1 00:00:02,720 --> 00:00:10,600 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,600 --> 00:00:14,600 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am 3 00:00:14,640 --> 00:00:18,560 Speaker 1: Eastern on Applecarplay and Android Auto with the Bloomberg Business App. 4 00:00:18,640 --> 00:00:21,920 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:21,960 --> 00:00:23,120 Speaker 1: us live on YouTube. 6 00:00:23,680 --> 00:00:25,520 Speaker 2: We have some economic data coming out right now. I 7 00:00:25,520 --> 00:00:28,360 Speaker 2: have some services data coming out forty nine point nine. 8 00:00:28,400 --> 00:00:30,960 Speaker 2: That headline consensus on US was fifty two, so not 9 00:00:31,080 --> 00:00:33,200 Speaker 2: kind of flirting with a little bit of a contraction 10 00:00:33,280 --> 00:00:35,080 Speaker 2: there in the services part of the economy, which again 11 00:00:35,120 --> 00:00:36,800 Speaker 2: is about seventy percent of the US economy. 12 00:00:37,159 --> 00:00:37,839 Speaker 3: Let's get right to it. 13 00:00:37,920 --> 00:00:40,120 Speaker 2: Steve Miller, a chair of the is some services PMI 14 00:00:40,320 --> 00:00:43,480 Speaker 2: on that data. Steve, I'm looking at that headline data 15 00:00:43,560 --> 00:00:44,760 Speaker 2: forty nine point nine. 16 00:00:44,880 --> 00:00:46,599 Speaker 3: That's below fifty. Talk to us about that. 17 00:00:47,800 --> 00:00:51,519 Speaker 4: Good morning, Thanks for having me back. You know, zo 18 00:00:51,520 --> 00:00:55,800 Speaker 4: point one percent below the flat in services industries. 19 00:00:56,440 --> 00:00:57,200 Speaker 3: Flat is bad. 20 00:00:57,360 --> 00:01:00,200 Speaker 4: You know, we've seen we see long term growth when 21 00:01:00,200 --> 00:01:04,240 Speaker 4: we get to flat or just below flat, certainly negative indicators. 22 00:01:04,640 --> 00:01:08,679 Speaker 4: On the positive side, we track the numbers by industry 23 00:01:08,840 --> 00:01:12,039 Speaker 4: and how they contribute to overall GDP. What we're seeing 24 00:01:12,120 --> 00:01:15,240 Speaker 4: is a slight increase in the percent of GDP that's 25 00:01:15,280 --> 00:01:19,160 Speaker 4: representing growth, and a slight decrease in those that are 26 00:01:19,200 --> 00:01:23,040 Speaker 4: saying that they're in contraction territory. What we saw bringing 27 00:01:23,040 --> 00:01:28,520 Speaker 4: the number overall down was for accommodations and food services 28 00:01:29,240 --> 00:01:32,720 Speaker 4: and the real estate rental and leasing. Although both still 29 00:01:32,720 --> 00:01:36,080 Speaker 4: an expansion territory, they're not as high or as fast 30 00:01:36,200 --> 00:01:38,080 Speaker 4: level of expansion as they were last month. 31 00:01:40,440 --> 00:01:43,360 Speaker 5: So I was confused as to how im services employment 32 00:01:43,440 --> 00:01:46,920 Speaker 5: actually ticked above that fifty level, whereas a new order 33 00:01:47,000 --> 00:01:49,760 Speaker 5: is just tanked to forty six and the overall index 34 00:01:49,920 --> 00:01:51,720 Speaker 5: is below fifty, what does that. 35 00:01:51,680 --> 00:01:57,320 Speaker 4: Mean well on the employment side, my interpretation of those 36 00:01:57,440 --> 00:02:01,280 Speaker 4: numbers is that we're still seeing confidence that the terror 37 00:02:01,320 --> 00:02:03,840 Speaker 4: situation is going to get worked out and we're going 38 00:02:03,880 --> 00:02:06,400 Speaker 4: to be able to return to growth. But the new 39 00:02:06,520 --> 00:02:11,239 Speaker 4: orders and actually seeing backlog as well backlocker orders, we're 40 00:02:11,240 --> 00:02:15,520 Speaker 4: seeing those very low. And another data point is when 41 00:02:15,520 --> 00:02:18,760 Speaker 4: I look at the average of new orders and backlog, 42 00:02:19,320 --> 00:02:22,600 Speaker 4: this is the lowest that it's been since two other 43 00:02:22,639 --> 00:02:25,840 Speaker 4: points in the last twenty years. One was the beginning 44 00:02:26,000 --> 00:02:29,320 Speaker 4: of the pandemic in March and April, and the other 45 00:02:29,600 --> 00:02:31,359 Speaker 4: was in the two thousand and eight two thousand and 46 00:02:31,400 --> 00:02:35,000 Speaker 4: nine time frame in the Great Recession. So for me, 47 00:02:35,160 --> 00:02:37,519 Speaker 4: that's the biggest red flag is the drop in new 48 00:02:37,639 --> 00:02:41,440 Speaker 4: orders as well as both the average level between the 49 00:02:41,480 --> 00:02:44,400 Speaker 4: new orders and the backlog of orders. 50 00:02:46,520 --> 00:02:48,720 Speaker 2: So we've got new orders lower that's concerned about just 51 00:02:48,760 --> 00:02:51,720 Speaker 2: the economy slowing down, and we've got services prices paid 52 00:02:52,160 --> 00:02:55,079 Speaker 2: coming in much higher than expected. 53 00:02:55,120 --> 00:02:55,840 Speaker 3: Is that inflation? 54 00:02:58,000 --> 00:03:01,880 Speaker 4: So I can't say yet whether it's inflationary, but I 55 00:03:01,880 --> 00:03:05,600 Speaker 4: would tell you that the two month growth rate is 56 00:03:05,680 --> 00:03:10,720 Speaker 4: what we saw just at the start of the acceleration 57 00:03:10,800 --> 00:03:12,600 Speaker 4: and inflation back during the pandemic. 58 00:03:14,080 --> 00:03:15,520 Speaker 3: So definitely that's right. 59 00:03:15,639 --> 00:03:16,480 Speaker 2: See, we appreciate it. 60 00:03:16,520 --> 00:03:16,840 Speaker 6: Thank you. 61 00:03:18,480 --> 00:03:20,080 Speaker 5: Yeah, we know you've got to run, so we'll let 62 00:03:20,080 --> 00:03:23,520 Speaker 5: you go. Steve Miller, Chair of the Ism Services, joining us. 63 00:03:23,520 --> 00:03:26,720 Speaker 5: They're really rough new order, so we will keep track 64 00:03:27,080 --> 00:03:28,280 Speaker 5: of all of that as it goes. 65 00:03:29,960 --> 00:03:33,680 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 66 00:03:33,760 --> 00:03:36,840 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 67 00:03:36,840 --> 00:03:40,160 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 68 00:03:40,200 --> 00:03:43,360 Speaker 1: you get your podcasts, or watch us live on YouTube. 69 00:03:43,840 --> 00:03:46,520 Speaker 5: So the economic data we keep hearing is going to 70 00:03:46,520 --> 00:03:48,760 Speaker 5: be a few months off till we see any negativity 71 00:03:48,800 --> 00:03:50,680 Speaker 5: hit the hard data. But let's just go over some 72 00:03:50,760 --> 00:03:52,440 Speaker 5: of the data we got today. We got the ADP 73 00:03:52,600 --> 00:03:56,440 Speaker 5: employment number, disappointing, coming in at just thirty seven thousand jobs. 74 00:03:56,480 --> 00:03:58,320 Speaker 5: Then you had the ISM services number and it was 75 00:03:58,360 --> 00:04:00,880 Speaker 5: pretty rough. You had the overall index below fifty. That's 76 00:04:00,920 --> 00:04:04,680 Speaker 5: contraction territory. But the big thing was new orders coming 77 00:04:04,680 --> 00:04:06,680 Speaker 5: in at the lowest level. Like we saw bask in 78 00:04:06,680 --> 00:04:09,520 Speaker 5: April twenty twenty. No one likes April of twenty twenty. 79 00:04:09,920 --> 00:04:12,080 Speaker 5: Also back in two thousand and eight, two thousand and nine, 80 00:04:12,080 --> 00:04:13,680 Speaker 5: no one liked two thousand and eight and two thousand 81 00:04:13,680 --> 00:04:15,520 Speaker 5: and nine joining us now for more. Michael mckeib when 82 00:04:15,560 --> 00:04:18,839 Speaker 5: we're going to National Economics and Policy correspondent, I'm like, 83 00:04:19,080 --> 00:04:20,680 Speaker 5: is this the stagflation kind of thing? 84 00:04:22,160 --> 00:04:24,160 Speaker 7: Well, if you took it at face value, it is 85 00:04:24,360 --> 00:04:27,880 Speaker 7: in the sense that we're looking at prices going up 86 00:04:27,960 --> 00:04:29,920 Speaker 7: and activity going down. 87 00:04:30,520 --> 00:04:32,080 Speaker 3: What we haven't seen. 88 00:04:32,000 --> 00:04:35,640 Speaker 7: Is, as you note, the hard data completely reflecting this, 89 00:04:35,760 --> 00:04:39,520 Speaker 7: we're starting to get numbers that do. Remember we saw 90 00:04:39,640 --> 00:04:44,000 Speaker 7: a big drop in imports during the last month, and 91 00:04:44,080 --> 00:04:48,080 Speaker 7: that was largely because so much was pulled forward because 92 00:04:48,080 --> 00:04:51,120 Speaker 7: of the impending tariffs, and so that will have an 93 00:04:51,120 --> 00:04:55,520 Speaker 7: impact on second quarter growth, but we're not at this 94 00:04:55,600 --> 00:04:58,440 Speaker 7: point able to say exactly where we go from there. 95 00:04:58,760 --> 00:05:01,120 Speaker 7: It looks like service are bad, and I know you 96 00:05:01,279 --> 00:05:06,240 Speaker 7: had the director of the Ism services on earlier and 97 00:05:06,279 --> 00:05:11,279 Speaker 7: he said that the new orders really are looking bad 98 00:05:11,480 --> 00:05:14,640 Speaker 7: right now. And that's just kind of a scary thought. 99 00:05:17,200 --> 00:05:20,200 Speaker 2: Hey, Mike in our group chat here, I dropped in 100 00:05:20,200 --> 00:05:22,080 Speaker 2: a note earlier that I said, you know, maybe a 101 00:05:22,120 --> 00:05:24,160 Speaker 2: few months time, we're going to look back on today 102 00:05:24,960 --> 00:05:28,880 Speaker 2: as the beginning of something, you know, whether it's tagflation, 103 00:05:29,080 --> 00:05:32,880 Speaker 2: whether it's recession, whether it's inflation really warring its head. 104 00:05:32,920 --> 00:05:34,240 Speaker 3: Am I being over dramatic there? 105 00:05:35,960 --> 00:05:38,039 Speaker 7: I don't know if I would say today, but it 106 00:05:38,080 --> 00:05:40,880 Speaker 7: could be this week in let's see what happens on 107 00:05:40,920 --> 00:05:42,080 Speaker 7: Friday with the jobs report. 108 00:05:42,720 --> 00:05:44,440 Speaker 3: This may be sort of the last. 109 00:05:44,240 --> 00:05:49,200 Speaker 7: Hurrah week where we see numbers that are okay in 110 00:05:49,320 --> 00:05:51,719 Speaker 7: terms of those things. The big question is going to 111 00:05:51,720 --> 00:05:56,360 Speaker 7: be whether ADP reflects reality or not, because any number 112 00:05:56,480 --> 00:06:00,560 Speaker 7: like that for Friday's payrolls figures would really scare the 113 00:06:00,600 --> 00:06:03,960 Speaker 7: pants off Wall Street and get everybody excited about FED 114 00:06:04,040 --> 00:06:06,200 Speaker 7: rate cuts, even if they're not going to happen right away, 115 00:06:06,680 --> 00:06:10,400 Speaker 7: So yes, this could be not mincing those time to remember, 116 00:06:13,480 --> 00:06:14,480 Speaker 7: Oh nice new us. 117 00:06:14,520 --> 00:06:16,599 Speaker 5: Then how do you square how do we think about 118 00:06:17,000 --> 00:06:20,960 Speaker 5: ADP versus the jolts that we got yesterday. I was thinking, like, 119 00:06:21,080 --> 00:06:23,360 Speaker 5: is it the companies just aren't hiring, but they're not 120 00:06:23,400 --> 00:06:26,240 Speaker 5: necessarily laying off either, Like how do we square those 121 00:06:26,240 --> 00:06:28,520 Speaker 5: two together in the broader economic jobs picture. 122 00:06:28,960 --> 00:06:31,000 Speaker 7: Well, it's not easy to square the two, except that 123 00:06:31,040 --> 00:06:34,240 Speaker 7: you note that ADP that the jolts rather is two 124 00:06:34,240 --> 00:06:38,960 Speaker 7: months old, so it is past data and things could 125 00:06:39,040 --> 00:06:42,279 Speaker 7: certainly have changed, which ADP suggests might be the case. 126 00:06:42,600 --> 00:06:45,880 Speaker 7: Now with ADP, what we're not seeing is whether companies 127 00:06:45,920 --> 00:06:49,800 Speaker 7: were letting anybody go and whether they have openings that 128 00:06:49,839 --> 00:06:52,760 Speaker 7: they want to fill. It just tells you they didn't 129 00:06:52,839 --> 00:06:56,560 Speaker 7: hire very many people or add to payrolls. Now, it 130 00:06:56,640 --> 00:06:59,839 Speaker 7: has historically been that ADP is usually way off from 131 00:07:00,160 --> 00:07:03,440 Speaker 7: the private sector hiring is in the non farm payrolls figure, 132 00:07:03,520 --> 00:07:06,520 Speaker 7: so we'll have to see how that proves out. On 133 00:07:06,600 --> 00:07:09,960 Speaker 7: Friday last month, ADP said there were only sixty thousand 134 00:07:10,280 --> 00:07:13,320 Speaker 7: private sector jobs created and the government found one hundred 135 00:07:13,320 --> 00:07:17,440 Speaker 7: and sixty seven thousand, So I don't know whether ADP 136 00:07:17,720 --> 00:07:19,920 Speaker 7: or Jolts gives us a better idea of what's going on, 137 00:07:19,960 --> 00:07:21,880 Speaker 7: But I don't think people are going to pay a 138 00:07:21,880 --> 00:07:24,560 Speaker 7: whole lot of attention to either one once we get 139 00:07:24,560 --> 00:07:25,440 Speaker 7: the Friday figures. 140 00:07:28,200 --> 00:07:31,720 Speaker 2: Tariffs, Mike, we have so many tariffs are very hard 141 00:07:31,760 --> 00:07:35,360 Speaker 2: to kind of keep them, keep them in focus here. 142 00:07:35,400 --> 00:07:36,240 Speaker 3: There's so many out there. 143 00:07:36,280 --> 00:07:39,200 Speaker 2: Do we have any idea kind of what percentage of 144 00:07:39,240 --> 00:07:41,640 Speaker 2: the tariffs have found their way into the economy at 145 00:07:41,640 --> 00:07:44,040 Speaker 2: this stage or is it just too early to tell here? 146 00:07:44,640 --> 00:07:46,680 Speaker 7: Well, there have been some rough back of the envelope 147 00:07:46,720 --> 00:07:50,960 Speaker 7: calculations that about what Bloomberg Economics has done one about 148 00:07:51,000 --> 00:07:54,280 Speaker 7: six percent of US imports have been affected by tariffs, 149 00:07:54,320 --> 00:07:57,760 Speaker 7: because we're looking at autos and we're looking at steel 150 00:07:57,800 --> 00:08:03,720 Speaker 7: and aluminum. Basically, tariff's likely coming. The Congressional Budget Office 151 00:08:03,760 --> 00:08:06,680 Speaker 7: just a short time ago put out a couple of 152 00:08:06,680 --> 00:08:09,920 Speaker 7: new reports, one suggesting that the Big Beautiful Bill is 153 00:08:09,960 --> 00:08:14,720 Speaker 7: going to add something like ten trillion dollars on to 154 00:08:15,000 --> 00:08:19,080 Speaker 7: the overall deficits over a period of years, and then 155 00:08:19,600 --> 00:08:24,239 Speaker 7: that the tariffs would reduce that by about three trillion. 156 00:08:25,120 --> 00:08:28,960 Speaker 7: So if all the tariffs were carried through and that's 157 00:08:29,000 --> 00:08:31,840 Speaker 7: the caveat that the CBO puts on their numbers today 158 00:08:32,160 --> 00:08:35,400 Speaker 7: that they don't know what tariffs are actually going to 159 00:08:35,400 --> 00:08:37,880 Speaker 7: be imposed. So that's the hard part for everybody at 160 00:08:37,920 --> 00:08:40,480 Speaker 7: the moment is how much are we going to tariff people? 161 00:08:40,520 --> 00:08:42,160 Speaker 7: And who are we going to tariff? 162 00:08:44,559 --> 00:08:46,680 Speaker 5: Mike, what's what's that nerdy chart that you have on 163 00:08:46,720 --> 00:08:48,080 Speaker 5: your desktop right now? 164 00:08:49,440 --> 00:08:49,760 Speaker 3: Actually? 165 00:08:49,840 --> 00:08:54,720 Speaker 7: I was looking at steel today and because of you, 166 00:08:54,800 --> 00:08:59,839 Speaker 7: of course, Alex Steele, the fact that when Trump put 167 00:08:59,880 --> 00:09:03,920 Speaker 7: on tariffs in twenty seventeen, we saw a short term 168 00:09:04,040 --> 00:09:08,040 Speaker 7: rise in employment at steel mills, but then that rolled 169 00:09:08,040 --> 00:09:13,960 Speaker 7: over and the number of jobs in the downstream people 170 00:09:13,960 --> 00:09:20,280 Speaker 7: who use steel in their industries fabricated medical metal producers 171 00:09:20,320 --> 00:09:25,160 Speaker 7: really fell significantly, lost about seventy five thousand jobs there. 172 00:09:25,559 --> 00:09:30,680 Speaker 7: So it'll be something we're gonna have to watch those 173 00:09:30,760 --> 00:09:34,959 Speaker 7: two numbers in Friday and the following month's reports on 174 00:09:35,600 --> 00:09:38,320 Speaker 7: how the steel tariffs are affecting the economy. 175 00:09:40,559 --> 00:09:42,440 Speaker 3: Yeah. I love that. I think I better come in 176 00:09:42,559 --> 00:09:45,319 Speaker 3: on Friday, Big Day. Are you going to be off Friday? No, 177 00:09:45,480 --> 00:09:47,319 Speaker 3: I think I'll be d I mean the thing is 178 00:09:47,720 --> 00:09:48,319 Speaker 3: from what we've been. 179 00:09:48,320 --> 00:09:50,360 Speaker 5: Learning, like maybe we'll get little cracks, but it's stillly 180 00:09:50,400 --> 00:09:51,920 Speaker 5: going to be in the next two months, maybe that 181 00:09:51,960 --> 00:09:53,760 Speaker 5: we'll get hard data. So I feel like you can 182 00:09:53,800 --> 00:09:56,000 Speaker 5: still get that on the Jersey Shore, but it's gonna 183 00:09:56,000 --> 00:09:58,080 Speaker 5: be rainy tvd oh well, then definitely come in from that. 184 00:09:58,160 --> 00:10:01,200 Speaker 5: All right, thanks, Mike, really appreciate it. Michael mckei, Bloomberger 185 00:10:01,280 --> 00:10:03,040 Speaker 5: National Economics and Policy Correspondent. 186 00:10:04,679 --> 00:10:08,360 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 187 00:10:08,440 --> 00:10:11,520 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 188 00:10:11,559 --> 00:10:14,840 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 189 00:10:14,920 --> 00:10:18,000 Speaker 1: you get your podcasts, or watch us live on YouTube. 190 00:10:18,320 --> 00:10:19,760 Speaker 5: All right, let's pick up with one of the stocks 191 00:10:19,760 --> 00:10:22,439 Speaker 5: that Norm was just talking about, and that is Wells 192 00:10:22,520 --> 00:10:25,240 Speaker 5: Fargo taking a look at that asset cat finally being 193 00:10:25,360 --> 00:10:28,080 Speaker 5: removed and what does it then mean after the seven 194 00:10:28,160 --> 00:10:30,960 Speaker 5: year old cap is removed for CEO Charlie Sharp, joining 195 00:10:31,000 --> 00:10:34,800 Speaker 5: us now is Hannah Levett, senior finance reporter from Bloomberg News. Now, Hannah, 196 00:10:34,920 --> 00:10:37,000 Speaker 5: Wells Fargo's been working at this for a very very 197 00:10:37,000 --> 00:10:39,840 Speaker 5: long time. How are they then positioned for this next 198 00:10:39,840 --> 00:10:40,640 Speaker 5: stage of growth? 199 00:10:41,000 --> 00:10:43,920 Speaker 8: Yeah, so this has truly been such a long saga 200 00:10:44,000 --> 00:10:47,440 Speaker 8: for them. Like I started covering Wells Fargo more than 201 00:10:47,480 --> 00:10:51,600 Speaker 8: seven years ago, they had just gotten put under this cap. 202 00:10:51,640 --> 00:10:54,000 Speaker 8: At the time, I was still enjoying my mid twenties, 203 00:10:55,120 --> 00:10:59,120 Speaker 8: and you know, now we are no longer there. For 204 00:10:59,240 --> 00:11:02,320 Speaker 8: Charlie Sharp, this means that he can finally play offense. 205 00:11:02,400 --> 00:11:05,040 Speaker 8: He can you know, they're not capped in size to 206 00:11:05,080 --> 00:11:07,839 Speaker 8: their level at the end of twenty seventeen anymore. And 207 00:11:07,920 --> 00:11:10,920 Speaker 8: remember that's been a huge deal for them along the way. 208 00:11:11,000 --> 00:11:13,520 Speaker 8: I mean some of the businesses that he's marked for growth, 209 00:11:13,640 --> 00:11:18,640 Speaker 8: like the trading business most notably, that's been constrained because 210 00:11:18,640 --> 00:11:20,600 Speaker 8: it's more balance sheet heavy and they haven't been able 211 00:11:20,640 --> 00:11:23,760 Speaker 8: to allocate that balance sheet because they're restricted. And like 212 00:11:23,960 --> 00:11:26,760 Speaker 8: just for context, JP Morgan, the biggest US bank, has 213 00:11:27,160 --> 00:11:30,559 Speaker 8: grown almost an entire Wells Fargo in terms of assets 214 00:11:30,559 --> 00:11:31,880 Speaker 8: in the time that Wells has been capped. 215 00:11:32,040 --> 00:11:35,960 Speaker 2: Wow, all right, hann I you know full discorder. I 216 00:11:35,960 --> 00:11:39,000 Speaker 2: have my checking account with Wells Fargo, but I'm guessing 217 00:11:39,000 --> 00:11:40,800 Speaker 2: the CEO and the management team there they want to 218 00:11:40,840 --> 00:11:42,560 Speaker 2: do something more than that. They think they can do 219 00:11:42,559 --> 00:11:44,480 Speaker 2: a little bit bigger and better than Paul's. And he's 220 00:11:44,520 --> 00:11:47,320 Speaker 2: checking account. So what are some of the businesses you 221 00:11:47,360 --> 00:11:51,120 Speaker 2: mentioned trading? Are there other eritors where they think they 222 00:11:51,160 --> 00:11:53,600 Speaker 2: can really grow by allocating more capital there? 223 00:11:54,160 --> 00:11:59,160 Speaker 8: Yeah, absolutely, so the businesses that Charlie Sharff marked for growth, 224 00:11:59,520 --> 00:12:01,320 Speaker 8: you know in time while he was running the firm, 225 00:12:01,360 --> 00:12:05,000 Speaker 8: but it was still under the cap where investment, banking 226 00:12:05,080 --> 00:12:09,640 Speaker 8: and trading and wealth management and credit card. But he 227 00:12:09,720 --> 00:12:12,760 Speaker 8: was saying on CNBC today that virtually every business aside 228 00:12:12,760 --> 00:12:15,360 Speaker 8: from mortgage, which they've said they're shrinking, and remember wells 229 00:12:15,360 --> 00:12:17,040 Speaker 8: Farga used to be huge, and mortgage at one point 230 00:12:17,240 --> 00:12:19,280 Speaker 8: they were churning out one in every three home loans 231 00:12:19,320 --> 00:12:22,800 Speaker 8: in the country. Every business other than that should grow 232 00:12:22,880 --> 00:12:24,760 Speaker 8: now and they have room to do that. But I 233 00:12:24,800 --> 00:12:29,760 Speaker 8: think those businesses where they've already said that they're targeting growth, 234 00:12:29,760 --> 00:12:33,600 Speaker 8: that may be where the earliest moves are. You know, 235 00:12:33,640 --> 00:12:37,120 Speaker 8: we've reported that they're working on a high end credit card, 236 00:12:37,240 --> 00:12:42,160 Speaker 8: so that could be something that people see. But yeah, 237 00:12:42,160 --> 00:12:43,840 Speaker 8: so it really just it goes across all of those 238 00:12:43,880 --> 00:12:48,920 Speaker 8: and beyond now because they don't have this constraint anymore, so. 239 00:12:49,040 --> 00:12:51,440 Speaker 5: How quickly can they scale in the other parts of 240 00:12:51,440 --> 00:12:52,280 Speaker 5: their business. 241 00:12:52,880 --> 00:12:55,600 Speaker 8: Yeah, Well, it's an interesting question, right because we've seen, 242 00:12:56,200 --> 00:12:58,520 Speaker 8: you know, the tales of banks trying to grow too 243 00:12:58,559 --> 00:13:02,560 Speaker 8: fast and then having you know, a calamitous blow up, 244 00:13:02,559 --> 00:13:05,400 Speaker 8: and so that's something that they definitely want to avoid. 245 00:13:05,400 --> 00:13:07,320 Speaker 8: And Charlie Sharff has talked about that that it's not 246 00:13:08,320 --> 00:13:11,760 Speaker 8: like an on switch day one, but it does give 247 00:13:11,800 --> 00:13:15,000 Speaker 8: them more flexibility so they can you know, the most 248 00:13:15,000 --> 00:13:17,559 Speaker 8: immediate thing is the trading business, where they just have 249 00:13:17,679 --> 00:13:22,080 Speaker 8: capacity today that they didn't have yesterday. But besides that, 250 00:13:22,120 --> 00:13:28,000 Speaker 8: it's more being able to lean into more enthusiastically those 251 00:13:28,040 --> 00:13:31,760 Speaker 8: growth initiatives that they've already kind of outlined. 252 00:13:33,040 --> 00:13:37,120 Speaker 2: Right, So, Hannah, they now have the regulatory capability to 253 00:13:37,160 --> 00:13:40,760 Speaker 2: maybe do more, to maybe grow a little bit more quickly. 254 00:13:41,080 --> 00:13:42,760 Speaker 3: Did they have the balance sheet to do that? Did 255 00:13:42,760 --> 00:13:43,960 Speaker 3: they have the capital to do that? 256 00:13:44,400 --> 00:13:46,319 Speaker 8: Yeah, they have a ton of excess capital. And that's 257 00:13:46,360 --> 00:13:49,520 Speaker 8: been a theme throughout. I mean even in the earliest 258 00:13:49,600 --> 00:13:53,200 Speaker 8: days of the asset cap like they couldn't deploy that capital, 259 00:13:53,280 --> 00:13:57,559 Speaker 8: so they gave investors a bigger dividend and more buybacks 260 00:13:57,640 --> 00:13:59,680 Speaker 8: than they were expecting. It was sort of like a 261 00:14:01,000 --> 00:14:02,920 Speaker 8: you wouldn't think that would be the outcome, but it 262 00:14:03,080 --> 00:14:07,599 Speaker 8: was at the time so they've had excess capital, and 263 00:14:07,920 --> 00:14:10,520 Speaker 8: also because the banks in general were preparing for the 264 00:14:10,559 --> 00:14:15,200 Speaker 8: possibility of tougher capital rules that have not panned out, 265 00:14:15,240 --> 00:14:16,720 Speaker 8: so they were a lot of them have been hoarding 266 00:14:16,760 --> 00:14:18,559 Speaker 8: capital anyway, sitting on a bunch of extra. 267 00:14:20,640 --> 00:14:22,640 Speaker 5: Well, we're seeing in Wall Street it's definitely a competition 268 00:14:22,720 --> 00:14:25,040 Speaker 5: for talent, particularly if you wrap in hedge funds as 269 00:14:25,040 --> 00:14:27,160 Speaker 5: well as huge ass at managers. 270 00:14:26,760 --> 00:14:27,600 Speaker 3: Are private equity. 271 00:14:27,920 --> 00:14:29,360 Speaker 5: Can weils Haargo play in that game? 272 00:14:30,360 --> 00:14:34,080 Speaker 8: Yeah, they already have been. I mean they hired Fernando 273 00:14:34,200 --> 00:14:37,360 Speaker 8: Rivas who is the head of the corporate investment bank there. 274 00:14:38,120 --> 00:14:41,880 Speaker 8: He was a major hire from JP Morgan, so that 275 00:14:41,880 --> 00:14:44,160 Speaker 8: that was huge for them. And you know they've made 276 00:14:44,240 --> 00:14:48,120 Speaker 8: other hires over the years. Doug Bronstein is there, another 277 00:14:48,160 --> 00:14:53,960 Speaker 8: former JPM executive and he's vice chair. They have Vary 278 00:14:54,000 --> 00:14:56,320 Speaker 8: Summers running wealth, so they have you know, they've been 279 00:14:56,360 --> 00:14:58,560 Speaker 8: able to get talent at the highest level and then 280 00:14:58,680 --> 00:15:01,920 Speaker 8: you know even further down as well. 281 00:15:02,000 --> 00:15:03,560 Speaker 2: All Right, I think the street kind of like this. 282 00:15:03,600 --> 00:15:05,760 Speaker 2: Stocks up about seven tens to one percent today, It's 283 00:15:05,840 --> 00:15:08,120 Speaker 2: up eight and a half percent year to date, up 284 00:15:08,160 --> 00:15:10,160 Speaker 2: thirty percent over the trailing twelve months, so it looks 285 00:15:10,200 --> 00:15:11,800 Speaker 2: like this street is kind of warming up to a 286 00:15:11,840 --> 00:15:13,440 Speaker 2: story which has been going to middle of the road. 287 00:15:13,640 --> 00:15:15,680 Speaker 2: Given some of the regulatory constraints, will stay on top 288 00:15:15,720 --> 00:15:15,880 Speaker 2: of that. 289 00:15:16,240 --> 00:15:16,680 Speaker 3: He a lovit. 290 00:15:16,720 --> 00:15:18,840 Speaker 2: Thanks so much for joining us at Bloomberg Senior financi 291 00:15:18,840 --> 00:15:20,800 Speaker 2: reporter on Wells Fargo. 292 00:15:22,120 --> 00:15:25,800 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 293 00:15:25,880 --> 00:15:29,000 Speaker 1: weekdays at ten am Eastern on Apple Cocklay and Android 294 00:15:29,000 --> 00:15:32,280 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 295 00:15:32,360 --> 00:15:36,040 Speaker 1: you get your podcasts, or watch us live on YouTube during. 296 00:15:35,960 --> 00:15:38,840 Speaker 5: Alex Seal alongside Paul Sweeney. This is Bloomberg Intelligence Radio. 297 00:15:38,920 --> 00:15:41,680 Speaker 5: We are broadcasting to live from the Galor National Convention 298 00:15:41,840 --> 00:15:45,400 Speaker 5: Center right here in Maryland. We're overlooking the Potomac. We 299 00:15:45,440 --> 00:15:48,480 Speaker 5: are at BNY Insight twenty twenty five as we talk 300 00:15:48,480 --> 00:15:51,480 Speaker 5: about wealth management and all the tools and tricks that 301 00:15:51,880 --> 00:15:55,640 Speaker 5: can be used to help navigate these markets. We're also 302 00:15:55,960 --> 00:15:58,480 Speaker 5: continuing to take a check in here on what's happening 303 00:15:58,520 --> 00:16:01,400 Speaker 5: in the overall market. We turned out to today's a 304 00:16:01,440 --> 00:16:05,800 Speaker 5: Big Take story. It talks about Tesla and what autonomous 305 00:16:05,880 --> 00:16:09,680 Speaker 5: driving and robotaxis say in Austin as Elon Musks keeps 306 00:16:09,680 --> 00:16:13,400 Speaker 5: talking about them, are talking about investigating whether the system 307 00:16:14,040 --> 00:16:16,560 Speaker 5: is actually too dangerous even if you have a human 308 00:16:16,680 --> 00:16:20,240 Speaker 5: behind the wheel. Joining us now is Global Autos editor 309 00:16:20,360 --> 00:16:23,320 Speaker 5: Craig Trudell. Craig, So, here's the title of the big take, 310 00:16:23,360 --> 00:16:26,480 Speaker 5: A fatal Tesla crash shows the limits of full self 311 00:16:26,560 --> 00:16:30,040 Speaker 5: driving walk us through the details of what the issues 312 00:16:30,080 --> 00:16:33,000 Speaker 5: are surrounding completely autonomous vehicles. 313 00:16:34,400 --> 00:16:36,840 Speaker 6: Yeah, so, I guess maybe the thing to start with 314 00:16:36,960 --> 00:16:39,200 Speaker 6: is the Teslas that you can buy today that are 315 00:16:39,240 --> 00:16:42,040 Speaker 6: on the road now are not that right, They are 316 00:16:42,040 --> 00:16:46,840 Speaker 6: not autonomous. You can pay extra for a system called 317 00:16:46,880 --> 00:16:50,920 Speaker 6: full self driving, and yet it's a miss snowmer. It's 318 00:16:51,080 --> 00:16:53,080 Speaker 6: a system that you have to pay attention to at 319 00:16:53,080 --> 00:16:57,240 Speaker 6: all times. You know, if you get into a crash, 320 00:16:57,400 --> 00:17:01,000 Speaker 6: it is on you. And we've seen that, you know, 321 00:17:01,080 --> 00:17:04,399 Speaker 6: play out. When Tesla customers have you know, tried to 322 00:17:04,400 --> 00:17:07,159 Speaker 6: come after the company, the company says, look, you know, 323 00:17:07,240 --> 00:17:10,440 Speaker 6: we we warned you. We told you that you know 324 00:17:10,680 --> 00:17:14,639 Speaker 6: you're you're responsible for driving while using this system. The 325 00:17:14,680 --> 00:17:17,200 Speaker 6: company is trying to make this leap that's been trying 326 00:17:17,200 --> 00:17:19,840 Speaker 6: to make the sleep for years to eventually get to 327 00:17:19,880 --> 00:17:22,119 Speaker 6: a point where you do not have to to supervise 328 00:17:22,240 --> 00:17:25,680 Speaker 6: and you know, even to take it further than that, 329 00:17:25,920 --> 00:17:28,440 Speaker 6: you know, take the human out from behind the wheel altogether. 330 00:17:29,080 --> 00:17:32,240 Speaker 6: And we hear Musk, you know, talk about that quite 331 00:17:32,240 --> 00:17:34,760 Speaker 6: a bit lately because it's something that they're actually trying 332 00:17:34,800 --> 00:17:37,960 Speaker 6: to commercialize, even just in the next matter of you know, 333 00:17:38,119 --> 00:17:42,000 Speaker 6: next week or so. There's a lot of questions about 334 00:17:42,040 --> 00:17:45,080 Speaker 6: how exactly they intend to do that, whether they can 335 00:17:45,119 --> 00:17:48,680 Speaker 6: do it, especially after he's predicted, you know, year after 336 00:17:48,760 --> 00:17:51,000 Speaker 6: year that they're on the cusp of doing it. And 337 00:17:51,200 --> 00:17:53,840 Speaker 6: part of the reason there are doubts is is because 338 00:17:53,920 --> 00:17:56,760 Speaker 6: of the hardware. And I think that's kind of an 339 00:17:56,800 --> 00:18:01,359 Speaker 6: important aspect of today's story is is this particular crash involves, 340 00:18:01,800 --> 00:18:04,680 Speaker 6: you know, an incident where a driver was using full 341 00:18:04,720 --> 00:18:09,200 Speaker 6: self driving driving into the sun, and that appeared to 342 00:18:09,520 --> 00:18:14,280 Speaker 6: play a part in the crash, which resulted in a fatality, 343 00:18:14,320 --> 00:18:17,960 Speaker 6: and it led to a federal investigation that is ongoing. 344 00:18:20,640 --> 00:18:23,800 Speaker 5: I mean, this is all very much feels as part 345 00:18:23,800 --> 00:18:25,879 Speaker 5: of the growing pains as we kind of understand this 346 00:18:25,960 --> 00:18:29,600 Speaker 5: technology and how it works itself out. So what are 347 00:18:29,600 --> 00:18:32,160 Speaker 5: the steps that Tesla's taking and that the regulators are 348 00:18:32,160 --> 00:18:32,920 Speaker 5: taking at this time? 349 00:18:34,560 --> 00:18:37,480 Speaker 6: Yeah, so you know, we should acknowledge that this incident 350 00:18:37,560 --> 00:18:41,520 Speaker 6: happened in November twenty twenty three. You know, Tesla has 351 00:18:41,560 --> 00:18:46,240 Speaker 6: has changed. They've they've made upgrades both to hardware and software. 352 00:18:46,880 --> 00:18:50,479 Speaker 6: You know, hardware for certain customers, they should say, but 353 00:18:50,640 --> 00:18:55,639 Speaker 6: you know, in terms of their approach to the sensor 354 00:18:55,640 --> 00:18:59,320 Speaker 6: system for their vehicles, Elon Musk has been you know, 355 00:18:59,400 --> 00:19:02,480 Speaker 6: really sort of down a limb and having this view 356 00:19:02,520 --> 00:19:06,439 Speaker 6: that all you need is cameras and company companies that 357 00:19:06,920 --> 00:19:09,159 Speaker 6: are also in this space. I think the one people 358 00:19:09,400 --> 00:19:13,600 Speaker 6: recognize the most is Weymo, the Google company, and they 359 00:19:13,720 --> 00:19:16,680 Speaker 6: use a mix of camera, radar and wide R and 360 00:19:17,040 --> 00:19:20,280 Speaker 6: their sensor set is much more expensive. It's more extensive. 361 00:19:20,480 --> 00:19:22,479 Speaker 6: You know, these sensors are placed all over the vehicle. 362 00:19:23,920 --> 00:19:27,159 Speaker 6: But you know, the sort of bet here on the 363 00:19:27,160 --> 00:19:29,520 Speaker 6: part of Weimo is that is worth it. It will 364 00:19:29,560 --> 00:19:32,439 Speaker 6: mean this system is safer. What Musk has tried to 365 00:19:32,480 --> 00:19:35,879 Speaker 6: do is go with the cheaper route, go with the 366 00:19:36,880 --> 00:19:38,879 Speaker 6: you know system that he can afford to put in 367 00:19:38,920 --> 00:19:41,840 Speaker 6: every Tesla, and make this bet that you know, he 368 00:19:41,920 --> 00:19:46,240 Speaker 6: can develop his way to autonomy faster by sort of 369 00:19:46,320 --> 00:19:49,959 Speaker 6: leveraging the broader Tesla fleet. Even if it means putting 370 00:19:50,080 --> 00:19:52,840 Speaker 6: you know, cars on the road that you know, draw 371 00:19:52,880 --> 00:19:55,879 Speaker 6: scrutiny from federal regulators as to whether or not that 372 00:19:56,040 --> 00:20:00,520 Speaker 6: this is you know, unreasonably unsafe. 373 00:20:01,720 --> 00:20:05,879 Speaker 2: So, Craig, I think Elon Musk is back at the company. 374 00:20:06,880 --> 00:20:07,560 Speaker 3: What does that mean? 375 00:20:07,680 --> 00:20:10,359 Speaker 2: I mean, are you hearing anything like, Okay, now we 376 00:20:10,359 --> 00:20:13,399 Speaker 2: can get back on track, Now we can really move forward, 377 00:20:13,400 --> 00:20:15,280 Speaker 2: maybe at you know, a higher velocity. 378 00:20:15,320 --> 00:20:15,880 Speaker 3: What's that mean? 379 00:20:17,560 --> 00:20:19,800 Speaker 6: Yeah, I'm you know, I think it's difficult to tell 380 00:20:19,840 --> 00:20:23,119 Speaker 6: at this point because he's kind of coming back to 381 00:20:23,240 --> 00:20:27,199 Speaker 6: business means coming back to so many businesses, right, and 382 00:20:27,280 --> 00:20:30,439 Speaker 6: so on a day to day Yeah, we're you know, 383 00:20:30,640 --> 00:20:34,439 Speaker 6: we're seeing him travel to to his various companies, you know, 384 00:20:34,640 --> 00:20:38,040 Speaker 6: devoting some time and attention to to them. But it's 385 00:20:38,080 --> 00:20:40,800 Speaker 6: not as though he's sort of one hundred percent, uh, 386 00:20:41,119 --> 00:20:44,719 Speaker 6: you know, focusing in on Tesla and neglecting all of 387 00:20:44,720 --> 00:20:48,320 Speaker 6: his other businesses. We see him you know, regularly engaging 388 00:20:48,400 --> 00:20:52,480 Speaker 6: with you know, users on x about you know, troubleshooting 389 00:20:52,800 --> 00:20:55,800 Speaker 6: problems that they have with that service. You know, I 390 00:20:55,840 --> 00:21:00,480 Speaker 6: would say he is you know more actively engaging there 391 00:21:00,560 --> 00:21:05,159 Speaker 6: on Tesla matters and definitely is trying to sort of 392 00:21:05,160 --> 00:21:07,840 Speaker 6: send this signal that you know, okay, it's it's time 393 00:21:07,880 --> 00:21:10,679 Speaker 6: to get back to business here. But whether or not 394 00:21:10,760 --> 00:21:13,320 Speaker 6: that's you know, resulting in sort of tangible changes at 395 00:21:13,320 --> 00:21:14,880 Speaker 6: the company, I think remains to be seen. 396 00:21:17,359 --> 00:21:21,119 Speaker 5: I guess, I mean quickly twenty seconds. What's the rush 397 00:21:21,160 --> 00:21:22,280 Speaker 5: for autonomous driving? 398 00:21:24,359 --> 00:21:28,359 Speaker 6: You know, I think forty thousand people die on US 399 00:21:28,440 --> 00:21:30,880 Speaker 6: roads every year, right, and so the rush, of course 400 00:21:30,960 --> 00:21:33,919 Speaker 6: is to bend that, you know, to change that. And 401 00:21:34,440 --> 00:21:36,679 Speaker 6: I think one of the challenges that you have if 402 00:21:37,000 --> 00:21:39,840 Speaker 6: you're a company in this space is we've now you know, 403 00:21:40,000 --> 00:21:42,080 Speaker 6: seen a lot of companies pursue this for you know, 404 00:21:42,200 --> 00:21:45,679 Speaker 6: roughly a decade that number has not budged. So you know, 405 00:21:46,000 --> 00:21:48,119 Speaker 6: we still have a long way to go to where 406 00:21:48,480 --> 00:21:53,080 Speaker 6: this capability is you know, making putting a dent in 407 00:21:53,119 --> 00:21:54,399 Speaker 6: those figures. 408 00:21:56,240 --> 00:21:58,000 Speaker 5: All right, Craig, Thanks A Lott, Really appreciate credit you 409 00:21:58,080 --> 00:22:02,159 Speaker 5: Dale joining US Global Auto's editor on Tesla and autonomous driving. 410 00:22:02,960 --> 00:22:07,639 Speaker 1: This is the Bloomberg Intelligence podcast, available on Apple, Spotify, 411 00:22:07,840 --> 00:22:11,320 Speaker 1: and anywhere else you get your podcasts. 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