1 00:00:05,800 --> 00:00:08,720 Speaker 1: Welcome to the Bloomberg p m L Podcast. I'm pim Fox. 2 00:00:08,760 --> 00:00:11,520 Speaker 1: Along with my co host Lisa Bramowitz. Each day we 3 00:00:11,640 --> 00:00:15,120 Speaker 1: bring you the most important, noteworthy, and useful interviews for 4 00:00:15,200 --> 00:00:17,840 Speaker 1: you and your money, whether you're at the grocery store 5 00:00:17,960 --> 00:00:20,720 Speaker 1: or the trading floor. Find the Bloomberg p m L 6 00:00:20,840 --> 00:00:33,879 Speaker 1: Podcast on Apple Podcasts, SoundCloud, and Bloomberg dot com. The 7 00:00:33,920 --> 00:00:36,000 Speaker 1: tone is more positive in markets today and a lot 8 00:00:36,000 --> 00:00:39,400 Speaker 1: of people are saying that this because the trade tensions 9 00:00:39,479 --> 00:00:43,640 Speaker 1: between US and China have eased. Why, well, it all 10 00:00:43,680 --> 00:00:46,400 Speaker 1: has to do with this company, ZTE Corporation. And here 11 00:00:46,440 --> 00:00:49,159 Speaker 1: to tell us what happened and what the significance of 12 00:00:49,200 --> 00:00:52,240 Speaker 1: this is is Leland Miller, chief executive of the China 13 00:00:52,360 --> 00:00:55,560 Speaker 1: Beige Book International in New York. Leland, thank you so 14 00:00:55,640 --> 00:00:58,280 Speaker 1: much for being with us. So just lay out in 15 00:00:58,320 --> 00:01:01,360 Speaker 1: broad strokes what happened and why this is a huge 16 00:01:01,360 --> 00:01:03,760 Speaker 1: deal in your opinion. Well, there's a lot of things 17 00:01:03,760 --> 00:01:05,520 Speaker 1: that are going on on the on the trade side, 18 00:01:05,520 --> 00:01:08,600 Speaker 1: and you've got the tariff list, multiple tariff lists. We've 19 00:01:08,640 --> 00:01:12,319 Speaker 1: got investment protection regimes that have been rumored for a 20 00:01:12,360 --> 00:01:15,000 Speaker 1: long time. Uh. You also have a crackdown on on 21 00:01:15,040 --> 00:01:18,640 Speaker 1: certain corporates, and the one that China is really really 22 00:01:18,760 --> 00:01:21,480 Speaker 1: upset about is this recent crackdown on z T, which 23 00:01:21,520 --> 00:01:23,760 Speaker 1: is one of their major telecom firms. It's one of 24 00:01:23,760 --> 00:01:26,759 Speaker 1: the two big ones along with Huawei. And what essentially 25 00:01:26,959 --> 00:01:30,800 Speaker 1: was done over the past month until potentially UH pulled 26 00:01:31,400 --> 00:01:34,520 Speaker 1: reversed by a tweet over the over the weekend, was 27 00:01:34,720 --> 00:01:41,200 Speaker 1: a um A near life almost a ban UH lifetime 28 00:01:41,240 --> 00:01:44,400 Speaker 1: ban of of the z T equipment. ZT was not 29 00:01:44,440 --> 00:01:46,959 Speaker 1: gonna be sold United States. They were being punished for 30 00:01:47,040 --> 00:01:49,760 Speaker 1: violation of US law. Essentially, the US was gonna put 31 00:01:49,840 --> 00:01:52,800 Speaker 1: z T out of business and and now well hold on. 32 00:01:53,280 --> 00:01:57,760 Speaker 1: So the Commerce Department enforced certain bands on z T 33 00:01:58,200 --> 00:02:01,320 Speaker 1: products and the reason why was because they had been 34 00:02:01,320 --> 00:02:04,720 Speaker 1: selling to Iran and North Korea. Is that right it is? 35 00:02:04,760 --> 00:02:06,840 Speaker 1: And then they lied about it and were caught lying 36 00:02:06,880 --> 00:02:09,639 Speaker 1: about it, and so this was a particularly egregious example 37 00:02:09,720 --> 00:02:12,040 Speaker 1: of the Chinese cheating. You know, if the if the 38 00:02:12,200 --> 00:02:15,960 Speaker 1: entire the entire U S. China trade push is about 39 00:02:16,240 --> 00:02:19,639 Speaker 1: cutting down on China's cheating, then this was the ultimate 40 00:02:19,680 --> 00:02:24,280 Speaker 1: example of brazenness and UH and cheating that hurt US 41 00:02:24,320 --> 00:02:26,679 Speaker 1: consumers in U S. NAH security and so the reversal 42 00:02:26,720 --> 00:02:30,800 Speaker 1: of this has significant repercussions beyond just a concession or 43 00:02:30,840 --> 00:02:34,519 Speaker 1: a chip that the President is offering up. Z t 44 00:02:34,880 --> 00:02:40,160 Speaker 1: E uses components that are made by Qualit, Common Intel correct. Correct, 45 00:02:40,760 --> 00:02:45,280 Speaker 1: and those companies cannot sell those products to z T 46 00:02:45,520 --> 00:02:49,600 Speaker 1: E because of current regulations. That was that was the 47 00:02:49,639 --> 00:02:54,160 Speaker 1: recent decision. Yes, okay, so the President would have to 48 00:02:54,240 --> 00:02:58,480 Speaker 1: reverse that in order to allow that that take place. Correct. 49 00:02:58,520 --> 00:03:01,480 Speaker 1: And what's happening right now is is that the Commerce 50 00:03:01,480 --> 00:03:04,079 Speaker 1: Department came out with a very strong language about how 51 00:03:04,400 --> 00:03:08,239 Speaker 1: much ZT had transgressed over the past few years. Wilbur 52 00:03:08,360 --> 00:03:10,560 Speaker 1: Ross had headed that up. And now what the tweet 53 00:03:10,600 --> 00:03:14,200 Speaker 1: suggests is that President Trump has ordered Secretary Ross to 54 00:03:14,400 --> 00:03:17,520 Speaker 1: reevaluate his conclusion on this and to find a way 55 00:03:17,520 --> 00:03:19,600 Speaker 1: to get around it. So it puts Secretary Ross in 56 00:03:19,600 --> 00:03:22,720 Speaker 1: a very difficult position here because some of the stuff 57 00:03:22,720 --> 00:03:25,800 Speaker 1: he said is really impossible to walk back. All Right, 58 00:03:25,880 --> 00:03:27,920 Speaker 1: So let's zoom out a little bit, because a lot 59 00:03:27,960 --> 00:03:29,839 Speaker 1: of people are looking at this deal and saying, well, 60 00:03:29,960 --> 00:03:32,600 Speaker 1: this is This shows that President Trump has taken a 61 00:03:32,639 --> 00:03:35,640 Speaker 1: softer line with China, is perhaps not as interested in 62 00:03:35,680 --> 00:03:37,640 Speaker 1: having a trade war that a lot of people say nobody, 63 00:03:37,680 --> 00:03:40,680 Speaker 1: nobody can win. This is a good thing for world 64 00:03:40,760 --> 00:03:46,400 Speaker 1: peace and world commerce. Why why is that not the case? Well, 65 00:03:46,560 --> 00:03:49,600 Speaker 1: the question is, you know, what is the US side 66 00:03:49,680 --> 00:03:51,640 Speaker 1: pushing for. I mean, that's been the question from day 67 00:03:51,680 --> 00:03:54,160 Speaker 1: one and has not yet been answered. If this is 68 00:03:54,160 --> 00:03:59,720 Speaker 1: pushing towards a more equal relationship, if this is pushing for, um, 69 00:03:58,400 --> 00:04:03,040 Speaker 1: a reckoning on the trade theft to eliminate hurdles for 70 00:04:03,040 --> 00:04:05,960 Speaker 1: the future, then all of this is good. Nobody wants 71 00:04:05,960 --> 00:04:08,440 Speaker 1: a terror for nobody wants a trade war. But if 72 00:04:08,480 --> 00:04:12,360 Speaker 1: you're if you're showing, if you're from the US perspective, 73 00:04:12,400 --> 00:04:15,320 Speaker 1: if you're showing weakness that a foreign company can exert 74 00:04:15,360 --> 00:04:18,360 Speaker 1: some economic leverage over you and have you reverse Nash 75 00:04:18,400 --> 00:04:21,560 Speaker 1: security decisions, it's a problem. It's also a problem if 76 00:04:21,560 --> 00:04:24,400 Speaker 1: you go into a trade negotiation thinking that the trade 77 00:04:24,400 --> 00:04:26,839 Speaker 1: deficit is what you should be negotiating instead of market 78 00:04:26,880 --> 00:04:30,120 Speaker 1: access or intellectual property theft or some of these other 79 00:04:30,160 --> 00:04:34,719 Speaker 1: important things that really do affect businesses and consumers. So 80 00:04:34,880 --> 00:04:36,719 Speaker 1: the question is what have we done this all for, 81 00:04:36,920 --> 00:04:40,280 Speaker 1: And if it ends up being something that sort of 82 00:04:40,520 --> 00:04:42,920 Speaker 1: dwindles out over the course of the next few weeks, 83 00:04:42,920 --> 00:04:44,920 Speaker 1: and months, which which I don't think will happen. Then 84 00:04:45,160 --> 00:04:48,080 Speaker 1: then you you're basically telling China that they've that they 85 00:04:48,120 --> 00:04:51,039 Speaker 1: have a ready made formula for putting this behind them, 86 00:04:51,279 --> 00:04:53,320 Speaker 1: and um, they don't have to to worry about these 87 00:04:53,360 --> 00:04:55,760 Speaker 1: things which just a few weeks ago were worthy of 88 00:04:55,800 --> 00:04:58,039 Speaker 1: a trade war. So it's it's it's all very bizarre. 89 00:04:58,680 --> 00:05:01,600 Speaker 1: Does it also matter that it coincides with the visit 90 00:05:01,680 --> 00:05:05,880 Speaker 1: to the United States and the Vice Premier Leu the 91 00:05:06,000 --> 00:05:09,560 Speaker 1: Chinese trade negotiator, so that what was told by the 92 00:05:09,640 --> 00:05:11,480 Speaker 1: Chinese to the U. S side was that they wouldn't 93 00:05:11,520 --> 00:05:14,039 Speaker 1: have the delegation unless CT was taken care of. So 94 00:05:14,640 --> 00:05:17,520 Speaker 1: the President wanted to make sure this trade delegation happened, 95 00:05:18,120 --> 00:05:22,479 Speaker 1: not mostly because there was trade stuff to discuss to discuss, 96 00:05:22,720 --> 00:05:24,800 Speaker 1: but also because North Korea is playing into this, and 97 00:05:24,880 --> 00:05:27,600 Speaker 1: so you've got a few different issues at play here. 98 00:05:28,040 --> 00:05:30,240 Speaker 1: You don't want disruption in front of the North Korea summit. 99 00:05:30,520 --> 00:05:32,760 Speaker 1: You don't want any of this trade war stuff to 100 00:05:32,760 --> 00:05:34,680 Speaker 1: blow up before the U. S has a plan in place, 101 00:05:34,720 --> 00:05:37,599 Speaker 1: and they've been very slow getting the documents for three 102 00:05:37,600 --> 00:05:41,000 Speaker 1: oh one ready, So the President apparently did not want 103 00:05:41,040 --> 00:05:43,719 Speaker 1: to lose steam on this and and decided to to 104 00:05:43,800 --> 00:05:47,640 Speaker 1: make the ZT decision. Um that said, all of this 105 00:05:48,360 --> 00:05:52,320 Speaker 1: is part of a long process. And whether Leoho visits 106 00:05:52,440 --> 00:05:54,440 Speaker 1: this week and they come to a mini bargain many 107 00:05:54,440 --> 00:05:57,880 Speaker 1: many deal, not a bargain um, then you know this. 108 00:05:57,880 --> 00:05:59,159 Speaker 1: This is something that's going to go on for a 109 00:05:59,160 --> 00:06:01,440 Speaker 1: long time. I want to thank you very much for 110 00:06:01,520 --> 00:06:04,119 Speaker 1: joining us. Leland Miller is the chief executive of China 111 00:06:04,360 --> 00:06:08,640 Speaker 1: beige Book International. You can follow their work on Twitter 112 00:06:08,800 --> 00:06:12,760 Speaker 1: at China beige Book. Talking about the President of the 113 00:06:12,839 --> 00:06:16,719 Speaker 1: United States, Donald Trump and his tweet regarding ZTE Corp. 114 00:06:16,800 --> 00:06:34,800 Speaker 1: And perhaps easing trade sanctions against the company. I want 115 00:06:34,800 --> 00:06:38,160 Speaker 1: to pick up on what Dave mentioned, Scientific Games rising 116 00:06:38,200 --> 00:06:42,039 Speaker 1: more than ten percent, so the shares also avoid Gaming 117 00:06:42,160 --> 00:06:48,480 Speaker 1: and GM and several other gaming companies also rising significantly 118 00:06:48,560 --> 00:06:51,279 Speaker 1: on the news that the Supreme Court struck down a 119 00:06:51,320 --> 00:06:55,080 Speaker 1: federal law that bars gambling on individual sporting events. Joining 120 00:06:55,160 --> 00:06:57,760 Speaker 1: US now, I am pleased to say Brian Eager, he 121 00:06:57,920 --> 00:07:01,680 Speaker 1: is senior gaming and lodging analyst with Bloomberg Intelligence. Brian, 122 00:07:02,360 --> 00:07:05,120 Speaker 1: how big of a deal is this decision by the U. S. 123 00:07:05,120 --> 00:07:08,240 Speaker 1: Supreme Court? So if you think of the pool um 124 00:07:08,560 --> 00:07:12,239 Speaker 1: of basically would have to date been illegal sports bets 125 00:07:12,240 --> 00:07:14,920 Speaker 1: that have been taking place, and you you assign a 126 00:07:14,920 --> 00:07:18,240 Speaker 1: reasonable wind whole rate to that, there's probably about a 127 00:07:18,280 --> 00:07:22,200 Speaker 1: seven and a half billion dollar UH newly released revenue 128 00:07:22,240 --> 00:07:26,520 Speaker 1: opportunity across h the across the states that would now 129 00:07:26,520 --> 00:07:29,080 Speaker 1: have an opportunity to have legalized sports betting. Among those, 130 00:07:29,360 --> 00:07:31,600 Speaker 1: New Jersey and Pennsylvania are kind of front of the line, 131 00:07:31,640 --> 00:07:35,480 Speaker 1: New Jersey being the petitioner here in Pennsylvania having recently 132 00:07:35,720 --> 00:07:40,440 Speaker 1: legalized on sports betting, but certainly an opportunity that both 133 00:07:40,520 --> 00:07:44,080 Speaker 1: casino operators and the back end operators of sports books 134 00:07:44,080 --> 00:07:47,080 Speaker 1: would all likely capitalize on. So who are some of 135 00:07:47,080 --> 00:07:49,760 Speaker 1: the big winners? I mean, Lisa was mentioning some of 136 00:07:49,760 --> 00:07:53,680 Speaker 1: the stocks, also adding BOYD Gaming, as she mentioned up 137 00:07:53,720 --> 00:07:56,880 Speaker 1: a little bit more than three ten, National Gaming up 138 00:07:56,920 --> 00:07:59,920 Speaker 1: four and a half percent, Empire Resorts higher by ten percent. 139 00:08:01,200 --> 00:08:03,080 Speaker 1: So I would kind of breaking it down at least 140 00:08:03,200 --> 00:08:07,080 Speaker 1: additionally into three categories. First, you've got operators like MGM 141 00:08:07,120 --> 00:08:10,440 Speaker 1: and Caesars that have existing operations in Nevada and also 142 00:08:10,440 --> 00:08:13,360 Speaker 1: an Atlantic city. Those are the two major public companies 143 00:08:13,360 --> 00:08:16,880 Speaker 1: that have operations in the Atlantic City market, which is 144 00:08:16,920 --> 00:08:20,760 Speaker 1: the petitioners here which be likely to benefit. Another subgroup 145 00:08:20,760 --> 00:08:23,160 Speaker 1: which we used to kind of touched upon our companies 146 00:08:23,240 --> 00:08:27,960 Speaker 1: like Churchill Downs, Boyd Gaming, National Gaming, El Dorado Resorts, 147 00:08:28,000 --> 00:08:31,480 Speaker 1: which either have or are in the process of acquiring 148 00:08:31,560 --> 00:08:36,200 Speaker 1: assets in the Pennsylvania market that stayed also legalized sports 149 00:08:36,200 --> 00:08:40,360 Speaker 1: betting subject to the Supreme Courts repeal of pasta which 150 00:08:40,400 --> 00:08:43,400 Speaker 1: happened today. And then the third group, Tim and Lisa 151 00:08:43,640 --> 00:08:47,319 Speaker 1: is the operators of the various gaming systems of sports 152 00:08:47,320 --> 00:08:50,520 Speaker 1: book operators. A couple comes to mind. William Hill, the 153 00:08:50,559 --> 00:08:55,760 Speaker 1: British company operates of all the Vada based retail sports books. 154 00:08:55,760 --> 00:08:58,600 Speaker 1: You've got the Stars group that acquired Sky Betting, and 155 00:08:58,640 --> 00:09:02,280 Speaker 1: then you've got Scientific Game which Lisa mentioned, which recently 156 00:09:02,320 --> 00:09:05,480 Speaker 1: acquired m i X Gaming, which has an open bet 157 00:09:05,480 --> 00:09:10,240 Speaker 1: platform which has the ability although right now UH takes 158 00:09:10,280 --> 00:09:12,760 Speaker 1: place in the UK to operate kind of the back 159 00:09:12,960 --> 00:09:16,000 Speaker 1: end of the sports betting platforms. So you basically got 160 00:09:16,160 --> 00:09:19,160 Speaker 1: you know, the Jersey operators, You've got the operators in 161 00:09:19,240 --> 00:09:22,040 Speaker 1: other regional states, and then you've got the operators of 162 00:09:22,120 --> 00:09:26,480 Speaker 1: the equipment and systems that could benefit from the expansion 163 00:09:26,520 --> 00:09:29,480 Speaker 1: of sports books nationwide. Just to give a sense of 164 00:09:29,559 --> 00:09:34,199 Speaker 1: how big a business this is. According to one research unit, 165 00:09:34,440 --> 00:09:38,000 Speaker 1: Americans place a hundred and fifty billion dollars a year 166 00:09:38,040 --> 00:09:42,040 Speaker 1: in illegal sports bets. Other research firms put that at 167 00:09:42,040 --> 00:09:45,000 Speaker 1: a much lower amount. But I'm just wondering, from your 168 00:09:45,040 --> 00:09:48,320 Speaker 1: perspective or most of these online do most people like 169 00:09:48,440 --> 00:09:50,839 Speaker 1: to go to a venue? What's sort of the look 170 00:09:51,040 --> 00:09:55,400 Speaker 1: of the most popular place to bet on individual teams? So, 171 00:09:55,520 --> 00:09:58,280 Speaker 1: the sports books in Nevada, although they only generate about 172 00:09:58,280 --> 00:10:01,440 Speaker 1: two of the total gaming revenue in that state, are 173 00:10:01,480 --> 00:10:05,040 Speaker 1: big traffic generators. They're not necessarily a sizeable casino ways 174 00:10:05,120 --> 00:10:07,960 Speaker 1: or generator, but they generate excitement that makes its way 175 00:10:08,040 --> 00:10:10,880 Speaker 1: by way of casino play into the gaming portions of 176 00:10:10,920 --> 00:10:15,200 Speaker 1: the casinos. You've got that portion right now. Gaming sports 177 00:10:15,240 --> 00:10:18,840 Speaker 1: betting only legal on an unrestricted basis uh A Nevada. 178 00:10:19,160 --> 00:10:21,559 Speaker 1: The hundred fifty billion dollar number you mentioned, that's the 179 00:10:21,600 --> 00:10:26,200 Speaker 1: American Gaming Association estimate of that amount currently wagered illegally 180 00:10:26,679 --> 00:10:29,640 Speaker 1: on sports betting. And so you put a five percent 181 00:10:29,760 --> 00:10:31,760 Speaker 1: hold rate on that, you get that the seven and 182 00:10:31,760 --> 00:10:35,559 Speaker 1: a half billion dollar revenue opportunity I mentioned. And to 183 00:10:35,600 --> 00:10:39,240 Speaker 1: answer your other question, you know physical venues actual sports 184 00:10:39,240 --> 00:10:41,800 Speaker 1: books UH where a lot of the action takes place. 185 00:10:41,800 --> 00:10:44,760 Speaker 1: But all these companies, among them William Pill and others 186 00:10:44,800 --> 00:10:49,280 Speaker 1: have kind of the mobile platforms UH the other ways, 187 00:10:49,320 --> 00:10:51,920 Speaker 1: where within the state's legal bounds, you could use a 188 00:10:52,520 --> 00:10:56,080 Speaker 1: mobile device, smartphone device, etcetera to place your bets. So 189 00:10:56,160 --> 00:10:59,120 Speaker 1: certainly mobile is the direction of the future, even though 190 00:10:59,160 --> 00:11:02,160 Speaker 1: there's there's a large physical presence of these sports books. 191 00:11:02,640 --> 00:11:04,719 Speaker 1: I want to thank you very much for joining us 192 00:11:04,760 --> 00:11:08,920 Speaker 1: and shedding light on this issue. Brian Edgar is our 193 00:11:09,080 --> 00:11:12,600 Speaker 1: expert when it comes to gaming and lodging for Bloomberg Intelligence. 194 00:11:12,600 --> 00:11:15,480 Speaker 1: He's our senior industry analysts and just taking a look 195 00:11:15,520 --> 00:11:17,560 Speaker 1: once again at some of the stocks making moves as 196 00:11:17,559 --> 00:11:22,040 Speaker 1: a result of the Supreme Court decision avoiding the ban 197 00:11:22,280 --> 00:11:40,880 Speaker 1: on national sports. But well, just last week we learned 198 00:11:40,880 --> 00:11:44,600 Speaker 1: that Alliance Bernstein is going to relocate about a thousand 199 00:11:44,600 --> 00:11:49,400 Speaker 1: of its employees to UH to Memphis, Nashville, Tennessee. I 200 00:11:49,480 --> 00:11:52,120 Speaker 1: beg your pardon, and perhaps it has to do with 201 00:11:52,200 --> 00:11:56,120 Speaker 1: compensation levels and making the money go a little bit further. 202 00:11:56,240 --> 00:11:59,360 Speaker 1: Here to tell us more about compensation and incentive pay 203 00:11:59,400 --> 00:12:02,680 Speaker 1: in the financial industry is Alan Johnson, President Managing director 204 00:12:02,679 --> 00:12:06,240 Speaker 1: and founder of Johnson Associates, Alan, thanks very much for 205 00:12:06,280 --> 00:12:09,640 Speaker 1: being with us. What is the current trend in terms 206 00:12:09,720 --> 00:12:14,560 Speaker 1: of compensation and head count in the financial services industry? 207 00:12:14,559 --> 00:12:16,280 Speaker 1: Will get into the specifics later, but what is the 208 00:12:16,320 --> 00:12:21,680 Speaker 1: general trend that you're seeing. Compensation is projected to be 209 00:12:22,640 --> 00:12:25,720 Speaker 1: higher in two thousand and eighteen, and sentives are probably 210 00:12:25,720 --> 00:12:30,080 Speaker 1: going to be up five or ten percent. Um Uh, 211 00:12:30,240 --> 00:12:34,120 Speaker 1: it's probably more of a mixed bag. And um in 212 00:12:34,200 --> 00:12:39,800 Speaker 1: recruiting and employment, probably more outside the traditional money centers, 213 00:12:39,920 --> 00:12:43,559 Speaker 1: more more in other parts of the country of the world. Um, 214 00:12:43,600 --> 00:12:45,000 Speaker 1: So it's got that's a little bit more of a 215 00:12:45,040 --> 00:12:48,680 Speaker 1: mixed bag. But clearly compensation is trending up for two 216 00:12:48,679 --> 00:12:51,160 Speaker 1: thousand and eighteen. Yeah. Alan, Well, if it weren't, I'd 217 00:12:51,200 --> 00:12:53,800 Speaker 1: be shocked because pretty much across the board we've seen 218 00:12:54,000 --> 00:12:56,960 Speaker 1: gains over the past twelve months. And Allen, I'm so 219 00:12:56,960 --> 00:12:58,800 Speaker 1: glad you could join us, because really, if you want 220 00:12:58,800 --> 00:13:00,360 Speaker 1: to know what's going on in Wall Street, just check 221 00:13:00,440 --> 00:13:02,640 Speaker 1: the bonuses and that will tell you everything you need 222 00:13:02,679 --> 00:13:04,680 Speaker 1: to know. And I was looking just to dig into 223 00:13:04,720 --> 00:13:08,600 Speaker 1: the details. I noticed that hedge funds, the average bonus 224 00:13:08,960 --> 00:13:12,360 Speaker 1: was a zero to five increase from last year, whereas 225 00:13:12,360 --> 00:13:17,040 Speaker 1: private equity was five to ten higher than last year. 226 00:13:17,080 --> 00:13:19,080 Speaker 1: Can you talk a little bit about that and sort 227 00:13:19,080 --> 00:13:21,600 Speaker 1: of what this tells you as far as private equity 228 00:13:21,640 --> 00:13:25,320 Speaker 1: being more of the place to be right now. Well, 229 00:13:25,360 --> 00:13:28,520 Speaker 1: private equity is continuing its momentum from the last three 230 00:13:28,640 --> 00:13:32,640 Speaker 1: or four years, the up the the higher markets. They 231 00:13:32,679 --> 00:13:36,480 Speaker 1: have had great realizations of prior investments. They have been 232 00:13:36,520 --> 00:13:39,480 Speaker 1: able to go out in fund raise. So private equity 233 00:13:39,720 --> 00:13:43,240 Speaker 1: is clicking on all cylinders. Hedge funds have had a 234 00:13:43,360 --> 00:13:46,880 Speaker 1: very difficult run in the last several years. There we're 235 00:13:46,880 --> 00:13:49,600 Speaker 1: projecting they're going to be up only slightly, perhaps zero 236 00:13:49,679 --> 00:13:52,440 Speaker 1: to five incentives for this year, and again it's their 237 00:13:52,480 --> 00:13:56,679 Speaker 1: fundamental business model of trying to beat the markets is 238 00:13:57,520 --> 00:14:01,040 Speaker 1: much harder UM, so they're one of the two different ends. 239 00:14:01,080 --> 00:14:03,800 Speaker 1: Private equity continues to be on a roll of hedge funds. 240 00:14:04,280 --> 00:14:08,640 Speaker 1: Hopefully the volatility will help them, but it's a question mark. Well, Alan, 241 00:14:08,960 --> 00:14:11,800 Speaker 1: maybe shift your attention now to investment in commercial banking 242 00:14:12,120 --> 00:14:15,760 Speaker 1: and UM you say that the incentive pay would be 243 00:14:15,840 --> 00:14:20,880 Speaker 1: generally in line with the entire firm's performance. Correct, Yes, 244 00:14:21,040 --> 00:14:24,800 Speaker 1: the the banks have done better. They don't get the 245 00:14:24,840 --> 00:14:27,040 Speaker 1: attention that they once did on their pay, but they 246 00:14:27,080 --> 00:14:31,240 Speaker 1: continue to do well. What's different than the past that 247 00:14:31,280 --> 00:14:34,120 Speaker 1: we all remember is that today it's somewhat of the 248 00:14:34,160 --> 00:14:38,680 Speaker 1: boring parts of the commercial banking, which is commercial lending, retail, 249 00:14:39,080 --> 00:14:44,240 Speaker 1: credit cards, cars, things that are steady and profitable um, 250 00:14:44,400 --> 00:14:46,760 Speaker 1: but not as much of their business is the more 251 00:14:47,000 --> 00:14:50,600 Speaker 1: um risky parts of the business that they used to 252 00:14:50,640 --> 00:14:53,440 Speaker 1: do so well ahead. One thing I'm wondering is how 253 00:14:53,480 --> 00:14:57,800 Speaker 1: the bonuses at US banks compared to those at European 254 00:14:57,920 --> 00:15:01,920 Speaker 1: banks and whether you've seen in a pretty big attrition 255 00:15:02,120 --> 00:15:06,760 Speaker 1: out of European banks and into into the US ones. Now, 256 00:15:06,800 --> 00:15:09,880 Speaker 1: that's a very good question. The US banks continue to 257 00:15:10,080 --> 00:15:12,960 Speaker 1: not only a business but all pay perspective, continue to 258 00:15:13,560 --> 00:15:16,280 Speaker 1: move ahead. The European banks have kind of been in 259 00:15:16,360 --> 00:15:19,600 Speaker 1: lembo now for a number of years. We saw Deutsche 260 00:15:19,640 --> 00:15:23,640 Speaker 1: Bank cutting back and others, so they have not had 261 00:15:23,680 --> 00:15:25,840 Speaker 1: the progress that the US banks have had in the 262 00:15:25,920 --> 00:15:29,080 Speaker 1: last five or so years, either from a business results, 263 00:15:29,080 --> 00:15:34,360 Speaker 1: stock price, or pay um. They are lagging UM significantly well. 264 00:15:34,360 --> 00:15:36,040 Speaker 1: But I have to wonder just you know, with Deutch 265 00:15:36,040 --> 00:15:38,080 Speaker 1: a bank, for example, I'd heard a while back that 266 00:15:38,120 --> 00:15:40,680 Speaker 1: they were actually offering some huge bonuses to try to 267 00:15:40,720 --> 00:15:44,360 Speaker 1: get talented people to come join them, given how much 268 00:15:44,400 --> 00:15:46,760 Speaker 1: bad press they've gotten. And I wonder if you do 269 00:15:46,880 --> 00:15:50,600 Speaker 1: see more sort of one off huge compensation offers from 270 00:15:50,600 --> 00:15:53,600 Speaker 1: banks that are looking to sort of revive their franchise. 271 00:15:55,520 --> 00:15:57,520 Speaker 1: You certainly don't see that as much in the United 272 00:15:57,560 --> 00:16:00,040 Speaker 1: States because they don't need to to do the have 273 00:16:00,160 --> 00:16:01,800 Speaker 1: and they don't want to. I think they don't need 274 00:16:01,840 --> 00:16:03,720 Speaker 1: you because sorry to break in, but they don't need 275 00:16:03,760 --> 00:16:05,520 Speaker 1: to because there are so many people looking for jobs 276 00:16:05,520 --> 00:16:07,920 Speaker 1: that they can hire. Uh, most of them are got 277 00:16:07,960 --> 00:16:11,120 Speaker 1: a pretty stable um cadre of senior people. They don't 278 00:16:11,200 --> 00:16:14,000 Speaker 1: really need. They don't need the savior at this point. 279 00:16:14,160 --> 00:16:17,680 Speaker 1: They're they're they're certainly looking for really good people, and 280 00:16:17,680 --> 00:16:20,480 Speaker 1: they're certainly going to pay a lot for expensive people, 281 00:16:20,480 --> 00:16:23,520 Speaker 1: but they don't need the savior you mentioned. If you're 282 00:16:23,680 --> 00:16:27,160 Speaker 1: more troubled or more um in a in a fall, 283 00:16:27,280 --> 00:16:29,520 Speaker 1: you're more likely to go out and spend an awful 284 00:16:29,520 --> 00:16:34,240 Speaker 1: lot of money a free agent um and perhaps overpay um. 285 00:16:34,400 --> 00:16:37,120 Speaker 1: The U S banks historically have always done that, but 286 00:16:37,160 --> 00:16:39,360 Speaker 1: it certainly in the last five years or more they 287 00:16:39,400 --> 00:16:42,000 Speaker 1: have not felt the need to or weren't allowed to 288 00:16:42,040 --> 00:16:44,640 Speaker 1: do that. Um, So you know you're right if you're 289 00:16:44,680 --> 00:16:46,880 Speaker 1: If you're going to hear an outsized number, it's not 290 00:16:47,000 --> 00:16:50,160 Speaker 1: likely to be a brand name US Bank. It's likely 291 00:16:50,200 --> 00:16:53,960 Speaker 1: to be somebody from probably from Europe. All Right, just 292 00:16:54,040 --> 00:16:56,680 Speaker 1: really quickly, about thirty seconds. I don't know if you 293 00:16:56,680 --> 00:16:59,680 Speaker 1: saw the news, Goldman Sachs is just announcing that to 294 00:17:00,160 --> 00:17:03,120 Speaker 1: heads out of the three that lead the securities division 295 00:17:03,200 --> 00:17:06,480 Speaker 1: are planning to retire. Just really quickly. Is this is 296 00:17:06,480 --> 00:17:11,320 Speaker 1: this a significant thing? Um? I think it's a significant 297 00:17:12,200 --> 00:17:15,600 Speaker 1: move for those two individuals. But certainly Goldman traditionally has 298 00:17:15,640 --> 00:17:17,679 Speaker 1: had duel heads and a lot of businesses to give 299 00:17:17,760 --> 00:17:20,520 Speaker 1: them a deeper bench. Um So, I don't think it 300 00:17:20,640 --> 00:17:24,560 Speaker 1: tells you anything that they continue to rotate quality people 301 00:17:24,600 --> 00:17:28,400 Speaker 1: through these jobs, and they've been I think the biggest 302 00:17:28,440 --> 00:17:31,840 Speaker 1: practitioner of having dual heads, which they have. Their view 303 00:17:31,880 --> 00:17:34,720 Speaker 1: is we need a deeper bench than relying on a 304 00:17:34,880 --> 00:17:37,080 Speaker 1: you know, just a single person most of the time. 305 00:17:37,400 --> 00:17:40,600 Speaker 1: So they still have somebody left from that team. Allan Johnson, 306 00:17:40,640 --> 00:17:42,680 Speaker 1: thank you so much for joining us today. Always a 307 00:17:42,720 --> 00:17:45,040 Speaker 1: pleasure and always important to take a look at what 308 00:17:45,080 --> 00:17:47,800 Speaker 1: those bonuses are showing us about Wall Street Allan Johnson, 309 00:17:47,920 --> 00:18:06,639 Speaker 1: managing director and founder of Johnson Associates, the shares of 310 00:18:06,960 --> 00:18:09,560 Speaker 1: n XP Semiconductor. They are hired by about nine and 311 00:18:09,560 --> 00:18:13,359 Speaker 1: a half percent after Chinese regulators have restarted their review 312 00:18:13,440 --> 00:18:19,320 Speaker 1: of Quacom's application to acquire an XP Semiconductors. They previously 313 00:18:19,359 --> 00:18:23,119 Speaker 1: had shelved this work in reaction to growing trade tensions 314 00:18:23,160 --> 00:18:25,679 Speaker 1: with the United States. This according to people familiar with 315 00:18:25,720 --> 00:18:29,000 Speaker 1: the matter, So better who better than Victoria Espinel, the 316 00:18:29,040 --> 00:18:32,440 Speaker 1: president and the chief executive of the Business Software Alliance 317 00:18:32,440 --> 00:18:35,400 Speaker 1: b s a UH to tell us a little bit 318 00:18:35,440 --> 00:18:38,320 Speaker 1: more about what's going on when it comes to trade, 319 00:18:38,359 --> 00:18:42,200 Speaker 1: intellectual property and technology between the United States and China. 320 00:18:42,320 --> 00:18:45,439 Speaker 1: She's also the president of Software dot org and she 321 00:18:45,480 --> 00:18:48,920 Speaker 1: can be followed on Twitter at Victoria Espinel. She joins 322 00:18:49,000 --> 00:18:51,040 Speaker 1: us in our eleven three oh studios. Victoria, thank you 323 00:18:51,080 --> 00:18:54,240 Speaker 1: very much for being with us UM. Just to give 324 00:18:54,240 --> 00:18:56,720 Speaker 1: people the background prior to being the head of the 325 00:18:56,720 --> 00:18:59,720 Speaker 1: the b s a UM, you or the United States 326 00:18:59,800 --> 00:19:04,399 Speaker 1: in Collectual Property Enforcement Coordinator for the White House UH, 327 00:19:04,440 --> 00:19:07,199 Speaker 1: and you were appointed by President Barack Obama back in 328 00:19:07,240 --> 00:19:10,160 Speaker 1: September of two thousand nine. So what is your take 329 00:19:10,240 --> 00:19:14,879 Speaker 1: on the back and forth over intellectual property and technology 330 00:19:14,880 --> 00:19:18,040 Speaker 1: issues between the United States and China that currently are 331 00:19:18,040 --> 00:19:20,800 Speaker 1: in the headlines. So this has been a long standing 332 00:19:20,840 --> 00:19:23,200 Speaker 1: issue UM. In fact, before my time at the White House, 333 00:19:23,240 --> 00:19:26,879 Speaker 1: I was a trade negotiator UM under the President Bush's 334 00:19:26,840 --> 00:19:29,240 Speaker 1: administration from two thousand and one to two thousand seven, 335 00:19:29,240 --> 00:19:31,879 Speaker 1: and I was the chief Intellectual property trade negotiator for 336 00:19:31,920 --> 00:19:35,240 Speaker 1: the United States. But these concerns between the United and 337 00:19:35,440 --> 00:19:38,959 Speaker 1: United States and China have predated even my time at USTR. 338 00:19:39,359 --> 00:19:42,240 Speaker 1: And so this is I think we're seeing what may 339 00:19:42,280 --> 00:19:45,960 Speaker 1: becoming close to the culmination of a long history of 340 00:19:46,040 --> 00:19:49,199 Speaker 1: concerns where some things in China have gotten better, but 341 00:19:49,320 --> 00:19:54,000 Speaker 1: other things have have gotten worse potentially. And I think 342 00:19:54,040 --> 00:19:56,719 Speaker 1: speaking from the respective of the software industry, well, we 343 00:19:56,800 --> 00:19:59,520 Speaker 1: definitely have concerns about intellectual property in China. I think 344 00:19:59,560 --> 00:20:02,560 Speaker 1: there are a are types of market access barriers that 345 00:20:02,600 --> 00:20:06,040 Speaker 1: are potentially even more concerning, so for example, joint venture 346 00:20:06,119 --> 00:20:10,000 Speaker 1: rules or the cybersecurity regulations that China has in place. 347 00:20:10,840 --> 00:20:15,240 Speaker 1: All that said, China is an incredibly important, perhaps the 348 00:20:15,280 --> 00:20:18,520 Speaker 1: most important bilateral trading partner that we have with the 349 00:20:18,600 --> 00:20:21,800 Speaker 1: United States, and so what I think is important for 350 00:20:21,920 --> 00:20:24,639 Speaker 1: everyone to remember at this point is what we really 351 00:20:24,680 --> 00:20:27,480 Speaker 1: need is for the United States in China to be 352 00:20:27,560 --> 00:20:31,639 Speaker 1: having a constructive dialogue and be working together on solutions 353 00:20:31,640 --> 00:20:34,360 Speaker 1: that are going to benefit both of us. I don't 354 00:20:34,359 --> 00:20:38,480 Speaker 1: think it's it is it's not beneficial for China or 355 00:20:38,520 --> 00:20:41,879 Speaker 1: the United States to be harmed in this process. Um. 356 00:20:41,920 --> 00:20:44,200 Speaker 1: And the second point I would make is it's about 357 00:20:44,200 --> 00:20:46,600 Speaker 1: the United States in China, but it's also about the 358 00:20:46,600 --> 00:20:49,080 Speaker 1: global economy. And so one thing that I think would 359 00:20:49,119 --> 00:20:51,679 Speaker 1: be very helpful that we're not seeing that much of 360 00:20:51,720 --> 00:20:54,040 Speaker 1: at the moment is for the United States to be 361 00:20:54,119 --> 00:20:57,320 Speaker 1: working with other countries as well. This is not just 362 00:20:57,440 --> 00:20:59,920 Speaker 1: about the United States in China. This is about making 363 00:21:00,040 --> 00:21:03,600 Speaker 1: the global economy work well. And I think, um, while 364 00:21:03,600 --> 00:21:07,359 Speaker 1: it has been hardening to see the administration working through 365 00:21:07,480 --> 00:21:11,399 Speaker 1: organizations like the World Trade Organization to a certain extent, um, 366 00:21:11,440 --> 00:21:14,000 Speaker 1: I think the more that we the United States can 367 00:21:14,000 --> 00:21:16,639 Speaker 1: be building alliances and we the United States can be 368 00:21:16,640 --> 00:21:20,359 Speaker 1: working constructively with a range of countries, including with China, 369 00:21:20,480 --> 00:21:23,360 Speaker 1: that's ultimately that's going to be helpful for everyone. So 370 00:21:23,760 --> 00:21:26,960 Speaker 1: one sort of battle that's being waged between China and 371 00:21:27,000 --> 00:21:30,600 Speaker 1: the US aside from the very clear headlines about trade 372 00:21:30,640 --> 00:21:34,439 Speaker 1: tensions is over artificial intelligence, and China has made a 373 00:21:34,480 --> 00:21:37,840 Speaker 1: real concerted effort to push forward any new technology on 374 00:21:37,880 --> 00:21:40,960 Speaker 1: that front. The White House had a meeting last week 375 00:21:41,240 --> 00:21:43,240 Speaker 1: where it had the executive of some of the leading 376 00:21:43,240 --> 00:21:46,679 Speaker 1: tech companies in the US, and White House officials said, listen, 377 00:21:46,800 --> 00:21:51,480 Speaker 1: if you want to experiment develop artificial intelligence, go crazy. 378 00:21:51,600 --> 00:21:53,679 Speaker 1: We are going to have a very light touch with 379 00:21:53,720 --> 00:21:56,600 Speaker 1: respect to regulating this. What is the cutting edge of 380 00:21:56,680 --> 00:21:59,479 Speaker 1: artificial intelligence? And how important is this sort of lazy, 381 00:21:59,560 --> 00:22:03,960 Speaker 1: fair at tude by US representatives. So I think artificial 382 00:22:03,960 --> 00:22:07,879 Speaker 1: intelligence is already and will become even more important to 383 00:22:08,000 --> 00:22:10,600 Speaker 1: our economy. So then the same way that trans software 384 00:22:10,600 --> 00:22:13,320 Speaker 1: transformed every sector of the economy. I mean, software is 385 00:22:13,600 --> 00:22:16,240 Speaker 1: like electricity, It is used by literally everyone, I think 386 00:22:16,240 --> 00:22:19,400 Speaker 1: eventually artificial intelligence is going to rise to that same 387 00:22:19,480 --> 00:22:23,159 Speaker 1: level of being a truly transformative technology in terms there 388 00:22:23,200 --> 00:22:25,800 Speaker 1: are a lot of different kinds of artificial intelligence. And 389 00:22:25,880 --> 00:22:27,840 Speaker 1: so one of the things that you're reading the headlines 390 00:22:27,880 --> 00:22:32,119 Speaker 1: in terms of China's investments and research, um, you know, 391 00:22:32,200 --> 00:22:35,840 Speaker 1: China is investing significant amounts of money, not just at 392 00:22:35,840 --> 00:22:38,000 Speaker 1: the central level, but at the prevential level. At the 393 00:22:38,040 --> 00:22:40,200 Speaker 1: same time, in the United States, more through the private 394 00:22:40,240 --> 00:22:44,160 Speaker 1: sector and through UM we are also having significant investments 395 00:22:44,160 --> 00:22:48,359 Speaker 1: in artificial intelligence. And speaking for the software industry, I 396 00:22:48,359 --> 00:22:50,760 Speaker 1: think what we are most focused on is how you 397 00:22:50,760 --> 00:22:54,920 Speaker 1: can use artificial intelligence to try to help people make 398 00:22:54,960 --> 00:22:58,440 Speaker 1: decisions better, So decisions that people are already making, how 399 00:22:58,480 --> 00:23:00,199 Speaker 1: to make how to give them the tools that they 400 00:23:00,200 --> 00:23:03,399 Speaker 1: are making those decisions more quickly and with more information. 401 00:23:03,680 --> 00:23:07,080 Speaker 1: And I can give you a couple of examples of that. 402 00:23:07,160 --> 00:23:08,720 Speaker 1: But I will also tell you I think this is 403 00:23:08,720 --> 00:23:14,520 Speaker 1: going to be present in every sector, healthcare, finances, manufacturing, agriculture. 404 00:23:14,880 --> 00:23:16,760 Speaker 1: I think, you know, five to ten years from now, 405 00:23:16,800 --> 00:23:19,080 Speaker 1: we're going to see the ripple effects of this across 406 00:23:19,119 --> 00:23:21,720 Speaker 1: the industry. Give us, though, one concrete example, just so 407 00:23:21,760 --> 00:23:24,639 Speaker 1: we have a picture in our head. Sure, I'll give 408 00:23:24,680 --> 00:23:28,080 Speaker 1: you one that's personally important to me. UM. So, I 409 00:23:28,119 --> 00:23:31,520 Speaker 1: have two boys, six and ten. UM And for a 410 00:23:31,720 --> 00:23:35,359 Speaker 1: very short period of time, Uh, my eldest son was 411 00:23:35,400 --> 00:23:38,119 Speaker 1: in the natal intensive care unit the nick you after 412 00:23:38,160 --> 00:23:41,760 Speaker 1: he was born. Uh And and happily he he was 413 00:23:41,840 --> 00:23:44,760 Speaker 1: and is fine. But one of the things that's happening 414 00:23:44,760 --> 00:23:46,920 Speaker 1: in artificial intelligence right now that I think is really 415 00:23:47,640 --> 00:23:51,680 Speaker 1: is really amazing as a mother, UH is that doctors 416 00:23:51,800 --> 00:23:55,600 Speaker 1: are using artificial intelligence to monitor the vital signs for 417 00:23:55,880 --> 00:23:58,320 Speaker 1: babies that are in nick u's and one of the 418 00:23:58,320 --> 00:24:00,840 Speaker 1: things that they have found in doing that at is 419 00:24:00,920 --> 00:24:05,360 Speaker 1: that it is actually a danger sign for for very 420 00:24:05,359 --> 00:24:10,000 Speaker 1: small babies when they're vital signs stabilized, which is completely counterintuitive, 421 00:24:10,119 --> 00:24:12,560 Speaker 1: right you would think the vital signs are stabilized, that 422 00:24:12,600 --> 00:24:15,439 Speaker 1: means um that that child is doing better and therefore 423 00:24:15,520 --> 00:24:18,840 Speaker 1: care should move to another baby. In fact, that is 424 00:24:18,880 --> 00:24:21,560 Speaker 1: not the case. In fact, when vital signs stabilized, that 425 00:24:21,680 --> 00:24:24,320 Speaker 1: is actually a very good predictor that a crash is coming, 426 00:24:24,560 --> 00:24:27,640 Speaker 1: and so monitoring of that babies should be increased rather 427 00:24:27,680 --> 00:24:30,040 Speaker 1: than decreased or the amount of care and attention to 428 00:24:30,119 --> 00:24:33,880 Speaker 1: it um. Doctors still don't know exactly why this is, 429 00:24:33,960 --> 00:24:36,600 Speaker 1: but one of the things with artificial intelligence is it 430 00:24:36,640 --> 00:24:38,920 Speaker 1: can be great to know why, but sometimes it also 431 00:24:39,160 --> 00:24:42,280 Speaker 1: just mataged to know that it is. And this is UH. 432 00:24:42,400 --> 00:24:45,720 Speaker 1: This is changing the way that doctors are treating UH 433 00:24:45,880 --> 00:24:48,040 Speaker 1: babies that are in native and that are in the 434 00:24:48,119 --> 00:24:50,600 Speaker 1: nick us and I think it's really important that that 435 00:24:50,720 --> 00:24:53,080 Speaker 1: is one example, you can look at almost any hairry 436 00:24:53,080 --> 00:24:55,720 Speaker 1: of health care right now and see the advances that 437 00:24:55,760 --> 00:24:58,000 Speaker 1: are being made in artificial intelligence, and most of them 438 00:24:58,000 --> 00:25:00,880 Speaker 1: go to to be more specific, they go to increasing 439 00:25:00,880 --> 00:25:05,119 Speaker 1: the accuracy of diagnoses, increasing the speed of diagnosis, and 440 00:25:05,160 --> 00:25:07,679 Speaker 1: then coming up with treatment plans that may not have 441 00:25:07,840 --> 00:25:11,600 Speaker 1: been as obvious to the doctors without the ability to 442 00:25:11,680 --> 00:25:14,920 Speaker 1: use artificial intelligence tools. I'm just wondering if you could 443 00:25:14,920 --> 00:25:16,760 Speaker 1: just give us maybe a twenty second update. In the 444 00:25:16,760 --> 00:25:21,760 Speaker 1: world of piracy and the piracy of either stealing software 445 00:25:21,880 --> 00:25:25,640 Speaker 1: code or intellectual property, it can be anything from movies 446 00:25:25,680 --> 00:25:30,920 Speaker 1: to music. But that's also a big concern for technology companies. So, 447 00:25:31,119 --> 00:25:32,919 Speaker 1: you know, I think for software, I don't like the 448 00:25:33,000 --> 00:25:35,000 Speaker 1: term piracy and I don't use it. You know. I 449 00:25:35,040 --> 00:25:37,800 Speaker 1: think we encourage We think all companies should use software 450 00:25:37,840 --> 00:25:39,840 Speaker 1: within the terms of their licenses. But I don't think 451 00:25:39,960 --> 00:25:42,960 Speaker 1: it's company that isn't is not an organization that I 452 00:25:43,000 --> 00:25:46,440 Speaker 1: would call a pirate. UM. I think there are, particularly 453 00:25:46,440 --> 00:25:52,080 Speaker 1: in counterfeit pharmaceuticals, there are organizations involved in criminal distribution UM, 454 00:25:52,240 --> 00:25:56,800 Speaker 1: and I think that's reprehensible behavior because of the public 455 00:25:56,800 --> 00:25:59,399 Speaker 1: safety impacts that it can have. UM. You know, I 456 00:25:59,480 --> 00:26:02,840 Speaker 1: think There's there's a lot of progress that's been made 457 00:26:03,040 --> 00:26:05,760 Speaker 1: in terms of trying to address intellectual property issues, and 458 00:26:05,800 --> 00:26:08,560 Speaker 1: I think that's going to continue. Victoria Espinel, thank you 459 00:26:08,560 --> 00:26:11,280 Speaker 1: so much for being with us. Victoria Espinel as President 460 00:26:11,480 --> 00:26:14,960 Speaker 1: and chief executive officer of the Business Software Alliance based 461 00:26:15,040 --> 00:26:21,520 Speaker 1: in Washington, d C. Thanks for listening to the Bloomberg 462 00:26:21,520 --> 00:26:24,199 Speaker 1: p m L podcast. You can subscribe and listen to 463 00:26:24,240 --> 00:26:28,760 Speaker 1: interviews at Apple Podcasts, SoundCloud, or whatever podcast platform you prefer. 464 00:26:29,160 --> 00:26:32,720 Speaker 1: I'm pim Fox. I'm on Twitter at pim Fox. I'm 465 00:26:32,760 --> 00:26:36,159 Speaker 1: on Twitter at Lisa abramoits one before the podcast. You 466 00:26:36,160 --> 00:26:38,720 Speaker 1: can always catch us worldwide on Bloomberg Radio.