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 --> 00:00:31,520 Speaker 1: Podcast on Apple Podcasts, SoundCloud and Bloomberg dot com. You know, 7 00:00:31,600 --> 00:00:34,879 Speaker 1: a Lisa. We are also awaiting President Trump. He's going 8 00:00:34,960 --> 00:00:38,559 Speaker 1: to be talking about the healthcare reform that he has 9 00:00:38,600 --> 00:00:41,040 Speaker 1: been trying to initiate, and maybe trying to do it 10 00:00:41,080 --> 00:00:44,440 Speaker 1: by executive order rather than by floating a specific plan 11 00:00:44,800 --> 00:00:47,400 Speaker 1: that would have to pass the Congress. This would, in 12 00:00:47,440 --> 00:00:50,120 Speaker 1: a sense, dilute the options. Even though they say they're 13 00:00:50,120 --> 00:00:53,080 Speaker 1: going to offer more options, it's gonna maybe dilute them 14 00:00:53,080 --> 00:00:56,760 Speaker 1: because of it more expensive. Well, here's the here's the challenge. 15 00:00:56,760 --> 00:00:59,840 Speaker 1: So basically, what President Trump, from my understanding, wants to 16 00:01:00,040 --> 00:01:05,400 Speaker 1: do is to allow insurance companies to offer a wider 17 00:01:05,560 --> 00:01:09,840 Speaker 1: array of plans to potential customers. In other words, you 18 00:01:09,880 --> 00:01:13,560 Speaker 1: could just get certain protection that would cover uh, primary 19 00:01:13,600 --> 00:01:17,760 Speaker 1: care visits or and catastrophic uh, you know, insurance. The 20 00:01:17,840 --> 00:01:22,600 Speaker 1: concern here is that this will essentially, uh, make it 21 00:01:22,880 --> 00:01:26,040 Speaker 1: more expensive for people who have pre existing conditions, and 22 00:01:26,200 --> 00:01:29,520 Speaker 1: we need to get more comprehensive plans, thus basically pricing 23 00:01:29,560 --> 00:01:32,200 Speaker 1: them out of the market. It follows, it follows the 24 00:01:32,280 --> 00:01:34,679 Speaker 1: letter of the law, which says that you can't deny 25 00:01:34,800 --> 00:01:39,080 Speaker 1: coverage for existing conditions pre existing conditions rather, but that 26 00:01:39,200 --> 00:01:42,600 Speaker 1: the cost would be so exorbitant that it wouldn't really 27 00:01:42,640 --> 00:01:45,600 Speaker 1: make any sense for people to be able to access 28 00:01:45,640 --> 00:01:47,120 Speaker 1: this because they wouldn't be able to pay for it. 29 00:01:47,280 --> 00:01:50,200 Speaker 1: And the treatments in many cases, as we've noted with, 30 00:01:50,280 --> 00:01:53,400 Speaker 1: you know, orphan drugs or so on, are so expensive 31 00:01:54,160 --> 00:01:58,000 Speaker 1: that you'd go broke just paying for the for the 32 00:01:58,920 --> 00:02:02,400 Speaker 1: for the insurance plan because the cost of the medication 33 00:02:02,560 --> 00:02:04,560 Speaker 1: or the treatment is so high. Yeah. I mean, it's 34 00:02:04,560 --> 00:02:07,600 Speaker 1: sort of interesting to see the reaction as we get 35 00:02:07,720 --> 00:02:10,839 Speaker 1: all of the new details out of President Trump's expected 36 00:02:10,919 --> 00:02:14,760 Speaker 1: plans come out, the reactions and healthcare shares right, because 37 00:02:15,280 --> 00:02:18,320 Speaker 1: you see them bouncing around and and responding to the volatility. 38 00:02:18,400 --> 00:02:22,440 Speaker 1: President Trump is also thrown out the idea of withholding 39 00:02:22,600 --> 00:02:27,240 Speaker 1: funds from the program which they have to subsidies subsidies, right, 40 00:02:27,280 --> 00:02:30,640 Speaker 1: that's right, And so this is something to It affects 41 00:02:30,639 --> 00:02:33,000 Speaker 1: a pretty wide variety of companies of just speaking from 42 00:02:33,000 --> 00:02:35,440 Speaker 1: a markets view and looking right now at Etna, its 43 00:02:35,440 --> 00:02:39,320 Speaker 1: shares are down today along with others, nearly one percent, 44 00:02:39,360 --> 00:02:41,959 Speaker 1: and they've been generally declining over the past few weeks. 45 00:02:41,960 --> 00:02:44,320 Speaker 1: So it's interesting just to note that this could end 46 00:02:44,400 --> 00:02:47,040 Speaker 1: up being a negative for them, or at least viewed 47 00:02:47,080 --> 00:02:50,760 Speaker 1: that way by by investors. Yeah. Sure, well, I mean 48 00:02:50,800 --> 00:02:54,760 Speaker 1: also Molina well Care Centene as well as Anthem. I mean, 49 00:02:54,800 --> 00:02:57,880 Speaker 1: these are insurers that all participate in the Affordable Care 50 00:02:57,919 --> 00:03:02,920 Speaker 1: Act exchanges, and the if the executive order goes to 51 00:03:02,960 --> 00:03:07,400 Speaker 1: the point where it makes those plans uh not competitive 52 00:03:07,480 --> 00:03:12,240 Speaker 1: in the marketplace because companies were forced to bottom, then 53 00:03:12,560 --> 00:03:15,080 Speaker 1: you're going to end up with a very fragmented market 54 00:03:15,200 --> 00:03:18,200 Speaker 1: that is going to be very difficult for consumers to untangle. 55 00:03:18,320 --> 00:03:22,000 Speaker 1: You know, I'm struggling with the idea that Congress tried 56 00:03:22,040 --> 00:03:27,160 Speaker 1: to pass some kind of healthcare law twice at least twice, right, 57 00:03:27,600 --> 00:03:30,839 Speaker 1: and they couldn't come up with something that could get 58 00:03:30,960 --> 00:03:34,320 Speaker 1: enough votes. And here we have the President acting unilaterally, 59 00:03:34,360 --> 00:03:39,080 Speaker 1: and I wonder what this does to Congressional negotiations going forward. 60 00:03:39,280 --> 00:03:42,760 Speaker 1: Given the fact that he's changing the backdrop quite a 61 00:03:42,760 --> 00:03:45,600 Speaker 1: bit and and he is making uh some people would 62 00:03:45,600 --> 00:03:48,760 Speaker 1: say A C A less viable. I want to bring 63 00:03:48,760 --> 00:03:51,480 Speaker 1: a Max Niece in biotech, pharma and healthcare calumnist for 64 00:03:51,680 --> 00:03:53,960 Speaker 1: Bloomberg gat Fly. He joins us here in eleven three 65 00:03:53,960 --> 00:03:57,360 Speaker 1: Oh Studios. Max, you know you wrote a fantastic column 66 00:03:57,480 --> 00:04:00,640 Speaker 1: basically saying that President Trump is kneecapping Uh, the A 67 00:04:00,800 --> 00:04:04,280 Speaker 1: C A otherwise known as Obama Care. What's the path 68 00:04:04,400 --> 00:04:08,000 Speaker 1: forward and how can A C A b resurrected? Is 69 00:04:08,040 --> 00:04:11,360 Speaker 1: their political will to give it a little bit more 70 00:04:11,800 --> 00:04:14,800 Speaker 1: after this? So there's sort of two components to this. 71 00:04:14,960 --> 00:04:19,400 Speaker 1: There's what the administration is already doing, which includes cutting 72 00:04:19,440 --> 00:04:21,919 Speaker 1: funds to to market the A C A and for 73 00:04:22,080 --> 00:04:24,880 Speaker 1: groups that help people sign up for insurance, as well 74 00:04:24,880 --> 00:04:27,320 Speaker 1: as shortening the period people have to enroll. And then 75 00:04:27,360 --> 00:04:29,960 Speaker 1: there's what is happening today, which is the signing of 76 00:04:30,000 --> 00:04:33,719 Speaker 1: an Executive Order UM that seeks to kind of make 77 00:04:33,760 --> 00:04:37,080 Speaker 1: it easier to offer insurance and sort of skirts around 78 00:04:37,600 --> 00:04:39,880 Speaker 1: some of the A c IS regulations. And what this 79 00:04:40,000 --> 00:04:43,760 Speaker 1: does is it basically all kind of conspires to to 80 00:04:43,960 --> 00:04:46,320 Speaker 1: damp and enrollment in the A C A and and 81 00:04:46,400 --> 00:04:50,039 Speaker 1: leave the pool that's left there as people that tend 82 00:04:50,080 --> 00:04:54,239 Speaker 1: to be sicker and higher costs, which raises premiums, which 83 00:04:54,480 --> 00:04:56,719 Speaker 1: means more fewer people sign up. So it's kind of 84 00:04:56,760 --> 00:05:00,560 Speaker 1: a really unfortunate cycle that that's difficult to derail. And 85 00:05:00,600 --> 00:05:03,760 Speaker 1: I'm not sure if there's political will to do otherwise, 86 00:05:03,800 --> 00:05:06,920 Speaker 1: because you know, the President has made his priorities known, 87 00:05:07,040 --> 00:05:11,920 Speaker 1: which is effectively weakening this market. So um it would 88 00:05:11,920 --> 00:05:14,400 Speaker 1: take action that that sort of contradicts him, and I'm 89 00:05:14,440 --> 00:05:16,600 Speaker 1: not sure that the Congress is quite up for that. 90 00:05:16,880 --> 00:05:19,120 Speaker 1: What does it also contradict the very notion of what 91 00:05:19,160 --> 00:05:22,320 Speaker 1: insurance is that you want a large pool of people 92 00:05:22,360 --> 00:05:26,160 Speaker 1: to pay into a group plan in order to diversify 93 00:05:26,279 --> 00:05:29,520 Speaker 1: their risk so that when one person needs the funds 94 00:05:29,520 --> 00:05:32,880 Speaker 1: in this case for healthcare, they exist while other people 95 00:05:32,960 --> 00:05:35,520 Speaker 1: continue to pay because they don't want to get sick, 96 00:05:35,600 --> 00:05:38,520 Speaker 1: but they might. Yeah, So that that was kind of 97 00:05:38,520 --> 00:05:41,080 Speaker 1: the central logic of the A C A, which was 98 00:05:41,160 --> 00:05:45,440 Speaker 1: to take you know, a large and fragmented individual market 99 00:05:45,920 --> 00:05:48,480 Speaker 1: and create a larger risk pool out of it by 100 00:05:48,560 --> 00:05:51,880 Speaker 1: subsidizing people, making people that couldn't previously afford it be 101 00:05:51,920 --> 00:05:54,919 Speaker 1: able to afford it and making it accessible to a 102 00:05:54,960 --> 00:05:58,080 Speaker 1: large group of people, and then adding the penalty if 103 00:05:58,080 --> 00:05:59,760 Speaker 1: you didn't sign up to encourage people to sign up, 104 00:05:59,800 --> 00:06:02,560 Speaker 1: because the insurance industry doesn't necessarily care where the money 105 00:06:02,600 --> 00:06:05,160 Speaker 1: comes exactly. They don't care who pays the premium as 106 00:06:05,200 --> 00:06:07,200 Speaker 1: long as the premium gets paid and its matched to 107 00:06:07,360 --> 00:06:10,719 Speaker 1: the actual liability. Yeah. So the thing that's damaging about 108 00:06:10,760 --> 00:06:14,120 Speaker 1: this order is that it it instead of making the 109 00:06:14,680 --> 00:06:18,440 Speaker 1: risk pool larger, it divides it by basically making it 110 00:06:18,440 --> 00:06:23,120 Speaker 1: easier to purchase cheap short term insurance and for little 111 00:06:23,160 --> 00:06:26,880 Speaker 1: groups of employers to band together and offer less generous 112 00:06:26,880 --> 00:06:30,760 Speaker 1: and cheaper coverage. So that will basically potentially siphon off 113 00:06:30,800 --> 00:06:34,600 Speaker 1: people from the individual market, making the risk wool worse. There. 114 00:06:35,040 --> 00:06:38,560 Speaker 1: Do you think that if President Trump goes through with 115 00:06:38,760 --> 00:06:42,960 Speaker 1: pairing back both the subsidies as well as the requirements 116 00:06:43,000 --> 00:06:45,960 Speaker 1: for insurance companies, that that will actually remove the pressure 117 00:06:46,080 --> 00:06:49,919 Speaker 1: on Congress to do something substantial with the A C A, 118 00:06:50,040 --> 00:06:53,239 Speaker 1: since they just have to uh since already been watered down, 119 00:06:53,279 --> 00:06:55,640 Speaker 1: and there'll be less money flowing toward it um. So 120 00:06:55,800 --> 00:06:58,120 Speaker 1: there there might be pressure on two sides, one other 121 00:06:58,120 --> 00:07:00,719 Speaker 1: pressure to do something to sort of counter this to 122 00:07:00,760 --> 00:07:03,960 Speaker 1: try and make the market a little more stable, um, 123 00:07:04,160 --> 00:07:07,760 Speaker 1: or if the the aim might be through these kind 124 00:07:07,800 --> 00:07:12,040 Speaker 1: of actions to deliberately destabilize it as a way to 125 00:07:12,040 --> 00:07:15,320 Speaker 1: to galvanize another repeal replaced effort, although that that would 126 00:07:15,320 --> 00:07:18,280 Speaker 1: obviously be complicated by the need to pass tax reform, 127 00:07:18,360 --> 00:07:19,840 Speaker 1: so it's unclear if they'll be able to do that. 128 00:07:20,520 --> 00:07:22,480 Speaker 1: Is there any in your mind can be and then 129 00:07:22,520 --> 00:07:25,560 Speaker 1: any explanation for why we haven't seen a huge reaction 130 00:07:25,640 --> 00:07:28,800 Speaker 1: in the stocks. I mean Anthem at United Health SIGNA. 131 00:07:28,840 --> 00:07:32,160 Speaker 1: I mean, you know, okay, over the last month, AT 132 00:07:32,360 --> 00:07:35,120 Speaker 1: is down four percent, but Anthem's up four tenths of 133 00:07:35,120 --> 00:07:37,680 Speaker 1: a percent today, Anthem is higher. I mean, there's no 134 00:07:37,840 --> 00:07:41,480 Speaker 1: real consensus here, is there? Um? I think if you 135 00:07:41,520 --> 00:07:43,680 Speaker 1: look at some of the smaller insurers that are a 136 00:07:43,680 --> 00:07:45,960 Speaker 1: little bit more narrowly focused on the A C A, 137 00:07:46,280 --> 00:07:48,440 Speaker 1: you'll see a little bit more of a reaction, and 138 00:07:49,120 --> 00:07:54,160 Speaker 1: Molina well care um, because everyone except Anthem has taken 139 00:07:54,200 --> 00:07:56,000 Speaker 1: an even Anthem has taken a pretty big step back 140 00:07:56,040 --> 00:07:58,000 Speaker 1: in the market. And the other thing is is it 141 00:07:58,160 --> 00:08:00,600 Speaker 1: might be that this this order is a little bit 142 00:08:01,120 --> 00:08:04,160 Speaker 1: less severe than than some were expecting. Over the last 143 00:08:04,160 --> 00:08:07,160 Speaker 1: week and previously UH kind of limits the expansion of 144 00:08:07,200 --> 00:08:10,760 Speaker 1: what are called association health plans to employers rather than 145 00:08:11,000 --> 00:08:13,760 Speaker 1: seeking to add individuals to it. That was something that 146 00:08:13,760 --> 00:08:16,120 Speaker 1: that people feared might happen. So so it's still bad, 147 00:08:16,160 --> 00:08:18,720 Speaker 1: but not as bad. And and there's no kind of 148 00:08:18,760 --> 00:08:23,040 Speaker 1: specific effort to make insurance UH be able to sell 149 00:08:23,040 --> 00:08:26,240 Speaker 1: insurance across state lines, which was also a potential policy remedy. 150 00:08:26,360 --> 00:08:30,080 Speaker 1: Are there any estimates on what President Trump's expected action 151 00:08:30,320 --> 00:08:33,960 Speaker 1: UH in a few moments will do with respect to 152 00:08:34,040 --> 00:08:38,520 Speaker 1: the number of uninsured in the US? UM? You know 153 00:08:38,640 --> 00:08:42,400 Speaker 1: that there isn't a specific estimate on on this exact proposal, 154 00:08:42,840 --> 00:08:46,280 Speaker 1: but pretty recently the CBO of the Congressional Budget Office 155 00:08:46,559 --> 00:08:50,400 Speaker 1: did substantially revise downward its estimates of how many people 156 00:08:50,400 --> 00:08:54,000 Speaker 1: would be on the individual exchanges UM, in part due 157 00:08:54,000 --> 00:08:56,360 Speaker 1: to the fact that, you know, they just haven't performed 158 00:08:56,400 --> 00:08:59,080 Speaker 1: as well as expected for a variety of reasons, but 159 00:08:59,160 --> 00:09:01,679 Speaker 1: in part because of UM, you know, other actions taken 160 00:09:01,679 --> 00:09:04,880 Speaker 1: by the president, like not committing to funding cast sharing 161 00:09:04,960 --> 00:09:10,520 Speaker 1: reduction subsidies. What will this due to actual doctors, health 162 00:09:10,520 --> 00:09:12,840 Speaker 1: care centers, I mean, does it actually have an effect 163 00:09:13,040 --> 00:09:16,360 Speaker 1: on the healthcare networks that have been set up in 164 00:09:16,400 --> 00:09:20,600 Speaker 1: different communities. It absolutely does, I mean, any any increase 165 00:09:20,640 --> 00:09:24,800 Speaker 1: in the number of uninsured people exposes insured and expose 166 00:09:24,880 --> 00:09:28,920 Speaker 1: hospitals to more uncompensated care. Um. And when people have 167 00:09:29,080 --> 00:09:30,880 Speaker 1: you know, if they signed up for these skimpy short 168 00:09:30,960 --> 00:09:35,040 Speaker 1: term plans, uh, they're likely to defer healthcare that they 169 00:09:35,080 --> 00:09:38,160 Speaker 1: might have otherwise consumed if they had a comprehensive plan. 170 00:09:38,720 --> 00:09:40,880 Speaker 1: And then there's the fact that you know, in insurance 171 00:09:40,960 --> 00:09:44,680 Speaker 1: is in place. Um. You know, comprehensive insurance is desirable 172 00:09:44,760 --> 00:09:48,040 Speaker 1: because you don't know when you're gonna need healthcare. I 173 00:09:48,080 --> 00:09:50,520 Speaker 1: mean that that's why one of the goals of the 174 00:09:50,520 --> 00:09:53,400 Speaker 1: a c A was to promote um you know, care 175 00:09:53,640 --> 00:09:58,000 Speaker 1: insurance that actually served its role as opposed to being 176 00:09:58,120 --> 00:10:01,080 Speaker 1: like so narrow or or having so much cost sharing 177 00:10:01,160 --> 00:10:04,679 Speaker 1: for the patient that you know, actually getting sick in 178 00:10:04,679 --> 00:10:07,200 Speaker 1: a real way was financially toxic. So you might see 179 00:10:07,240 --> 00:10:09,560 Speaker 1: some of the return of that, you know, Max. One 180 00:10:09,600 --> 00:10:11,240 Speaker 1: of the things that strikes me as ironic is that 181 00:10:11,280 --> 00:10:14,920 Speaker 1: you have Medicare and Medicaid, although Medicaid typically administered by 182 00:10:14,920 --> 00:10:19,360 Speaker 1: the states in a variety of places, but Medicare national plan, right, 183 00:10:19,600 --> 00:10:22,199 Speaker 1: and then you have the situation where you cannot sell 184 00:10:22,880 --> 00:10:26,520 Speaker 1: health insurance plans across state lines. It's almost as if 185 00:10:26,520 --> 00:10:28,520 Speaker 1: we're sort of, you know, trying to do something with 186 00:10:28,559 --> 00:10:31,880 Speaker 1: one hand tied behind your back. Is that accurate? Um, 187 00:10:32,000 --> 00:10:35,440 Speaker 1: a little bit. It is tough to have a you know, 188 00:10:36,320 --> 00:10:38,600 Speaker 1: unless you're the size of Medicare, and you know it's 189 00:10:38,600 --> 00:10:41,080 Speaker 1: a program that's been around for many years. It's sort 190 00:10:41,120 --> 00:10:46,280 Speaker 1: of tough to have UM insurance that extends across multiple 191 00:10:46,280 --> 00:10:48,480 Speaker 1: places because you have to design a plan and a 192 00:10:48,520 --> 00:10:53,120 Speaker 1: provider network UM and account for state regulations. But you know, 193 00:10:53,480 --> 00:10:57,320 Speaker 1: the privately run Medicare advantage programs do kind of tend 194 00:10:57,360 --> 00:10:59,560 Speaker 1: to be considered within states. So there's a little bit 195 00:10:59,600 --> 00:11:01,600 Speaker 1: of a let's put in that market as well. Do 196 00:11:01,640 --> 00:11:05,600 Speaker 1: you have any sense of whose advising President Trump and 197 00:11:05,840 --> 00:11:11,120 Speaker 1: drafting what he's doing today? UM? I mean this, this 198 00:11:11,240 --> 00:11:16,359 Speaker 1: particular piece of this particular executive order has Rand Paul's 199 00:11:16,520 --> 00:11:19,760 Speaker 1: fingerprints all over it. Uh. It kind of has some 200 00:11:21,000 --> 00:11:23,360 Speaker 1: some proposals that that he's kind of been in favor 201 00:11:23,400 --> 00:11:25,280 Speaker 1: of for a long time, although not all of them. 202 00:11:25,280 --> 00:11:28,400 Speaker 1: But I'm sure he's still thrilled at the result today. 203 00:11:28,679 --> 00:11:32,679 Speaker 1: Hospital corporations. Uh, what what pain are they going to 204 00:11:32,800 --> 00:11:36,280 Speaker 1: feel if indeed this happens. You know, it's a it's 205 00:11:36,320 --> 00:11:40,199 Speaker 1: a segment. Hospitals are already struggling with kind of reimbursement 206 00:11:40,240 --> 00:11:44,439 Speaker 1: issues and uh generally like a kind of over consolidation 207 00:11:44,679 --> 00:11:47,360 Speaker 1: and a lot of debt. So UM, any anything at 208 00:11:47,400 --> 00:11:51,360 Speaker 1: the margin that reduces their flow of business, as you know, 209 00:11:51,400 --> 00:11:54,719 Speaker 1: arise in the uninsured rate um and an uncompensied care 210 00:11:54,760 --> 00:11:56,800 Speaker 1: could is definitely a bad thing. Because I was looking 211 00:11:56,840 --> 00:11:59,200 Speaker 1: at Tenant Healthcare, for example, and the stock is down 212 00:11:59,200 --> 00:12:01,640 Speaker 1: five and a half percent this year and shares are 213 00:12:01,800 --> 00:12:04,400 Speaker 1: you know, down again today and that's going to be 214 00:12:04,480 --> 00:12:06,319 Speaker 1: a difficult business, right, I mean they're down more than 215 00:12:06,320 --> 00:12:08,319 Speaker 1: three and a half percent. So the hospital seemed to 216 00:12:08,360 --> 00:12:11,840 Speaker 1: be bearing the brunt of this absolutely. Um. You know, 217 00:12:11,920 --> 00:12:14,599 Speaker 1: especially something like Tenant that that has a really substantial 218 00:12:14,600 --> 00:12:17,320 Speaker 1: debtload and UM, you know it's trying to dispose chunks 219 00:12:17,360 --> 00:12:20,400 Speaker 1: of the business to pay it down. UM. And anything 220 00:12:20,520 --> 00:12:23,760 Speaker 1: that that looks negative will obviously be reacted to. Well. 221 00:12:23,840 --> 00:12:25,880 Speaker 1: But max, will this make it cheaper for the US 222 00:12:25,920 --> 00:12:30,080 Speaker 1: with respect to their healthcare bills? Um? For a subset 223 00:12:30,120 --> 00:12:33,160 Speaker 1: of people, you know, if you're healthy and young and 224 00:12:33,280 --> 00:12:36,320 Speaker 1: only one really limited insurance, you might have a better 225 00:12:36,360 --> 00:12:40,320 Speaker 1: option now that just has various knock on effects. And 226 00:12:40,360 --> 00:12:42,800 Speaker 1: if you become not healthy then uh, you know, that's 227 00:12:42,800 --> 00:12:45,000 Speaker 1: the position we were in before the A you're potentially 228 00:12:45,080 --> 00:12:46,839 Speaker 1: a lot of trouble. Actually was talking about the federal 229 00:12:46,840 --> 00:12:48,880 Speaker 1: government and that that was one thing that people were 230 00:12:48,920 --> 00:12:51,480 Speaker 1: talking about, was that reducing the A S A would 231 00:12:51,480 --> 00:12:53,880 Speaker 1: actually free up all this money and it could kind 232 00:12:53,880 --> 00:12:56,880 Speaker 1: of bridge any budget deficits that would arise from the 233 00:12:57,000 --> 00:13:00,480 Speaker 1: tax plan. You know, the truly ironic thinking is that 234 00:13:00,520 --> 00:13:04,640 Speaker 1: there's a really good chance that this will increase federal expenditures. Um. 235 00:13:04,920 --> 00:13:07,800 Speaker 1: It sounds kind of um contradictory. You think of the 236 00:13:07,800 --> 00:13:10,360 Speaker 1: A C as a big government program that pairing it 237 00:13:10,400 --> 00:13:15,000 Speaker 1: back might reduce federal spending. But because you're taking all 238 00:13:15,000 --> 00:13:19,839 Speaker 1: these actions that are likely to send insurance premiums up um. 239 00:13:19,880 --> 00:13:24,960 Speaker 1: For the for about the individual market that gets subsidies, Uh, 240 00:13:25,080 --> 00:13:27,120 Speaker 1: they'll still want this insurance, they don't pay for a 241 00:13:27,160 --> 00:13:29,920 Speaker 1: whole lot of it. The subsidies are tied to their ensure, 242 00:13:30,080 --> 00:13:33,760 Speaker 1: their their income levels and tied to premiums. So when 243 00:13:33,760 --> 00:13:37,320 Speaker 1: premiums go up, those subsidies go up, and and those 244 00:13:37,360 --> 00:13:39,160 Speaker 1: premiums are set to go up a lot because of 245 00:13:39,160 --> 00:13:42,400 Speaker 1: these actions. So so in addition to kind of disrupting 246 00:13:42,440 --> 00:13:43,960 Speaker 1: the market, this might actually turn out to be very 247 00:13:43,960 --> 00:13:47,040 Speaker 1: expensive for the government. Max Neeson our gad Fly columnist 248 00:13:47,080 --> 00:13:51,679 Speaker 1: expert when it comes to biotechnology, pharmaceuticals and healthcare, and Max, 249 00:13:51,840 --> 00:13:54,040 Speaker 1: I'm sorry to keep harping on the hospitals because this 250 00:13:54,120 --> 00:13:56,000 Speaker 1: is kind of, you know, the point of care, right 251 00:13:56,240 --> 00:13:58,440 Speaker 1: And I've just been looking at the stocks and Tenant 252 00:13:58,559 --> 00:14:01,800 Speaker 1: is down eighteen and a half percent this over the 253 00:14:01,880 --> 00:14:04,319 Speaker 1: last month. I beg your pardon over the last month. 254 00:14:04,679 --> 00:14:11,119 Speaker 1: Community Health down over the last month. H C a 255 00:14:11,200 --> 00:14:16,880 Speaker 1: life point all the universal health. If the investing public 256 00:14:16,960 --> 00:14:20,600 Speaker 1: is saying we don't want to own a hospital, uh, 257 00:14:20,800 --> 00:14:23,400 Speaker 1: what's that going to due to the infrastructure of those 258 00:14:23,440 --> 00:14:25,840 Speaker 1: institutions that are going to be the ones to actually 259 00:14:25,840 --> 00:14:27,880 Speaker 1: administer they care where they're going to get the money, 260 00:14:27,880 --> 00:14:31,400 Speaker 1: They're gonna have to go out and borrow more money. Yeah, 261 00:14:31,480 --> 00:14:34,520 Speaker 1: So I'm a kind of rough equity environment for for 262 00:14:34,600 --> 00:14:38,560 Speaker 1: hospitals does make it a lot tougher. Um And when 263 00:14:38,600 --> 00:14:41,960 Speaker 1: you have these sort of big consolidated groups, um, you know, 264 00:14:42,000 --> 00:14:45,200 Speaker 1: they're they're kind of struggling in this market, and um, 265 00:14:46,360 --> 00:14:49,040 Speaker 1: you know, it's unclear whether that model is gonna end 266 00:14:49,120 --> 00:14:52,280 Speaker 1: up being sustainable. Um. So yeah, really really not sure 267 00:14:52,280 --> 00:14:53,920 Speaker 1: how this is gonna impact because the whole point of 268 00:14:53,920 --> 00:14:56,680 Speaker 1: consolidation for the hospital industry was that it was supposed 269 00:14:56,720 --> 00:15:00,360 Speaker 1: to lower costs and improve patient care. Have they've done 270 00:15:00,360 --> 00:15:03,080 Speaker 1: away with the same kind of state by state regulations 271 00:15:03,120 --> 00:15:06,080 Speaker 1: that would limit, for example, the sharing of information between 272 00:15:06,160 --> 00:15:09,040 Speaker 1: hospital groups or is that still part of you know, 273 00:15:09,120 --> 00:15:11,760 Speaker 1: the privacy laws. So yeah, that that was sort of 274 00:15:11,800 --> 00:15:15,200 Speaker 1: the promised impact of these big consolidation moves. But but 275 00:15:15,240 --> 00:15:20,400 Speaker 1: obviously it hasn't quite come to fruition as as the 276 00:15:20,480 --> 00:15:23,040 Speaker 1: investor the I banks might have pitched when they were 277 00:15:23,080 --> 00:15:26,320 Speaker 1: making these deals, because you know, the amount of debt 278 00:15:26,600 --> 00:15:29,840 Speaker 1: that they raised has not kind of been it's been 279 00:15:29,920 --> 00:15:33,160 Speaker 1: out of proportion with the sort of synergies and and 280 00:15:33,240 --> 00:15:36,160 Speaker 1: anything they've realized by actually doing these transactions. Max Neison, 281 00:15:36,200 --> 00:15:38,200 Speaker 1: thank you so much for joining us. Always a pleasure 282 00:15:38,240 --> 00:15:41,960 Speaker 1: to get your insights, and always his columns are full 283 00:15:42,120 --> 00:15:45,480 Speaker 1: of insights, So I recommend people read at Bloomberg dot com, 284 00:15:45,600 --> 00:15:48,400 Speaker 1: slash gad Fly, Max Neeson is a Bloomberg gad Fly 285 00:15:48,480 --> 00:15:54,520 Speaker 1: columnist focusing on the healthcare and and biopharmaceutical companies and 286 00:15:54,560 --> 00:16:09,080 Speaker 1: everything else related to that field. Yeah, all right, let's 287 00:16:09,280 --> 00:16:11,720 Speaker 1: turn our attention now to the world of banking and finance. 288 00:16:11,760 --> 00:16:13,520 Speaker 1: I want to bring in Frank Sorentino. He is the 289 00:16:13,600 --> 00:16:16,200 Speaker 1: chairman and the chief executive of connect to One Bank, 290 00:16:16,240 --> 00:16:19,320 Speaker 1: assets under management four point seven billion dollars, based in 291 00:16:19,400 --> 00:16:24,320 Speaker 1: Englewood Cliffs, New Jersey, and you can follow Frank online 292 00:16:24,360 --> 00:16:28,920 Speaker 1: on Twitter at Frank and just Roman numeral three. Frank, 293 00:16:29,000 --> 00:16:32,640 Speaker 1: always good to have you here. You know, maybe you 294 00:16:32,640 --> 00:16:35,040 Speaker 1: could just start off by one of the things I 295 00:16:35,080 --> 00:16:38,560 Speaker 1: know slightly in the weeds. But when I think of 296 00:16:38,600 --> 00:16:40,560 Speaker 1: a bank, I don't necessarily think of changes in the 297 00:16:40,560 --> 00:16:43,920 Speaker 1: transportation industry. But I've got to think about that when 298 00:16:43,920 --> 00:16:47,560 Speaker 1: I think I'll connect one. Because you specialized in taxi 299 00:16:47,600 --> 00:16:52,200 Speaker 1: medallions and find helping to finance taxi taxi medallions, the 300 00:16:52,360 --> 00:16:54,960 Speaker 1: business has got to really have changed in the last 301 00:16:55,000 --> 00:16:56,800 Speaker 1: five years. I wonder if you could just tell us 302 00:16:57,080 --> 00:16:59,920 Speaker 1: your relationship how that's changed, and then how do you 303 00:17:00,120 --> 00:17:02,360 Speaker 1: meet a change like that, Because it's not as if 304 00:17:02,360 --> 00:17:05,760 Speaker 1: people still don't want to travel by automobile. PIM. Great 305 00:17:05,800 --> 00:17:08,720 Speaker 1: to be here again, Thank you so much. And yes, 306 00:17:08,760 --> 00:17:10,639 Speaker 1: of course, you know, there's lots of change in the 307 00:17:10,640 --> 00:17:14,320 Speaker 1: world today and transportation is one of those areas that 308 00:17:14,440 --> 00:17:18,199 Speaker 1: have changed dramatically. We we don't think about transportation in 309 00:17:18,200 --> 00:17:21,000 Speaker 1: the same way that we did even three years ago, 310 00:17:21,119 --> 00:17:24,080 Speaker 1: never mind five or ten years ago. Um, and here 311 00:17:24,080 --> 00:17:26,480 Speaker 1: it connect one bank. While that's a very very small 312 00:17:26,520 --> 00:17:30,200 Speaker 1: piece of what we do, we've seen and we continue 313 00:17:30,240 --> 00:17:33,679 Speaker 1: to see changes in all aspects of the businesses that 314 00:17:33,720 --> 00:17:37,200 Speaker 1: were involved in, whether it's in the transportation space, whether 315 00:17:37,240 --> 00:17:42,160 Speaker 1: it's in the retail space. There's tremendous change going on there, habitation, 316 00:17:42,400 --> 00:17:46,679 Speaker 1: office space. But I want to tell me about you 317 00:17:46,760 --> 00:17:48,480 Speaker 1: used to mean, I remember because you put them on 318 00:17:48,520 --> 00:17:50,879 Speaker 1: the balance sheet, they were listed as held for sale. 319 00:17:50,920 --> 00:17:53,320 Speaker 1: To just explain what it is you you used to 320 00:17:53,320 --> 00:17:55,720 Speaker 1: set you specialize in this, well, we never it was 321 00:17:55,760 --> 00:17:59,880 Speaker 1: never a specialty, very very small piece of our balance sheet, PIM. 322 00:17:59,880 --> 00:18:03,200 Speaker 1: We we're near a five billion dollar institution and this 323 00:18:03,280 --> 00:18:05,920 Speaker 1: is this is one percent of our entire balance sheet, 324 00:18:05,920 --> 00:18:08,840 Speaker 1: So I wouldn't call it a specialty. But um, we 325 00:18:08,960 --> 00:18:12,280 Speaker 1: certainly liked the transportation space in New York and that's 326 00:18:12,400 --> 00:18:14,680 Speaker 1: you know, that's what the taxi industry is about, and 327 00:18:14,760 --> 00:18:18,440 Speaker 1: taxing and the ownership of taxi medallion um and that 328 00:18:18,520 --> 00:18:23,000 Speaker 1: has definitely changed dramatically, and our view of how that 329 00:18:23,040 --> 00:18:25,040 Speaker 1: transportation is going to take place in New York City 330 00:18:25,040 --> 00:18:28,399 Speaker 1: has changed dramatically over time. Frank, I want to broaden 331 00:18:28,400 --> 00:18:32,200 Speaker 1: out a little bit into the relationship of community banks 332 00:18:32,480 --> 00:18:38,280 Speaker 1: with the incredible upsurge in financial technology, and I'm wondering, 333 00:18:38,560 --> 00:18:43,359 Speaker 1: from your firm's perspective, how have you upgraded your systems 334 00:18:43,400 --> 00:18:48,200 Speaker 1: and kind of adopted some more modern technology to both 335 00:18:48,400 --> 00:18:53,199 Speaker 1: streamline your employees as well as catered to potentially a 336 00:18:53,240 --> 00:18:56,840 Speaker 1: younger well, just as a jumping off from you know, 337 00:18:56,880 --> 00:19:00,479 Speaker 1: what's gone on in the transportation space. Uh, it's the 338 00:19:00,520 --> 00:19:04,320 Speaker 1: same thing here at connect One Bank and many other 339 00:19:04,359 --> 00:19:06,479 Speaker 1: financial institutions. You know, people, when we used to think 340 00:19:06,520 --> 00:19:08,879 Speaker 1: about a bank, you say the word bank, there's a 341 00:19:08,920 --> 00:19:11,080 Speaker 1: segment of the population today that thinks about a limestone 342 00:19:11,119 --> 00:19:14,160 Speaker 1: building with you know, with with leather couches and stone floors. 343 00:19:15,000 --> 00:19:17,760 Speaker 1: But today when we say bank, and you know, there's 344 00:19:17,760 --> 00:19:21,040 Speaker 1: another segment of the population who thinks about their mobile 345 00:19:21,080 --> 00:19:23,560 Speaker 1: device and thinks about ones and zeros and thinks about 346 00:19:23,600 --> 00:19:27,119 Speaker 1: an electronic media as opposed to you know, cash that 347 00:19:27,160 --> 00:19:29,600 Speaker 1: you get out of the vault at the bank and 348 00:19:29,680 --> 00:19:33,560 Speaker 1: connect One has always been a technological leader relative to 349 00:19:33,840 --> 00:19:38,359 Speaker 1: employing different ways of bringing banking services to our clients 350 00:19:38,440 --> 00:19:43,399 Speaker 1: and being able to leverage technology, innovative technology to to 351 00:19:43,520 --> 00:19:46,320 Speaker 1: create a better experience for our clients. But how because 352 00:19:46,400 --> 00:19:48,919 Speaker 1: a lot of the big banks have been spending an 353 00:19:48,920 --> 00:19:52,520 Speaker 1: increasing amount of money, hundreds of billions of dollars on 354 00:19:52,680 --> 00:19:57,399 Speaker 1: their technological infrastructure. Uh, given the size of your bank, 355 00:19:57,680 --> 00:20:01,320 Speaker 1: how do you have a competitive advantage or edge or 356 00:20:01,320 --> 00:20:03,720 Speaker 1: even keep up. So, as you know, recently, we just 357 00:20:03,800 --> 00:20:08,120 Speaker 1: announced the partnership with zel, which is a consortium of 358 00:20:08,600 --> 00:20:12,480 Speaker 1: a number of large financial institutions in the payment space, 359 00:20:12,560 --> 00:20:15,320 Speaker 1: and this will be a product that will compete against 360 00:20:15,440 --> 00:20:18,399 Speaker 1: venmo and other types of payments. It will have the 361 00:20:18,440 --> 00:20:21,920 Speaker 1: security that banks are known for, and so we believe 362 00:20:21,960 --> 00:20:24,800 Speaker 1: this is going to be a very popular products as 363 00:20:24,800 --> 00:20:28,679 Speaker 1: time moves on. We also announced the pretty substantial partnership 364 00:20:28,720 --> 00:20:33,280 Speaker 1: with Encino, which is a deposit and loan origination platform 365 00:20:33,720 --> 00:20:37,879 Speaker 1: which brings us technology that rivals the largest institutions and 366 00:20:37,920 --> 00:20:40,560 Speaker 1: will allow us to be much more efficient than how 367 00:20:40,640 --> 00:20:44,520 Speaker 1: we manage our client relationships. Uh. And so there are 368 00:20:44,560 --> 00:20:47,119 Speaker 1: partners out there. We don't have to have that i 369 00:20:47,240 --> 00:20:51,320 Speaker 1: T department and create, you know, the technological innovation. There 370 00:20:51,320 --> 00:20:54,080 Speaker 1: are partners that we will get together with in the future. 371 00:20:54,119 --> 00:20:56,639 Speaker 1: And these are two examples where we can bring the 372 00:20:56,720 --> 00:21:00,920 Speaker 1: same level of client service as our largest intitution. Colleagues, 373 00:21:01,560 --> 00:21:04,600 Speaker 1: what's your thoughts on bitcoin? Do you agree with Jamie 374 00:21:04,600 --> 00:21:07,320 Speaker 1: Diamond or I think I'm more in the Jamie Diamond 375 00:21:07,320 --> 00:21:10,600 Speaker 1: camp than than not. Um, I am a big fan 376 00:21:11,000 --> 00:21:15,680 Speaker 1: of the blockchain technology. I don't know that the Federal 377 00:21:15,720 --> 00:21:18,920 Speaker 1: Reserve is prepared to let go of our currency as 378 00:21:18,920 --> 00:21:21,639 Speaker 1: we sit here today. Uh and I and I believe 379 00:21:21,720 --> 00:21:26,040 Speaker 1: that's what bitcoin represents, right, it represents an alternate currency. Um. 380 00:21:26,080 --> 00:21:29,560 Speaker 1: We can just imagine what that will mean and how 381 00:21:29,560 --> 00:21:32,320 Speaker 1: it's going to be used. But I don't think that. 382 00:21:32,359 --> 00:21:34,760 Speaker 1: I think the Federal Reserve is allowing the sandbox to 383 00:21:34,880 --> 00:21:37,080 Speaker 1: occur for right now, but at some point they're going 384 00:21:37,119 --> 00:21:40,080 Speaker 1: to take control or maintain control of our currency. Well. Actually, 385 00:21:40,119 --> 00:21:42,439 Speaker 1: just to sort of update or give a little more 386 00:21:42,520 --> 00:21:46,840 Speaker 1: nuance to Jamie Diamond's statements, JP Morgan's Marianna Lake came 387 00:21:46,880 --> 00:21:49,440 Speaker 1: out today and said that JP Morgan is quote very 388 00:21:49,440 --> 00:21:53,480 Speaker 1: open minded to possible uses for cryptocurrencies like bitcoin if 389 00:21:53,480 --> 00:21:58,440 Speaker 1: they quote are properly controlled and regulated. Based on Frank 390 00:21:58,480 --> 00:22:01,720 Speaker 1: what you just said, you think proper controlled regulation will 391 00:22:01,760 --> 00:22:06,520 Speaker 1: ultimately kill these cryptocurrencies, I think in the format that 392 00:22:06,600 --> 00:22:08,440 Speaker 1: we look at them today. Yeah, that would be a 393 00:22:08,480 --> 00:22:12,320 Speaker 1: true statement. Excuse me. I think that over time, though, 394 00:22:12,320 --> 00:22:16,680 Speaker 1: the technologies that that that are behind bitcoin and other 395 00:22:16,760 --> 00:22:19,719 Speaker 1: types of currencies maybe things we will see in our 396 00:22:19,760 --> 00:22:23,680 Speaker 1: own currency system. So you mean as far as blockchain goes, well, 397 00:22:23,680 --> 00:22:27,320 Speaker 1: but what's the advantage of blockchain versus say, just an 398 00:22:27,359 --> 00:22:31,040 Speaker 1: automatic computer system held by JP Morgan, which is basically 399 00:22:31,080 --> 00:22:34,040 Speaker 1: just you know, a spreadsheet basically of accounts. I mean, 400 00:22:34,080 --> 00:22:38,600 Speaker 1: why is blockchain better? I wouldn't sit here and profess 401 00:22:38,680 --> 00:22:42,240 Speaker 1: to be an expert in blockchain. However, the technology there 402 00:22:42,520 --> 00:22:46,080 Speaker 1: is certainly more ubiquitous, and it is not controlled by 403 00:22:46,119 --> 00:22:50,320 Speaker 1: any single source um and it can be relied upon 404 00:22:50,400 --> 00:22:53,800 Speaker 1: in ways that current technology cannot. And I think that's 405 00:22:53,800 --> 00:22:56,600 Speaker 1: what the attractiveness is there. And I think there are 406 00:22:57,400 --> 00:23:01,000 Speaker 1: many institutions that are looking to utilize blockchain, and lots 407 00:23:01,040 --> 00:23:03,840 Speaker 1: of places, whether it be in currency as bitcoin, but 408 00:23:03,880 --> 00:23:07,439 Speaker 1: also in the real estate area entitle um, you know, 409 00:23:07,480 --> 00:23:11,080 Speaker 1: in ownership chains. There are just lots of places where 410 00:23:11,560 --> 00:23:16,280 Speaker 1: that type of technology will replace many archaic systems. And 411 00:23:16,640 --> 00:23:19,080 Speaker 1: you know, again, I know we started the conversation there 412 00:23:19,160 --> 00:23:23,320 Speaker 1: disrupt industries that exist today in a big way. If 413 00:23:23,400 --> 00:23:26,399 Speaker 1: there was one rule that you could change having to 414 00:23:26,440 --> 00:23:30,160 Speaker 1: do with the banking industry, what would it be? Oh boy, 415 00:23:30,520 --> 00:23:34,760 Speaker 1: um pim, that's a tough one. Um. You know. I 416 00:23:34,560 --> 00:23:38,440 Speaker 1: I like to look at all regulation in the industry 417 00:23:38,480 --> 00:23:41,280 Speaker 1: and think about why it came to be, and think 418 00:23:41,320 --> 00:23:46,000 Speaker 1: about the iterative change over time that has created a better, 419 00:23:46,040 --> 00:23:48,720 Speaker 1: safer system today. I don't really think I have a 420 00:23:48,760 --> 00:23:51,320 Speaker 1: favorite or maybe that's not the right word to use, 421 00:23:51,359 --> 00:23:53,920 Speaker 1: but I can't even I can't even begin to think. 422 00:23:53,920 --> 00:23:56,720 Speaker 1: There are so many places where I do believe change 423 00:23:56,760 --> 00:24:00,000 Speaker 1: needs to occur, um, some places more subtle than other 424 00:24:00,040 --> 00:24:02,560 Speaker 1: ers and and I think we're actually starting to see 425 00:24:02,560 --> 00:24:05,800 Speaker 1: that occur, right. We're seeing some very different tonal change 426 00:24:05,800 --> 00:24:08,879 Speaker 1: at the top of the regulatory structures. Uh. And I 427 00:24:08,920 --> 00:24:12,359 Speaker 1: think it's becoming a better environment for banks in general. Frank, 428 00:24:12,520 --> 00:24:14,560 Speaker 1: I'd love to get your take, just on the banking 429 00:24:14,680 --> 00:24:17,480 Speaker 1: business itself, the idea of lending money out, the idea 430 00:24:17,480 --> 00:24:23,800 Speaker 1: of having deposits. UM, what's your outlook for community banking 431 00:24:23,920 --> 00:24:25,800 Speaker 1: and from your own perspective, where do you see the 432 00:24:25,880 --> 00:24:30,840 Speaker 1: biggest opportunity for your firm? So, I think there's still 433 00:24:31,200 --> 00:24:35,000 Speaker 1: great opportunity in the marketplace for community banks like connect 434 00:24:35,040 --> 00:24:37,840 Speaker 1: One Bank, and you know what we're starting, what we 435 00:24:37,880 --> 00:24:40,520 Speaker 1: are seeing and have seen over the last number of years, 436 00:24:40,520 --> 00:24:42,840 Speaker 1: there's been a lot of consolidation going on for a 437 00:24:42,840 --> 00:24:45,120 Speaker 1: lot of the smaller players, and I think what we're 438 00:24:45,119 --> 00:24:49,320 Speaker 1: gonna get to is our much larger small banks and 439 00:24:49,400 --> 00:24:52,360 Speaker 1: connect One is one of those types of institutions where 440 00:24:52,400 --> 00:24:55,320 Speaker 1: we're getting larger, but we're still a small bank in 441 00:24:55,359 --> 00:24:57,800 Speaker 1: a in a community such as the New York metro market, 442 00:24:57,840 --> 00:24:59,840 Speaker 1: which represents some ten percent of our g d P. 443 00:25:00,880 --> 00:25:03,240 Speaker 1: So I think there'll be a place for banks like 444 00:25:03,320 --> 00:25:06,040 Speaker 1: connect One. UM. I think the opportunities are going to 445 00:25:06,119 --> 00:25:09,639 Speaker 1: be tremendous. I think people still want that, you know, 446 00:25:09,720 --> 00:25:13,399 Speaker 1: personalized client service that they just can't get at some 447 00:25:13,440 --> 00:25:16,760 Speaker 1: of the lords that we have more hands on kind 448 00:25:16,760 --> 00:25:19,600 Speaker 1: of approach. Yeah, I think you can get to the decision. 449 00:25:19,800 --> 00:25:24,080 Speaker 1: Look if you have a UM cookie cutter need. Uh, 450 00:25:24,119 --> 00:25:27,320 Speaker 1: there's plenty and there will be plenty of opportunity for 451 00:25:27,359 --> 00:25:29,600 Speaker 1: people to be able to do that online without ever 452 00:25:29,840 --> 00:25:32,760 Speaker 1: talking to an individual. But if you're an entrepreneur and 453 00:25:32,760 --> 00:25:35,000 Speaker 1: you're going to start a business and you're gonna need 454 00:25:35,040 --> 00:25:37,560 Speaker 1: some advice and you're gonna need help and trying to 455 00:25:37,600 --> 00:25:40,159 Speaker 1: figure your way through this system, and I believe that 456 00:25:40,200 --> 00:25:42,840 Speaker 1: will always be the case, then you're gonna need a 457 00:25:42,880 --> 00:25:45,000 Speaker 1: place like connect One Bank to come to to speak 458 00:25:45,040 --> 00:25:47,440 Speaker 1: to a banker. Well, you're going to be speaking, I believe. 459 00:25:47,480 --> 00:25:51,720 Speaker 1: On Sunday, on a panel at the annual Convention of 460 00:25:51,760 --> 00:25:55,200 Speaker 1: the American Bankers Association, the theme you describe this year 461 00:25:55,240 --> 00:26:00,920 Speaker 1: is called rapid Change? Is UH? Is there any um, 462 00:26:01,000 --> 00:26:03,200 Speaker 1: Is there any sort of detail that you can share 463 00:26:03,200 --> 00:26:06,080 Speaker 1: in terms of what has been the biggest stumbling block 464 00:26:06,160 --> 00:26:08,320 Speaker 1: to change for for the banks? Is it just is 465 00:26:08,359 --> 00:26:12,240 Speaker 1: it management decision making? Is it cost? What? Him? I 466 00:26:12,240 --> 00:26:15,280 Speaker 1: think you know our industry and you started right. You 467 00:26:15,320 --> 00:26:18,280 Speaker 1: know they're talking about disruption in the transportation space. It's 468 00:26:18,320 --> 00:26:20,720 Speaker 1: the same thing in banking. There's a lot of disruption 469 00:26:20,760 --> 00:26:23,000 Speaker 1: that's going on in the banking space, and there are 470 00:26:23,080 --> 00:26:26,399 Speaker 1: other players out there who are coming to market with 471 00:26:26,400 --> 00:26:30,920 Speaker 1: with products and services that seem to be more streamlined, 472 00:26:31,000 --> 00:26:33,320 Speaker 1: you know, take away a lot of the friction that's 473 00:26:33,320 --> 00:26:35,680 Speaker 1: in the system. And I think as banks and bankers 474 00:26:36,000 --> 00:26:39,639 Speaker 1: community bankers, we need to recognize that we need to 475 00:26:39,680 --> 00:26:41,879 Speaker 1: get that friction out of this system as well, and 476 00:26:41,960 --> 00:26:45,040 Speaker 1: we need to develop. We need to develop and deliver 477 00:26:45,320 --> 00:26:50,159 Speaker 1: a product that you know, can compete with our fintech brethren, UM, 478 00:26:50,160 --> 00:26:52,280 Speaker 1: and partner with those people in order to come up 479 00:26:52,320 --> 00:26:55,720 Speaker 1: with the change that that the economy is requiring. You know, 480 00:26:55,800 --> 00:26:59,359 Speaker 1: the speed of change today is just extraordinary. Frank, real quick, 481 00:26:59,720 --> 00:27:02,200 Speaker 1: how much do you think that you can grow your 482 00:27:02,200 --> 00:27:06,399 Speaker 1: assets in the next couple of years? UM, So, I 483 00:27:06,440 --> 00:27:10,080 Speaker 1: can't give forward looking statement there, but we've been growing 484 00:27:10,320 --> 00:27:12,800 Speaker 1: in the mid to high teens for the last I 485 00:27:12,840 --> 00:27:16,879 Speaker 1: don't know how many years, and you know, consistent with 486 00:27:16,960 --> 00:27:20,240 Speaker 1: the marketplace that we're in today and consistent with the 487 00:27:20,280 --> 00:27:23,080 Speaker 1: market share grab that we're able to get from the 488 00:27:23,200 --> 00:27:27,200 Speaker 1: larger institutions, I don't really see anything standing on our way. 489 00:27:27,560 --> 00:27:30,400 Speaker 1: Thank you so much for joining us. Frank Sorrentino, Chairman 490 00:27:30,520 --> 00:27:34,160 Speaker 1: and chief executive officer of Connect One Bank, which has 491 00:27:34,160 --> 00:27:38,720 Speaker 1: nearly five billion dollars under management and is based in Englewood, Cliff's, 492 00:27:38,880 --> 00:27:42,199 Speaker 1: New Jersey. He's on Twitter at Frank s I, I, 493 00:27:42,520 --> 00:27:46,840 Speaker 1: I and uh talking about the connection between community banks 494 00:27:46,840 --> 00:27:50,600 Speaker 1: and fintech. Definitely an increasing trend where firms are partnering 495 00:27:51,000 --> 00:27:54,440 Speaker 1: with existing platforms to get state of the art technology. 496 00:27:54,440 --> 00:27:56,880 Speaker 1: At least rom woit's with pim Fox. This is Bloomberg. 497 00:28:09,200 --> 00:28:12,480 Speaker 1: So what to do when machines do Everything? How to 498 00:28:12,520 --> 00:28:17,080 Speaker 1: get ahead in a world of artificial intelligence, algorithms, bots 499 00:28:17,160 --> 00:28:20,159 Speaker 1: and big data? Well, perhaps the first thing you do 500 00:28:20,240 --> 00:28:22,800 Speaker 1: is should call Ben Pring. He is the co director 501 00:28:22,960 --> 00:28:26,200 Speaker 1: of the Future of Work Center for Cognizant. They're based 502 00:28:26,240 --> 00:28:30,640 Speaker 1: in Boston, home the Bloomberg one one Boston, Newburyport, Metro 503 00:28:30,720 --> 00:28:32,679 Speaker 1: West and the South Shore, and he is the co 504 00:28:32,840 --> 00:28:36,240 Speaker 1: author of the book What to Do When Machines Do Everything? Well, Ben, 505 00:28:36,560 --> 00:28:38,920 Speaker 1: thank you for being here in our studios. What do 506 00:28:39,040 --> 00:28:41,480 Speaker 1: you do other than I imagine, first of all, you 507 00:28:41,520 --> 00:28:44,360 Speaker 1: read the book, that's the right, yeah, say all right, 508 00:28:44,400 --> 00:28:46,400 Speaker 1: I got a machine might have been able to give 509 00:28:46,400 --> 00:28:48,160 Speaker 1: you that answer, But the end of the interview that's 510 00:28:49,080 --> 00:28:53,320 Speaker 1: well so, But seriously, what what First of all can 511 00:28:53,360 --> 00:28:58,000 Speaker 1: you just describe what attitude should you have when you're 512 00:28:58,040 --> 00:29:04,160 Speaker 1: trying to learn about the challenges of automation and artificial intelligence. 513 00:29:04,200 --> 00:29:07,920 Speaker 1: Should you have one of fear, defensiveness, optimism, what what 514 00:29:07,960 --> 00:29:10,080 Speaker 1: should you hold? I think, Yeah, it's a great question, 515 00:29:10,120 --> 00:29:12,000 Speaker 1: and it's really the central question of the book, And 516 00:29:12,000 --> 00:29:14,520 Speaker 1: what we're trying to argue is that rather than worrying 517 00:29:14,520 --> 00:29:18,960 Speaker 1: about sort of the ethical implications of robots in fifty 518 00:29:19,040 --> 00:29:21,800 Speaker 1: years time, the issue most business people have to focus 519 00:29:21,800 --> 00:29:23,680 Speaker 1: on is what do you do about it now? What 520 00:29:23,720 --> 00:29:25,200 Speaker 1: do you do about it in the next few months, 521 00:29:25,280 --> 00:29:28,680 Speaker 1: the next few quarters. Because these technologies, which are incredibly 522 00:29:28,720 --> 00:29:32,280 Speaker 1: powerful and developing incredibly fast, are going to change all 523 00:29:32,320 --> 00:29:35,440 Speaker 1: aspects of society or aspects of business. So we're trying 524 00:29:35,480 --> 00:29:37,400 Speaker 1: to offer advice in the book to people about how 525 00:29:37,400 --> 00:29:40,200 Speaker 1: to make the trend your friend. Not worry about too 526 00:29:40,200 --> 00:29:42,680 Speaker 1: that the far off future. Worry about what you can 527 00:29:42,840 --> 00:29:45,880 Speaker 1: you can do today. And the first sort of fundamental 528 00:29:46,080 --> 00:29:48,320 Speaker 1: building block of that is accepting, as you say, Phim, 529 00:29:48,360 --> 00:29:51,680 Speaker 1: that this is real and you can use these technologies today. 530 00:29:51,800 --> 00:29:54,400 Speaker 1: You can adopt them in your financial services practice, you 531 00:29:54,400 --> 00:29:56,640 Speaker 1: can adopt them in your health care practice. You can 532 00:29:56,680 --> 00:30:00,120 Speaker 1: adopt them in the way you schedule meetings, and all 533 00:30:00,120 --> 00:30:02,040 Speaker 1: of these little kind of incremental things are going to 534 00:30:02,120 --> 00:30:05,400 Speaker 1: have profound implications in the next few years. So can 535 00:30:05,440 --> 00:30:09,480 Speaker 1: you point to a specific industry that is currently undergoing 536 00:30:09,960 --> 00:30:14,240 Speaker 1: a transformation on the heels of increased use of artificial 537 00:30:14,280 --> 00:30:18,920 Speaker 1: intelligence and computers that serves as a poster child for 538 00:30:19,080 --> 00:30:22,960 Speaker 1: what happens. Who loses jobs, who gains? Can you give 539 00:30:23,000 --> 00:30:25,320 Speaker 1: us an example. I think the financial services sector is 540 00:30:25,320 --> 00:30:27,840 Speaker 1: probably the most obvious one where this is happening very 541 00:30:27,920 --> 00:30:30,880 Speaker 1: very quickly. Out of the top ten hedge funds are 542 00:30:30,880 --> 00:30:34,240 Speaker 1: now basically albo traded. Um. You see what's happening in 543 00:30:34,280 --> 00:30:37,960 Speaker 1: the big the big banks who are replacing traders with 544 00:30:37,960 --> 00:30:40,760 Speaker 1: with people who can write code. Um. You hear what 545 00:30:40,800 --> 00:30:43,120 Speaker 1: people are saying about the back office in big banks, 546 00:30:43,160 --> 00:30:46,080 Speaker 1: how that's going to be sort of fundamentally rewired using 547 00:30:46,120 --> 00:30:48,760 Speaker 1: automation software in the next few years. So yeah, I 548 00:30:48,760 --> 00:30:51,040 Speaker 1: think you can look to New York, You can look 549 00:30:51,080 --> 00:30:55,080 Speaker 1: to this town Wall Street to is for an industry 550 00:30:55,080 --> 00:30:58,120 Speaker 1: that's really taking this seriously. They've seen the disruption and 551 00:30:58,160 --> 00:31:03,800 Speaker 1: other industries and media in in um in um entertainment 552 00:31:04,120 --> 00:31:06,680 Speaker 1: by software is that comes in and eats that industry, 553 00:31:06,880 --> 00:31:08,440 Speaker 1: and they don't want to let that happen to them. 554 00:31:08,640 --> 00:31:11,240 Speaker 1: So one of the claims in your book was that 555 00:31:11,360 --> 00:31:16,200 Speaker 1: an increased use of technology doesn't necessarily lead to fewer jobs. 556 00:31:16,560 --> 00:31:19,760 Speaker 1: And yet, certainly what we've seen with financial services the 557 00:31:19,920 --> 00:31:22,960 Speaker 1: poster child right now, is a loss of jobs. Fewer 558 00:31:23,000 --> 00:31:25,400 Speaker 1: people already did. This is all wrapped up in the 559 00:31:25,480 --> 00:31:27,360 Speaker 1: cost cutting that we're seeing at the big bank. So 560 00:31:27,400 --> 00:31:29,760 Speaker 1: can you square those two ideas? Yeah. Again, that's what 561 00:31:29,800 --> 00:31:32,080 Speaker 1: we try and get into in real detail in the book, 562 00:31:32,120 --> 00:31:35,600 Speaker 1: and our conclusion is that these sort of predictions about 563 00:31:35,600 --> 00:31:38,560 Speaker 1: a jobless future, about jobs going away in the next 564 00:31:38,600 --> 00:31:41,080 Speaker 1: few years, they're they're pretty wide of the mark. They're 565 00:31:41,080 --> 00:31:43,080 Speaker 1: not really they don't really stand up when you drill 566 00:31:43,120 --> 00:31:46,080 Speaker 1: into them. The reality is that the churn is going 567 00:31:46,120 --> 00:31:48,080 Speaker 1: to happen in the next few years. The work that 568 00:31:48,120 --> 00:31:49,640 Speaker 1: you do today is not the work you're going to 569 00:31:49,680 --> 00:31:51,480 Speaker 1: do in the future. But to imagine that all the 570 00:31:51,560 --> 00:31:54,120 Speaker 1: jobs are going to go away, that's unrealistic. And we 571 00:31:54,560 --> 00:31:56,760 Speaker 1: spend a lot of time in our book. Again, one 572 00:31:56,760 --> 00:31:58,840 Speaker 1: of the central messages of the book is that there's 573 00:31:58,840 --> 00:32:02,600 Speaker 1: so much innovation going on around technology. I mean around 574 00:32:02,600 --> 00:32:05,959 Speaker 1: the blockchain revolution. There's going to create new work for 575 00:32:05,960 --> 00:32:07,800 Speaker 1: people to do. It's not going to be the work 576 00:32:07,800 --> 00:32:10,920 Speaker 1: people do today or in the past. But if you can, 577 00:32:11,120 --> 00:32:14,000 Speaker 1: you know, if you can have that perspective from a 578 00:32:14,040 --> 00:32:18,640 Speaker 1: portfolio perspective within your organization, you know, redeploy people who 579 00:32:18,640 --> 00:32:22,040 Speaker 1: were doing X into why. That's how we think in 580 00:32:22,240 --> 00:32:26,120 Speaker 1: ten years time, UH net employment levels will be actually 581 00:32:26,200 --> 00:32:29,240 Speaker 1: higher than they are now. That's the part of the story. 582 00:32:29,320 --> 00:32:31,040 Speaker 1: A lot of people missing, we think at the moment. 583 00:32:31,720 --> 00:32:34,800 Speaker 1: Ben one example, and I want to get your reaction 584 00:32:34,880 --> 00:32:37,440 Speaker 1: to this that I recently was shown. It was a 585 00:32:37,480 --> 00:32:42,440 Speaker 1: demonstration of software whereby a camera was put into an 586 00:32:42,480 --> 00:32:46,600 Speaker 1: industrial kitchen and the goal was to make sure that 587 00:32:46,680 --> 00:32:50,920 Speaker 1: everybody in this industrial kitchen was wearing the appropriate coveralls, 588 00:32:52,320 --> 00:32:56,080 Speaker 1: gloves and hats, and the point being that it's a 589 00:32:56,160 --> 00:32:59,640 Speaker 1: very difficult thing to keep track of on a regular basis. 590 00:32:59,760 --> 00:33:03,560 Speaker 1: But the camera was loaded with software that would zoom 591 00:33:03,560 --> 00:33:07,520 Speaker 1: in on each of the members of the culinary team 592 00:33:07,920 --> 00:33:10,800 Speaker 1: and it would make sure it would track whether they 593 00:33:10,800 --> 00:33:12,880 Speaker 1: were wearing the right hats, whether they had the right 594 00:33:12,880 --> 00:33:15,480 Speaker 1: gloves on, and so on, and that at the end 595 00:33:15,480 --> 00:33:17,440 Speaker 1: of the day this could be reviewed or it could 596 00:33:17,480 --> 00:33:19,840 Speaker 1: even be automated to the point where if they didn't 597 00:33:20,480 --> 00:33:23,560 Speaker 1: follow these specific rules that would be noted. Is that 598 00:33:23,600 --> 00:33:26,040 Speaker 1: an example of the kind of thing that's going to happen. Yeah. 599 00:33:26,040 --> 00:33:27,600 Speaker 1: I mean, one again, one of the sort of core 600 00:33:27,640 --> 00:33:29,360 Speaker 1: trends that's been going on for a long time, but 601 00:33:29,400 --> 00:33:33,520 Speaker 1: it's now collided with these machine learning systems of intelligence 602 00:33:33,960 --> 00:33:37,320 Speaker 1: is the data that's being generated by IoT sensors. In 603 00:33:37,320 --> 00:33:40,640 Speaker 1: that kind of context, you're basically sensor enabling the whole 604 00:33:41,000 --> 00:33:44,480 Speaker 1: physical environment using you know, visual but also using other 605 00:33:44,480 --> 00:33:48,800 Speaker 1: types of sensor that's throwing off huge data, more data 606 00:33:48,840 --> 00:33:51,840 Speaker 1: than people can make sense of. So you need these 607 00:33:51,840 --> 00:33:54,320 Speaker 1: new machines to then be able to create sort of 608 00:33:54,320 --> 00:33:58,200 Speaker 1: business rules and business decisions and business results out of that. Now, 609 00:33:58,200 --> 00:34:01,880 Speaker 1: of course, you know the some are e raise raises 610 00:34:01,960 --> 00:34:04,840 Speaker 1: lots of privacy sort of kind I understand that, but 611 00:34:04,880 --> 00:34:06,760 Speaker 1: I'm just talking about in terms of safety issues. I mean, 612 00:34:06,840 --> 00:34:09,200 Speaker 1: for example, if you have someone handling any kind of 613 00:34:09,239 --> 00:34:12,200 Speaker 1: hazardous material, you know there are certain protocols that you 614 00:34:12,200 --> 00:34:15,400 Speaker 1: would have to follow. And I'm wondering what are the businesses. 615 00:34:15,400 --> 00:34:17,879 Speaker 1: Who are the companies that you know of that are 616 00:34:17,920 --> 00:34:21,520 Speaker 1: able to exploit this from a technological point, yeah, I 617 00:34:21,520 --> 00:34:23,439 Speaker 1: mean a lot of people are talking about the three 618 00:34:23,520 --> 00:34:26,840 Speaker 1: D s dull, dirty and dangerous work being replaced by 619 00:34:26,920 --> 00:34:29,839 Speaker 1: this type of automation software, and we certainly buy into that. 620 00:34:30,040 --> 00:34:32,520 Speaker 1: I mean, the mining industry is one where where this 621 00:34:32,600 --> 00:34:36,799 Speaker 1: is pretty advanced. Now, the big big minds in Australia, 622 00:34:36,800 --> 00:34:39,640 Speaker 1: around um in South Africa, they're using this kind of 623 00:34:39,640 --> 00:34:44,040 Speaker 1: technology already from an automation perspective, both in the vehicles 624 00:34:44,120 --> 00:34:46,279 Speaker 1: and in the safety context as well. So that's you know, 625 00:34:46,360 --> 00:34:48,680 Speaker 1: it's a it's a great example. Ben, you were saying 626 00:34:48,719 --> 00:34:52,799 Speaker 1: that the net jobs could potentially even increase due to 627 00:34:53,200 --> 00:34:56,520 Speaker 1: the adoption of artificial intelligence. But one very big concern 628 00:34:56,680 --> 00:34:58,560 Speaker 1: is that the people who are going to get the 629 00:34:58,680 --> 00:35:02,319 Speaker 1: jobs will be people with higher levels of education. That 630 00:35:02,400 --> 00:35:06,200 Speaker 1: this will only widen the divide between the wealthier and 631 00:35:06,280 --> 00:35:10,640 Speaker 1: more educated versus the poor and less educated, basically as 632 00:35:10,719 --> 00:35:14,200 Speaker 1: people who do the triple D jobs are unable to 633 00:35:14,239 --> 00:35:17,080 Speaker 1: find those jobs anymore. Well, again, it's a great question. 634 00:35:17,200 --> 00:35:19,200 Speaker 1: It's a central theme within the book that we try 635 00:35:19,239 --> 00:35:21,960 Speaker 1: to discuss, and again we think that people need to 636 00:35:21,960 --> 00:35:25,920 Speaker 1: take personal agency to recognize, you know, what's going on 637 00:35:26,680 --> 00:35:29,359 Speaker 1: and to to you know, figure out that they need 638 00:35:29,400 --> 00:35:33,640 Speaker 1: to sort of upscale themselves, retrain themselves, um, be able 639 00:35:33,680 --> 00:35:37,360 Speaker 1: to learn to use these new tools and understood. I 640 00:35:37,360 --> 00:35:39,719 Speaker 1: guess that there's there's a big concern though, that there 641 00:35:39,760 --> 00:35:43,600 Speaker 1: are entire swaths, entire communities of people who have kind 642 00:35:43,600 --> 00:35:45,440 Speaker 1: of been left behind. That's where a lot of the 643 00:35:45,480 --> 00:35:50,240 Speaker 1: anger has been driven. And how do those communities, uh, 644 00:35:50,360 --> 00:35:53,759 Speaker 1: you know, find the tools and the requirements. I mean, 645 00:35:53,760 --> 00:35:55,640 Speaker 1: this is sort of a big sort of tension. This 646 00:35:55,719 --> 00:35:57,920 Speaker 1: is a big policy issue. This is you know, this 647 00:35:58,000 --> 00:36:03,160 Speaker 1: is a government full issue. This is a local, um 648 00:36:03,160 --> 00:36:09,400 Speaker 1: political issue. It's a societal issue. Um. The root of it, 649 00:36:09,600 --> 00:36:13,360 Speaker 1: that's the only solution to it, fundamentally is is in training. 650 00:36:13,480 --> 00:36:17,800 Speaker 1: Is in STEM based education and and stem based education 651 00:36:17,880 --> 00:36:20,160 Speaker 1: that people from an arts background or from a you know, 652 00:36:20,400 --> 00:36:23,680 Speaker 1: a non technical background can use those tools to be 653 00:36:23,800 --> 00:36:27,240 Speaker 1: relevant in the future. I mean, our book is about 654 00:36:27,400 --> 00:36:31,640 Speaker 1: wealth creation rather than wealth distribution. That that that's a 655 00:36:31,680 --> 00:36:34,440 Speaker 1: broader issue in a way. It's a very real issue. 656 00:36:34,480 --> 00:36:37,000 Speaker 1: And obviously, you know, the future of work is being 657 00:36:37,040 --> 00:36:39,600 Speaker 1: dominated by Mr Trump and Mr Robot. They're the two 658 00:36:39,680 --> 00:36:41,760 Speaker 1: kind of central characters in this story at the moment, 659 00:36:41,840 --> 00:36:45,279 Speaker 1: just us quickly. If if I had the time, where 660 00:36:45,320 --> 00:36:48,880 Speaker 1: would you send me physically to go and see this 661 00:36:49,000 --> 00:36:52,239 Speaker 1: kind of future in action right now? Well on the 662 00:36:52,320 --> 00:36:54,520 Speaker 1: robotic side, I mean, look at the just look at 663 00:36:54,560 --> 00:36:57,680 Speaker 1: the Kiva videos, the Amazon Warehouse videos. I mean, if 664 00:36:57,680 --> 00:36:59,399 Speaker 1: that doesn't blow your mind, I don't know what will. 665 00:36:59,719 --> 00:37:02,800 Speaker 1: On a more sort of tactical, very sort of points solution, 666 00:37:03,239 --> 00:37:05,000 Speaker 1: There's a great company here in New York called x 667 00:37:05,040 --> 00:37:08,600 Speaker 1: dot Ai. Check them out. They have software that automates 668 00:37:08,680 --> 00:37:11,279 Speaker 1: meeting scheduling. I don't when you guys have heard of that. 669 00:37:11,320 --> 00:37:13,200 Speaker 1: I mean you think about how how much time people 670 00:37:13,239 --> 00:37:17,560 Speaker 1: spend scheduling meetings. Uh, time is money. You can automate 671 00:37:17,600 --> 00:37:20,200 Speaker 1: that all the way. That's a great little example. Thank 672 00:37:20,239 --> 00:37:22,680 Speaker 1: you so much for joining us. Bennett Pring of Cognizance, 673 00:37:23,120 --> 00:37:25,280 Speaker 1: an I T futurist and co leader of the Future 674 00:37:25,400 --> 00:37:28,759 Speaker 1: were of Work Center, also the co author of a 675 00:37:28,840 --> 00:37:44,520 Speaker 1: new book, What to Do When Machines Do Everything All Right. 676 00:37:44,760 --> 00:37:48,960 Speaker 1: President Donald Trump is said to be angered by learning 677 00:37:49,120 --> 00:37:53,040 Speaker 1: that the change to certain tax breaks for people in 678 00:37:53,120 --> 00:37:57,080 Speaker 1: high tax states would hurt middle class income taxpayers, and 679 00:37:57,120 --> 00:37:59,520 Speaker 1: here to tell us more. As Kevin Cirelli covers, the 680 00:37:59,560 --> 00:38:01,960 Speaker 1: President the White House and all things politics and joining 681 00:38:02,000 --> 00:38:03,799 Speaker 1: us from Washington, d C. And of course you can 682 00:38:03,840 --> 00:38:08,280 Speaker 1: follow Kevin on Twitter at Kevin Surreally. Alright, keV SURRELLI, 683 00:38:08,680 --> 00:38:12,840 Speaker 1: what's the I thought? Did the President not know previously 684 00:38:12,880 --> 00:38:16,359 Speaker 1: that this would be, uh, you know, an obstacle for 685 00:38:16,400 --> 00:38:20,600 Speaker 1: people in the middle class who take those deductions? Hey? Then, 686 00:38:20,719 --> 00:38:23,719 Speaker 1: so I spoke with some sources yesterday who told me 687 00:38:23,800 --> 00:38:28,400 Speaker 1: that the President was frustrated when reports came out regarding 688 00:38:28,440 --> 00:38:32,560 Speaker 1: these state and local deduction that, of course at tax 689 00:38:32,719 --> 00:38:35,359 Speaker 1: that salt as a commonly called inside the Beltway. Now 690 00:38:35,719 --> 00:38:37,960 Speaker 1: supporters of it are saying that it would be a 691 00:38:38,000 --> 00:38:41,600 Speaker 1: source of one point three trillion dollars in revenue, a 692 00:38:41,680 --> 00:38:43,960 Speaker 1: huge chunk of the six trillion that the tax plan 693 00:38:44,040 --> 00:38:46,640 Speaker 1: will cost. But I have to be really honest here. 694 00:38:46,680 --> 00:38:49,880 Speaker 1: Many Republicans on Capitol Hill are divided on this, and 695 00:38:49,920 --> 00:38:52,880 Speaker 1: the President was frustrated when he realized that some reports 696 00:38:52,920 --> 00:38:56,320 Speaker 1: suggest that taxes would actually be raised on the middle 697 00:38:56,360 --> 00:39:00,520 Speaker 1: class should this plan go through. We're told if the 698 00:39:00,520 --> 00:39:04,279 Speaker 1: President is making tweaks to this plan sometimes over the 699 00:39:04,280 --> 00:39:07,560 Speaker 1: next couple of weeks ago announced the later name Kevin. 700 00:39:07,600 --> 00:39:11,040 Speaker 1: I want to bring to you some headlines. Gary Cone, 701 00:39:11,280 --> 00:39:15,640 Speaker 1: the chief economic advisor to President Trump, just told reporters 702 00:39:15,680 --> 00:39:19,160 Speaker 1: that President Trump is not reconsidering state his state and 703 00:39:19,280 --> 00:39:24,040 Speaker 1: local tax position. Um. And he said this two reporters. 704 00:39:24,400 --> 00:39:26,680 Speaker 1: I find this compelling. It's sort of this push and 705 00:39:26,719 --> 00:39:29,799 Speaker 1: pull that we're getting, which is that perhaps there will 706 00:39:29,840 --> 00:39:33,080 Speaker 1: be some kind of rewrite around this to uh, among 707 00:39:33,120 --> 00:39:38,080 Speaker 1: other things, short support among New York Republicans right uh, 708 00:39:38,120 --> 00:39:41,600 Speaker 1: and also to alleviate any burden to middle class voters. 709 00:39:41,640 --> 00:39:45,680 Speaker 1: This seems to suggest maybe not what's your take on this, Well, 710 00:39:45,960 --> 00:39:49,040 Speaker 1: the votes right now, there's a huge, large contingency of 711 00:39:49,080 --> 00:39:52,080 Speaker 1: folks in the House of Representatives, being led by Representatives 712 00:39:52,280 --> 00:39:56,920 Speaker 1: Peter King, who are really um against UH this, and 713 00:39:57,040 --> 00:39:59,719 Speaker 1: so any type of tweaks that are going to be 714 00:39:59,800 --> 00:40:02,319 Speaker 1: made UH would have to be made in order to 715 00:40:02,360 --> 00:40:06,000 Speaker 1: win some of their support because right now, Garry Cone, 716 00:40:06,360 --> 00:40:08,879 Speaker 1: and I'm not really sure he's that influential in Capitol Hill. 717 00:40:08,920 --> 00:40:11,200 Speaker 1: Most people expect him to be out by the end 718 00:40:11,239 --> 00:40:13,400 Speaker 1: of the year if you ain't even have the president's 719 00:40:13,400 --> 00:40:17,160 Speaker 1: fare anymore. UM. But you know, Gary Cone really just 720 00:40:17,200 --> 00:40:20,640 Speaker 1: hasn't been able to form a winning coalition in order 721 00:40:20,680 --> 00:40:24,839 Speaker 1: to get this across the finish line. Um, So it'll 722 00:40:24,880 --> 00:40:26,520 Speaker 1: be interesting to see whether or not he has any 723 00:40:26,520 --> 00:40:29,120 Speaker 1: more influence with a lot of these conservatives up on 724 00:40:29,120 --> 00:40:32,320 Speaker 1: Capital Will quite frankly, have never really spoken to Garry 725 00:40:32,360 --> 00:40:36,600 Speaker 1: Cone to begin with. Kevin, is the plan still supposed 726 00:40:36,640 --> 00:40:43,000 Speaker 1: to be revenue neutral? Well, that's another sticking more in them. Uh. 727 00:40:43,040 --> 00:40:45,360 Speaker 1: And there are some Republicans who wanted to be and 728 00:40:45,440 --> 00:40:48,480 Speaker 1: others you don't. Uh. And that's really drove a lot 729 00:40:48,520 --> 00:40:54,360 Speaker 1: of the separation before uh, behind the uh, behind the scenes, 730 00:40:54,440 --> 00:40:56,480 Speaker 1: because a lot of folks are concerned about the deficit, 731 00:40:56,520 --> 00:40:59,239 Speaker 1: people like Senator Bob Corker, who we all know is 732 00:40:59,280 --> 00:41:02,840 Speaker 1: in in tangled in a tip for tat with with 733 00:41:02,960 --> 00:41:05,920 Speaker 1: folks earlier today. So I'm sorry with the president earlier 734 00:41:05,960 --> 00:41:09,520 Speaker 1: this week. So right now, if you were a betting 735 00:41:09,600 --> 00:41:12,600 Speaker 1: kind of guy, was your expectation that there will be 736 00:41:12,719 --> 00:41:16,440 Speaker 1: some formal bill that will at least be presented in 737 00:41:16,600 --> 00:41:20,560 Speaker 1: Congress within the next few weeks. Well, the tax rating 738 00:41:20,560 --> 00:41:22,880 Speaker 1: committees are hard at work on this. I think the 739 00:41:22,960 --> 00:41:25,759 Speaker 1: dynamic between conservatives and the Freedom Caucus, as well as 740 00:41:25,800 --> 00:41:28,960 Speaker 1: other conservatives in the Senate their relationship with the Big sixes. 741 00:41:29,000 --> 00:41:32,200 Speaker 1: They're known as that's really where all of the framework 742 00:41:32,280 --> 00:41:34,840 Speaker 1: is being hammered out, um, and there's a lot of 743 00:41:34,920 --> 00:41:39,040 Speaker 1: tension there. I mean chronicled this policies, ideological conservative fits 744 00:41:39,120 --> 00:41:41,279 Speaker 1: over several years now and there's still alive as well. 745 00:41:41,320 --> 00:41:43,719 Speaker 1: We just all it exists on healthcare. I think we're 746 00:41:43,719 --> 00:41:46,480 Speaker 1: gonna watch it again on fold the tax reform, Has 747 00:41:46,520 --> 00:41:50,719 Speaker 1: there been any more detail offered than those nine pages? Now? 748 00:41:50,920 --> 00:41:53,640 Speaker 1: There's literally been no details. And that's really what's been 749 00:41:53,680 --> 00:41:56,800 Speaker 1: frustrating for a lot of folks on Capitol Hills that 750 00:41:56,840 --> 00:41:59,480 Speaker 1: typically tax reform is something that has talked about a 751 00:41:59,640 --> 00:42:02,120 Speaker 1: nod him, and so the idea that this would not 752 00:42:03,040 --> 00:42:05,480 Speaker 1: be discussed has really mean a lot of people frustrated 753 00:42:05,520 --> 00:42:07,799 Speaker 1: because right now they're just being asked to come out 754 00:42:07,840 --> 00:42:11,160 Speaker 1: against you know, taxes, lowering tax cuts essentially, which no 755 00:42:11,239 --> 00:42:13,840 Speaker 1: Republican will come out and say, but they're again, but 756 00:42:13,920 --> 00:42:16,480 Speaker 1: in terms of how to achieve those goals, the details 757 00:42:16,520 --> 00:42:20,600 Speaker 1: us simply aren't there, no matter what Jerry Tone seemingly 758 00:42:20,600 --> 00:42:26,120 Speaker 1: wants to suggest. Well, kevinnes Well, he just called in 759 00:42:26,160 --> 00:42:28,960 Speaker 1: that he wasn't offended. I do want to just wonder, though, 760 00:42:29,040 --> 00:42:31,960 Speaker 1: is there anyone talking about infrastructure spending at this point, 761 00:42:32,000 --> 00:42:34,240 Speaker 1: because we also heard a lot about that, and there's 762 00:42:34,360 --> 00:42:37,360 Speaker 1: nothing that I can see that points to anything on 763 00:42:37,400 --> 00:42:41,319 Speaker 1: that real quick, no nothing, nothing, No new developments on infrastructure. 764 00:42:41,400 --> 00:42:46,800 Speaker 1: Really tragic conversation on tax reform um and foreign policy. 765 00:42:47,239 --> 00:42:50,000 Speaker 1: But yeah, there has lived virtually been silent on the infrastructure. 766 00:42:50,000 --> 00:42:52,319 Speaker 1: From Kevin's really, thank you so much for joining us, 767 00:42:52,320 --> 00:42:55,520 Speaker 1: and thank you. We'll be hearing more from you as 768 00:42:55,680 --> 00:42:59,200 Speaker 1: this whole tax reform plan goes forward. Kevin's really as 769 00:42:59,239 --> 00:43:05,040 Speaker 1: a White House course on it for Bloomberg. Thanks for 770 00:43:05,120 --> 00:43:07,759 Speaker 1: listening to the Bloomberg P and L podcast. You can 771 00:43:07,800 --> 00:43:11,640 Speaker 1: subscribe and listen to interviews at Apple Podcasts, SoundCloud, or 772 00:43:11,680 --> 00:43:15,160 Speaker 1: whatever podcast platform you prefer. I'm pim Fox. I'm on 773 00:43:15,200 --> 00:43:19,040 Speaker 1: Twitter at pim Fox. I'm on Twitter at Lisa Abramo. 774 00:43:19,160 --> 00:43:21,759 Speaker 1: It's one before the podcast. You can always catch us 775 00:43:21,800 --> 00:43:23,360 Speaker 1: worldwide on Bloomberg Radio.