1 00:00:02,480 --> 00:00:10,480 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. This is Bloomberg business 2 00:00:10,480 --> 00:00:14,360 Speaker 1: Week Daily reporting from the magazine that helps global leaders 3 00:00:14,400 --> 00:00:18,320 Speaker 1: stay ahead with insight on the people, companies, and trends 4 00:00:18,360 --> 00:00:23,360 Speaker 1: shaping today's complex economy. Plus global business, finance and tech 5 00:00:23,440 --> 00:00:27,320 Speaker 1: news as it happens. The Bloomberg Business Week Daily Podcast 6 00:00:27,640 --> 00:00:31,720 Speaker 1: with Carol Masser and Tim Stenebeck on Bloomberg Radio. 7 00:00:32,159 --> 00:00:35,000 Speaker 2: The surgeon oil sparked by the escalating war, sending stocks 8 00:00:35,000 --> 00:00:38,239 Speaker 2: and bonds lower. It's certainly part of today's story. The 9 00:00:38,280 --> 00:00:40,040 Speaker 2: other part is what Charlie was just talking about, with 10 00:00:40,080 --> 00:00:42,760 Speaker 2: these tech stocks, Wall Street being rattled by these renewed 11 00:00:42,800 --> 00:00:46,000 Speaker 2: concerns over these AI investments, these massive AA investments, and 12 00:00:46,040 --> 00:00:46,960 Speaker 2: if they're going to pay off. 13 00:00:47,280 --> 00:00:49,760 Speaker 3: Yeah, I think that's such a huge question. 14 00:00:49,840 --> 00:00:51,760 Speaker 4: The Bloomberg mag seven you've been talking about this, the 15 00:00:51,800 --> 00:00:53,199 Speaker 4: total return into ex gauge. 16 00:00:53,040 --> 00:00:54,600 Speaker 5: Of I keep mentioning this gap. 17 00:00:54,680 --> 00:00:59,280 Speaker 2: It's such a superlative it is given given how crazy 18 00:00:59,280 --> 00:01:03,000 Speaker 2: things have been over the last fourteen months. Yeah, I'm 19 00:01:03,080 --> 00:01:05,920 Speaker 2: shocked that today's route is on par with what we 20 00:01:05,959 --> 00:01:07,280 Speaker 2: saw post Liberation Day. 21 00:01:07,360 --> 00:01:09,559 Speaker 4: Yeah, you're talking about April twenty twenty five, the terror 22 00:01:09,560 --> 00:01:10,480 Speaker 4: fueled meltdown. 23 00:01:10,600 --> 00:01:12,319 Speaker 3: So a little bit of perspective. 24 00:01:12,360 --> 00:01:15,280 Speaker 2: Write in context, Alphabet down about seven percent after raising 25 00:01:15,280 --> 00:01:18,320 Speaker 2: its CAPEX forecast, Tesla down fourteen percent of profit fell 26 00:01:18,360 --> 00:01:21,720 Speaker 2: even after strong EV deliveries. Ed Ludlow has been following 27 00:01:21,760 --> 00:01:23,480 Speaker 2: this all. He's the host of Bloomberg Tech. He joins 28 00:01:23,520 --> 00:01:26,600 Speaker 2: us from our San Francisco bureau. Ed, I'm going to 29 00:01:26,720 --> 00:01:28,920 Speaker 2: leave it to you on where to start here because 30 00:01:29,000 --> 00:01:31,800 Speaker 2: both of these huge stories today and they're driving certainly 31 00:01:31,800 --> 00:01:33,000 Speaker 2: to make acap tech trade. 32 00:01:33,080 --> 00:01:35,440 Speaker 6: So I think the way you frame it in how 33 00:01:35,520 --> 00:01:38,920 Speaker 6: markets have react against history is completely right. You know, 34 00:01:39,000 --> 00:01:41,800 Speaker 6: this is a big move lower in Alphabet in particular. 35 00:01:42,800 --> 00:01:44,520 Speaker 6: You know, we're on track for literally the biggest drop 36 00:01:44,560 --> 00:01:48,360 Speaker 6: since May of last year, but a seven percentage point 37 00:01:48,400 --> 00:01:51,880 Speaker 6: move when we got data that we were expecting, you know, 38 00:01:52,000 --> 00:01:55,240 Speaker 6: everyone expected them to raise capital expenditure guidance for this 39 00:01:55,400 --> 00:01:58,400 Speaker 6: year and signal that CAPEX will continue to grow over 40 00:01:58,440 --> 00:01:59,480 Speaker 6: a multi year horizon. 41 00:02:00,000 --> 00:02:02,560 Speaker 7: Exactly what we got. I know that you guys, I 42 00:02:02,600 --> 00:02:02,920 Speaker 7: don't know. 43 00:02:03,000 --> 00:02:05,160 Speaker 6: I have mixed feelings about this, but seven percent is 44 00:02:05,160 --> 00:02:07,480 Speaker 6: big because you know, it's a three and a half 45 00:02:07,520 --> 00:02:11,680 Speaker 6: standards deviation move on a stock that typically won't react 46 00:02:11,720 --> 00:02:15,799 Speaker 6: like that, but I recognize a big change in psychology 47 00:02:15,800 --> 00:02:18,839 Speaker 6: overnight from where we started our discussion yesterday of Mandita now, 48 00:02:18,919 --> 00:02:21,760 Speaker 6: which is there was the evidence that the AI spend 49 00:02:21,800 --> 00:02:26,120 Speaker 6: is paying off yesterday. Now it's much like how high 50 00:02:26,160 --> 00:02:28,799 Speaker 6: is the cost going to be? And that's where we're at. 51 00:02:28,919 --> 00:02:32,480 Speaker 6: Similarly with Tesla. 52 00:02:31,320 --> 00:02:35,280 Speaker 4: That's a really good point, right like, Okay, the buy 53 00:02:35,320 --> 00:02:38,839 Speaker 4: in is there, but at what cost? Right Like, that's 54 00:02:38,880 --> 00:02:41,520 Speaker 4: where the conversation is getting. I feel like ed a 55 00:02:41,560 --> 00:02:46,040 Speaker 4: lot more specific and detailed, like we're in we get it, 56 00:02:46,120 --> 00:02:49,480 Speaker 4: we understand what's going on here, but again it's not 57 00:02:49,600 --> 00:02:50,400 Speaker 4: at any cost. 58 00:02:51,480 --> 00:02:54,359 Speaker 6: Yeah, I mean Alphabet, there's just so much rich data 59 00:02:54,480 --> 00:02:57,000 Speaker 6: to try and work out what the direction of travel 60 00:02:57,120 --> 00:02:59,600 Speaker 6: is with AI. So they have a backlog that's five 61 00:02:59,680 --> 00:03:03,480 Speaker 6: hundred fifteen billion dollars backlog of orders. And you'll remember 62 00:03:03,520 --> 00:03:05,880 Speaker 6: Mande actually thought that number was a little bit low, 63 00:03:06,240 --> 00:03:08,640 Speaker 6: you know, he'd expected it to be higher. They have 64 00:03:08,800 --> 00:03:11,920 Speaker 6: eight hundred and eleven billion dollars of contracted spending. In 65 00:03:11,919 --> 00:03:14,520 Speaker 6: other words, there's all these projects that Alphabet's committed to, 66 00:03:15,040 --> 00:03:17,839 Speaker 6: and as disclothes in their regulatory filings, all of those 67 00:03:17,840 --> 00:03:20,080 Speaker 6: commitments total eight hundred and eleven billion dollars. So people 68 00:03:20,080 --> 00:03:22,760 Speaker 6: like look at that and they're like backlog versus spending. 69 00:03:23,720 --> 00:03:27,200 Speaker 6: There's a mismatch there still, you know, on the question 70 00:03:27,320 --> 00:03:29,960 Speaker 6: of what are the returns that AI is giving these 71 00:03:29,960 --> 00:03:31,520 Speaker 6: companies that are spending big. 72 00:03:32,360 --> 00:03:33,160 Speaker 8: Well, what what. 73 00:03:34,760 --> 00:03:36,720 Speaker 2: Like what's the other side of this coin? Ad for 74 00:03:36,760 --> 00:03:39,040 Speaker 2: alphabet The other side of this coin is that they 75 00:03:39,040 --> 00:03:45,200 Speaker 2: can leverage excuse me, leverage the existing customer base that 76 00:03:45,240 --> 00:03:48,160 Speaker 2: they have and bring in a ton of revenue as 77 00:03:48,200 --> 00:03:50,640 Speaker 2: a result of being more efficient when it comes to 78 00:03:50,680 --> 00:03:54,120 Speaker 2: AD sales and being more efficient and just better when 79 00:03:54,120 --> 00:03:55,240 Speaker 2: it comes to Google Cloud. 80 00:03:55,280 --> 00:03:56,520 Speaker 8: Right, that's still the ballcase. 81 00:03:57,080 --> 00:03:59,840 Speaker 6: Yeah, So there's also data points that are definitely evidence 82 00:03:59,840 --> 00:04:04,040 Speaker 6: of demand. Google Cloud continues to grow at an astonishing 83 00:04:04,080 --> 00:04:06,440 Speaker 6: rate eighty two percent year an year, and the quarter 84 00:04:06,520 --> 00:04:08,880 Speaker 6: gone there is the backlog number of five hundred and 85 00:04:08,880 --> 00:04:12,800 Speaker 6: fourteen billion dollars and more than half of that backlog. 86 00:04:12,840 --> 00:04:15,200 Speaker 6: You know, this is like such CFO speak because I 87 00:04:15,240 --> 00:04:17,440 Speaker 6: always like, think about the technology. I think we should say, like, 88 00:04:17,600 --> 00:04:20,480 Speaker 6: is Google's AI getting traction with the world, And there's 89 00:04:20,520 --> 00:04:22,680 Speaker 6: lots of evidence it is, But that five hundred and 90 00:04:22,720 --> 00:04:24,159 Speaker 6: fourteen billion dollar backlog. 91 00:04:24,400 --> 00:04:25,960 Speaker 7: What they said was very specific. 92 00:04:26,080 --> 00:04:29,600 Speaker 6: They expect more than half of it to translate into 93 00:04:29,640 --> 00:04:35,200 Speaker 6: revenue over two full financial years, according to you know, 94 00:04:35,240 --> 00:04:37,039 Speaker 6: to the CFO, like, is that a long time? A 95 00:04:37,040 --> 00:04:37,479 Speaker 6: short time? 96 00:04:37,480 --> 00:04:37,880 Speaker 7: I don't know. 97 00:04:38,000 --> 00:04:39,560 Speaker 2: I want to throw something at you, Ed, I just 98 00:04:39,640 --> 00:04:41,440 Speaker 2: I just did this on this is this is I 99 00:04:41,560 --> 00:04:41,880 Speaker 2: used as. 100 00:04:42,040 --> 00:04:43,400 Speaker 7: Tree or metaphorically. 101 00:04:44,200 --> 00:04:46,039 Speaker 2: If you were any closer, I'd be able to do 102 00:04:46,080 --> 00:04:48,839 Speaker 2: it literally. Okay, you got to ask being throw and 103 00:04:48,920 --> 00:04:51,799 Speaker 2: I was just curious. I looked and I saw that 104 00:04:52,120 --> 00:04:55,640 Speaker 2: Tesla's down almost thirty percent this year. Our alphabet is 105 00:04:55,640 --> 00:04:57,280 Speaker 2: only up about one and a half percent this year. 106 00:04:57,279 --> 00:04:58,960 Speaker 2: I'm like, Okay, what are all the other mag seven 107 00:04:59,520 --> 00:05:03,719 Speaker 2: companies doing so far this year? Apple's up eighteen percent 108 00:05:04,160 --> 00:05:08,120 Speaker 2: and Videos up more than eleven percent. You have Amazon 109 00:05:08,200 --> 00:05:10,120 Speaker 2: up about one point two percent, Mets down more than 110 00:05:10,120 --> 00:05:12,400 Speaker 2: eight percent. Microsoft is down more than twenty percent. We've 111 00:05:12,400 --> 00:05:14,160 Speaker 2: done a lot of reporting on that, and as I mentioned, 112 00:05:14,160 --> 00:05:17,839 Speaker 2: Tesla down almost thirty percent. Talk to us a little 113 00:05:17,839 --> 00:05:20,440 Speaker 2: bit about Apple and how Apple has been sort of 114 00:05:20,920 --> 00:05:23,400 Speaker 2: the quiet the quiet one. We're gonna hear from Apple 115 00:05:23,440 --> 00:05:25,600 Speaker 2: next week, but Apple's been the quiet one over the 116 00:05:25,640 --> 00:05:26,040 Speaker 2: last year. 117 00:05:26,120 --> 00:05:27,400 Speaker 3: It did lag for a while, it did. 118 00:05:27,920 --> 00:05:30,720 Speaker 4: We're doing stories about comme on Apple, what's going on? 119 00:05:31,240 --> 00:05:35,080 Speaker 6: So I posted this on X yesterday before the market closed. 120 00:05:35,080 --> 00:05:38,200 Speaker 6: Here's the mag seven year state performance from being gaining. 121 00:05:38,320 --> 00:05:40,320 Speaker 8: I love this, great minds think alike. I got to 122 00:05:40,320 --> 00:05:41,240 Speaker 8: look at your ex more. 123 00:05:41,880 --> 00:05:44,719 Speaker 6: And so then loads of people, like after the market 124 00:05:44,800 --> 00:05:47,880 Speaker 6: had closed and all the earnings came, loads of people 125 00:05:47,920 --> 00:05:48,920 Speaker 6: replied saying, do this. 126 00:05:48,880 --> 00:05:51,600 Speaker 7: Again tomorrow and see if anything changes. 127 00:05:52,640 --> 00:05:57,800 Speaker 6: You know, Apple the stock story changed where investors came 128 00:05:57,880 --> 00:06:01,159 Speaker 6: to love that they did not have a cap expenditures story. 129 00:06:01,240 --> 00:06:04,400 Speaker 6: It was a complete reversal. For a long time, everyone 130 00:06:04,520 --> 00:06:08,599 Speaker 6: wanted Apple to invest aggressively to show that they could 131 00:06:08,680 --> 00:06:11,440 Speaker 6: get into the AI game. But it's the structure of 132 00:06:11,480 --> 00:06:15,520 Speaker 6: Apple's business. They are not a hyperscaler. They don't deploy 133 00:06:15,640 --> 00:06:18,440 Speaker 6: their own compute at the scale that the hyperscalers do. 134 00:06:19,160 --> 00:06:21,839 Speaker 6: And so then they got some insulation from that equation. 135 00:06:22,320 --> 00:06:25,520 Speaker 6: You know, the market really came to cheer them for 136 00:06:25,760 --> 00:06:28,839 Speaker 6: not having to spend at that level. And so where 137 00:06:28,880 --> 00:06:30,960 Speaker 6: they can spend is maybe on talent or R and 138 00:06:31,040 --> 00:06:33,919 Speaker 6: D and things like that. But that's a part of 139 00:06:33,960 --> 00:06:36,600 Speaker 6: the stock story that and that you know, they've kind 140 00:06:36,640 --> 00:06:38,880 Speaker 6: of more got their act together on their. 141 00:06:38,760 --> 00:06:41,000 Speaker 7: AI next phase on the hardware devices side. 142 00:06:41,040 --> 00:06:42,560 Speaker 6: I don't know if you guys had Mark Goumman on 143 00:06:42,600 --> 00:06:46,359 Speaker 6: this week about always detailed reporting on the next generations 144 00:06:46,360 --> 00:06:47,240 Speaker 6: of Mac that are coming. 145 00:06:47,240 --> 00:06:50,080 Speaker 4: For example, he's super excited about stuff coming. 146 00:06:50,240 --> 00:06:50,520 Speaker 3: Yeah. 147 00:06:50,839 --> 00:06:54,279 Speaker 6: Yeah, and those those stories really resonate with investors and 148 00:06:54,360 --> 00:06:57,920 Speaker 6: with you know, Apple users of Apple hardware and software. 149 00:06:58,320 --> 00:07:00,600 Speaker 4: You know, I want to go back to alphabet for second, though, 150 00:07:00,680 --> 00:07:02,560 Speaker 4: I do think about this backlog. 151 00:07:02,839 --> 00:07:04,240 Speaker 3: It's like I. 152 00:07:04,160 --> 00:07:06,240 Speaker 4: Think you it was a good question about like when 153 00:07:06,240 --> 00:07:08,800 Speaker 4: they talk about this and how long it's going to 154 00:07:08,880 --> 00:07:11,640 Speaker 4: take to work off. I mean, this is where you know, 155 00:07:12,080 --> 00:07:16,080 Speaker 4: you hope I would assume that their CFO team and 156 00:07:16,160 --> 00:07:19,080 Speaker 4: all of their in house financial experts are being Okay, 157 00:07:19,080 --> 00:07:22,120 Speaker 4: so if we're going to get this realization of this revenue, 158 00:07:22,440 --> 00:07:24,560 Speaker 4: but at what cost? Like they've got to be figuring 159 00:07:24,560 --> 00:07:29,760 Speaker 4: this out right, because if they're spending, spending, spending like 160 00:07:30,520 --> 00:07:34,840 Speaker 4: that revenue spread over that time frame, I don't. 161 00:07:34,640 --> 00:07:35,640 Speaker 3: Know, you really have to. 162 00:07:36,440 --> 00:07:39,800 Speaker 6: Also, backlogs also tend to get bigger over time, Like 163 00:07:39,840 --> 00:07:42,280 Speaker 6: we haven't seen anyone really eat away at that backlog. 164 00:07:42,440 --> 00:07:45,680 Speaker 6: I mean, so you can think about it in financial terms, 165 00:07:45,680 --> 00:07:47,600 Speaker 6: which I think is the right way, because that's how 166 00:07:47,680 --> 00:07:50,360 Speaker 6: management presented it on the call last night. In the 167 00:07:50,360 --> 00:07:55,559 Speaker 6: AI economy, how much a particular company or Frontier Labs 168 00:07:55,600 --> 00:07:58,920 Speaker 6: AI is getting used is measured in tokens, and one 169 00:07:58,920 --> 00:08:02,200 Speaker 6: of the data points that they gave is that they 170 00:08:02,240 --> 00:08:06,920 Speaker 6: were doing twenty two billion token Gemini tokens per minute 171 00:08:07,400 --> 00:08:11,080 Speaker 6: through the API, and that really resonates because people in 172 00:08:11,200 --> 00:08:14,600 Speaker 6: industry are like, Okay, I understand that twenty two billion 173 00:08:14,600 --> 00:08:17,640 Speaker 6: Gemini APO tokens per minute. What I've been trying to 174 00:08:17,680 --> 00:08:19,160 Speaker 6: spend all day doing is like, do we have an 175 00:08:19,160 --> 00:08:23,440 Speaker 6: equivalent figure from Amazon Aws, from Microsoft, from the Frontier 176 00:08:23,480 --> 00:08:27,040 Speaker 6: Labs themselves, And they aren't. They aren't apples to apples. 177 00:08:27,080 --> 00:08:29,760 Speaker 6: But there is a lot of evidence that all of 178 00:08:29,800 --> 00:08:33,000 Speaker 6: the work that Google's been doing in AI has got 179 00:08:33,040 --> 00:08:35,360 Speaker 6: traction in the real world, the world of business and 180 00:08:35,400 --> 00:08:37,839 Speaker 6: with the consumer. One thing that Man Deep and I 181 00:08:37,880 --> 00:08:39,560 Speaker 6: don't again I don't want to speak on his behalf. 182 00:08:39,600 --> 00:08:42,480 Speaker 6: I just think he's really smart. He's always exactly on 183 00:08:42,559 --> 00:08:44,960 Speaker 6: the pulse of what's happening. Pointed out is that they're 184 00:08:45,000 --> 00:08:48,000 Speaker 6: behind on their latest models and that has hurt Google. 185 00:08:48,120 --> 00:08:51,599 Speaker 3: Oh man, can we just go another ten minutes to that? 186 00:08:52,240 --> 00:08:55,320 Speaker 8: Come on, guys, stay with us. 187 00:08:55,360 --> 00:08:58,360 Speaker 2: More from Bloomberg Business Week Daily coming up after this. 188 00:09:02,480 --> 00:09:06,320 Speaker 1: You're listening to the Bloomberg Business Week Daily Podcast. Catch 189 00:09:06,400 --> 00:09:09,080 Speaker 1: us live weekday afternoons from two to five eas during 190 00:09:09,280 --> 00:09:13,199 Speaker 1: Listen on Applecarplay and Android Otto with the Bloomberg Business app, 191 00:09:13,360 --> 00:09:15,480 Speaker 1: or watch us Live on YouTube. 192 00:09:16,240 --> 00:09:18,440 Speaker 2: It's been on the President's mind though for some time. 193 00:09:18,520 --> 00:09:21,079 Speaker 2: He's talked about building ships in the US for quite 194 00:09:21,080 --> 00:09:23,600 Speaker 2: a while, including just after returning to the White House 195 00:09:23,679 --> 00:09:26,600 Speaker 2: early last year in March of twenty twenty five, when 196 00:09:26,640 --> 00:09:28,880 Speaker 2: he gave a joint address to Congress. 197 00:09:29,280 --> 00:09:31,439 Speaker 3: To booster defense industrial base. 198 00:09:31,520 --> 00:09:36,120 Speaker 9: We are also going to resurrect the American shipbuilding industry, 199 00:09:36,120 --> 00:09:47,480 Speaker 9: including commercial shipbuilding and military shipbuilding. And for that purpose, 200 00:09:47,559 --> 00:09:51,640 Speaker 9: I'm announcing tonight that we will create a new Office 201 00:09:51,679 --> 00:09:54,520 Speaker 9: of Shipbuilding in the White House and or for special 202 00:09:54,600 --> 00:09:58,400 Speaker 9: tax incentives to bring this industry home to America where 203 00:09:58,400 --> 00:09:58,880 Speaker 9: it belongs. 204 00:09:58,920 --> 00:10:02,560 Speaker 4: With that, of course, was President Trump March fourth, twenty 205 00:10:02,600 --> 00:10:05,760 Speaker 4: twenty five, when he gave a joint Congress a joint address, 206 00:10:05,800 --> 00:10:09,280 Speaker 4: I should say to Congress, they're talking about shipbuilding but 207 00:10:09,480 --> 00:10:13,880 Speaker 4: on this what's interesting, there was an announcement actually earlier 208 00:10:14,280 --> 00:10:15,760 Speaker 4: today in Washington. 209 00:10:15,559 --> 00:10:18,240 Speaker 2: Yeah, formally announcing the signing of a nine figure deal 210 00:10:18,280 --> 00:10:21,760 Speaker 2: that establishes Siemens as a key technology partner for HD 211 00:10:21,960 --> 00:10:26,960 Speaker 2: Hyundai's next generation shilpbuilding and digitization strategy. Those two companies 212 00:10:27,000 --> 00:10:30,000 Speaker 2: formally announcing that deal earlier today with US. 213 00:10:29,960 --> 00:10:33,600 Speaker 4: Right now is Tony Hemilgarn. He is president CEO of 214 00:10:33,559 --> 00:10:37,360 Speaker 4: Seamen's Digital industry software and also with US as sekwe Hung, 215 00:10:37,480 --> 00:10:40,560 Speaker 4: he's the president and CEO of HD Hyundai USA. 216 00:10:40,679 --> 00:10:42,480 Speaker 3: And again they both joined us from Washington. 217 00:10:42,520 --> 00:10:46,040 Speaker 4: Gentlemen, Welcome, welcome, delighted to have you here on Bloomberg. 218 00:10:46,840 --> 00:10:48,280 Speaker 3: Tony, I want to kick it off with you. 219 00:10:48,320 --> 00:10:51,680 Speaker 4: What does this deal solidify specifically and mean. 220 00:10:51,880 --> 00:10:53,720 Speaker 3: For shipbuilding here in the US. What does it mean 221 00:10:53,760 --> 00:10:53,960 Speaker 3: for you? 222 00:10:54,000 --> 00:10:56,000 Speaker 4: Come for the two companies, but what does it mean 223 00:10:56,240 --> 00:10:58,800 Speaker 4: for maybe shipbuilding more broadly here in the United States. 224 00:11:00,920 --> 00:11:04,079 Speaker 10: Yeah, So we're very proud of the partnership here with 225 00:11:04,760 --> 00:11:07,319 Speaker 10: HD Hundai, and a big part of that was how 226 00:11:07,320 --> 00:11:09,280 Speaker 10: do they move faster? How do they build ships faster? 227 00:11:09,360 --> 00:11:12,520 Speaker 10: How do they design, engineer, manufacture faster? And so what 228 00:11:12,559 --> 00:11:15,280 Speaker 10: our software is is we provide the tools that allow 229 00:11:15,320 --> 00:11:17,760 Speaker 10: you to do that. And so when you think about 230 00:11:17,840 --> 00:11:21,280 Speaker 10: then advancement of shipbuilding here in the US, part of 231 00:11:21,280 --> 00:11:24,680 Speaker 10: the announcement today between the US and Korean governments is 232 00:11:24,679 --> 00:11:27,360 Speaker 10: how do we promote more of that commercial building here 233 00:11:27,360 --> 00:11:29,319 Speaker 10: in the US and our tools are the tools that 234 00:11:29,400 --> 00:11:31,640 Speaker 10: help you do that, to help you go a lot faster, 235 00:11:31,760 --> 00:11:34,120 Speaker 10: to create that digital environment to be able to produce 236 00:11:34,600 --> 00:11:38,280 Speaker 10: manufacturing engineer. So it's something that's a key enabler to 237 00:11:38,280 --> 00:11:40,120 Speaker 10: be able to promote this business here in the US. 238 00:11:40,000 --> 00:11:41,760 Speaker 2: And SECON one, I want to talk to you about 239 00:11:41,760 --> 00:11:43,440 Speaker 2: what it takes to actually build a ship in a 240 00:11:43,440 --> 00:11:47,000 Speaker 2: sustainable way here in the US rather than in another 241 00:11:47,080 --> 00:11:50,160 Speaker 2: part of the world. Specifically with the deals such as this, 242 00:11:50,280 --> 00:11:52,480 Speaker 2: how do you pencil it out and make the numbers 243 00:11:52,559 --> 00:11:54,720 Speaker 2: work for you and for Hyundai. 244 00:11:56,720 --> 00:12:00,560 Speaker 11: Well, we see great momentum from the Hill and the 245 00:12:00,640 --> 00:12:05,680 Speaker 11: strong leadership from the US administration, but at the same time, 246 00:12:05,760 --> 00:12:08,120 Speaker 11: when it comes to the reality and you know, the 247 00:12:08,200 --> 00:12:10,520 Speaker 11: day to day operation, there are many challenges. 248 00:12:11,080 --> 00:12:11,240 Speaker 2: Uh. 249 00:12:11,480 --> 00:12:14,640 Speaker 11: One of the great challenges that that we we we 250 00:12:14,679 --> 00:12:16,920 Speaker 11: are facing here in the United States would be a 251 00:12:17,440 --> 00:12:20,840 Speaker 11: shortage of labor, especially the skilled labor. 252 00:12:21,480 --> 00:12:21,680 Speaker 4: Uh. 253 00:12:21,720 --> 00:12:26,200 Speaker 11: And what the digitalization the digital shipyard that we are 254 00:12:26,200 --> 00:12:30,520 Speaker 11: building together with a gievemans do in that relation, uh, 255 00:12:30,760 --> 00:12:37,080 Speaker 11: is to create a virtual three D type digital shipyard 256 00:12:37,840 --> 00:12:41,360 Speaker 11: where everything is connected, you know, all information come together, 257 00:12:41,559 --> 00:12:44,600 Speaker 11: and by that we we make a better, better decision 258 00:12:44,760 --> 00:12:49,240 Speaker 11: and optimize our resources you know, you know better. Uh. 259 00:12:49,360 --> 00:12:53,760 Speaker 11: In that way, we think that uh, you know, it 260 00:12:53,840 --> 00:13:00,640 Speaker 11: will enable us to faster automation and digitalization and a departments. 261 00:13:00,920 --> 00:13:04,920 Speaker 11: In that you know, we can solve the labor issue here. Uh, 262 00:13:04,960 --> 00:13:07,120 Speaker 11: and there will be a powerful tool to have here. 263 00:13:08,040 --> 00:13:10,920 Speaker 3: So sequon, let me just follow up on that. 264 00:13:11,200 --> 00:13:17,119 Speaker 4: So how much can a digital shipyard basically reduce construction 265 00:13:17,280 --> 00:13:20,120 Speaker 4: time for let's say a destroyer, a submarine or an 266 00:13:20,160 --> 00:13:21,480 Speaker 4: auxiliary ship. 267 00:13:23,800 --> 00:13:24,760 Speaker 3: There's a great question. 268 00:13:25,960 --> 00:13:29,439 Speaker 11: We don't engage the the success of the digital shipyard 269 00:13:29,480 --> 00:13:32,920 Speaker 11: thing in terms of the time that that we reduce. 270 00:13:34,000 --> 00:13:39,440 Speaker 11: What we more focus more is you know, uh, whether well, 271 00:13:39,960 --> 00:13:42,560 Speaker 11: let me put it this way. We believe with this 272 00:13:42,679 --> 00:13:47,480 Speaker 11: digital tool, on time and on budget delivery will be 273 00:13:48,360 --> 00:13:51,440 Speaker 11: you know, will be possible, uh, in a in a 274 00:13:51,559 --> 00:13:58,280 Speaker 11: more efficient way. So uh, we try to reduce the time, 275 00:13:58,480 --> 00:14:02,319 Speaker 11: but more focus are say for now is to keep 276 00:14:02,360 --> 00:14:06,440 Speaker 11: the time and the labor force ready for that on 277 00:14:06,520 --> 00:14:07,160 Speaker 11: time delivery. 278 00:14:07,640 --> 00:14:10,200 Speaker 2: Yeah, Tony, that's a good a good question to you too, 279 00:14:10,280 --> 00:14:13,000 Speaker 2: and about this labor force and the way that digital tools, 280 00:14:13,200 --> 00:14:16,280 Speaker 2: in your view, are offsetting some of the challenges that 281 00:14:16,320 --> 00:14:19,920 Speaker 2: the US industrial base has or the US labor force has. 282 00:14:20,000 --> 00:14:23,040 Speaker 2: Here given the shortages of welders, how much can these 283 00:14:23,040 --> 00:14:27,160 Speaker 2: digital tools offset that shortage of skilled well welders, pipe fitters, 284 00:14:27,200 --> 00:14:28,040 Speaker 2: and electricians. 285 00:14:30,440 --> 00:14:32,280 Speaker 10: Yeah, I guess I'd first start though, with just the 286 00:14:32,320 --> 00:14:34,200 Speaker 10: design right, and that before. 287 00:14:33,920 --> 00:14:36,640 Speaker 2: We even get to the actual labor that it takes 288 00:14:36,720 --> 00:14:38,880 Speaker 2: to physically build this right. 289 00:14:38,880 --> 00:14:40,520 Speaker 10: Because you're going to get the design right, you've got 290 00:14:40,520 --> 00:14:42,680 Speaker 10: to get the engineering right, the physics right of the product. 291 00:14:42,760 --> 00:14:46,240 Speaker 10: And we talked about this as a digital twin, and 292 00:14:46,280 --> 00:14:48,800 Speaker 10: the idea of the digital twin is how closely the 293 00:14:48,840 --> 00:14:52,840 Speaker 10: digital world can represent the real world, and the closer 294 00:14:52,880 --> 00:14:56,040 Speaker 10: we can make that relationship, the faster companies like HI 295 00:14:56,160 --> 00:14:59,320 Speaker 10: can go. Because you think about these products are highly complex. 296 00:14:59,360 --> 00:15:05,000 Speaker 10: You've got soft ware, you've got mechanical design, electronics, electrical manufacturing, engineering, 297 00:15:05,520 --> 00:15:08,840 Speaker 10: the plant layout, plant simulation, all of these things. If 298 00:15:08,880 --> 00:15:11,680 Speaker 10: we can simulate that this is a very complex environment. 299 00:15:11,720 --> 00:15:14,000 Speaker 10: The complexity is not going to go away. But if 300 00:15:14,000 --> 00:15:15,840 Speaker 10: I can simulate it and I can do what ifs 301 00:15:15,840 --> 00:15:18,880 Speaker 10: and make changes and other types of things, that allows 302 00:15:18,920 --> 00:15:20,760 Speaker 10: me to go a lot quicker. And once I do 303 00:15:20,840 --> 00:15:22,800 Speaker 10: all of that, then it comes to what do I 304 00:15:22,800 --> 00:15:24,560 Speaker 10: do with welding? What do I do with the simulation 305 00:15:24,640 --> 00:15:27,400 Speaker 10: of what happens in the plant? We bring all that 306 00:15:27,480 --> 00:15:29,720 Speaker 10: together and this is where you really start to get 307 00:15:29,760 --> 00:15:33,240 Speaker 10: the value of what our software can deliver, because now 308 00:15:33,680 --> 00:15:36,480 Speaker 10: I can make these decisions in confidence in a very 309 00:15:36,480 --> 00:15:39,440 Speaker 10: complex world. And that's truly a competitive advantage. If I 310 00:15:39,480 --> 00:15:41,960 Speaker 10: can simulate and do all of that work much faster 311 00:15:42,080 --> 00:15:44,720 Speaker 10: than the next guy, it's a big advantage. And so 312 00:15:44,800 --> 00:15:47,120 Speaker 10: we take that. And then also these tools are enabled 313 00:15:47,120 --> 00:15:49,480 Speaker 10: for the workers. They can use these tools. We can 314 00:15:49,520 --> 00:15:51,320 Speaker 10: simulate what the workers are going to do, we can 315 00:15:51,320 --> 00:15:53,760 Speaker 10: show them how to perform the work, to provide the 316 00:15:53,800 --> 00:15:56,400 Speaker 10: work instructions, all of these types of things. So it's 317 00:15:56,440 --> 00:15:59,760 Speaker 10: really assisting what's going on as well as programming the 318 00:15:59,840 --> 00:16:02,600 Speaker 10: row of us simulate the robotic simulation. All of that 319 00:16:02,720 --> 00:16:03,720 Speaker 10: is part of our software. 320 00:16:04,080 --> 00:16:06,360 Speaker 4: So secon one, let me go back to you then, 321 00:16:06,440 --> 00:16:09,560 Speaker 4: so I get it like the timing and it sounds 322 00:16:09,640 --> 00:16:11,360 Speaker 4: like things will be much faster. 323 00:16:11,760 --> 00:16:12,640 Speaker 3: So give us an idea. 324 00:16:12,640 --> 00:16:15,160 Speaker 4: I want to go back to, like, so, how does 325 00:16:15,200 --> 00:16:18,600 Speaker 4: this change output? Can you give us some kind of 326 00:16:18,640 --> 00:16:23,080 Speaker 4: we're into numbers here, some context in terms of six months, 327 00:16:23,080 --> 00:16:25,440 Speaker 4: what gets changed twelve months? Like, give us an idea 328 00:16:25,560 --> 00:16:29,440 Speaker 4: of how output is changed, especially when you've got a 329 00:16:29,480 --> 00:16:33,400 Speaker 4: president who we're monitoring right now and talking about data 330 00:16:33,440 --> 00:16:35,320 Speaker 4: centers and so on and so forth in power, but 331 00:16:35,400 --> 00:16:39,320 Speaker 4: also thinking about shipbuilding, which he has talked about and 332 00:16:39,400 --> 00:16:41,760 Speaker 4: increasing that because many people have said you can't do 333 00:16:41,840 --> 00:16:45,520 Speaker 4: this quickly in terms of the US shipbuilding industry, change 334 00:16:45,520 --> 00:16:46,960 Speaker 4: it and increase it. 335 00:16:46,960 --> 00:16:48,160 Speaker 3: It doesn't happen overnight. 336 00:16:49,840 --> 00:16:53,040 Speaker 11: Well, the current timeline that we have in minds is 337 00:16:53,120 --> 00:16:59,000 Speaker 11: to to to be able to apply this digital sheet 338 00:16:59,080 --> 00:17:04,520 Speaker 11: yard concept to our starting the design in twenty twenty eight, 339 00:17:05,640 --> 00:17:10,640 Speaker 11: but there will be the starting point in reality, and 340 00:17:10,960 --> 00:17:15,360 Speaker 11: it will take some more time to develop a program 341 00:17:15,400 --> 00:17:19,840 Speaker 11: to cover the whole shipyard and the whole the entire 342 00:17:20,359 --> 00:17:22,359 Speaker 11: ship that we build in o. 343 00:17:22,440 --> 00:17:26,000 Speaker 4: Earn Well, and then so you know, I want to 344 00:17:26,240 --> 00:17:30,520 Speaker 4: bring you back here to in on this conversation Tony. 345 00:17:30,560 --> 00:17:33,240 Speaker 4: When it comes to timelines like what's the timeline on 346 00:17:33,280 --> 00:17:35,080 Speaker 4: you and how the kind of the pressure of the 347 00:17:35,080 --> 00:17:39,040 Speaker 4: demands on you guys in terms of delivering the software 348 00:17:39,080 --> 00:17:42,520 Speaker 4: and the changes that our need to kind of basically 349 00:17:42,680 --> 00:17:45,879 Speaker 4: modernize the shipbuilding industry here in the United States. 350 00:17:47,480 --> 00:17:50,520 Speaker 10: Software is here improven now, it's established. So we have software, 351 00:17:50,560 --> 00:17:52,800 Speaker 10: we've been We sell the software all the time. The 352 00:17:53,560 --> 00:17:57,080 Speaker 10: work is for us to integrate that into the workflows 353 00:17:57,400 --> 00:17:59,800 Speaker 10: and the way that HD HYNDI works, for example, how 354 00:17:59,800 --> 00:18:01,919 Speaker 10: they design and we do a lot of this all 355 00:18:01,960 --> 00:18:05,440 Speaker 10: over the globe. Many most manufacturing and engineering companies in 356 00:18:05,480 --> 00:18:08,240 Speaker 10: the world use some portion of our software, and so 357 00:18:08,320 --> 00:18:10,320 Speaker 10: we have what we call a digital thread. The idea is, 358 00:18:10,320 --> 00:18:11,840 Speaker 10: how do you get from point A to point B 359 00:18:12,200 --> 00:18:16,120 Speaker 10: in a design process, Like you mentioned things like sustainability 360 00:18:16,240 --> 00:18:19,440 Speaker 10: or whatever it might be. We can simulate, for example, 361 00:18:20,000 --> 00:18:22,680 Speaker 10: that ship flowing through the water and the resistance of 362 00:18:22,720 --> 00:18:24,399 Speaker 10: the water at the same time the resistance of the 363 00:18:24,400 --> 00:18:27,440 Speaker 10: airflow and the ship as it's going with computational fluid dynamics. 364 00:18:27,760 --> 00:18:30,359 Speaker 10: From that, we can determine how efficient we can make 365 00:18:30,400 --> 00:18:32,720 Speaker 10: the product, how we can reduce energy, how we can 366 00:18:32,800 --> 00:18:36,000 Speaker 10: lightweight the product. So we have all of these processes established, 367 00:18:36,280 --> 00:18:38,440 Speaker 10: and now what we do is we sit with HD 368 00:18:38,520 --> 00:18:40,680 Speaker 10: Hyundai and establishing them in their workflows. And this is 369 00:18:40,720 --> 00:18:43,520 Speaker 10: work we've started already, so we feel very confident that 370 00:18:43,520 --> 00:18:45,720 Speaker 10: we can go very quickly in the design, engineering and 371 00:18:45,760 --> 00:18:49,000 Speaker 10: manufacturing process. Of course, building out some of the work 372 00:18:49,000 --> 00:18:51,679 Speaker 10: in the plants takes a little bit longer to what 373 00:18:51,680 --> 00:18:53,640 Speaker 10: we're doing, but the software is ready to go now. 374 00:18:53,640 --> 00:18:55,320 Speaker 3: Right, So you guys are ready to go. 375 00:18:55,320 --> 00:18:57,160 Speaker 4: It's just a case of integrating all of this into 376 00:18:57,280 --> 00:18:59,760 Speaker 4: the existing systems that are there at Hyundai. 377 00:19:00,119 --> 00:19:03,560 Speaker 3: Gentlemen. Fascinating As we continue to see and. 378 00:19:03,600 --> 00:19:07,320 Speaker 4: Talk a lot about the reindustrialization of the United States, 379 00:19:07,320 --> 00:19:09,679 Speaker 4: some say it's really difficult, but you guys are doing it. 380 00:19:09,680 --> 00:19:11,919 Speaker 4: With this announcement, I hope you will come back in 381 00:19:11,960 --> 00:19:14,159 Speaker 4: a few months and let us and give us a 382 00:19:14,160 --> 00:19:21,240 Speaker 4: status update. We'd really appreciate it. Great congratulat congratulations. All right, folks, 383 00:19:21,400 --> 00:19:24,600 Speaker 4: We are continuing. Tony Hemilgarn he is president CEO of 384 00:19:24,680 --> 00:19:28,080 Speaker 4: Semen's Digital Industry Software there in DC, along with Sekwon Hung. 385 00:19:28,160 --> 00:19:30,080 Speaker 4: He's president CEO. 386 00:19:29,880 --> 00:19:33,480 Speaker 3: Of HD hun USA. So interesting stuff there. 387 00:19:34,640 --> 00:19:35,400 Speaker 8: Stay with us. 388 00:19:35,480 --> 00:19:38,639 Speaker 2: More from Bloomberg Business Week Daily coming up after this. 389 00:19:42,600 --> 00:19:46,440 Speaker 1: You're listening to the Bloomberg Business Week Daily Podcast. Catch 390 00:19:46,520 --> 00:19:49,200 Speaker 1: us live weekday afternoons from two to five ees during 391 00:19:49,200 --> 00:19:52,000 Speaker 1: this listen on Apple Karplay and Android Auto with the 392 00:19:52,080 --> 00:19:56,040 Speaker 1: Bloomberg Business app, or watch us live on YouTube. 393 00:19:56,359 --> 00:19:56,760 Speaker 8: How do you Do It? 394 00:19:56,800 --> 00:19:59,119 Speaker 2: Makes your stock fell earlier today as much as six 395 00:19:59,200 --> 00:20:01,679 Speaker 2: percent this after the regional lender reported second quarter net 396 00:20:01,680 --> 00:20:04,639 Speaker 2: interest margin that missed expectations. I want to bring back 397 00:20:04,720 --> 00:20:07,600 Speaker 2: Zach Wasserman, CFO of the thirty five billion dollar market 398 00:20:07,600 --> 00:20:09,960 Speaker 2: cap Huntington Bank shares. It's the parent of Huntington Bank, 399 00:20:10,000 --> 00:20:13,119 Speaker 2: based in Columbus, Ohio, got more than fourteen hundred branches 400 00:20:13,160 --> 00:20:14,959 Speaker 2: in twenty one states, and Zach is joining us from 401 00:20:15,000 --> 00:20:18,200 Speaker 2: Columbus right now. Also with us, Nina Trentman, she's Bloomberg 402 00:20:18,240 --> 00:20:20,640 Speaker 2: new senior editor. She's the editor of the CFO Briefing newsletter. 403 00:20:20,680 --> 00:20:23,520 Speaker 2: You can subscribe to that at Bloomberg dot com slash 404 00:20:23,680 --> 00:20:28,360 Speaker 2: CFO Dash Briefing. I want to start Zach with the consumer. 405 00:20:28,400 --> 00:20:31,479 Speaker 2: There's a story about Albertsons. The shares are just tanking 406 00:20:31,520 --> 00:20:35,000 Speaker 2: today and it's on my radar because Albertsons is saying 407 00:20:35,000 --> 00:20:38,560 Speaker 2: that a softer consumer demand in addition to a competitive 408 00:20:38,960 --> 00:20:44,520 Speaker 2: environment is hitting the company this quarter, and there's concern 409 00:20:44,560 --> 00:20:46,600 Speaker 2: about that. We have higher oil prices, as we just 410 00:20:46,680 --> 00:20:49,440 Speaker 2: heard from Charlie diesel above five bucks a gallon, gas 411 00:20:49,440 --> 00:20:51,000 Speaker 2: above four dollars a gallon. 412 00:20:51,480 --> 00:20:53,800 Speaker 8: How is the Huntington Bank consumer doing? 413 00:20:55,080 --> 00:20:57,359 Speaker 12: What we're seeing actually is not that we're seeing a 414 00:20:57,359 --> 00:21:00,359 Speaker 12: lot of resilience and strength in the consumer franchise. 415 00:21:00,400 --> 00:21:02,040 Speaker 8: That we're seeing both uh. 416 00:21:02,160 --> 00:21:05,960 Speaker 12: Spending activities continue to be very normal, borrowing activities continue 417 00:21:05,960 --> 00:21:06,719 Speaker 12: to be very normal. 418 00:21:07,320 --> 00:21:07,919 Speaker 11: Uh. 419 00:21:07,960 --> 00:21:10,600 Speaker 12: And I think you know partly what it probably is, tim, 420 00:21:10,680 --> 00:21:12,840 Speaker 12: is a little bit of that further evidence of a 421 00:21:12,920 --> 00:21:16,720 Speaker 12: K shaped economy. Our business is very much keyed toward 422 00:21:16,800 --> 00:21:21,040 Speaker 12: the mass affluent and UH and higher income segments of 423 00:21:21,040 --> 00:21:25,000 Speaker 12: the consumer uh uh uh populace. And you know, in 424 00:21:25,040 --> 00:21:28,160 Speaker 12: that group, we're still seeing strong employment, strong consumer spending, 425 00:21:28,760 --> 00:21:29,960 Speaker 12: and fairly normal trends. 426 00:21:31,280 --> 00:21:33,560 Speaker 13: Just following up here, talk to us a little bit 427 00:21:33,560 --> 00:21:36,000 Speaker 13: about your loan growth. I know that that's been an 428 00:21:36,040 --> 00:21:38,720 Speaker 13: important category for for your business. What does that tell 429 00:21:38,760 --> 00:21:43,160 Speaker 13: you about specifically business clients and their plans for the future. 430 00:21:44,200 --> 00:21:47,119 Speaker 12: You know, the pipelines that we have for loan growth 431 00:21:47,119 --> 00:21:48,760 Speaker 12: as we think about the second half of the year 432 00:21:49,119 --> 00:21:52,280 Speaker 12: are stronger today than they were three months ago when 433 00:21:52,359 --> 00:21:54,800 Speaker 12: when I was talking to you before. So we're seeing 434 00:21:54,800 --> 00:21:59,639 Speaker 12: a continued acceleration actually in a customer demand for borrowing, 435 00:21:59,680 --> 00:22:02,560 Speaker 12: which is obviously a healthy sign for the economy generally. 436 00:22:02,880 --> 00:22:05,840 Speaker 12: What's interesting is if you look at the results from 437 00:22:05,840 --> 00:22:09,159 Speaker 12: the second quarter of the ten large regional banks in 438 00:22:09,200 --> 00:22:12,679 Speaker 12: and around Huntington, size eight of those ten were growing 439 00:22:12,720 --> 00:22:16,880 Speaker 12: loans annualized rate of between nine and above percent, which 440 00:22:16,920 --> 00:22:19,600 Speaker 12: is very fast actually, and if you look back over 441 00:22:19,640 --> 00:22:22,040 Speaker 12: the last three years, it is by far the fastest 442 00:22:22,119 --> 00:22:25,720 Speaker 12: quarter of lone growth across the entire large banking sector. 443 00:22:25,760 --> 00:22:27,720 Speaker 12: And so I think you're just seeing that kind of 444 00:22:27,760 --> 00:22:30,600 Speaker 12: reflected not only in what I'm seeing on the ground 445 00:22:30,800 --> 00:22:34,000 Speaker 12: for our own business, but broadly across the sector. 446 00:22:34,720 --> 00:22:37,760 Speaker 13: Your stock has tank quite a bit today. We saw 447 00:22:37,800 --> 00:22:40,840 Speaker 13: the decline in a net interest margin that you reported. 448 00:22:41,080 --> 00:22:43,040 Speaker 13: Talk to us a little bit about that, like us 449 00:22:43,200 --> 00:22:46,760 Speaker 13: investors overreacting or what is that that we're seeing in 450 00:22:46,800 --> 00:22:47,800 Speaker 13: the decline in the stock? 451 00:22:48,600 --> 00:22:48,959 Speaker 7: Sure? 452 00:22:49,119 --> 00:22:52,000 Speaker 12: Well, look, spread revenue is just a little under three 453 00:22:52,080 --> 00:22:55,240 Speaker 12: quarters of our revenue, and so anytime there's a movement 454 00:22:55,240 --> 00:22:58,240 Speaker 12: in the margin, investors react to that, and I understand that. 455 00:22:58,400 --> 00:23:00,840 Speaker 12: I think you know, the thing that probably being missed 456 00:23:01,320 --> 00:23:03,879 Speaker 12: is that just as there's somewhat more competition or on 457 00:23:03,960 --> 00:23:08,080 Speaker 12: deposit costs, which have modestly reduced an interest margin, we're 458 00:23:08,080 --> 00:23:11,120 Speaker 12: seeing the offsetting benefit in terms of higher fee revenues. 459 00:23:11,960 --> 00:23:16,120 Speaker 12: Value added fee services grew thirty percent year on year 460 00:23:16,280 --> 00:23:20,040 Speaker 12: in the second quarter, and that's organically, not including any acquisitions, 461 00:23:20,040 --> 00:23:22,720 Speaker 12: and of course it's even faster given the partnerships that 462 00:23:22,760 --> 00:23:26,040 Speaker 12: we've completed and integrated now. So we're seeing the opportunity 463 00:23:26,080 --> 00:23:29,760 Speaker 12: to manage our revenues overall, and the guidance we've given 464 00:23:30,040 --> 00:23:33,840 Speaker 12: for revenue growth in total is effectively unchanged. So you know, 465 00:23:34,000 --> 00:23:37,200 Speaker 12: from our perspective, the business performs exceptionally well. We're seeing 466 00:23:37,200 --> 00:23:39,679 Speaker 12: a very strong second half of the year, albeit with 467 00:23:39,720 --> 00:23:41,719 Speaker 12: a little different mix in terms of the revenues. 468 00:23:41,800 --> 00:23:44,440 Speaker 3: Nina, all right, so yeah, let's talk about the second half. 469 00:23:44,480 --> 00:23:47,280 Speaker 4: I mean, what is your outlook, Zach when it comes 470 00:23:47,320 --> 00:23:49,320 Speaker 4: to interest rates and the impact it could have You 471 00:23:49,359 --> 00:23:51,480 Speaker 4: got on you guys, because we are increasingly talking about 472 00:23:51,480 --> 00:23:53,880 Speaker 4: a higher rate environment here in the United States. 473 00:23:55,000 --> 00:23:57,800 Speaker 12: You know, it's a big change, Carol from what we 474 00:23:57,840 --> 00:24:00,359 Speaker 12: had thought six months ago, right, we were just just 475 00:24:00,600 --> 00:24:02,880 Speaker 12: thinking about this internally a little bit earlier today. I mean, 476 00:24:03,200 --> 00:24:06,200 Speaker 12: coming into this year, there were six rate reductions over 477 00:24:06,240 --> 00:24:08,960 Speaker 12: the coming six quarters. Now there's the forecast for two 478 00:24:09,000 --> 00:24:11,280 Speaker 12: and a half rate increases baked into the curve. So 479 00:24:12,280 --> 00:24:14,040 Speaker 12: you know, that's the kind of environment we're in now. 480 00:24:14,040 --> 00:24:17,920 Speaker 12: It's a lot of choppy, volatile expectation. Our view is 481 00:24:17,960 --> 00:24:20,280 Speaker 12: that we're going to have a higher for longer rate 482 00:24:20,400 --> 00:24:23,200 Speaker 12: environment for at least the foreseeable future, and if there 483 00:24:23,240 --> 00:24:25,640 Speaker 12: is a rate change, it is likely to be up. 484 00:24:25,960 --> 00:24:27,720 Speaker 12: With that being said, I think we'll have to wait 485 00:24:27,760 --> 00:24:31,720 Speaker 12: and see whether it actually comes to pass. And you know, 486 00:24:31,760 --> 00:24:34,040 Speaker 12: I think we're all waiting with baited breath for what 487 00:24:34,119 --> 00:24:35,280 Speaker 12: happens in September. 488 00:24:35,400 --> 00:24:39,159 Speaker 4: But that's a problem, the uncertainty. And we have a 489 00:24:39,200 --> 00:24:42,000 Speaker 4: great column. My team knows. I'm obsessed by Simon White 490 00:24:42,080 --> 00:24:45,199 Speaker 4: about the most fundamental macro risk is back and it 491 00:24:45,320 --> 00:24:49,199 Speaker 4: is about specifically the volatility of inflation is also sharply 492 00:24:49,280 --> 00:24:51,800 Speaker 4: rising get and you know it impacts everything goods price is, 493 00:24:51,880 --> 00:24:54,840 Speaker 4: barring rates, fed policy and cash flows. 494 00:24:54,840 --> 00:24:57,240 Speaker 3: It becomes more uncertain when. 495 00:24:57,080 --> 00:24:58,879 Speaker 2: These I'm going to send it to Zach on the terminals. 496 00:24:58,920 --> 00:25:01,840 Speaker 2: Zach's on the terminals going to the link. Okay, in 497 00:25:01,840 --> 00:25:02,880 Speaker 2: case he hasn't seen it yet. 498 00:25:02,880 --> 00:25:06,120 Speaker 4: Because people can't make people can't make decisions, people won't 499 00:25:06,119 --> 00:25:08,760 Speaker 4: take loans, businesses people like and soon you know. 500 00:25:08,840 --> 00:25:11,000 Speaker 12: This is the new normal, Carol. I mean, this is 501 00:25:11,000 --> 00:25:12,720 Speaker 12: the new normal that we're in right now at this point, 502 00:25:12,760 --> 00:25:13,040 Speaker 12: I think. 503 00:25:13,320 --> 00:25:15,680 Speaker 3: But it's tough, right for you and your clients. 504 00:25:16,480 --> 00:25:17,280 Speaker 5: It is hard. 505 00:25:17,280 --> 00:25:19,480 Speaker 12: It doesn't make it hard, There's no doubt about that. 506 00:25:19,560 --> 00:25:19,840 Speaker 5: I think. 507 00:25:20,000 --> 00:25:21,720 Speaker 8: Look, what is. 508 00:25:22,040 --> 00:25:24,600 Speaker 12: What is really encouraging is to see that in the 509 00:25:24,640 --> 00:25:28,320 Speaker 12: macroeconomy generally, we have seen an extraordinary amount of resilience 510 00:25:28,760 --> 00:25:32,920 Speaker 12: notwithstanding this uncertainty, you know, go back to Liberation Day 511 00:25:32,960 --> 00:25:36,600 Speaker 12: and the and the changes around potential you know, UH, 512 00:25:36,640 --> 00:25:40,680 Speaker 12: tariff policy. Then we have inflation and interest rate uncertainty 513 00:25:40,720 --> 00:25:43,480 Speaker 12: as we came into this year, and then obviously geopolitical 514 00:25:43,520 --> 00:25:46,399 Speaker 12: conflicts that that bleed into lots of different elements of 515 00:25:46,440 --> 00:25:49,240 Speaker 12: the economy. And notwithstanding all of that, you continue to 516 00:25:49,240 --> 00:25:54,240 Speaker 12: see employment be strong, consumer spending be robust, UH, corporate 517 00:25:54,960 --> 00:25:59,040 Speaker 12: activity continue to be pretty strong. Obviously there's a AI 518 00:25:59,320 --> 00:26:02,919 Speaker 12: infrastructure sure investment super cycle going on that helps, but 519 00:26:02,920 --> 00:26:05,000 Speaker 12: I think it's broader than that about. 520 00:26:04,800 --> 00:26:07,120 Speaker 2: How does it I'm just curious how it affects how 521 00:26:07,160 --> 00:26:11,320 Speaker 2: that uncertainty affects your role. Like if you if you 522 00:26:11,359 --> 00:26:13,159 Speaker 2: know you have to figure out you have to make 523 00:26:13,160 --> 00:26:15,159 Speaker 2: predictions about the future. You have to decide on how 524 00:26:15,240 --> 00:26:17,760 Speaker 2: much to spend, where to open branches, who to hire, 525 00:26:17,800 --> 00:26:20,480 Speaker 2: and how much to pay all these folks everything you 526 00:26:20,600 --> 00:26:24,000 Speaker 2: just highlighted, there is uncertainty. So how does that change 527 00:26:24,000 --> 00:26:26,119 Speaker 2: the way that you think about the way that you 528 00:26:26,119 --> 00:26:27,080 Speaker 2: deploy resources. 529 00:26:27,600 --> 00:26:30,399 Speaker 12: Look, we definitely need to be on our toes and 530 00:26:30,480 --> 00:26:34,560 Speaker 12: more dynamic. The frequency with which we are looking at 531 00:26:34,640 --> 00:26:38,800 Speaker 12: channel checking what's happening in the environment, understanding really on 532 00:26:38,840 --> 00:26:40,800 Speaker 12: the ground, what are we seeing right now so that 533 00:26:40,840 --> 00:26:43,880 Speaker 12: we can pivot as we need to is is heightened 534 00:26:43,920 --> 00:26:46,960 Speaker 12: for sure. And I think you know for us, the 535 00:26:47,080 --> 00:26:49,720 Speaker 12: kind of the dynamic way that we who we manage 536 00:26:49,720 --> 00:26:52,120 Speaker 12: the business. We're always as a CFO, I'm always thinking 537 00:26:52,119 --> 00:26:54,480 Speaker 12: about two sides of the coin. I want to invest 538 00:26:54,520 --> 00:26:58,199 Speaker 12: as much as is possible to drive competitive differentiation, to 539 00:26:58,280 --> 00:27:00,720 Speaker 12: drive sustainable long term growth, but I also want to 540 00:27:00,760 --> 00:27:03,160 Speaker 12: be able to modulate that, and in fact, we're doing 541 00:27:03,240 --> 00:27:04,240 Speaker 12: both at the same time. 542 00:27:04,720 --> 00:27:05,480 Speaker 8: Tim, I'll tell. 543 00:27:05,320 --> 00:27:08,320 Speaker 12: You this year, for the last seven years, we have 544 00:27:08,440 --> 00:27:10,840 Speaker 12: re engineered more than one percent of the cost spase 545 00:27:10,880 --> 00:27:13,440 Speaker 12: out of the company every year. This year is one 546 00:27:13,480 --> 00:27:16,080 Speaker 12: point six percent. So we're doing more of that, and 547 00:27:16,160 --> 00:27:19,880 Speaker 12: yet we're also investing more. The average investment rate growth 548 00:27:19,960 --> 00:27:22,040 Speaker 12: rate for the last six years has been twenty percent. 549 00:27:22,280 --> 00:27:25,760 Speaker 12: This year is thirty two percent. More investments in technology, 550 00:27:25,800 --> 00:27:28,600 Speaker 12: in marketing, and hiring new people. And so you've got 551 00:27:28,600 --> 00:27:30,440 Speaker 12: to be doing both of those things. And I think 552 00:27:30,720 --> 00:27:34,840 Speaker 12: you know, frankly, the companies that have the capability to 553 00:27:35,000 --> 00:27:37,919 Speaker 12: manage dynamically in that way, that really can continue to 554 00:27:37,920 --> 00:27:40,879 Speaker 12: be successful and find the pockets of profitable growth in 555 00:27:40,920 --> 00:27:43,159 Speaker 12: this new normal of uncertainty. 556 00:27:43,960 --> 00:27:47,800 Speaker 13: Zach, you reported quarterly earnings today. There's a proposal out 557 00:27:47,800 --> 00:27:50,879 Speaker 13: from the SEC to make that voluntary and to shift 558 00:27:50,920 --> 00:27:54,679 Speaker 13: to SEMU annual reporting. There was a common period that 559 00:27:54,800 --> 00:27:58,119 Speaker 13: ended earlier this month where a huge amount as a 560 00:27:58,240 --> 00:28:01,399 Speaker 13: ninety nine percent of respondence to the SEC said that 561 00:28:01,480 --> 00:28:03,720 Speaker 13: they don't think it's a good idea. Do you think 562 00:28:03,760 --> 00:28:06,439 Speaker 13: you would change the frequency of your reporting if you 563 00:28:06,480 --> 00:28:07,399 Speaker 13: were given the chance to. 564 00:28:09,400 --> 00:28:12,199 Speaker 12: I think that our key stakeholders, our investors, appreciate the 565 00:28:12,240 --> 00:28:16,800 Speaker 12: frequency with which we are sharing information. I mean, frankly, Nina, 566 00:28:17,240 --> 00:28:19,480 Speaker 12: we not only report every quarter, you know, at the 567 00:28:19,560 --> 00:28:21,920 Speaker 12: quarter end, but then at least once a quarter, if 568 00:28:21,920 --> 00:28:24,400 Speaker 12: not twice. We're up on stage at a major conference 569 00:28:24,440 --> 00:28:27,560 Speaker 12: talking about financial projections, talking about what we're seeing on 570 00:28:27,600 --> 00:28:29,800 Speaker 12: the ground, and I think, you know, investors have been 571 00:28:30,520 --> 00:28:33,119 Speaker 12: accustomed to that and frankly value that. So you know, 572 00:28:33,119 --> 00:28:36,640 Speaker 12: we'd be pretty reactive to what our stakeholders want, which 573 00:28:36,680 --> 00:28:38,880 Speaker 12: I believe at this point is continue with that frequency 574 00:28:38,880 --> 00:28:39,960 Speaker 12: of at least quarterly. 575 00:28:40,920 --> 00:28:44,400 Speaker 13: Okay, just want follow up. You mentioned AI earlier. Big 576 00:28:44,480 --> 00:28:46,840 Speaker 13: question amongst the CFOs that I'm speaking to for the 577 00:28:46,880 --> 00:28:49,320 Speaker 13: CFO briefing is this question as to how do you 578 00:28:49,440 --> 00:28:53,000 Speaker 13: keep a tab or lid on costs to make sure 579 00:28:53,000 --> 00:28:56,240 Speaker 13: that AI spending for tokens doesn't go through your budget. 580 00:28:56,280 --> 00:28:57,920 Speaker 13: How do you manage that at Huntington. 581 00:28:59,000 --> 00:29:01,240 Speaker 12: Yeah, it's it's a big area of focus. I will 582 00:29:01,240 --> 00:29:03,640 Speaker 12: tell you At this point, we're still very much defaulted 583 00:29:03,640 --> 00:29:07,600 Speaker 12: toward we want our teams to lean into to quickly 584 00:29:07,600 --> 00:29:12,040 Speaker 12: adopt this technology, and we want to see all of 585 00:29:12,080 --> 00:29:15,960 Speaker 12: the innovation and promise of it first. With that being said, 586 00:29:15,960 --> 00:29:18,640 Speaker 12: what I'm thinking about as a CFO and as an aside, 587 00:29:18,840 --> 00:29:21,880 Speaker 12: I co lead with our chief technology officer the company's 588 00:29:21,920 --> 00:29:24,800 Speaker 12: AI efforts, and so I'm particularly close to this is 589 00:29:25,360 --> 00:29:28,280 Speaker 12: in the background. We are building a lot of infrastructure 590 00:29:28,320 --> 00:29:31,520 Speaker 12: to be able to infect, manage token costs, and optimize 591 00:29:31,520 --> 00:29:33,200 Speaker 12: the cost of AI as we go forward, and a 592 00:29:33,240 --> 00:29:35,480 Speaker 12: lot of that's going to come down to what's the 593 00:29:35,520 --> 00:29:38,640 Speaker 12: best model for the right use case at the right 594 00:29:38,720 --> 00:29:41,520 Speaker 12: time to be able to optimize that. I'm personally pretty 595 00:29:41,560 --> 00:29:45,360 Speaker 12: sanguine here from what we're seeing. We're seeing significant ROI 596 00:29:45,720 --> 00:29:48,280 Speaker 12: at this but albeit at the very early stages. This 597 00:29:48,400 --> 00:29:51,120 Speaker 12: is where we are just at the cusp of this revolution. 598 00:29:51,360 --> 00:29:53,200 Speaker 4: Zach, you're not saying to the guys down the hall, hey, 599 00:29:53,280 --> 00:29:55,560 Speaker 4: get off of the AI. It's costing us money. 600 00:29:55,600 --> 00:29:56,160 Speaker 3: Are you doing that? 601 00:29:56,320 --> 00:29:58,040 Speaker 12: I'm actually if it's funny you say that we are 602 00:29:58,120 --> 00:30:01,080 Speaker 12: celebrating usage. We are trying to urge people to use 603 00:30:01,120 --> 00:30:02,280 Speaker 12: it as much as we possibly can. 604 00:30:02,480 --> 00:30:06,280 Speaker 4: Always appreciate time with you, Zach Wasserman. He's ce CFO. Oop, 605 00:30:06,320 --> 00:30:09,880 Speaker 4: sorry to tell the CEO CFO of Huntington Bank Shares 606 00:30:09,960 --> 00:30:12,400 Speaker 4: and of course our Anina Trentman Bloomberg New senior editor 607 00:30:12,520 --> 00:30:15,080 Speaker 4: editor of the CFO Briefing newsletter. You can find it 608 00:30:15,080 --> 00:30:18,760 Speaker 4: at Bloomberg dot com slash CFO Dash Briefing. 609 00:30:20,160 --> 00:30:23,240 Speaker 2: Stay with us more from Bloomberg BusinessWeek Daily coming up 610 00:30:23,480 --> 00:30:23,920 Speaker 2: after this. 611 00:30:28,440 --> 00:30:32,320 Speaker 1: You're listening to the Bloomberg Business Week Daily Podcast. Catch 612 00:30:32,360 --> 00:30:35,040 Speaker 1: us live weekday afternoons from two to five eas during 613 00:30:35,280 --> 00:30:39,160 Speaker 1: Listen on Applecarplay and Android Auto with the Bloomberg Business app, 614 00:30:39,360 --> 00:30:41,480 Speaker 1: or watch us Live on YouTube. 615 00:30:42,200 --> 00:30:43,600 Speaker 2: Well it is today's big Take. It's one of the 616 00:30:43,640 --> 00:30:46,160 Speaker 2: most read stories on the Bloomberg terminal. It's a Bloomberg 617 00:30:46,160 --> 00:30:49,640 Speaker 2: exclusive too. President Trump signed the Genius Act into law 618 00:30:49,680 --> 00:30:52,479 Speaker 2: a year ago. This month celebrated. He celebrated it as 619 00:30:52,520 --> 00:30:55,560 Speaker 2: a step toward bringing digital assets into the mainstream of 620 00:30:55,640 --> 00:30:56,600 Speaker 2: American finance. 621 00:30:56,680 --> 00:30:59,640 Speaker 4: He did in interviews at a court filing, and inside 622 00:30:59,680 --> 00:31:03,320 Speaker 4: account to the negotiation surrounding the law has emerged in 623 00:31:03,360 --> 00:31:06,120 Speaker 4: the months before and after President Trump took office. His 624 00:31:06,200 --> 00:31:09,680 Speaker 4: advisors Howard Lutnik and Bell Hines worked behind the scenes 625 00:31:09,720 --> 00:31:12,840 Speaker 4: to loosen safeguards and shape the law in ways that 626 00:31:12,920 --> 00:31:15,920 Speaker 4: benefited the world's dominant stable coin issuer. 627 00:31:15,880 --> 00:31:17,320 Speaker 8: Teather Bloomberg reporters. 628 00:31:17,320 --> 00:31:20,200 Speaker 2: He examined court filings and interviewed people familiar with the 629 00:31:20,280 --> 00:31:23,120 Speaker 2: legislative process to report this story. One of those reporters 630 00:31:23,480 --> 00:31:27,239 Speaker 2: is David Kochanski, senior investigative reporter based out of our 631 00:31:27,280 --> 00:31:29,160 Speaker 2: Princeton Bureau. David joins US now. 632 00:31:29,200 --> 00:31:29,440 Speaker 8: David. 633 00:31:29,440 --> 00:31:31,840 Speaker 2: First of all, congratulations to you and the team on 634 00:31:32,200 --> 00:31:35,000 Speaker 2: this story. It's a deep dive. I encourage everybody to 635 00:31:35,040 --> 00:31:36,720 Speaker 2: read it. We're going to give people a little taste 636 00:31:36,720 --> 00:31:38,600 Speaker 2: of it right now, and I want to start with 637 00:31:38,640 --> 00:31:42,040 Speaker 2: the basics about the Genius Act. What exactly did it 638 00:31:42,160 --> 00:31:45,280 Speaker 2: do and how does it differ from previous attempts to 639 00:31:45,320 --> 00:31:47,600 Speaker 2: write legislation for regulating stable coins. 640 00:31:48,960 --> 00:31:52,600 Speaker 14: You know, the Genius Act was the first legislatives attempt 641 00:31:52,600 --> 00:31:55,600 Speaker 14: by the Trump administration to make the US the crypto 642 00:31:55,680 --> 00:31:58,800 Speaker 14: capital of the world. It was set to regulate a 643 00:31:58,840 --> 00:32:01,720 Speaker 14: type of crypto on his stateable coins. Stable coins are 644 00:32:01,960 --> 00:32:05,640 Speaker 14: pegged to the US dollar. There's unlike bitcoin and other 645 00:32:06,000 --> 00:32:08,640 Speaker 14: crypto it's supposed to have a stable value, which makes 646 00:32:08,640 --> 00:32:12,760 Speaker 14: it it's widely used for international transfers and also for 647 00:32:12,840 --> 00:32:17,000 Speaker 14: other bitcoin related and crypto transactions. So this is a 648 00:32:17,000 --> 00:32:19,640 Speaker 14: way to make it standardized and to make sure that 649 00:32:19,840 --> 00:32:23,440 Speaker 14: first of all, the companies would have to have enough 650 00:32:24,400 --> 00:32:27,200 Speaker 14: transparency and talk about the reserves and how those stable 651 00:32:27,240 --> 00:32:31,160 Speaker 14: coins were backed, and also have us AML requirements. Because 652 00:32:31,160 --> 00:32:34,840 Speaker 14: stable coins, because they're quick and cheap, they are often 653 00:32:34,960 --> 00:32:37,360 Speaker 14: used by illicit transfers, for sanctioned. 654 00:32:37,320 --> 00:32:39,800 Speaker 5: Evasion and for criminal organizations, and. 655 00:32:39,760 --> 00:32:41,520 Speaker 14: So this is an attempt to bring them under US 656 00:32:41,560 --> 00:32:43,360 Speaker 14: regulations the way that banks are regulated. 657 00:32:43,800 --> 00:32:43,960 Speaker 3: Now. 658 00:32:44,000 --> 00:32:48,520 Speaker 4: The legislation Legislation David does apply to every stable coin issuer. 659 00:32:48,640 --> 00:32:53,200 Speaker 4: How to Tether though specifically benefit from the provisions in 660 00:32:53,280 --> 00:32:53,720 Speaker 4: the act. 661 00:32:54,680 --> 00:32:57,360 Speaker 14: You know, Tether is the world's largest stable coin company. 662 00:32:57,400 --> 00:33:00,600 Speaker 14: It's got like sixty percent of the global market, but 663 00:33:00,680 --> 00:33:03,800 Speaker 14: it is based outside of the US. It was first 664 00:33:03,840 --> 00:33:06,400 Speaker 14: based in the Caribbean and has recently moved. 665 00:33:06,120 --> 00:33:07,120 Speaker 5: To l Salvador. 666 00:33:07,560 --> 00:33:10,960 Speaker 14: So it was able to operate without being subject to 667 00:33:11,120 --> 00:33:16,320 Speaker 14: us AML requirements or US transparency requirements. So, you know, 668 00:33:16,360 --> 00:33:18,680 Speaker 14: there was a big push and going back to twenty 669 00:33:18,720 --> 00:33:23,160 Speaker 14: twenty four, because Tether was so widely used among criminals 670 00:33:23,240 --> 00:33:26,360 Speaker 14: and sanctions of vaders, there was some discussions in the 671 00:33:26,400 --> 00:33:30,000 Speaker 14: Biden administration about banning them from the US. There was 672 00:33:30,040 --> 00:33:33,120 Speaker 14: a decision was not to do a ban, but to 673 00:33:33,160 --> 00:33:37,240 Speaker 14: try to bring them into the US under regulations, but 674 00:33:37,440 --> 00:33:42,600 Speaker 14: when the legislation was being formulated, there were steps taid 675 00:33:42,840 --> 00:33:44,760 Speaker 14: that gave them a few loopholes or allowed them to 676 00:33:44,800 --> 00:33:47,720 Speaker 14: avoid the kind of regulation that US companies go under. 677 00:33:48,200 --> 00:33:51,600 Speaker 2: We're speaking with David Kochineski, senior investigative reporter. He's based 678 00:33:51,640 --> 00:33:54,080 Speaker 2: out of our Princeton Bureau. He and the team are 679 00:33:54,120 --> 00:33:56,680 Speaker 2: behind today's big take and one of the most read 680 00:33:56,720 --> 00:33:59,600 Speaker 2: stories on the Bloomberg terminal. This brings us to the 681 00:33:59,600 --> 00:34:03,440 Speaker 2: trumpet insiders that shaped stable coin legislation before and after 682 00:34:03,760 --> 00:34:07,400 Speaker 2: the President returned to office in January twenty five. This 683 00:34:07,480 --> 00:34:09,960 Speaker 2: is the heart of your story. How did this work? 684 00:34:11,080 --> 00:34:14,560 Speaker 14: Well, there's two insiders who we were told were involved 685 00:34:14,560 --> 00:34:17,200 Speaker 14: in it. First was Howard Lutnick, who's now the Commerce Secretary. 686 00:34:17,640 --> 00:34:19,319 Speaker 14: Now there's Bo Hines, who is the head of the 687 00:34:19,320 --> 00:34:23,000 Speaker 14: President's Digital Assets Council. 688 00:34:24,000 --> 00:34:25,719 Speaker 5: Lutnick since twenty twenty one, he. 689 00:34:25,680 --> 00:34:29,319 Speaker 14: Says, was the CEO of Canter Fitzgerald. They worked with 690 00:34:29,360 --> 00:34:32,680 Speaker 14: Tether Managing. There are hundreds of billions, one hundred and 691 00:34:32,719 --> 00:34:33,919 Speaker 14: eighty billion dollars. 692 00:34:33,560 --> 00:34:35,120 Speaker 5: Of reserves that they have now. 693 00:34:35,880 --> 00:34:39,400 Speaker 14: And you know he worked with he worked with Tether 694 00:34:39,880 --> 00:34:42,960 Speaker 14: in the run up to the election in twenty twenty four, 695 00:34:43,920 --> 00:34:46,759 Speaker 14: he bought a piece, bought a he encounter, bought a 696 00:34:46,760 --> 00:34:49,680 Speaker 14: convertible bond which gave them the rights to own five 697 00:34:49,680 --> 00:34:54,440 Speaker 14: percent of Tether. He as the Trump campaign moved forward 698 00:34:54,480 --> 00:34:59,440 Speaker 14: and President then presidential candidate Trump became closer to Crypto, 699 00:35:00,120 --> 00:35:01,440 Speaker 14: he then worked. 700 00:35:01,200 --> 00:35:02,080 Speaker 5: Behind the scenes. 701 00:35:02,680 --> 00:35:05,000 Speaker 14: He went to Washington and spoke to people working on 702 00:35:05,040 --> 00:35:08,480 Speaker 14: a crypto bill that would have been more restrictive for 703 00:35:08,560 --> 00:35:10,880 Speaker 14: Tether and kind of urged them to reconsider it and 704 00:35:10,960 --> 00:35:13,200 Speaker 14: back off a few things and said, hey, if you 705 00:35:13,239 --> 00:35:17,200 Speaker 14: wait till after the election, we have a chance to 706 00:35:17,239 --> 00:35:19,960 Speaker 14: do something different, because they thought President Trump was going 707 00:35:19,960 --> 00:35:23,920 Speaker 14: to win. So he before the election was involved in that. 708 00:35:24,320 --> 00:35:27,160 Speaker 14: During the transition, you know, Lutnik was one of the 709 00:35:27,200 --> 00:35:30,520 Speaker 14: co chairs of the Transition Committee. He also worked with 710 00:35:30,560 --> 00:35:34,560 Speaker 14: Tether to make investments. He and Counterford Gerald had them 711 00:35:34,560 --> 00:35:38,840 Speaker 14: invest in Rumble, which is a very the company the 712 00:35:38,840 --> 00:35:43,280 Speaker 14: streaming company that hosts truth Social, the president's streaming company, 713 00:35:43,960 --> 00:35:49,480 Speaker 14: and is also its investors included jd Vance, David Sachs, 714 00:35:49,960 --> 00:35:53,080 Speaker 14: you know who is the cryptosar for the Trump administration, 715 00:35:53,480 --> 00:35:56,799 Speaker 14: Dan Benino, who was in the FBI. So he kind 716 00:35:56,800 --> 00:35:59,960 Speaker 14: of brought them into the financial orbit during the transition. 717 00:36:01,440 --> 00:36:06,400 Speaker 14: Once the administration took place, Bohines took over from the 718 00:36:06,400 --> 00:36:06,879 Speaker 14: White House. 719 00:36:07,640 --> 00:36:11,000 Speaker 4: To be fair, let's take first from Tether. How did 720 00:36:11,000 --> 00:36:14,000 Speaker 4: they respond to the reporting here? 721 00:36:15,160 --> 00:36:18,360 Speaker 14: You know, Tather said that it everything it did was 722 00:36:18,360 --> 00:36:23,759 Speaker 14: was appropriate. Like many companies, it lobbied. It did hire 723 00:36:23,840 --> 00:36:26,279 Speaker 14: a lobbyist who was the same lobbyist who Canter Fitzgerald 724 00:36:26,360 --> 00:36:27,279 Speaker 14: had lobbying on the bill. 725 00:36:27,840 --> 00:36:30,120 Speaker 5: But it said that it was you know, everything it 726 00:36:30,120 --> 00:36:31,040 Speaker 5: did was above board. 727 00:36:31,560 --> 00:36:34,399 Speaker 4: And what about mister Lutnik and mister Hines, what did 728 00:36:34,440 --> 00:36:36,200 Speaker 4: they or how did they respond to this? 729 00:36:37,760 --> 00:36:38,920 Speaker 5: Mister Lutnik the same thing. 730 00:36:38,920 --> 00:36:43,720 Speaker 14: He said that he has a ethics is an ethics 731 00:36:43,719 --> 00:36:47,640 Speaker 14: waiver and an ethics agreement with the Ethics Office, and 732 00:36:47,680 --> 00:36:50,239 Speaker 14: he said he was totally in compliance with it. He 733 00:36:50,280 --> 00:36:53,120 Speaker 14: said that once in office he did not take any 734 00:36:53,160 --> 00:36:58,080 Speaker 14: part in the Genius Act negotiations. Bohines did not respond, 735 00:36:58,120 --> 00:37:01,240 Speaker 14: and Tether where he now works, not respond to anything 736 00:37:01,239 --> 00:37:02,240 Speaker 14: about his involvement. 737 00:37:03,120 --> 00:37:06,600 Speaker 4: You know. To be fair, maybe I'm playing Devil's Advocate 738 00:37:07,040 --> 00:37:11,720 Speaker 4: David here a little bit, but I mean we often see, 739 00:37:11,920 --> 00:37:15,960 Speaker 4: you know, folks in government go to the private sector. 740 00:37:16,200 --> 00:37:18,840 Speaker 4: We see, you know, back and forth. 741 00:37:19,040 --> 00:37:20,920 Speaker 8: We'll say the president saiduring his first term, that was 742 00:37:20,960 --> 00:37:21,279 Speaker 8: going to. 743 00:37:21,239 --> 00:37:24,520 Speaker 4: Stop, right, right, We talked about this, right, he talked 744 00:37:24,520 --> 00:37:26,200 Speaker 4: about the swamp, like the revolving door. 745 00:37:26,320 --> 00:37:27,840 Speaker 8: He said that that wasn't going to happen. 746 00:37:28,040 --> 00:37:34,440 Speaker 4: But Republicans, Democrats alike, What though in the reporting says 747 00:37:34,480 --> 00:37:38,160 Speaker 4: something maybe is a little bit above and beyond that 748 00:37:38,280 --> 00:37:40,560 Speaker 4: kind of normal back and forth between the private and 749 00:37:40,600 --> 00:37:46,680 Speaker 4: public sector of individuals and whether influencing or donating, which 750 00:37:46,719 --> 00:37:50,840 Speaker 4: is all legal in terms of political contributions, there is 751 00:37:50,840 --> 00:37:53,640 Speaker 4: always kind of some sway. But what in the reporting 752 00:37:54,080 --> 00:37:57,360 Speaker 4: maybe makes this standout perhaps a little bit more. 753 00:37:58,480 --> 00:38:01,520 Speaker 14: Again, I think you're very accurately. There's not any indication 754 00:38:01,640 --> 00:38:05,520 Speaker 14: that the ethics rolls that exist now were violated. But 755 00:38:05,680 --> 00:38:07,560 Speaker 14: for Bohinz, it was interesting that in less than a 756 00:38:07,600 --> 00:38:10,400 Speaker 14: month after the after the bill was signed, he was 757 00:38:10,440 --> 00:38:14,960 Speaker 14: working for Tether and in second Commerce Secretary Aleutnux. 758 00:38:16,360 --> 00:38:18,000 Speaker 5: Instance. I think it has to do with the amount 759 00:38:18,000 --> 00:38:19,000 Speaker 5: of money involved. 760 00:38:19,680 --> 00:38:23,640 Speaker 14: You know, he bought a stake in Tether a convertible 761 00:38:23,680 --> 00:38:26,720 Speaker 14: bond in twenty twenty four for six hundred million dollars. 762 00:38:27,120 --> 00:38:28,760 Speaker 5: At the time, it was probably. 763 00:38:28,320 --> 00:38:30,200 Speaker 14: Worth about six billion if you look at the way 764 00:38:30,280 --> 00:38:34,360 Speaker 14: the companies were valued. And after the bill was signed, 765 00:38:34,680 --> 00:38:39,360 Speaker 14: you know, he divested with as most cabinet secretaries have 766 00:38:39,400 --> 00:38:39,680 Speaker 14: to do. 767 00:38:40,239 --> 00:38:43,320 Speaker 5: He had invested by selling to his children. And the 768 00:38:43,440 --> 00:38:44,520 Speaker 5: day after they. 769 00:38:44,400 --> 00:38:48,799 Speaker 14: Bought him out, they received a loan from tether a 770 00:38:48,840 --> 00:38:49,720 Speaker 14: trust that they control. 771 00:38:50,560 --> 00:38:53,279 Speaker 5: Received a loan. They won't talk about what it was, 772 00:38:53,440 --> 00:38:55,440 Speaker 5: what it was for. They won't talk about whether they 773 00:38:55,560 --> 00:38:56,560 Speaker 5: used it to buy him out. 774 00:38:56,640 --> 00:39:00,560 Speaker 14: But in Congress two senators have said there they've asked 775 00:39:00,640 --> 00:39:02,560 Speaker 14: Lutnick for more details about it because that said they 776 00:39:02,600 --> 00:39:04,799 Speaker 14: want to be sure the Teather wasn't trying to. 777 00:39:04,760 --> 00:39:05,719 Speaker 5: Influence or bribe it. 778 00:39:06,960 --> 00:39:09,880 Speaker 4: There's a lot in this story. We highly recommend that 779 00:39:10,080 --> 00:39:11,319 Speaker 4: folks go to it. 780 00:39:11,360 --> 00:39:11,880 Speaker 3: We don't want to. 781 00:39:11,880 --> 00:39:15,239 Speaker 4: Rush through more, but there's a lot of information about 782 00:39:15,280 --> 00:39:18,759 Speaker 4: the deep dive and the investigation and investigative reporting that 783 00:39:18,800 --> 00:39:21,080 Speaker 4: you guys have done. David, Thank you so much. I'm 784 00:39:21,080 --> 00:39:24,719 Speaker 4: glad we could bring it to Thank you. David Kotchinski. 785 00:39:25,040 --> 00:39:28,759 Speaker 4: He is senior investigative reporter for Bloomberg News out there 786 00:39:28,800 --> 00:39:29,760 Speaker 4: in our Princeton bureau. 787 00:39:30,880 --> 00:39:36,360 Speaker 1: This is the Bloomberg Business Weekdaily podcast, available on Apple Spotify, 788 00:39:36,520 --> 00:39:40,560 Speaker 1: and anywhere else you get your podcasts. 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