaker 11: of Bill Hoong or archade Goes before, and and that 881 00:41:31,000 --> 00:41:34,200 Speaker 11: kind of means that they have been getting a finance 882 00:41:34,239 --> 00:41:37,680 Speaker 11: one o one finance one on one sounds challenging in itself, 883 00:41:37,719 --> 00:41:41,200 Speaker 11: But then if the prosecutors and the defense lawyers have 884 00:41:41,200 --> 00:41:43,719 Speaker 11: to spend much of their time trying to explain security 885 00:41:43,760 --> 00:41:48,879 Speaker 11: based swaps, margin leverage, even discuss what memes talks and 886 00:41:48,920 --> 00:41:50,560 Speaker 11: what they're not, and have to define for some of 887 00:41:50,560 --> 00:41:55,120 Speaker 11: these people what Goldman Sachs is It'll be very interesting 888 00:41:55,160 --> 00:41:57,720 Speaker 11: to see how it pans out. Because when you're listening 889 00:41:57,760 --> 00:41:59,879 Speaker 11: to some of the arguments in court, when you when 890 00:41:59,880 --> 00:42:02,560 Speaker 11: you when you hear prosecutors talk about a lot of 891 00:42:02,600 --> 00:42:05,880 Speaker 11: heavy investing towards close of market, they were lifting the 892 00:42:05,960 --> 00:42:08,799 Speaker 11: firm limit to dry and drive the price up. And 893 00:42:08,920 --> 00:42:11,960 Speaker 11: yet on counter you kind of understand that that is 894 00:42:11,960 --> 00:42:14,520 Speaker 11: how business is done on Wall Street. I mean, some 895 00:42:14,680 --> 00:42:20,239 Speaker 11: of this jargon sounds sinister, but isn't necessarily sinister. But 896 00:42:20,680 --> 00:42:23,520 Speaker 11: how we see and perceive it doesn't matter. It's what's 897 00:42:23,560 --> 00:42:26,560 Speaker 11: getting through to the jury. The prosecution rests its case today, 898 00:42:26,640 --> 00:42:29,480 Speaker 11: the defense gets another couple of days, and after a 899 00:42:29,560 --> 00:42:31,960 Speaker 11: break next week, we will come back with closing remarks, 900 00:42:32,000 --> 00:42:34,600 Speaker 11: and then we will get the final verdict on this one. 901 00:42:35,560 --> 00:42:38,120 Speaker 2: All right, that's gonna be fascinating. This is a fascinating article. 902 00:42:38,120 --> 00:42:40,040 Speaker 2: Big Take article on the Bloomberg trumbling check out on 903 00:42:40,120 --> 00:42:42,720 Speaker 2: a Bloomberg dot com slash Big Take as well. Shrinanna 904 00:42:42,760 --> 00:42:45,439 Speaker 2: Roger and Bloomberg News senior financial reporter on the Big 905 00:42:45,480 --> 00:42:49,319 Speaker 2: Take story. The last seventy two hours of our chae 906 00:42:49,320 --> 00:42:51,640 Speaker 2: goes and you I've been reading it this whole time. 907 00:42:51,680 --> 00:42:54,880 Speaker 2: Here It's just minute by minute, and it is a 908 00:42:54,920 --> 00:42:57,319 Speaker 2: really amazing look at this explosion. 909 00:42:57,560 --> 00:43:02,120 Speaker 1: This is the Bloomberg Intelligence Podcast, available on apples, Spotify, 910 00:43:02,280 --> 00:43:05,480 Speaker 1: and anywhere else you get your podcasts. Listen live each 911 00:43:05,520 --> 00:43:08,920 Speaker 1: weekday ten am to noon Eastern on Bloomberg dot com, 912 00:43:09,000 --> 00:43:12,399 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 913 00:43:12,520 --> 00:43:15,520 Speaker 1: You can also watch us live every weekday on YouTube 914 00:43:15,760 --> 00:43:17,640 Speaker 1: and always on the Bloomberg Terminal