1 00:00:00,800 --> 00:00:04,040 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney. Alongside 2 00:00:04,040 --> 00:00:06,920 Speaker 1: my co host Matt Miller. Every business day we bring 3 00:00:06,960 --> 00:00:11,520 Speaker 1: you interviews from CEOs, market pros, and Bloomberg experts, along 4 00:00:11,560 --> 00:00:15,560 Speaker 1: with essential market moving news. Find the Bloomberg Markets Podcast 5 00:00:15,600 --> 00:00:18,479 Speaker 1: on Apple Podcasts or wherever you listen to podcasts, and 6 00:00:18,480 --> 00:00:22,720 Speaker 1: at Bloomberg dot com slash podcast. We have been hearing 7 00:00:22,840 --> 00:00:27,680 Speaker 1: a lot about helping out businesses, small businesses, about helping 8 00:00:27,720 --> 00:00:32,480 Speaker 1: out marginalized businesses, women and minorities over the past couple 9 00:00:32,479 --> 00:00:37,600 Speaker 1: of days from the big gigantic bank CEOs on Capitol Hill. UM. 10 00:00:37,640 --> 00:00:42,879 Speaker 1: But they typically come out with surprisingly small numbers. Really, UM, 11 00:00:43,440 --> 00:00:45,720 Speaker 1: I guess Goldman Sachs is a really is a real exception. 12 00:00:45,760 --> 00:00:48,760 Speaker 1: They've been doing this ten thousand small business program for 13 00:00:48,760 --> 00:00:51,960 Speaker 1: our decade now. But Chris Saklakis joins us right now. 14 00:00:52,000 --> 00:00:56,600 Speaker 1: He's the CEO of a global nonprofit called Kiva, which 15 00:00:56,720 --> 00:01:02,400 Speaker 1: is really a micro financing business that aims at UM 16 00:01:02,640 --> 00:01:10,360 Speaker 1: marginalized business owners UM to raise and disperse crowdfunded loans. UM. Chris, 17 00:01:10,400 --> 00:01:12,399 Speaker 1: welcome to the program. Thanks for joining us. What a 18 00:01:12,480 --> 00:01:14,679 Speaker 1: time to be in this business. How did you get 19 00:01:14,680 --> 00:01:18,000 Speaker 1: into this because I know you came from the famous 20 00:01:18,040 --> 00:01:24,560 Speaker 1: online wine platform Vivino. Yeah. So I've been at Kiva 21 00:01:24,680 --> 00:01:28,720 Speaker 1: precisely one month in two days, so I'm very to it. 22 00:01:28,800 --> 00:01:34,560 Speaker 1: But yeah, exactly so. Uh what I what I decided 23 00:01:34,600 --> 00:01:37,520 Speaker 1: when I left Vino was that I really liked technology 24 00:01:37,600 --> 00:01:40,479 Speaker 1: and online marketplaces, but I wanted I wanted to put 25 00:01:40,520 --> 00:01:44,120 Speaker 1: my expertise to better use, and I wanted to I 26 00:01:44,160 --> 00:01:46,000 Speaker 1: wanted to fulfill two things. One was to be a 27 00:01:46,040 --> 00:01:49,120 Speaker 1: positive role model for my sons, who are both teenagers, 28 00:01:49,720 --> 00:01:52,160 Speaker 1: and to work in the organization that actually has a 29 00:01:52,160 --> 00:01:56,040 Speaker 1: positive impact on people's lives. And so when Civa came along, 30 00:01:56,720 --> 00:01:59,360 Speaker 1: it was a perfect combination of those two things. We use. 31 00:02:00,040 --> 00:02:04,080 Speaker 1: We Kiva used technology through an online marketplace kiva dot org, 32 00:02:04,520 --> 00:02:08,880 Speaker 1: where lenders can come in UH and find information on 33 00:02:09,000 --> 00:02:12,080 Speaker 1: borrowers in the United States and around the world and 34 00:02:12,200 --> 00:02:15,400 Speaker 1: decide on how much they want to give as a loan, 35 00:02:15,520 --> 00:02:17,520 Speaker 1: And they can give as little as twenty five dollars 36 00:02:18,040 --> 00:02:22,160 Speaker 1: UH to fund a loan for someone in Cambodia who's 37 00:02:22,240 --> 00:02:25,520 Speaker 1: trying to buy seed for a farm, or someone in 38 00:02:25,520 --> 00:02:30,960 Speaker 1: the United States who's trying to establish a restaurant. So Chris, 39 00:02:31,040 --> 00:02:34,840 Speaker 1: You know, this pandemic obviously has been hugely disruptive, disruptive 40 00:02:34,880 --> 00:02:39,440 Speaker 1: to the entire planet, to the economics of the entire planet, 41 00:02:39,480 --> 00:02:44,240 Speaker 1: and particularly on small businesses, minority businesses, things like that. 42 00:02:44,320 --> 00:02:48,440 Speaker 1: So as you think about your company, your effort at Kiva, 43 00:02:48,480 --> 00:02:51,679 Speaker 1: how do you expect your business to change maybe going 44 00:02:51,760 --> 00:02:53,920 Speaker 1: forward as you probably interact with a lot of these 45 00:02:53,960 --> 00:02:58,920 Speaker 1: small businesses that have been impacted, Well, a lot of 46 00:02:58,919 --> 00:03:01,120 Speaker 1: what we're doing is continue knewing what we've done in 47 00:03:01,160 --> 00:03:04,800 Speaker 1: the past. We we made some big shifts during COVID 48 00:03:04,880 --> 00:03:07,760 Speaker 1: last year, but over the course of the fifteen year 49 00:03:07,919 --> 00:03:11,560 Speaker 1: history of Kiva, we have funded over one point five 50 00:03:11,680 --> 00:03:16,280 Speaker 1: billion dollars worth of loans to to nearly four million 51 00:03:16,320 --> 00:03:20,120 Speaker 1: people in seventy seven countries, and roughly ten percent of 52 00:03:20,160 --> 00:03:22,760 Speaker 1: what we've done over the last few years has gone 53 00:03:22,760 --> 00:03:26,440 Speaker 1: to businesses in the United States. The people we target 54 00:03:26,960 --> 00:03:30,680 Speaker 1: are people who traditionally aren't able to get loans. We 55 00:03:30,760 --> 00:03:33,040 Speaker 1: call them the unbanked, the people who don't have access 56 00:03:33,040 --> 00:03:36,600 Speaker 1: to financial services. And so as part of what we 57 00:03:36,640 --> 00:03:40,680 Speaker 1: did with COVID, we were available, we were able to 58 00:03:40,800 --> 00:03:44,080 Speaker 1: provide loans to people who would get rejected from other 59 00:03:44,120 --> 00:03:47,360 Speaker 1: banks people who couldn't get p PP loans, and so 60 00:03:47,680 --> 00:03:52,040 Speaker 1: very often those are minorities of black and Latin X 61 00:03:52,120 --> 00:03:56,360 Speaker 1: business owners women. UM. In fact, the vast majority of 62 00:03:56,400 --> 00:03:59,240 Speaker 1: the loans we do in the United States, UM are 63 00:03:59,360 --> 00:04:03,840 Speaker 1: too are two women and two people of color and immigrants. Right. 64 00:04:03,840 --> 00:04:06,240 Speaker 1: I mean, how many times have I been in a 65 00:04:06,320 --> 00:04:08,760 Speaker 1: cab in New York City only to find out that 66 00:04:08,800 --> 00:04:12,400 Speaker 1: my driver is actually was a doctor when he was 67 00:04:12,400 --> 00:04:16,000 Speaker 1: working in Bulgaria or something crazy like that, UM, and 68 00:04:16,080 --> 00:04:18,800 Speaker 1: just doesn't have any credit or any access to the 69 00:04:18,839 --> 00:04:23,080 Speaker 1: financial system when he gets to the US. Yeah, that's right. 70 00:04:23,120 --> 00:04:25,240 Speaker 1: So we we fund a lot of immigrants. Most of 71 00:04:25,279 --> 00:04:28,280 Speaker 1: our funding goes to entrepreneurs, people who are starting businesses 72 00:04:28,400 --> 00:04:31,320 Speaker 1: or who have businesses as who want to continue. And 73 00:04:31,440 --> 00:04:33,640 Speaker 1: one of the reasons Kiva was so resonant for me 74 00:04:33,760 --> 00:04:36,720 Speaker 1: is because my parents are immigrants. They immigrated from Greece. 75 00:04:37,080 --> 00:04:39,960 Speaker 1: When my dad came here, he really had nothing. He 76 00:04:40,040 --> 00:04:42,960 Speaker 1: started as a laborer in the steel mill. He eventually 77 00:04:43,000 --> 00:04:48,240 Speaker 1: became an apprentice with an electrician, became qualified electricians, started 78 00:04:48,279 --> 00:04:51,960 Speaker 1: his own electrical contracting business, and then started real listening 79 00:04:52,000 --> 00:04:54,640 Speaker 1: to the development. But he couldn't have started that business 80 00:04:54,760 --> 00:04:57,400 Speaker 1: or done his real estate development without access to capital, 81 00:04:57,400 --> 00:05:00,320 Speaker 1: without a loan. And so the loans that you give 82 00:05:00,400 --> 00:05:04,000 Speaker 1: to small businesses with Kiva resonate with me because they 83 00:05:04,000 --> 00:05:06,880 Speaker 1: go to entrepreneurs just like my dad. Chris gives a 84 00:05:06,880 --> 00:05:09,400 Speaker 1: sense just briefly about thirty seconds, kind of the financial 85 00:05:09,440 --> 00:05:13,119 Speaker 1: returns for the folks that do crowds fund these loans. 86 00:05:13,120 --> 00:05:16,080 Speaker 1: How's how's it worked out. Yeah, So if you're a 87 00:05:16,160 --> 00:05:19,880 Speaker 1: lender on Kiva, it's a zero interest, zero percent interest loan, 88 00:05:20,400 --> 00:05:24,880 Speaker 1: but there's the repayment rate historically has been so if 89 00:05:24,880 --> 00:05:27,360 Speaker 1: you put in a hundred dollars today, over the course 90 00:05:27,400 --> 00:05:29,800 Speaker 1: of the next two years, you'll get ninety six dollars back, 91 00:05:30,080 --> 00:05:32,760 Speaker 1: and then you can re lend that money if you want. 92 00:05:32,960 --> 00:05:37,320 Speaker 1: So relative to a donation, Uh, this is this is 93 00:05:37,360 --> 00:05:39,080 Speaker 1: a loan. The money comes back and then you can 94 00:05:39,120 --> 00:05:41,440 Speaker 1: re lend it. If you keep the money in the 95 00:05:41,520 --> 00:05:43,760 Speaker 1: Kiva system for a period of four or five years, 96 00:05:43,760 --> 00:05:46,799 Speaker 1: that hundred dollars could result in five hundred, six hundred 97 00:05:46,839 --> 00:05:50,640 Speaker 1: dollars worth of loans back to people who needed That's 98 00:05:50,760 --> 00:05:52,440 Speaker 1: very ingenious. I was trying to think about how the 99 00:05:52,520 --> 00:05:54,719 Speaker 1: economics of that work, and you should do a reverse 100 00:05:54,760 --> 00:05:57,120 Speaker 1: repo facility. You know, the FED got I think four 101 00:05:57,480 --> 00:06:01,120 Speaker 1: eight six billion dollars at zero present yesterday from like 102 00:06:01,240 --> 00:06:05,520 Speaker 1: fifty banks. Um. No, it's a fascinating business, and yours 103 00:06:05,640 --> 00:06:08,320 Speaker 1: is I think a really interesting story. Chris. So, it's great, 104 00:06:08,880 --> 00:06:12,200 Speaker 1: um to have smart people like you doing this kind 105 00:06:12,240 --> 00:06:15,440 Speaker 1: of good work to help. You know, other people out 106 00:06:15,440 --> 00:06:16,920 Speaker 1: there just want to get a lug up, just need 107 00:06:16,960 --> 00:06:20,359 Speaker 1: to get into the system. Chris Sokolochus, there is the 108 00:06:20,480 --> 00:06:28,480 Speaker 1: CEO of Kiva. This is Bloomberg. Are bringing Laurence sour 109 00:06:28,640 --> 00:06:31,919 Speaker 1: right now, Associate Professor of Emergency Medicine at Johns Hopkins 110 00:06:32,000 --> 00:06:36,120 Speaker 1: School of Medicine, And Lauren, I got a question. I've 111 00:06:36,160 --> 00:06:40,360 Speaker 1: always thought about this, and I think because of the pandemic, 112 00:06:40,520 --> 00:06:42,640 Speaker 1: I finally know the answer, but I want to hear 113 00:06:42,640 --> 00:06:45,880 Speaker 1: it from you. You know, there've been anti vaxers around forever, 114 00:06:46,520 --> 00:06:49,360 Speaker 1: and I always thought, like, who cares if their kids 115 00:06:49,560 --> 00:06:53,080 Speaker 1: aren't vaccinated? As long as my kids are. Now, the 116 00:06:53,120 --> 00:06:56,000 Speaker 1: same question is coming up in terms of COVID, like 117 00:06:56,520 --> 00:06:59,880 Speaker 1: if of the public doesn't get vaccinated, does it matter 118 00:07:00,000 --> 00:07:04,000 Speaker 1: to the six of us that does. Yeah, I think 119 00:07:04,520 --> 00:07:06,479 Speaker 1: I definitely think it matters because I think we have 120 00:07:06,560 --> 00:07:10,440 Speaker 1: this sort of social contract and depending on the thresholds 121 00:07:10,440 --> 00:07:13,480 Speaker 1: that people that people are looking at, it changes how 122 00:07:13,520 --> 00:07:15,320 Speaker 1: safe it is to reopen and be in public, And 123 00:07:15,440 --> 00:07:17,520 Speaker 1: especially with the disease like this, where we don't actually 124 00:07:17,560 --> 00:07:20,080 Speaker 1: know what reinfection is going to look like and what 125 00:07:20,160 --> 00:07:24,360 Speaker 1: the potential future threats are UM, the more people getting 126 00:07:24,400 --> 00:07:27,480 Speaker 1: vaccinated can only be better. When you think about people 127 00:07:27,560 --> 00:07:30,800 Speaker 1: who are sort of anti vacts and UM, especially in 128 00:07:30,840 --> 00:07:34,679 Speaker 1: the pediatric population, they're making decisions for kids who don't 129 00:07:34,720 --> 00:07:37,760 Speaker 1: have sort of a say in that process, and on 130 00:07:37,840 --> 00:07:42,640 Speaker 1: top of that before they were born. Yeah, that's true. UM, 131 00:07:42,680 --> 00:07:45,640 Speaker 1: but there are kids who and kids and teachers and 132 00:07:45,760 --> 00:07:48,360 Speaker 1: parents and family members of those kids who are not 133 00:07:48,440 --> 00:07:51,520 Speaker 1: vaccinated who can't get vaccinated for various reasons. They may 134 00:07:51,560 --> 00:07:54,000 Speaker 1: have a vaccine allergy, or they may have an immune 135 00:07:54,040 --> 00:07:57,880 Speaker 1: compromise situation or UM. You know, there's several reasons why 136 00:07:57,920 --> 00:08:00,200 Speaker 1: people may not be able to get vaccinated, and so 137 00:08:00,240 --> 00:08:02,040 Speaker 1: then you're putting those people at risk. So that's a 138 00:08:02,040 --> 00:08:04,560 Speaker 1: good point. In fact, I read a story I think 139 00:08:04,680 --> 00:08:07,560 Speaker 1: maybe it was in the Times about UM. For example, 140 00:08:07,640 --> 00:08:13,880 Speaker 1: people who have received organ transplants UM aren't really aren't 141 00:08:13,880 --> 00:08:15,920 Speaker 1: able to be vaccinated or the vaccine doesn't work as 142 00:08:15,920 --> 00:08:18,480 Speaker 1: well for them. My theory had been this, Lauren, I thought, 143 00:08:18,480 --> 00:08:20,240 Speaker 1: you know, what do I care if somebody in the 144 00:08:20,280 --> 00:08:23,400 Speaker 1: bar isn't vaccinated and has COVID. As long as I am, 145 00:08:23,600 --> 00:08:26,080 Speaker 1: I'm not going to get it. But what I was 146 00:08:26,120 --> 00:08:28,640 Speaker 1: thinking is maybe if too much, if too many people 147 00:08:28,640 --> 00:08:30,760 Speaker 1: don't get vaccinated, then the virus lives on and it 148 00:08:30,840 --> 00:08:33,920 Speaker 1: you takes into something even crazier, and then it overtakes 149 00:08:33,920 --> 00:08:37,680 Speaker 1: my vaccine power. Yeah, I think that's always a risk. 150 00:08:37,720 --> 00:08:40,480 Speaker 1: I mean, mutations, variants are are going to continue to 151 00:08:40,520 --> 00:08:44,520 Speaker 1: be a risk and um, and you could have a 152 00:08:44,600 --> 00:08:47,559 Speaker 1: situation like we don't know about sterilizing immunity as as 153 00:08:47,600 --> 00:08:50,640 Speaker 1: much as we want to yet, right, So you could 154 00:08:50,640 --> 00:08:52,559 Speaker 1: have a situation where you're on the tail end of 155 00:08:52,600 --> 00:08:55,319 Speaker 1: meeting another vaccination, you get a low grade infection from 156 00:08:55,360 --> 00:08:59,040 Speaker 1: that person and and it does overtake your vaccine, or 157 00:08:59,240 --> 00:09:02,240 Speaker 1: you take very low grade infection that you may not 158 00:09:02,280 --> 00:09:04,959 Speaker 1: even know that you have to someone else. And so 159 00:09:05,000 --> 00:09:08,800 Speaker 1: there's there's situations where this chain of events happens, putting 160 00:09:08,840 --> 00:09:11,520 Speaker 1: people who have no choice in the matter at risk. 161 00:09:11,760 --> 00:09:14,760 Speaker 1: And that's where we want to really target, UM, bringing 162 00:09:14,800 --> 00:09:17,760 Speaker 1: people who are not interested currently to getting vaccinated to 163 00:09:17,800 --> 00:09:20,720 Speaker 1: the table and say what's stopping you, what's holding you back? 164 00:09:20,800 --> 00:09:23,600 Speaker 1: What can we do to support bringing you to the 165 00:09:23,679 --> 00:09:27,680 Speaker 1: vaccine table. How about something that's maybe even I think simpler, 166 00:09:27,720 --> 00:09:31,160 Speaker 1: which is simply masking Here in New York, so I 167 00:09:31,160 --> 00:09:33,040 Speaker 1: guess we're we've had a week or two of you 168 00:09:33,040 --> 00:09:36,160 Speaker 1: don't have to mask indoor? Uh In New Jersey. As 169 00:09:36,160 --> 00:09:39,040 Speaker 1: of today where I live, you don't have to mask 170 00:09:39,120 --> 00:09:41,120 Speaker 1: indoor and you can actually stand at a bar and 171 00:09:41,160 --> 00:09:44,280 Speaker 1: have a drink. I think, God forbid. What are your thoughts, 172 00:09:44,679 --> 00:09:49,040 Speaker 1: Lauren about masking indoors? Let's just let' let's assume the 173 00:09:49,040 --> 00:09:51,680 Speaker 1: outdoors is you know, that's pretty clear, clear cut. But 174 00:09:51,679 --> 00:09:54,600 Speaker 1: what do you think about indoors? Yeah? For me, I 175 00:09:54,640 --> 00:09:58,800 Speaker 1: think the risk is still high enough. My personal opinion 176 00:09:58,880 --> 00:10:02,440 Speaker 1: is that I would so mask indoors wherever possible. UM. 177 00:10:02,640 --> 00:10:06,800 Speaker 1: I think in general, we've relaxed these indoor mask mandates 178 00:10:06,840 --> 00:10:09,960 Speaker 1: too soon. We're getting really close, and I think everyone's 179 00:10:10,000 --> 00:10:12,280 Speaker 1: just so excited to you know, quote unquote get back 180 00:10:12,280 --> 00:10:14,959 Speaker 1: to normal that they're willing to let their guard down. 181 00:10:15,000 --> 00:10:17,000 Speaker 1: And I think that is where we get into a 182 00:10:17,040 --> 00:10:20,400 Speaker 1: little bit of a high risk situation, and and masking 183 00:10:20,559 --> 00:10:24,240 Speaker 1: is not you know, it's it's not that hard to do, 184 00:10:24,559 --> 00:10:27,240 Speaker 1: and it is a simple step that we can take 185 00:10:27,280 --> 00:10:30,280 Speaker 1: to protect ourselves and protect those other people that we 186 00:10:30,280 --> 00:10:32,640 Speaker 1: were just talking about, you know. And so for me, 187 00:10:32,720 --> 00:10:36,040 Speaker 1: I would like to see the mask the masking continue indoors, 188 00:10:36,160 --> 00:10:39,040 Speaker 1: especially in those more crowded locations, until we get to 189 00:10:39,080 --> 00:10:44,960 Speaker 1: those higher vaccinated levels. You know. Um, we're finally starting 190 00:10:44,960 --> 00:10:48,400 Speaker 1: to look at the most at the simplest possible explanation 191 00:10:48,480 --> 00:10:51,880 Speaker 1: for how this virus um got started at a market 192 00:10:51,880 --> 00:10:55,679 Speaker 1: in Wuhan, down the street from a coronavirus lab in Wuhan. 193 00:10:56,280 --> 00:11:00,840 Speaker 1: But even if the quote unquote conspiracy area's proved true, 194 00:11:01,080 --> 00:11:03,640 Speaker 1: does it really matter where it came from to the 195 00:11:03,679 --> 00:11:09,960 Speaker 1: medical field? Do you need those details? No? I mean, 196 00:11:10,040 --> 00:11:12,680 Speaker 1: I think I think it matters to some people, and 197 00:11:12,720 --> 00:11:16,200 Speaker 1: I think there's always an interest in exploring origins, But 198 00:11:16,320 --> 00:11:18,160 Speaker 1: I don't think we're going to get there with some 199 00:11:18,360 --> 00:11:22,840 Speaker 1: targeted um exploration of whether or not this is a 200 00:11:22,880 --> 00:11:26,160 Speaker 1: cover up, or whether or not the origins were because 201 00:11:26,160 --> 00:11:29,960 Speaker 1: of some some purposeful or unintentional things that happened in 202 00:11:29,960 --> 00:11:33,520 Speaker 1: a lab. You know that we don't need that information 203 00:11:33,720 --> 00:11:37,080 Speaker 1: to improve our response the next time we have a pandemic. 204 00:11:37,160 --> 00:11:39,760 Speaker 1: We don't need that information to take care of these patients. 205 00:11:40,080 --> 00:11:43,520 Speaker 1: We don't need that information clearly to build vaccines, to 206 00:11:43,600 --> 00:11:47,400 Speaker 1: build therapeutics. What we need is to focus those efforts 207 00:11:47,480 --> 00:11:49,760 Speaker 1: on how we get out of this pandemic and how 208 00:11:49,880 --> 00:11:53,840 Speaker 1: we move move the global health forward to be able 209 00:11:53,880 --> 00:11:55,920 Speaker 1: to prepare for the next one. And that's not through 210 00:11:55,960 --> 00:11:59,520 Speaker 1: an origins discussion. Lauren, thank you so much once again 211 00:11:59,559 --> 00:12:01,320 Speaker 1: for join as you do every week, and we really 212 00:12:01,320 --> 00:12:04,280 Speaker 1: appreciate your time. Laurence Sour, Social Professor of Emergency Medicine 213 00:12:04,320 --> 00:12:06,439 Speaker 1: at Johns Hopkins School of Medicine. We should note that 214 00:12:06,440 --> 00:12:08,600 Speaker 1: the Bloomberg School of Public Health is supported by Michael 215 00:12:08,640 --> 00:12:11,719 Speaker 1: Are Bloomberg found Our, Bloomberg LP, Bloomberg Philanthropies, and this 216 00:12:11,880 --> 00:12:17,880 Speaker 1: radio operation. Cities across the United States and the state 217 00:12:17,920 --> 00:12:22,040 Speaker 1: of California, they're starting to make a case for local reparations. 218 00:12:22,440 --> 00:12:25,160 Speaker 1: Are good. Folks at Bloomberg Business Week took a deep 219 00:12:25,200 --> 00:12:29,520 Speaker 1: dive one of those cities. Susan Burfield. Burfield, Senior investigative 220 00:12:29,520 --> 00:12:32,640 Speaker 1: reporter for Bloomberg Business Week, uh and also the author 221 00:12:32,720 --> 00:12:35,680 Speaker 1: of The Hour of Fate, Theodore Roosevelt, JP Morgan, and 222 00:12:35,760 --> 00:12:39,400 Speaker 1: the Battle to Transform American Capitalism. So thanks so much 223 00:12:39,400 --> 00:12:41,600 Speaker 1: for joining us here. You guys took a look at 224 00:12:41,640 --> 00:12:45,160 Speaker 1: this whole reparation's issue as it relates to a small 225 00:12:45,240 --> 00:12:49,480 Speaker 1: town of Evanston, Illinois. What did you guys find? Yeah, 226 00:12:49,480 --> 00:12:52,439 Speaker 1: so thanks so much for having me on. So Evanston, 227 00:12:52,559 --> 00:12:55,800 Speaker 1: Illinois is um uh, as you said, a small city 228 00:12:55,920 --> 00:12:59,480 Speaker 1: just north of Chicago, and UM, it has the distinction 229 00:12:59,600 --> 00:13:03,360 Speaker 1: of being the first city in the US to offer 230 00:13:03,440 --> 00:13:08,680 Speaker 1: reparations to its black residents, and UM, the first kind 231 00:13:08,679 --> 00:13:11,960 Speaker 1: of effort that it's making, UM is to redress the 232 00:13:12,000 --> 00:13:17,280 Speaker 1: housing discrimination UM that many black residents faced beginning as 233 00:13:17,320 --> 00:13:22,599 Speaker 1: far back as nineteen nineteen. I'd say that I absolutely 234 00:13:22,640 --> 00:13:26,880 Speaker 1: loved the story, Susan. It was really the kind of 235 00:13:26,960 --> 00:13:28,800 Speaker 1: it was like a book you just can't put down. 236 00:13:28,880 --> 00:13:31,600 Speaker 1: I was taking care of my baby and trying to 237 00:13:31,640 --> 00:13:33,880 Speaker 1: feed her bottle, and I just I couldn't really do 238 00:13:33,960 --> 00:13:38,240 Speaker 1: anything until I no, I mean, I just I I 239 00:13:38,440 --> 00:13:42,559 Speaker 1: noticed that she couldn't distract me. I was. I found 240 00:13:42,559 --> 00:13:45,240 Speaker 1: it really fascinating And at first, you know, it starts 241 00:13:45,240 --> 00:13:49,320 Speaker 1: out really disturbing, because, Um, I was reading about Lucia's 242 00:13:49,320 --> 00:13:52,800 Speaker 1: Sutton at the very beginning, and I was thinking, how 243 00:13:52,920 --> 00:13:56,320 Speaker 1: is this possible, this kind of injustice in you know, 244 00:13:56,400 --> 00:14:00,360 Speaker 1: the nineteen hundreds, that's my century. I could have imagine 245 00:14:00,360 --> 00:14:04,800 Speaker 1: it happening in the eighteen hundreds. But it's just, Um, 246 00:14:04,840 --> 00:14:07,360 Speaker 1: it's something everyone should read, even people who have been 247 00:14:07,480 --> 00:14:10,240 Speaker 1: have become kind of numb to the social justice and 248 00:14:11,040 --> 00:14:14,560 Speaker 1: the Congressman we're talking about woke capitalism. But when you 249 00:14:14,559 --> 00:14:18,959 Speaker 1: read this, you can understand why it's worth fighting for. Um. 250 00:14:19,040 --> 00:14:23,560 Speaker 1: The one thing I kept thinking to myself, Susan, is yes, 251 00:14:23,760 --> 00:14:26,680 Speaker 1: you run into these real problems, especially on the local level, 252 00:14:26,680 --> 00:14:29,560 Speaker 1: and you make this point in the story, if it's 253 00:14:29,600 --> 00:14:32,040 Speaker 1: done on a federal level, it would be you'd have 254 00:14:32,160 --> 00:14:36,360 Speaker 1: less you'd have fewer problems. Right. Yeah. Well, first of all, 255 00:14:36,440 --> 00:14:40,520 Speaker 1: just thanks so much for the kind words about the story. UM. 256 00:14:40,520 --> 00:14:45,080 Speaker 1: It was been a wonderful privilege really to be able 257 00:14:45,120 --> 00:14:47,560 Speaker 1: to spend so much time on it, um and with 258 00:14:47,680 --> 00:14:50,960 Speaker 1: people in Evanston, so um it kind of makes me 259 00:14:50,960 --> 00:14:55,360 Speaker 1: want to move to Evanston. It's a beautiful place and 260 00:14:55,400 --> 00:14:57,320 Speaker 1: they're good apparently good that they're good people. For the 261 00:14:57,320 --> 00:15:00,560 Speaker 1: most part, right, they if they're taking this on, Yeah, 262 00:15:00,600 --> 00:15:03,080 Speaker 1: they're trying to do the right thing. And you know, 263 00:15:03,440 --> 00:15:07,440 Speaker 1: to your question, UM, you know, at the local level, UM, 264 00:15:07,440 --> 00:15:09,960 Speaker 1: at it. You know, in a city like Evanston or 265 00:15:10,080 --> 00:15:13,760 Speaker 1: in any city in the US, UM, there are always 266 00:15:13,800 --> 00:15:19,000 Speaker 1: going to be different points of view about what reparations 267 00:15:19,160 --> 00:15:22,160 Speaker 1: should look like at the local level, you know, and 268 00:15:22,240 --> 00:15:25,880 Speaker 1: part of that is kind of what kind of discrimination 269 00:15:26,080 --> 00:15:31,760 Speaker 1: or injustice to take on. First, how much money any 270 00:15:31,840 --> 00:15:35,920 Speaker 1: city is going to be able, uh to to use 271 00:15:36,040 --> 00:15:38,680 Speaker 1: to essentially you know, pay down the debt it owes 272 00:15:38,760 --> 00:15:42,360 Speaker 1: to its black residents. UM. And you know, just the 273 00:15:42,480 --> 00:15:45,480 Speaker 1: nature of city government or even state government. You know, 274 00:15:45,520 --> 00:15:49,880 Speaker 1: there's UM lots of opportunities for people to comment, so 275 00:15:50,000 --> 00:15:52,880 Speaker 1: you can hear very directly from lots of people. UM. 276 00:15:52,920 --> 00:15:56,600 Speaker 1: And you know, at the national level, UM, there's been 277 00:15:57,240 --> 00:16:02,280 Speaker 1: uh increasing MOMENTUM might say, UM ward the discussion. You know, 278 00:16:02,400 --> 00:16:05,400 Speaker 1: so the cities are taking it many steps further than 279 00:16:05,440 --> 00:16:07,920 Speaker 1: what's happening on the national level. But there is at 280 00:16:07,960 --> 00:16:11,040 Speaker 1: least the discussion. You know, there is UM. There are 281 00:16:11,400 --> 00:16:17,240 Speaker 1: studies that would help calculate how much reparations should be UM. 282 00:16:17,400 --> 00:16:21,320 Speaker 1: And of course that's chillions of dollars, and in Evanston 283 00:16:21,400 --> 00:16:25,400 Speaker 1: we're talking about millions of dollars. How does the process 284 00:16:25,480 --> 00:16:29,600 Speaker 1: actually work if someone feels that they are due reparations, 285 00:16:30,120 --> 00:16:34,520 Speaker 1: how's the process work? So in Evanston, UM, the first 286 00:16:34,920 --> 00:16:39,040 Speaker 1: round of money, which is about four hundred thousand dollars 287 00:16:39,160 --> 00:16:41,840 Speaker 1: UM and is going to be given out to recipients 288 00:16:41,880 --> 00:16:46,760 Speaker 1: this summer. UH and essentially anyone who lived in Evanston, 289 00:16:46,880 --> 00:16:50,640 Speaker 1: any black residents who lived in Evanston from nineteen nineteen 290 00:16:51,040 --> 00:16:54,840 Speaker 1: to nineteen sixty nine UM. That's the year after the 291 00:16:54,840 --> 00:16:58,800 Speaker 1: federal government passed the Fair Housing Act. So if you 292 00:16:59,120 --> 00:17:02,760 Speaker 1: lived in evans Been during that time, you're eligible and 293 00:17:02,800 --> 00:17:07,399 Speaker 1: you're given first priority. Second priority is to the descendants 294 00:17:07,440 --> 00:17:11,400 Speaker 1: of those people, and third priority is to a resident 295 00:17:11,880 --> 00:17:16,360 Speaker 1: who moved or lived in Evanston after that and can 296 00:17:16,359 --> 00:17:21,960 Speaker 1: show that they faced discrimination. It's hard for me, UM 297 00:17:22,000 --> 00:17:24,879 Speaker 1: to be flippant about this, because when you read about 298 00:17:25,000 --> 00:17:28,320 Speaker 1: the Cannon family, the Simmons family, what happened to the 299 00:17:28,359 --> 00:17:32,800 Speaker 1: Sutton family. UM, you just have to take it seriously. 300 00:17:32,920 --> 00:17:35,880 Speaker 1: But being flippant is in my nature, and I want 301 00:17:35,920 --> 00:17:38,320 Speaker 1: to say that it seems like the best thing you 302 00:17:38,320 --> 00:17:40,800 Speaker 1: can do for social justice. If you visit Evanston is 303 00:17:40,840 --> 00:17:45,840 Speaker 1: by weed, right, I mean because the first the money 304 00:17:45,880 --> 00:17:49,159 Speaker 1: that they're getting comes from the three percent cannabis tax 305 00:17:49,320 --> 00:17:53,160 Speaker 1: and they've only got one weed vendor in town. So 306 00:17:53,720 --> 00:17:56,119 Speaker 1: if you do go there, stop by and get yourself 307 00:17:56,160 --> 00:17:59,199 Speaker 1: a pre rolled joint or something. Yes, well you're not 308 00:17:59,280 --> 00:18:03,280 Speaker 1: the only one. The Alderman as they're called, Derek City 309 00:18:03,280 --> 00:18:06,120 Speaker 1: Council member UM who came up with the idea UM. 310 00:18:06,160 --> 00:18:08,440 Speaker 1: She's no longer serving, but I spoke to her while 311 00:18:08,480 --> 00:18:11,000 Speaker 1: she was still in office and her message was, you know, 312 00:18:11,080 --> 00:18:14,959 Speaker 1: come to Evanston and pleased buy drugs. Robin Ruth Simmons 313 00:18:15,480 --> 00:18:18,600 Speaker 1: was that it was the Alderman now, uh, well that 314 00:18:18,720 --> 00:18:21,679 Speaker 1: was Anne Rainey. Robin Ruth Simmons though UM is the 315 00:18:21,680 --> 00:18:26,360 Speaker 1: one who first proposed reparations UM idea UM and then 316 00:18:26,440 --> 00:18:29,840 Speaker 1: you know, worked with some other city council members to 317 00:18:29,880 --> 00:18:32,400 Speaker 1: help create it UM. And it was Anne Rainey who 318 00:18:32,400 --> 00:18:34,680 Speaker 1: came up with the idea of using the money from 319 00:18:34,680 --> 00:18:37,800 Speaker 1: this new tax, you know, money that was unclaimed UM 320 00:18:37,840 --> 00:18:40,840 Speaker 1: that they calculated would bring in about a million dollars 321 00:18:40,880 --> 00:18:44,480 Speaker 1: a year, and then they devoted UM the first ten 322 00:18:44,520 --> 00:18:47,600 Speaker 1: million dollars UM to the program, and you know, maybe 323 00:18:47,600 --> 00:18:49,840 Speaker 1: that will take ten years to pless maybe less well 324 00:18:49,880 --> 00:18:52,479 Speaker 1: hopefully UM, well they can raise those taxes a little bit. 325 00:18:52,480 --> 00:18:54,040 Speaker 1: I think everyone will be willing to pay a little 326 00:18:54,080 --> 00:18:56,679 Speaker 1: bit more UM for their for a good weed. But 327 00:18:56,880 --> 00:18:59,080 Speaker 1: I have to say now for you, as as senior 328 00:18:59,119 --> 00:19:02,800 Speaker 1: investigative report or UM, you may not notice, but as 329 00:19:03,000 --> 00:19:06,000 Speaker 1: for a regular person, the history that these people have discovered, 330 00:19:06,440 --> 00:19:10,040 Speaker 1: the research that they've put in to to go back three, 331 00:19:10,200 --> 00:19:13,399 Speaker 1: four or five generations and get you know, titles and 332 00:19:13,440 --> 00:19:16,920 Speaker 1: deeds and the stories that they have the story just 333 00:19:16,960 --> 00:19:20,200 Speaker 1: for that to me is worth it UM. I love 334 00:19:20,280 --> 00:19:23,200 Speaker 1: the family history that that they have discovered that you've 335 00:19:23,240 --> 00:19:26,280 Speaker 1: reported here. Susan, thanks so much for joining us UM. 336 00:19:26,320 --> 00:19:30,160 Speaker 1: Susan Bearfield and Jordan Holman wrote the story first US 337 00:19:30,200 --> 00:19:37,959 Speaker 1: City Too Back Reparations meets hard Reality. Now let's delve 338 00:19:38,119 --> 00:19:42,000 Speaker 1: into crypto. I don't think we've mentioned bitcoin at all today. 339 00:19:42,400 --> 00:19:47,760 Speaker 1: Paul or Doge or ether or Tether. Mike mcgloan joins 340 00:19:47,840 --> 00:19:53,680 Speaker 1: US Commodities Strategists for Bloomberg Intelligence on crypto UM. I mean, 341 00:19:54,720 --> 00:19:57,639 Speaker 1: the volatility has been amazing, but the lineup of guests 342 00:19:57,640 --> 00:20:01,240 Speaker 1: that we've had, Mike has been insane of the last week. 343 00:20:01,440 --> 00:20:06,160 Speaker 1: I have interviewed uh Nick Carter, who is a brilliant 344 00:20:06,520 --> 00:20:10,480 Speaker 1: writer from Castle Island Ventures, Sam Bankman Freed, who is 345 00:20:10,800 --> 00:20:12,720 Speaker 1: one of the richest people in America now and he's 346 00:20:12,720 --> 00:20:16,280 Speaker 1: only twenty nine. It's got like forty billion dollars in 347 00:20:16,320 --> 00:20:20,760 Speaker 1: crypto And Bobby Lee, who is a pioneer in the 348 00:20:20,840 --> 00:20:25,520 Speaker 1: space UM. He started BTC China and now has a 349 00:20:25,600 --> 00:20:32,480 Speaker 1: really cool UM hardware wallet out. Uh, Mike, what what 350 00:20:32,560 --> 00:20:35,960 Speaker 1: are your what's your current thinking on bitcoin? Is? We've 351 00:20:36,000 --> 00:20:39,480 Speaker 1: gone through these wild up and down swings. Is it 352 00:20:39,520 --> 00:20:41,760 Speaker 1: gonna Is it here to stay? The volatility for right now? 353 00:20:41,760 --> 00:20:43,639 Speaker 1: Are are we getting past it? Well? Hey, man, I 354 00:20:43,680 --> 00:20:46,520 Speaker 1: appreciate you mentioned some very smart people that I list 355 00:20:46,560 --> 00:20:49,119 Speaker 1: basically enjoyed those interviews, and I think the key thing 356 00:20:49,160 --> 00:20:51,000 Speaker 1: to think about in cryptos is it's a bool market 357 00:20:51,080 --> 00:20:54,040 Speaker 1: that's corrected. Got way too excited and I'm one of 358 00:20:54,080 --> 00:20:56,480 Speaker 1: the people got suckered into. What really brought me and 359 00:20:56,600 --> 00:20:58,920 Speaker 1: we thought it would continue up was when valtily dropped 360 00:20:59,400 --> 00:21:01,960 Speaker 1: sixty dave out and bitcoin dropped to the lowest of 361 00:21:01,960 --> 00:21:04,120 Speaker 1: the year right before the claps. It was like, oh, 362 00:21:04,320 --> 00:21:06,399 Speaker 1: typically that means it's going to go higher. So it 363 00:21:06,480 --> 00:21:08,160 Speaker 1: was a sign that was just way too much spec 364 00:21:08,240 --> 00:21:10,560 Speaker 1: to exus is you know the minute that dose coin 365 00:21:10,560 --> 00:21:13,480 Speaker 1: got in SATURNI live, that was the bell ringing. Okay, 366 00:21:13,560 --> 00:21:17,000 Speaker 1: let's look back now, let's look forward. Right now, Ethereums 367 00:21:17,080 --> 00:21:20,919 Speaker 1: up two on the year. The Bloomberg Galaxy Crypto index 368 00:21:21,000 --> 00:21:25,119 Speaker 1: is up a hundred percent. Bitcoins up, bitcoins add the 369 00:21:25,119 --> 00:21:28,199 Speaker 1: rest of the space. Ethereum is a stud and but 370 00:21:28,240 --> 00:21:31,240 Speaker 1: I think that's that that appreciates is going to continue 371 00:21:31,280 --> 00:21:34,840 Speaker 1: because the fundamental underpinions are still quite strong. How about 372 00:21:34,880 --> 00:21:38,200 Speaker 1: the regulatory overhang, it's beginning to build here. We've seen 373 00:21:38,240 --> 00:21:40,960 Speaker 1: some central bankers, including some folks in China. How do 374 00:21:41,000 --> 00:21:43,080 Speaker 1: you think about that. Yes, that's the key thing point 375 00:21:43,520 --> 00:21:45,000 Speaker 1: you brought that in there, and the key thing that 376 00:21:45,080 --> 00:21:46,800 Speaker 1: Kathy would said. There's just not much you can do 377 00:21:46,880 --> 00:21:50,679 Speaker 1: to really regulate bitcoin anymore. It's the world's largest decentralized network. 378 00:21:50,720 --> 00:21:54,399 Speaker 1: It's open source software. So China his his. What China 379 00:21:54,440 --> 00:21:56,680 Speaker 1: did recently, I think it's a good indication of how 380 00:21:57,160 --> 00:21:59,560 Speaker 1: significant bitcoin is now here. We have a country that 381 00:21:59,640 --> 00:22:02,480 Speaker 1: had let's not have I mean, it's becoming a surveillance state, 382 00:22:02,600 --> 00:22:05,120 Speaker 1: doesn't have free full capital, certainly doesn't have a discourse, 383 00:22:05,280 --> 00:22:07,880 Speaker 1: and they have to limit their their people from from 384 00:22:07,920 --> 00:22:10,359 Speaker 1: Winnie the Pooh and from the Internet, so they have 385 00:22:10,440 --> 00:22:13,480 Speaker 1: to limit Bitcoin and they have to limit flow of capital. 386 00:22:13,520 --> 00:22:15,520 Speaker 1: So that's a significant sign. But it's also what's going 387 00:22:15,600 --> 00:22:17,520 Speaker 1: to really tilt the US, I think to embrace it 388 00:22:17,560 --> 00:22:20,119 Speaker 1: more because there's a cold war that's really brilliant and 389 00:22:20,160 --> 00:22:22,280 Speaker 1: getting more and more. And that is what's I pointed 390 00:22:22,280 --> 00:22:24,159 Speaker 1: out on the crypto chat this morning, is it's the 391 00:22:24,200 --> 00:22:28,840 Speaker 1: digitalization of money. It's enhancing dollar dominance. The most widely 392 00:22:28,840 --> 00:22:31,399 Speaker 1: traded crypto on the planet is tether. I've mentioned this before. 393 00:22:31,680 --> 00:22:35,000 Speaker 1: It's double the volume of Bitcoin, and it's a digital dollar, 394 00:22:35,080 --> 00:22:37,760 Speaker 1: and it's an ethereum token. So key things there. Dollars 395 00:22:37,800 --> 00:22:42,520 Speaker 1: dominating ethereums gaining dominant theorems that significant, and the US 396 00:22:42,600 --> 00:22:44,679 Speaker 1: is probably gonna say, oh, we also have to do 397 00:22:45,000 --> 00:22:47,600 Speaker 1: is nothing here and we're beating China and the world 398 00:22:47,600 --> 00:22:51,119 Speaker 1: and this big battle against the two major powers. Is 399 00:22:51,160 --> 00:22:57,320 Speaker 1: there any um crypto token that you think is ideal 400 00:22:57,359 --> 00:23:00,880 Speaker 1: for spending Because my idea is somethings gonna come along 401 00:23:00,920 --> 00:23:02,479 Speaker 1: where people say, you know what, I don't care if 402 00:23:02,480 --> 00:23:05,840 Speaker 1: a regulator embraces this. I don't care if some central 403 00:23:05,880 --> 00:23:07,800 Speaker 1: bank says stay away and I'm gonna use this and 404 00:23:07,800 --> 00:23:10,280 Speaker 1: get around the system. The problem is, right now, it's 405 00:23:10,280 --> 00:23:12,919 Speaker 1: too difficult to do that with bitcoin because it's so 406 00:23:12,960 --> 00:23:16,120 Speaker 1: hard to spend. I'll be sarcastic tether. I mean, it's 407 00:23:16,119 --> 00:23:19,400 Speaker 1: a digital dollar, I'll be honest. The digital the global 408 00:23:19,520 --> 00:23:22,480 Speaker 1: reserve currency is the dollar, and it's gaining dominance despite 409 00:23:22,520 --> 00:23:24,879 Speaker 1: the fact US GDPs of client because after what's happened 410 00:23:24,920 --> 00:23:27,600 Speaker 1: in China and Hong Kong, the world SE's okay, okay, 411 00:23:27,640 --> 00:23:28,879 Speaker 1: it's not the best place in the world. It is 412 00:23:28,920 --> 00:23:30,560 Speaker 1: not the best, but the dollar is the best place, 413 00:23:30,640 --> 00:23:32,679 Speaker 1: the best thing to transact. And then there's this global 414 00:23:32,720 --> 00:23:34,919 Speaker 1: digital reserve asset. Now it used to be gold was 415 00:23:34,960 --> 00:23:38,120 Speaker 1: the digital store value. It's becoming more and more bitcoin. 416 00:23:38,240 --> 00:23:41,840 Speaker 1: So I think for spending dollars, it's actually gaining in 417 00:23:41,960 --> 00:23:45,399 Speaker 1: terms of digitalization. And as far as actually spending, it 418 00:23:45,400 --> 00:23:47,240 Speaker 1: depends what you mean by that. The key thing that's 419 00:23:47,320 --> 00:23:50,120 Speaker 1: really happening globally is a lot of third world countries 420 00:23:50,200 --> 00:23:53,320 Speaker 1: or countries with don't have stable currencies like we are 421 00:23:53,400 --> 00:23:56,439 Speaker 1: blessed with are all turning to cryptos and they can 422 00:23:56,480 --> 00:23:58,200 Speaker 1: do it on their phones, and they're getting phones because 423 00:23:58,200 --> 00:24:00,359 Speaker 1: they're leap frogging that technology. They might ahead of the 424 00:24:00,400 --> 00:24:03,199 Speaker 1: wires to running the electricity out in rural India or 425 00:24:03,400 --> 00:24:06,960 Speaker 1: world sub Sahara, Africa, but they can do They're getting 426 00:24:07,040 --> 00:24:09,800 Speaker 1: fun So that's happening everywhere. So like, what what's the 427 00:24:09,800 --> 00:24:12,520 Speaker 1: bigcoin chat? Why am I not on this? I'll get 428 00:24:12,560 --> 00:24:15,600 Speaker 1: you on the cryptot Please don't. I don't think you 429 00:24:15,640 --> 00:24:17,720 Speaker 1: want to invite him in here. You need to be 430 00:24:17,760 --> 00:24:19,280 Speaker 1: on that because Matt, you're so funny. But I'll be 431 00:24:19,320 --> 00:24:22,240 Speaker 1: in the on Saturday morning tomorrow morning and hopping on 432 00:24:22,320 --> 00:24:25,439 Speaker 1: a plane to go to Miami for the bitcoin conference. 433 00:24:25,440 --> 00:24:26,879 Speaker 1: It is supposed to be the biggest one on the 434 00:24:26,920 --> 00:24:29,679 Speaker 1: plan and it's live, it's not virtual. Where there you go? 435 00:24:29,880 --> 00:24:33,359 Speaker 1: All right, here you go. Don't need masks when I 436 00:24:33,400 --> 00:24:35,680 Speaker 1: go to Miami Beach. I don't go to a bitcoin conference. Post. 437 00:24:35,920 --> 00:24:39,040 Speaker 1: Thanks for listening to the Bloomberg Markets podcast. You can 438 00:24:39,040 --> 00:24:42,840 Speaker 1: subscribe and listen to interviews with Apple Podcasts or whatever 439 00:24:42,920 --> 00:24:46,560 Speaker 1: podcast platform you prefer. I'm Matt Miller. I'm on Twitter 440 00:24:46,840 --> 00:24:50,359 Speaker 1: at Matt Miller three, pet On ball Sweeney, I'm on 441 00:24:50,359 --> 00:24:53,280 Speaker 1: Twitter at pt Sweeney. Before the podcast, you can always 442 00:24:53,320 --> 00:24:55,440 Speaker 1: catch us worldwide at Bloomberg Radio