1 00:00:00,500 --> 00:00:02,982 [SQUEAKING] 2 00:00:02,982 --> 00:00:03,973 [RUSTLING] 3 00:00:04,473 --> 00:00:05,964 [CLICKING] 4 00:00:12,730 --> 00:00:15,620 GARY GENSLER: So welcome back. 5 00:00:15,620 --> 00:00:19,880 We're going to keep this journey going on FinTech. 6 00:00:19,880 --> 00:00:23,480 We spoke about payments in our last class. 7 00:00:23,480 --> 00:00:30,320 And here in Class 7, we're going to dive into credit, 8 00:00:30,320 --> 00:00:32,310 and there's a lot to cover. 9 00:00:32,310 --> 00:00:34,910 There are so many different segments and sectors 10 00:00:34,910 --> 00:00:37,940 in the credit space, and there's a lot going on 11 00:00:37,940 --> 00:00:40,280 with financial technology, not just because 12 00:00:40,280 --> 00:00:44,720 of artificial intelligence, Open API, but even 13 00:00:44,720 --> 00:00:47,510 the earlier things that were brought into the tech. 14 00:00:47,510 --> 00:00:52,730 Now, technology stack around mobile phones and the like 15 00:00:52,730 --> 00:00:56,810 still gives a lot of opportunity to break in here, 16 00:00:56,810 --> 00:01:00,660 and the use of alternative data. 17 00:01:00,660 --> 00:01:04,790 So I'm going to bring up-- 18 00:01:04,790 --> 00:01:09,260 share some slides and get going here. 19 00:01:16,910 --> 00:01:18,890 First, I should also say to those 20 00:01:18,890 --> 00:01:25,100 who celebrate such things, happy Earth Day, April 22. 21 00:01:25,100 --> 00:01:27,350 It's also my daughter's birthday, my eldest, 22 00:01:27,350 --> 00:01:30,140 my first daughter at 3. 23 00:01:30,140 --> 00:01:34,580 So today's a special day, Earth Day and my daughter's birthday. 24 00:01:34,580 --> 00:01:36,320 So happy birthday, Anna. 25 00:01:42,020 --> 00:01:44,780 So I'm going to do a little update on Facebook. 26 00:01:44,780 --> 00:01:49,520 We spoke about Facebook in our last class about payments. 27 00:01:49,520 --> 00:01:51,950 And there were interesting announcements, actually, 28 00:01:51,950 --> 00:01:54,740 as we were together. 29 00:01:54,740 --> 00:01:57,350 Facebook was announcing some updates. 30 00:01:57,350 --> 00:01:59,740 And then dive into the credit world. 31 00:01:59,740 --> 00:02:02,210 And before we dive into FinTech, just 32 00:02:02,210 --> 00:02:05,120 talk a little bit about those credit sectors 33 00:02:05,120 --> 00:02:06,830 and the market designing credit. 34 00:02:06,830 --> 00:02:09,650 And that provides, as we'll see, some 35 00:02:09,650 --> 00:02:13,520 of the disruptive potential and how disruptive Taq 36 00:02:13,520 --> 00:02:16,440 can break into the credit value chain. 37 00:02:16,440 --> 00:02:19,470 What you're always looking for in a business, 38 00:02:19,470 --> 00:02:21,260 whether it's about FinTech or otherwise, 39 00:02:21,260 --> 00:02:25,100 is somehow to break into another party's value chain 40 00:02:25,100 --> 00:02:28,280 or to create value for customers. 41 00:02:28,280 --> 00:02:31,370 Either you can create value where others haven't seen it, 42 00:02:31,370 --> 00:02:33,990 or you want to break into somebody else's value chain. 43 00:02:33,990 --> 00:02:35,840 So we'll talk a little bit about that, 44 00:02:35,840 --> 00:02:41,610 how we see that pretty early in this area 45 00:02:41,610 --> 00:02:44,100 of financial technology. 46 00:02:44,100 --> 00:02:47,220 And then a review of the competitive landscape 47 00:02:47,220 --> 00:02:49,776 by the different marketplaces. 48 00:02:49,776 --> 00:02:55,280 I'll touch on marketplace lending and credit scoring, 49 00:02:55,280 --> 00:02:58,310 and then I'll close with just a comment on professionalism 50 00:02:58,310 --> 00:03:00,040 and academic integrity, as people 51 00:03:00,040 --> 00:03:03,240 are gearing up for their papers and group work, and so forth, 52 00:03:03,240 --> 00:03:03,740 again. 53 00:03:06,140 --> 00:03:10,040 The readings included a review of 12 FinTech companies. 54 00:03:10,040 --> 00:03:11,480 This was just a taste test. 55 00:03:11,480 --> 00:03:15,850 It was one article in reaction to Apple Credit Card. 56 00:03:15,850 --> 00:03:18,450 And these were FinTech companies in the credit card space. 57 00:03:18,450 --> 00:03:20,130 But as we'll see today, we're going 58 00:03:20,130 --> 00:03:24,590 to review a lot of the other spaces, as well. 59 00:03:24,590 --> 00:03:27,320 A brief article that I thought was 60 00:03:27,320 --> 00:03:29,420 helpful about how tech companies are 61 00:03:29,420 --> 00:03:32,930 seeing how to get into the lending business, big tech, 62 00:03:32,930 --> 00:03:34,100 particularly. 63 00:03:34,100 --> 00:03:36,920 Marketplace lenders, we'll look at Lending Club 64 00:03:36,920 --> 00:03:41,360 more particularly, and then alternative data. 65 00:03:41,360 --> 00:03:43,910 Study questions, again, are not just for you 66 00:03:43,910 --> 00:03:47,340 to gear up and prepare for the class, 67 00:03:47,340 --> 00:03:50,570 but this is where I want to sort of end how 68 00:03:50,570 --> 00:03:54,620 we can think about this, really importantly, how big tech 69 00:03:54,620 --> 00:03:57,630 firms are positioning themselves to offer credit. 70 00:03:57,630 --> 00:03:59,180 And I don't know, Romain, if anybody 71 00:03:59,180 --> 00:04:03,300 is going to sort of get the cobwebs off and give us 72 00:04:03,300 --> 00:04:05,407 some thoughts, but I'm going to turn 73 00:04:05,407 --> 00:04:07,990 it to Romain to see if there's anybody that wants to just give 74 00:04:07,990 --> 00:04:11,350 it a thought, broad overview of big tech in this space, 75 00:04:11,350 --> 00:04:16,600 whether it's from China, Europe, the US, Latin America. 76 00:04:16,600 --> 00:04:18,880 OK, let's go for today's class. 77 00:04:18,880 --> 00:04:22,910 Who would like to be the first volunteer? 78 00:04:22,910 --> 00:04:23,790 Michael. 79 00:04:23,790 --> 00:04:24,290 Thank you. 80 00:04:28,760 --> 00:04:31,290 AUDIENCE: I guess something from the article 81 00:04:31,290 --> 00:04:34,050 that [INAUDIBLE] just kind of seeing over the last decade, 82 00:04:34,050 --> 00:04:38,100 what's going on, there's been a lot more availability 83 00:04:38,100 --> 00:04:38,820 of lending. 84 00:04:38,820 --> 00:04:41,082 I think Lending Club was-- 85 00:04:41,082 --> 00:04:44,150 I kind of saw it more from a personal investing 86 00:04:44,150 --> 00:04:46,580 point of view, but kind of thinking of who can actually 87 00:04:46,580 --> 00:04:50,080 have access to credit has been a huge position of tech 88 00:04:50,080 --> 00:04:56,450 in the US, and also the speed of the traditional credit 89 00:04:56,450 --> 00:04:58,490 process for consumers and small businesses 90 00:04:58,490 --> 00:05:00,830 has been kind of painful. 91 00:05:00,830 --> 00:05:04,230 So that's definitely a big area that big tech 92 00:05:04,230 --> 00:05:10,155 is trying to tackle with AI and just automated processes. 93 00:05:10,155 --> 00:05:11,280 GARY GENSLER: Right, right. 94 00:05:11,280 --> 00:05:15,470 But Michael, if you add to it, think about big tech companies. 95 00:05:15,470 --> 00:05:18,770 How are big tech companies strategically positioning 96 00:05:18,770 --> 00:05:19,630 themselves? 97 00:05:19,630 --> 00:05:22,010 I mean, Lending Club and the marketplace lenders 98 00:05:22,010 --> 00:05:27,000 are a very important trend here, as well, 99 00:05:27,000 --> 00:05:29,000 these sort of more disruptive companies, 100 00:05:29,000 --> 00:05:31,890 some of them becoming incumbents in their space. 101 00:05:31,890 --> 00:05:34,360 But how about big platforms? 102 00:05:34,360 --> 00:05:37,580 I guess embedding it with their current services, products 103 00:05:37,580 --> 00:05:38,570 that they already have. 104 00:05:38,570 --> 00:05:39,920 Like, Apple Pay was a good example, 105 00:05:39,920 --> 00:05:41,420 where it's just kind of everybody's 106 00:05:41,420 --> 00:05:44,180 already using an iPhone, so if they can just make it seamless 107 00:05:44,180 --> 00:05:47,490 with their existing processes. 108 00:05:47,490 --> 00:05:49,470 So this is again [INAUDIBLE]---- well, 109 00:05:49,470 --> 00:05:50,720 I see a couple other hands up. 110 00:05:50,720 --> 00:05:53,420 So, Romain? 111 00:05:53,420 --> 00:05:54,975 TA: Alessandro? 112 00:05:54,975 --> 00:05:55,600 AUDIENCE: Yeah. 113 00:05:55,600 --> 00:06:00,710 I think, also, Amazon is a very interesting case where, 114 00:06:00,710 --> 00:06:03,350 thanks to all the data, they have gathered on sellers 115 00:06:03,350 --> 00:06:06,560 from their marketplace, they are able to offer 116 00:06:06,560 --> 00:06:10,590 short-term lending to all the sellers on the marketplace. 117 00:06:10,590 --> 00:06:14,570 And this also gives them a competitive advantage. 118 00:06:14,570 --> 00:06:17,760 These would be banks, commercial banks, first of all. 119 00:06:17,760 --> 00:06:21,700 Because the notion of this lending is very small. 120 00:06:21,700 --> 00:06:25,020 So it's comparable to microlending. 121 00:06:25,020 --> 00:06:26,910 And second, because they have access 122 00:06:26,910 --> 00:06:32,950 to a huge amount of data on the business of these sellers. 123 00:06:32,950 --> 00:06:37,650 And third, they have a direct accessed repayment. 124 00:06:37,650 --> 00:06:40,140 Because basically, these repayments 125 00:06:40,140 --> 00:06:44,810 are automatic from the business of the sellers on the Amazon 126 00:06:44,810 --> 00:06:46,367 Marketplace. 127 00:06:46,367 --> 00:06:47,200 GARY GENSLER: Right. 128 00:06:47,200 --> 00:06:54,580 So what Michael and Alexandro have said is-- 129 00:06:54,580 --> 00:06:57,320 well, first, we talked a little bit about the disruptors. 130 00:06:57,320 --> 00:06:59,960 But in terms of big tech, they have 131 00:06:59,960 --> 00:07:03,110 a lot of network advantages, whether it's Apple. 132 00:07:03,110 --> 00:07:04,610 And there's so many people that have 133 00:07:04,610 --> 00:07:07,070 their phones and their products, whether it's 134 00:07:07,070 --> 00:07:08,780 Amazon in the case that-- 135 00:07:08,780 --> 00:07:11,030 Alexandro, we can go to other countries as well. 136 00:07:11,030 --> 00:07:14,670 This is certainly true in a very significant way in China. 137 00:07:14,670 --> 00:07:18,050 But if it's not just isolated in China and the US 138 00:07:18,050 --> 00:07:23,060 is that they have big networks of users. 139 00:07:23,060 --> 00:07:25,310 They collect data and particularly 140 00:07:25,310 --> 00:07:29,780 if you're a marketplace like Amazon or Alibaba. 141 00:07:29,780 --> 00:07:32,270 When you're selling product, you're 142 00:07:32,270 --> 00:07:34,070 seeing both sides of a market. 143 00:07:34,070 --> 00:07:37,580 You're seeing the consumer side, the hundreds of millions 144 00:07:37,580 --> 00:07:39,470 of people in China or the tens of millions 145 00:07:39,470 --> 00:07:40,730 of people in the US. 146 00:07:40,730 --> 00:07:43,100 But you're seeing the merchant side. 147 00:07:43,100 --> 00:07:46,190 And so that data, and that flow, and that activity 148 00:07:46,190 --> 00:07:50,030 gives you a natural competitive edge. 149 00:07:50,030 --> 00:07:52,370 And then lastly, what was just mentioned 150 00:07:52,370 --> 00:07:55,250 is automatic payment, particularly 151 00:07:55,250 --> 00:07:59,450 if you're in an online platform selling something. 152 00:07:59,450 --> 00:08:02,060 You see that merchant's payment stream, 153 00:08:02,060 --> 00:08:04,130 but also, you lower the credit risk. 154 00:08:04,130 --> 00:08:06,050 Because consumers are buying. 155 00:08:06,050 --> 00:08:09,500 You take your piece to pay back, whether it's a revolving 156 00:08:09,500 --> 00:08:11,340 or term loan to a merchant. 157 00:08:11,340 --> 00:08:15,980 So a lot of competitive edges or even advantages 158 00:08:15,980 --> 00:08:19,700 in this space for them to build upon 159 00:08:19,700 --> 00:08:22,945 to provide a credit product. 160 00:08:22,945 --> 00:08:24,820 TA: Sijin would also like to share a thought. 161 00:08:24,820 --> 00:08:26,750 GARY GENSLER: Yeah, please. 162 00:08:26,750 --> 00:08:28,880 AUDIENCE: Yeah, I think the case of Alibaba 163 00:08:28,880 --> 00:08:30,020 is really interesting. 164 00:08:30,020 --> 00:08:33,200 Because just like Gary had mentioned, 165 00:08:33,200 --> 00:08:34,820 there are a lot of transaction data 166 00:08:34,820 --> 00:08:37,880 and also use their data in Alibaba. 167 00:08:37,880 --> 00:08:42,559 So right now, Alibaba not only offer the payment system, 168 00:08:42,559 --> 00:08:44,600 it also offer a credit system. 169 00:08:44,600 --> 00:08:46,610 You can borrow money from Alibaba. 170 00:08:46,610 --> 00:08:50,010 Actually, it has its own credit system that can-- 171 00:08:50,010 --> 00:08:51,420 I mean, the credit rating. 172 00:08:51,420 --> 00:08:53,330 They can determine how much money 173 00:08:53,330 --> 00:08:55,100 you can borrow from Alibaba. 174 00:08:55,100 --> 00:08:57,700 So I think this case is fairly interesting. 175 00:08:57,700 --> 00:08:59,150 GARY GENSLER: Yeah, so two things 176 00:08:59,150 --> 00:09:04,340 that I think I want to tease out of that is the idea of building 177 00:09:04,340 --> 00:09:06,320 credit on top of payments. 178 00:09:06,320 --> 00:09:08,480 Now, this is not a new phenomena. 179 00:09:08,480 --> 00:09:12,620 This goes back centuries that any good banker 180 00:09:12,620 --> 00:09:14,810 knew that if you were in the center of payments, 181 00:09:14,810 --> 00:09:16,220 you had more information. 182 00:09:16,220 --> 00:09:21,110 You had more data, even in a pre-computer age. 183 00:09:21,110 --> 00:09:24,230 But what we find is a lot of the big tech companies 184 00:09:24,230 --> 00:09:29,030 as well as the disruptors chose to get into the payment space 185 00:09:29,030 --> 00:09:32,240 and then build upon that credit. 186 00:09:32,240 --> 00:09:35,090 Now, as it relates to Alibaba, what 187 00:09:35,090 --> 00:09:38,030 better way to do that than to provide a payment 188 00:09:38,030 --> 00:09:41,750 mechanism to purchase the products on your platform, 189 00:09:41,750 --> 00:09:43,310 similar with Amazon? 190 00:09:43,310 --> 00:09:45,200 And then you can build credit upon that. 191 00:09:45,200 --> 00:09:47,930 Because you've got an incredible amount of data. 192 00:09:47,930 --> 00:09:49,970 But also, you can provide credit in what's 193 00:09:49,970 --> 00:09:53,360 called point-of-sale credit. 194 00:09:53,360 --> 00:09:57,620 Buy something, pay for it over 6 weeks, 8 weeks, 10 weeks 195 00:09:57,620 --> 00:10:01,970 when you're purchasing, so good points. 196 00:10:01,970 --> 00:10:04,760 So what is marketplace lending, this phenomena 197 00:10:04,760 --> 00:10:08,512 that started out at the United Kingdom? 198 00:10:08,512 --> 00:10:10,220 We'll talk a little bit about LendingClub 199 00:10:10,220 --> 00:10:16,710 here in the US, started about a dozen to 15 years ago. 200 00:10:16,710 --> 00:10:18,530 What is it in its theory? 201 00:10:18,530 --> 00:10:21,590 And where is it right now? 202 00:10:21,590 --> 00:10:25,760 Anybody want to chat about that for a minute? 203 00:10:25,760 --> 00:10:29,330 LendingClub, LendingTree-- a lot of companies 204 00:10:29,330 --> 00:10:30,670 that we can chat about here. 205 00:10:30,670 --> 00:10:31,170 TA: Alida? 206 00:10:34,818 --> 00:10:37,130 AUDIENCE: Yes, the marketplace [INAUDIBLE] 207 00:10:37,130 --> 00:10:41,310 lending instead of the concept of allowing individuals 208 00:10:41,310 --> 00:10:44,640 to lend to other individuals or companies 209 00:10:44,640 --> 00:10:46,410 through a marketplace. 210 00:10:46,410 --> 00:10:49,800 And while they've been around for a while, 211 00:10:49,800 --> 00:10:54,030 they've really just come into lending platforms. 212 00:10:54,030 --> 00:10:58,110 And they're really supported by a securitization market 213 00:10:58,110 --> 00:11:01,830 behind them now, rather than individuals lending 214 00:11:01,830 --> 00:11:03,997 on the platform for the most part. 215 00:11:03,997 --> 00:11:04,830 GARY GENSLER: Right. 216 00:11:04,830 --> 00:11:05,330 Right. 217 00:11:05,330 --> 00:11:07,770 And Michael spoke about this earlier as well. 218 00:11:07,770 --> 00:11:09,610 I think it's an interesting concept, 219 00:11:09,610 --> 00:11:14,010 but that it hasn't actually lived up to its early promise. 220 00:11:14,010 --> 00:11:20,700 The promise, when this came about in 2005 to 2007, 221 00:11:20,700 --> 00:11:24,330 was that you and I could use the internet to communicate. 222 00:11:24,330 --> 00:11:27,510 And I could lend to you, and you could borrow from me, 223 00:11:27,510 --> 00:11:33,180 peer to peer, without a central intermediary. 224 00:11:33,180 --> 00:11:35,760 Now, there was always going to be some intermediary. 225 00:11:35,760 --> 00:11:42,000 Because there was a platform, a software provider taking a fee, 226 00:11:42,000 --> 00:11:46,200 but somehow matching lenders to borrowers 227 00:11:46,200 --> 00:11:49,320 in a peer-to-peer network. 228 00:11:49,320 --> 00:11:52,800 What we found over these 13 or 15 years 229 00:11:52,800 --> 00:11:57,570 is that the marketplace lenders like LendingClub 230 00:11:57,570 --> 00:12:01,050 have shifted to securitization market 231 00:12:01,050 --> 00:12:05,490 to raise their money, a highly organized and somewhat 232 00:12:05,490 --> 00:12:08,730 centralized market securitization market. 233 00:12:08,730 --> 00:12:12,390 And on the lending side, you're still very much saying 234 00:12:12,390 --> 00:12:14,620 that you're going through a portal 235 00:12:14,620 --> 00:12:16,830 and that there's only so many of these portals. 236 00:12:16,830 --> 00:12:20,790 So it's not that it's truly peer to peer. 237 00:12:20,790 --> 00:12:24,090 And in fact, often it's now called marketplace lending 238 00:12:24,090 --> 00:12:26,790 in its platforms. 239 00:12:26,790 --> 00:12:30,540 I think that it's still a very important part 240 00:12:30,540 --> 00:12:33,420 of the disruptive credit landscape, 241 00:12:33,420 --> 00:12:36,320 but it's a small percentage of that marketplace. 242 00:12:36,320 --> 00:12:39,120 And it's shifting very dramatically from peer 243 00:12:39,120 --> 00:12:42,330 to peer to online portals. 244 00:12:42,330 --> 00:12:47,130 It's still access centralized credit in many ways. 245 00:12:47,130 --> 00:12:47,820 And we'll see. 246 00:12:47,820 --> 00:12:49,278 And we'll chat a little bit about-- 247 00:12:49,278 --> 00:12:51,150 LendingClub is even now buying-- 248 00:12:51,150 --> 00:12:55,140 announced earlier in 2020 to buy a bank 249 00:12:55,140 --> 00:12:57,735 and merged with the bank itself. 250 00:13:01,020 --> 00:13:03,740 And then there's already been some discussion 251 00:13:03,740 --> 00:13:06,710 of alternative data, but alternative data 252 00:13:06,710 --> 00:13:11,810 building upon a history in many countries 253 00:13:11,810 --> 00:13:16,510 for four or five decades to use data to make credit decisions 254 00:13:16,510 --> 00:13:17,410 by changing it. 255 00:13:17,410 --> 00:13:21,070 And I see a hand raised on this, maybe, Romain? 256 00:13:21,070 --> 00:13:22,480 Or no? 257 00:13:22,480 --> 00:13:23,920 TA: I don't see any hands raised. 258 00:13:23,920 --> 00:13:25,210 I'm sure one will come up. 259 00:13:25,210 --> 00:13:27,250 GARY GENSLER: Going down. 260 00:13:27,250 --> 00:13:29,560 So where does that take us? 261 00:13:29,560 --> 00:13:32,780 Let me go back to Facebook Libra just for a moment. 262 00:13:32,780 --> 00:13:35,560 And this is where we closed our last class is 263 00:13:35,560 --> 00:13:39,250 that Facebook Libra had announced in June of 2019. 264 00:13:39,250 --> 00:13:42,550 And then the People's Bank of China 265 00:13:42,550 --> 00:13:45,550 had already been working on the digital currency project. 266 00:13:45,550 --> 00:13:49,633 But then they sped that up a bit and announced 267 00:13:49,633 --> 00:13:52,050 within a month or two that they were going to move forward 268 00:13:52,050 --> 00:13:54,060 with their currency project. 269 00:13:54,060 --> 00:13:57,510 Libra had announced a token pegged 270 00:13:57,510 --> 00:13:59,670 to four or five other currencies, 271 00:13:59,670 --> 00:14:03,180 so is a multi-currency basket. 272 00:14:03,180 --> 00:14:05,730 And there was a lot of push-back from central banks 273 00:14:05,730 --> 00:14:08,340 around the globe on this concept that they 274 00:14:08,340 --> 00:14:10,320 would create what Facebook actually 275 00:14:10,320 --> 00:14:15,000 announced-- a global currency for billions of people. 276 00:14:15,000 --> 00:14:19,530 There was concern amongst the G7 and G20 countries, 277 00:14:19,530 --> 00:14:23,250 but there was also concern of a broader group of countries 278 00:14:23,250 --> 00:14:25,980 developing countries as well as to what this meant 279 00:14:25,980 --> 00:14:31,140 for their monetary policy, how stable this would really be, 280 00:14:31,140 --> 00:14:33,620 and whether it would compete with fiat currencies 281 00:14:33,620 --> 00:14:37,208 in not just a positive way, but maybe a negative way. 282 00:14:37,208 --> 00:14:39,000 And there were also a lot of concerns about 283 00:14:39,000 --> 00:14:43,830 whether it would support and somehow become 284 00:14:43,830 --> 00:14:46,110 the domain of illicit activity-- 285 00:14:46,110 --> 00:14:48,560 drug runners, and the like, and so forth. 286 00:14:48,560 --> 00:14:53,660 So Facebook is a big company. 287 00:14:53,660 --> 00:14:55,373 They stub their toes from time to time. 288 00:14:55,373 --> 00:14:57,040 This might have been one of those times, 289 00:14:57,040 --> 00:14:58,540 but it was an innovative project. 290 00:14:58,540 --> 00:15:01,210 So they announced last week some changes. 291 00:15:01,210 --> 00:15:04,100 And most importantly for this conversation-- 292 00:15:04,100 --> 00:15:07,180 and this is just a slide taken from-- 293 00:15:07,180 --> 00:15:10,190 I think it was a Medium post I found. 294 00:15:10,190 --> 00:15:13,780 They said that Libra would now be a platform. 295 00:15:13,780 --> 00:15:17,190 And they would do single currency tokens-- 296 00:15:17,190 --> 00:15:21,700 a euro token, a US dollar token, a sterling token, et cetera, 297 00:15:21,700 --> 00:15:22,420 et cetera. 298 00:15:22,420 --> 00:15:24,430 They'll still have a multi-basket, 299 00:15:24,430 --> 00:15:27,820 a multi-currency basket coin called Libra. 300 00:15:27,820 --> 00:15:31,120 But they'll have what's, in essence, stable value tokens. 301 00:15:31,120 --> 00:15:35,150 And they feel that there's still enough opportunity 302 00:15:35,150 --> 00:15:37,800 or as what we talked about-- pain points in the payment 303 00:15:37,800 --> 00:15:41,820 system that a dollar token, a euro token, a British sterling 304 00:15:41,820 --> 00:15:48,600 token, and the like is relevant and an important layer. 305 00:15:48,600 --> 00:15:50,970 What Libra also announced is that they're 306 00:15:50,970 --> 00:15:56,380 taking a tiered approach to this whole topic 307 00:15:56,380 --> 00:16:00,130 of anti-money laundering and know your customer. 308 00:16:00,130 --> 00:16:03,550 In essence, working with governments around the globe, 309 00:16:03,550 --> 00:16:09,220 they're saying they would only work with wallet providers. 310 00:16:09,220 --> 00:16:10,990 This would be single currency wallet 311 00:16:10,990 --> 00:16:15,010 providers or multi-currency Libra wallet providers. 312 00:16:15,010 --> 00:16:18,840 They'd only work with a digital wallet provider 313 00:16:18,840 --> 00:16:23,010 if it was in a jurisdiction that had regulation 314 00:16:23,010 --> 00:16:26,370 and those wallets and exchanges, if it 315 00:16:26,370 --> 00:16:29,340 was on a crypto exchange were well regulated 316 00:16:29,340 --> 00:16:32,610 within those countries or at least regulated and registered 317 00:16:32,610 --> 00:16:36,750 within those countries under the guidance around the globe 318 00:16:36,750 --> 00:16:39,060 that's issued by the FATF. 319 00:16:39,060 --> 00:16:42,600 The Financial Action Task Force is anti-money 320 00:16:42,600 --> 00:16:45,833 laundering standard setters around the globe. 321 00:16:45,833 --> 00:16:47,250 And they had said that they wanted 322 00:16:47,250 --> 00:16:49,410 to take a tiered approach that would even 323 00:16:49,410 --> 00:16:53,970 include on the permissioned blockchain in the protocol 324 00:16:53,970 --> 00:16:57,150 layer, in the software itself some protections 325 00:16:57,150 --> 00:16:58,170 against sanctions. 326 00:16:58,170 --> 00:16:59,628 Now, they didn't say whether it was 327 00:16:59,628 --> 00:17:03,700 sanctions that were UN sanctions, European sanctions, 328 00:17:03,700 --> 00:17:04,619 US sanctions. 329 00:17:04,619 --> 00:17:07,349 And then you get into some interesting geopolitical issues 330 00:17:07,349 --> 00:17:10,619 as to how Libra, the associations 331 00:17:10,619 --> 00:17:12,240 would sort through this. 332 00:17:12,240 --> 00:17:13,530 But it's interesting. 333 00:17:13,530 --> 00:17:15,839 Facebook is not giving up, just because there's 334 00:17:15,839 --> 00:17:17,460 a lot of push-back. 335 00:17:17,460 --> 00:17:19,920 And for those of you that might watch this online 336 00:17:19,920 --> 00:17:22,670 and might watch it in 2021 or 2022-- 337 00:17:22,670 --> 00:17:27,660 but this course will have a life for a while, offered online. 338 00:17:27,660 --> 00:17:29,090 It'll be interesting to look back 339 00:17:29,090 --> 00:17:33,300 to see what other adjustments at Facebook and Libra, 340 00:17:33,300 --> 00:17:37,650 done in '20 and 2021, to continue 341 00:17:37,650 --> 00:17:46,650 to meet the official sector and bring this thing to life going 342 00:17:46,650 --> 00:17:47,400 forward. 343 00:17:47,400 --> 00:17:49,890 Any questions on Libra? 344 00:17:49,890 --> 00:17:51,060 I had the opportunity. 345 00:17:51,060 --> 00:17:54,240 They actually reached out to me last week after our class. 346 00:17:54,240 --> 00:17:57,150 And they wanted to give you a little briefing to your faculty 347 00:17:57,150 --> 00:17:58,640 member on this. 348 00:18:03,230 --> 00:18:05,145 TA: I don't see any hands raised, Gary. 349 00:18:05,145 --> 00:18:06,145 GARY GENSLER: All right. 350 00:18:06,145 --> 00:18:08,840 So I'm going to sneak into credit. 351 00:18:08,840 --> 00:18:10,148 So what are the credit sectors? 352 00:18:10,148 --> 00:18:11,190 I mean, we all know them. 353 00:18:11,190 --> 00:18:15,820 This is pretty straightforward-- household sector 354 00:18:15,820 --> 00:18:17,340 and corporate sector. 355 00:18:17,340 --> 00:18:19,630 But the household sector-- the big pieces. 356 00:18:19,630 --> 00:18:22,400 And those of you that took the half semester 357 00:18:22,400 --> 00:18:25,210 of consumer finance course remember all this-- 358 00:18:25,210 --> 00:18:28,930 mortgages, autos, credit cards, personal loans, student loans. 359 00:18:28,930 --> 00:18:31,060 And then you can have sub-sectors. 360 00:18:31,060 --> 00:18:33,340 If you're thinking about disrupting this space, 361 00:18:33,340 --> 00:18:36,040 you would think, all right, where am I going to slice into? 362 00:18:36,040 --> 00:18:38,670 Am I going to try to do something in mortgages, 363 00:18:38,670 --> 00:18:40,750 or credit cards, or where? 364 00:18:40,750 --> 00:18:45,130 Am I going to try to go to the high end, the low credit 365 00:18:45,130 --> 00:18:47,110 risk super prime? 366 00:18:47,110 --> 00:18:50,730 Or am I going to try to be in the sub-prime marketplace? 367 00:18:50,730 --> 00:18:53,520 And these markets are vast. 368 00:18:53,520 --> 00:18:56,410 They're vast in nearly every country. 369 00:18:56,410 --> 00:19:00,490 So you'd pick and target what you're actually going for 370 00:19:00,490 --> 00:19:04,030 and literally whether you're picking debt consolidation 371 00:19:04,030 --> 00:19:08,140 or point-of-sale lending matters as well. 372 00:19:08,140 --> 00:19:10,180 The corporate sector is interesting. 373 00:19:10,180 --> 00:19:13,870 In terms of fintech, the corporate sector 374 00:19:13,870 --> 00:19:18,160 has been disrupted dramatically in earlier decades 375 00:19:18,160 --> 00:19:20,770 by the securitization markets. 376 00:19:20,770 --> 00:19:24,100 And asset securitizations happen primarily 377 00:19:24,100 --> 00:19:26,500 around the household sector. 378 00:19:26,500 --> 00:19:28,990 But asset securitization or a way 379 00:19:28,990 --> 00:19:33,580 to fund lending through the securities markets 380 00:19:33,580 --> 00:19:37,090 has come to the real estate and more recently 381 00:19:37,090 --> 00:19:41,560 to the collateralized loan markets or CLO markets. 382 00:19:41,560 --> 00:19:43,570 But in fact, when we really think 383 00:19:43,570 --> 00:19:45,970 about these markets, what's been focused 384 00:19:45,970 --> 00:19:49,090 on in terms of financial disruption 385 00:19:49,090 --> 00:19:51,550 is primarily the household sector. 386 00:19:51,550 --> 00:19:54,490 And then I circled the small business 387 00:19:54,490 --> 00:19:56,650 and small and medium-sized enterprise. 388 00:19:56,650 --> 00:19:59,110 Now, SME, mid-market companies could 389 00:19:59,110 --> 00:20:00,640 be defined all sorts of ways. 390 00:20:00,640 --> 00:20:03,550 In the middle of this corona crisis in the US, 391 00:20:03,550 --> 00:20:05,740 we seem to have latched on to companies that 392 00:20:05,740 --> 00:20:08,560 are less than 500 employees. 393 00:20:08,560 --> 00:20:12,790 It's not a specific definition somewhere around the globe. 394 00:20:12,790 --> 00:20:18,500 But large enterprises can access the securities markets 395 00:20:18,500 --> 00:20:19,000 directly. 396 00:20:19,000 --> 00:20:21,730 Large enterprises are, by and large, 397 00:20:21,730 --> 00:20:25,210 borrowing from big banks or securities markets. 398 00:20:25,210 --> 00:20:27,580 And the greatest opportunities have really 399 00:20:27,580 --> 00:20:32,710 been in the small business or SME market place. 400 00:20:32,710 --> 00:20:35,830 And it could be products like cash advance products, 401 00:20:35,830 --> 00:20:38,380 purchased credit, working capital lines. 402 00:20:38,380 --> 00:20:40,270 We'll get a little bit into this. 403 00:20:40,270 --> 00:20:42,970 But again, if you're thinking about credit, 404 00:20:42,970 --> 00:20:44,410 it's a vast market. 405 00:20:44,410 --> 00:20:48,700 And it's not one to just forget about all the little pieces 406 00:20:48,700 --> 00:20:49,810 in there. 407 00:20:49,810 --> 00:20:52,040 Romain, I think there were some questions. 408 00:20:52,040 --> 00:20:52,730 Sure. 409 00:20:52,730 --> 00:20:54,400 TA: Yes, we have a question from Victor. 410 00:20:54,400 --> 00:20:56,320 GARY GENSLER: Please. 411 00:20:56,320 --> 00:21:01,150 AUDIENCE: [INAUDIBLE] see the point 412 00:21:01,150 --> 00:21:07,905 of why [INAUDIBLE] euro, dollar, whatever. 413 00:21:07,905 --> 00:21:09,280 The stable dollar already exceeds 414 00:21:09,280 --> 00:21:11,170 in the cryptocurrency market. 415 00:21:11,170 --> 00:21:15,040 And I even, in that case, fully understand what [INAUDIBLE] 416 00:21:15,040 --> 00:21:17,092 with less fees. 417 00:21:17,092 --> 00:21:17,800 GARY GENSLER: OK. 418 00:21:17,800 --> 00:21:20,170 So, Romain, Victor was cutting in and out. 419 00:21:20,170 --> 00:21:24,880 I think, if I understood the question, is back to Facebook 420 00:21:24,880 --> 00:21:29,230 and why they have the stable individual currencies, 421 00:21:29,230 --> 00:21:30,340 but I'm not certain. 422 00:21:30,340 --> 00:21:31,630 I'm sorry. 423 00:21:31,630 --> 00:21:37,180 So around the globe, there are definitely 424 00:21:37,180 --> 00:21:41,950 shortcomings of our fiat payment systems, these pain points. 425 00:21:41,950 --> 00:21:45,430 Some of it just relates to whether the payment systems 426 00:21:45,430 --> 00:21:47,800 are 24 hours a day, seven days a week. 427 00:21:47,800 --> 00:21:53,230 In terms of the euro, actually the target payment system 428 00:21:53,230 --> 00:21:59,950 run by the European Central Bank does have attributes of 24/7. 429 00:21:59,950 --> 00:22:03,050 The US-- we have more challenges in that regard. 430 00:22:03,050 --> 00:22:08,050 But the bigger issue often in payment systems are costs. 431 00:22:08,050 --> 00:22:13,680 And so what Facebook Libra is saying is, 432 00:22:13,680 --> 00:22:19,440 we can provide something that can compete in this space. 433 00:22:19,440 --> 00:22:22,560 But money is already digital Fiat money, 434 00:22:22,560 --> 00:22:23,940 the euro is already digital. 435 00:22:23,940 --> 00:22:26,490 So Libra and Facebook are not providing that. 436 00:22:26,490 --> 00:22:29,330 They're saying this is a different digital euro 437 00:22:29,330 --> 00:22:32,130 or a different digital dollar that can maybe 438 00:22:32,130 --> 00:22:35,160 move 24 hours a day, seven days a week 439 00:22:35,160 --> 00:22:38,080 where you can get instantaneous settlement. 440 00:22:38,080 --> 00:22:39,990 Now, the US Federal Reserve is moving there. 441 00:22:39,990 --> 00:22:42,300 And we'll be there by 2023 or '24. 442 00:22:42,300 --> 00:22:45,970 And in fact, even in the US, the clearinghouse, 443 00:22:45,970 --> 00:22:47,820 as we talked about, the organization 444 00:22:47,820 --> 00:22:53,130 of about 24 major banks have it in a continuous real time 445 00:22:53,130 --> 00:22:54,300 payment system. 446 00:22:54,300 --> 00:22:57,540 Europe is already moving to that continuous real time payment 447 00:22:57,540 --> 00:22:58,040 system. 448 00:22:58,040 --> 00:23:03,240 So you might say, why would a Libra euro compete with that? 449 00:23:03,240 --> 00:23:07,880 Partly because it would be on the Facebook platform. 450 00:23:07,880 --> 00:23:10,620 And the thought is that Facebook would embed it 451 00:23:10,620 --> 00:23:12,850 into their system. 452 00:23:12,850 --> 00:23:14,800 It's to some extent to try to compete 453 00:23:14,800 --> 00:23:17,890 with what Amazon, and Alibaba, and Tencent 454 00:23:17,890 --> 00:23:20,800 are doing elsewhere as well. 455 00:23:20,800 --> 00:23:24,580 But implied in your question is, so what? 456 00:23:24,580 --> 00:23:26,270 Why would this matter? 457 00:23:26,270 --> 00:23:28,210 And I think it's a competitive landscape. 458 00:23:28,210 --> 00:23:31,750 And time will tell us whether it will really matter. 459 00:23:31,750 --> 00:23:33,700 Because we already had digital euros. 460 00:23:33,700 --> 00:23:36,920 This would be a different form of a digital euro. 461 00:23:36,920 --> 00:23:39,080 AUDIENCE: [INAUDIBLE] of an overlap, I guess. 462 00:23:39,080 --> 00:23:40,205 GARY GENSLER: That's right. 463 00:23:40,205 --> 00:23:41,320 That's right. 464 00:23:41,320 --> 00:23:43,120 TA: And I think, Gary, on the same topic, 465 00:23:43,120 --> 00:23:44,667 we might have a question from Luke. 466 00:23:44,667 --> 00:23:45,500 GARY GENSLER: It is. 467 00:23:45,500 --> 00:23:46,340 Luke? 468 00:23:46,340 --> 00:23:48,500 AUDIENCE: [INAUDIBLE] 469 00:23:48,500 --> 00:23:50,500 GARY GENSLER: Again, Luke is not coming through. 470 00:23:50,500 --> 00:23:51,220 I don't know. 471 00:23:51,220 --> 00:23:52,450 AUDIENCE: I'm here. 472 00:23:52,450 --> 00:23:54,970 So each question is, what is the main difference 473 00:23:54,970 --> 00:23:58,420 between Libra 1.0 and the 2.0? 474 00:23:58,420 --> 00:24:01,600 Because 1.0, I believe, was suggesting currency basket. 475 00:24:01,600 --> 00:24:04,680 And second question was regarding LendingClub. 476 00:24:04,680 --> 00:24:06,040 It's down a lot-- 477 00:24:06,040 --> 00:24:10,210 42% in three months and 93% since five years. 478 00:24:10,210 --> 00:24:14,890 And will it drive during this consumer equity crunch that 479 00:24:14,890 --> 00:24:18,310 is the quarantine recession we have now 480 00:24:18,310 --> 00:24:20,800 or suffer from high leverage? 481 00:24:20,800 --> 00:24:23,410 Because it acquired a brick and mortar bank, 482 00:24:23,410 --> 00:24:25,890 which seems untimely these days. 483 00:24:25,890 --> 00:24:29,460 And regarding the currency basket, 484 00:24:29,460 --> 00:24:31,750 wouldn't it suffer during economy downturns 485 00:24:31,750 --> 00:24:34,600 when there's a distortion between safe currencies 486 00:24:34,600 --> 00:24:42,070 such as the US dollar, Swiss franc, and the emerging market 487 00:24:42,070 --> 00:24:46,000 currency that is R&B or whatever they're really 488 00:24:46,000 --> 00:24:47,308 putting in the basket? 489 00:24:47,308 --> 00:24:48,100 GARY GENSLER: Yeah. 490 00:24:48,100 --> 00:24:49,780 First, let me compliment. 491 00:24:49,780 --> 00:24:52,380 I love the Edvard Munch that you have behind you. 492 00:24:52,380 --> 00:24:54,820 I assume it's just a visual. 493 00:24:54,820 --> 00:24:59,210 But if it's an original, protected safely. 494 00:24:59,210 --> 00:25:01,600 To your second question, LendingClub, 495 00:25:01,600 --> 00:25:05,650 I think that all of the marketplace lenders 496 00:25:05,650 --> 00:25:09,010 have some challenges in the middle of the corona crisis. 497 00:25:09,010 --> 00:25:13,310 I think that their early promise has improved that completely. 498 00:25:13,310 --> 00:25:15,940 So you're right that it went-- 499 00:25:15,940 --> 00:25:17,380 it's a public company, actually-- 500 00:25:17,380 --> 00:25:17,950 LendingClub. 501 00:25:17,950 --> 00:25:19,020 It went public. 502 00:25:19,020 --> 00:25:21,970 Its stock came off dramatically, 70% or 80%, 503 00:25:21,970 --> 00:25:26,860 even well before this corona crisis. 504 00:25:26,860 --> 00:25:31,120 Then within the crisis, it's come off some more as well. 505 00:25:31,120 --> 00:25:32,140 It's buying a bank. 506 00:25:32,140 --> 00:25:34,120 It's not technically a bricks and mortar bank. 507 00:25:34,120 --> 00:25:37,660 That bank, I think, has one location in Massachusetts, 508 00:25:37,660 --> 00:25:39,550 maybe in Boston. 509 00:25:39,550 --> 00:25:41,380 It's an online bank. 510 00:25:41,380 --> 00:25:43,150 And what they're trying to do-- 511 00:25:43,150 --> 00:25:45,670 their theory of the case is that they want 512 00:25:45,670 --> 00:25:47,440 to lower their borrowing costs. 513 00:25:47,440 --> 00:25:50,260 Because marketplace lenders-- and we'll see this 514 00:25:50,260 --> 00:25:51,690 in a moment-- 515 00:25:51,690 --> 00:25:57,060 arrange with some banks to borrow money. 516 00:25:57,060 --> 00:26:01,000 So marketplace lenders are from the markets. 517 00:26:01,000 --> 00:26:04,200 Some of it's securitized, some from banks. 518 00:26:04,200 --> 00:26:06,540 And what they're saying is, we can maybe lower our costs 519 00:26:06,540 --> 00:26:09,060 by embedding a bank. 520 00:26:09,060 --> 00:26:12,510 Back to Libra, and Facebook, and the like, 521 00:26:12,510 --> 00:26:17,030 the main difference between Libra 1.0 and 2.0 522 00:26:17,030 --> 00:26:18,362 are the two that I mentioned. 523 00:26:18,362 --> 00:26:20,820 I mean, they would say there's three or four other changes. 524 00:26:20,820 --> 00:26:28,320 But one is rather than only be a multi-currency coin, Libra, 525 00:26:28,320 --> 00:26:30,275 they're adding individual coins. 526 00:26:30,275 --> 00:26:32,400 They're not getting rid of the multi-currency coin. 527 00:26:32,400 --> 00:26:34,780 The multi-currency coin is still there. 528 00:26:34,780 --> 00:26:38,310 It's still their aspiration to have a multi-currency coin. 529 00:26:38,310 --> 00:26:40,830 But they're adding the single coins 530 00:26:40,830 --> 00:26:45,070 to try to give a new euro digital dollar to it. 531 00:26:45,070 --> 00:26:47,865 And secondly, they're adding much more-- 532 00:26:50,690 --> 00:26:54,710 know your customer anti-money laundering regimes by saying, 533 00:26:54,710 --> 00:26:59,290 look, we're only going to work with digital wallets and crypto 534 00:26:59,290 --> 00:27:02,160 exchanges in certain jurisdictions which 535 00:27:02,160 --> 00:27:06,160 are registered and following anti-money laundering law. 536 00:27:06,160 --> 00:27:11,590 And additionally, we'll embed in the software some protocols, 537 00:27:11,590 --> 00:27:16,390 literally in the software to guard against either sanctions 538 00:27:16,390 --> 00:27:17,620 and some other things. 539 00:27:17,620 --> 00:27:21,250 Whether this will be enough to satisfy the official sector, 540 00:27:21,250 --> 00:27:22,540 yet to be seen. 541 00:27:22,540 --> 00:27:24,880 It looks like they're moving first with Switzerland 542 00:27:24,880 --> 00:27:29,070 and trying to have Switzerland's regulator, FINMA, capture 543 00:27:29,070 --> 00:27:30,597 it and move forward. 544 00:27:30,597 --> 00:27:32,680 I'll take one brief-- more question, because we've 545 00:27:32,680 --> 00:27:35,140 got a lot to cover, but sure. 546 00:27:35,140 --> 00:27:38,230 TA: So Cindy had her hand up for one. 547 00:27:38,230 --> 00:27:40,855 If you want to talk, unmute yourself, please. 548 00:27:40,855 --> 00:27:41,480 AUDIENCE: Yeah. 549 00:27:41,480 --> 00:27:43,690 I'll just ask briefly. 550 00:27:43,690 --> 00:27:48,100 But with household private sectors, 551 00:27:48,100 --> 00:27:52,390 how are they preventing against predatory lending? 552 00:27:52,390 --> 00:27:55,850 Because just through reading some of the articles, 553 00:27:55,850 --> 00:28:00,850 it seems like that becomes a gray line when you're targeting 554 00:28:00,850 --> 00:28:04,270 specific type of customer who doesn't 555 00:28:04,270 --> 00:28:07,427 qualify for traditional loans. 556 00:28:07,427 --> 00:28:09,760 GARY GENSLER: So you're talking about more broadly, just 557 00:28:09,760 --> 00:28:13,750 in terms of, how do we guard in any country 558 00:28:13,750 --> 00:28:15,090 against predatory lending? 559 00:28:15,090 --> 00:28:16,850 It's hard. 560 00:28:16,850 --> 00:28:17,650 It's hard. 561 00:28:17,650 --> 00:28:23,140 The entire credit space has a lot of protections 562 00:28:23,140 --> 00:28:26,260 and regulations starting in-- 563 00:28:26,260 --> 00:28:30,220 well, I would say starting hundreds of years ago, really. 564 00:28:30,220 --> 00:28:32,590 One would even go back to the Hammurabi Code 565 00:28:32,590 --> 00:28:34,950 and say there was regulation of interest rates. 566 00:28:34,950 --> 00:28:38,350 But in the modern days, we embedded-- 567 00:28:38,350 --> 00:28:40,840 let's take the US for a moment. 568 00:28:40,840 --> 00:28:42,570 Two really important things. 569 00:28:42,570 --> 00:28:45,010 One was the Equal Credit Opportunity 570 00:28:45,010 --> 00:28:48,550 Act or what some people call ECOA, 571 00:28:48,550 --> 00:28:51,347 which was in the late 1960s and then 572 00:28:51,347 --> 00:28:53,680 something called the Fair Credit Reporting Act, I think, 573 00:28:53,680 --> 00:28:54,880 by 1972. 574 00:28:54,880 --> 00:29:00,490 These two came out of an earlier way, the fintech, an earlier 575 00:29:00,490 --> 00:29:05,950 wave of credit cards, an earlier wave of lending 576 00:29:05,950 --> 00:29:10,818 and directly to this question about whether it was fair 577 00:29:10,818 --> 00:29:11,860 and whether it was equal. 578 00:29:11,860 --> 00:29:15,790 Everybody had the same access, Equal Credit Opportunity Act, 579 00:29:15,790 --> 00:29:18,790 that you couldn't differentiate because of gender, or race, 580 00:29:18,790 --> 00:29:23,800 or nationality, and the like and Fair Credit Reporting, 581 00:29:23,800 --> 00:29:25,470 that those credit reports. 582 00:29:25,470 --> 00:29:31,270 The things that we came to know and in about 30 countries rely 583 00:29:31,270 --> 00:29:35,440 on, is these FICO scores from a company called the Fair Isaac 584 00:29:35,440 --> 00:29:38,170 company, that those scores-- 585 00:29:38,170 --> 00:29:40,710 we'd have to be able to know something about them. 586 00:29:40,710 --> 00:29:43,120 And if we were turned down, somebody 587 00:29:43,120 --> 00:29:47,980 has to explain to us how we were turned down. 588 00:29:47,980 --> 00:29:50,950 Well, now, fast forward to 2020. 589 00:29:50,950 --> 00:29:51,790 Absolutely. 590 00:29:51,790 --> 00:29:52,840 The question is right. 591 00:29:52,840 --> 00:29:56,770 How can we protect that we still have equal credit 592 00:29:56,770 --> 00:29:59,110 and that it's explainable? 593 00:29:59,110 --> 00:30:00,980 And why is somebody turned down? 594 00:30:00,980 --> 00:30:06,310 And once somebody is not allowed to take credit, 595 00:30:06,310 --> 00:30:09,400 it gets tougher with artificial intelligence and machine 596 00:30:09,400 --> 00:30:09,980 learning. 597 00:30:09,980 --> 00:30:11,530 It also gets tougher when there's not 598 00:30:11,530 --> 00:30:13,510 a physical location. 599 00:30:13,510 --> 00:30:15,550 And thirdly, many of these companies 600 00:30:15,550 --> 00:30:19,030 are not regulated or registered as banks. 601 00:30:19,030 --> 00:30:21,760 And regulators around the globe tended 602 00:30:21,760 --> 00:30:27,670 to look to banks to make sure that these laws were 603 00:30:27,670 --> 00:30:28,780 fairly applied. 604 00:30:28,780 --> 00:30:31,850 Now, they also look to the credit reporting agencies. 605 00:30:31,850 --> 00:30:35,740 So I think the real answer is in these changing times, 606 00:30:35,740 --> 00:30:38,860 the official sector around the globe 607 00:30:38,860 --> 00:30:43,570 has to adapt and sometimes change a little bit of who 608 00:30:43,570 --> 00:30:47,110 is regulated and even if you're a non-bank, that you still 609 00:30:47,110 --> 00:30:50,417 have to comply with some of these things, importantly. 610 00:30:50,417 --> 00:30:51,250 AUDIENCE: Thank you. 611 00:30:53,448 --> 00:30:54,990 GARY GENSLER: So let me just give you 612 00:30:54,990 --> 00:30:56,460 a sense of the size and scope. 613 00:30:56,460 --> 00:30:59,280 The household sector-- you can look at this later 614 00:30:59,280 --> 00:31:02,010 in the Canvas slides, but the household sector-- 615 00:31:02,010 --> 00:31:03,610 grown dramatically. 616 00:31:03,610 --> 00:31:08,100 And if you look in the United States, 617 00:31:08,100 --> 00:31:12,510 we're no longer the top percent of GDP. 618 00:31:12,510 --> 00:31:16,380 In fact, I think Luke is in Korea now. 619 00:31:16,380 --> 00:31:18,980 Your country is now peaked up to be number two. 620 00:31:18,980 --> 00:31:20,280 But look at China. 621 00:31:20,280 --> 00:31:25,440 China from 10 to 20% of GDP just 15 years ago. 622 00:31:25,440 --> 00:31:28,080 And all of a sudden, 50% of GDP. 623 00:31:28,080 --> 00:31:30,990 So these markets have grown a lot in many countries. 624 00:31:30,990 --> 00:31:33,990 I wouldn't just think about this in the US. 625 00:31:33,990 --> 00:31:36,510 And Brazil and India-- 626 00:31:36,510 --> 00:31:39,220 I would predict, will grow significantly as well. 627 00:31:39,220 --> 00:31:44,730 Now, in the US, we've got about $14 trillion of household debt. 628 00:31:44,730 --> 00:31:48,690 Before the corona crisis, we had at $22 trillion economy. 629 00:31:48,690 --> 00:31:50,970 And so you could see it's about 2/3 630 00:31:50,970 --> 00:31:55,590 of our economy, the underlying consumer household debt. 631 00:31:55,590 --> 00:31:58,635 The corporate sector-- very important as well. 632 00:32:02,280 --> 00:32:05,610 But it's the household sector dominated in the US 633 00:32:05,610 --> 00:32:07,710 by mortgages-- 634 00:32:07,710 --> 00:32:11,730 2/3 of that 2/3 or about $10 trillion, $11 trillion 635 00:32:11,730 --> 00:32:14,760 of mortgage market. 636 00:32:14,760 --> 00:32:17,820 But each of these markets are really significant. 637 00:32:17,820 --> 00:32:20,190 Even the auto lending market-- 638 00:32:20,190 --> 00:32:27,360 it might look small at these numbers here, but they're not. 639 00:32:27,360 --> 00:32:30,210 That's a big number when you come at it 640 00:32:30,210 --> 00:32:32,550 and if you wanted to pursue that business. 641 00:32:32,550 --> 00:32:35,340 And a little bit on the non-financial corporate debt 642 00:32:35,340 --> 00:32:37,290 market-- 643 00:32:37,290 --> 00:32:38,930 we'll see this shake out. 644 00:32:38,930 --> 00:32:42,000 Post the corona crisis, a lot of these numbers 645 00:32:42,000 --> 00:32:44,860 will go up significantly. 646 00:32:44,860 --> 00:32:48,090 And I would say one thing just off the topic of fintech. 647 00:32:48,090 --> 00:32:52,800 I think that though we didn't enter this crisis 648 00:32:52,800 --> 00:32:57,100 with a household debt problem in most countries, 649 00:32:57,100 --> 00:33:01,550 we had a real household debt problem going into 2008 crisis. 650 00:33:01,550 --> 00:33:04,890 While we didn't enter this with a household debt crisis, 651 00:33:04,890 --> 00:33:07,210 within three to six months in most countries, 652 00:33:07,210 --> 00:33:09,690 we will have a household debt crisis, I fear. 653 00:33:09,690 --> 00:33:16,120 Because the consumer sector can't be supporting their auto 654 00:33:16,120 --> 00:33:18,130 loans and credit card loans. 655 00:33:18,130 --> 00:33:19,750 And one of the reasons I think this 656 00:33:19,750 --> 00:33:22,420 is unlikely to be of the recession, 657 00:33:22,420 --> 00:33:24,490 but it's going to be a long U recession, 658 00:33:24,490 --> 00:33:26,110 almost like it's a bathtub trying 659 00:33:26,110 --> 00:33:29,590 to get out the slippery slopes of this recession, 660 00:33:29,590 --> 00:33:31,870 is around the globe, households are 661 00:33:31,870 --> 00:33:34,440 going to have to repair their balance sheets. 662 00:33:34,440 --> 00:33:36,760 You're going to have to slowly repair balance sheets. 663 00:33:36,760 --> 00:33:40,990 And it's not going to be easy, so true also 664 00:33:40,990 --> 00:33:43,990 in the corporate sector, most likely. 665 00:33:43,990 --> 00:33:45,850 But the market design matters-- 666 00:33:45,850 --> 00:33:48,710 if you are creating a fintech company, 667 00:33:48,710 --> 00:33:51,190 you would think about the market design. 668 00:33:51,190 --> 00:33:53,420 And I'm not going to dive into this. 669 00:33:53,420 --> 00:33:56,530 But each one of these pieces gives an opportunity 670 00:33:56,530 --> 00:33:58,570 to break into the credit markets. 671 00:33:58,570 --> 00:34:00,400 It might be around data. 672 00:34:00,400 --> 00:34:05,110 You might have a particular area that you could do better data 673 00:34:05,110 --> 00:34:06,940 or like Credit Karma. 674 00:34:06,940 --> 00:34:12,610 Credit Karma was really about providing free credit scoring. 675 00:34:12,610 --> 00:34:15,610 Think about this-- just free credit scores. 676 00:34:15,610 --> 00:34:18,880 And Credit Karma then could cross sell and market 677 00:34:18,880 --> 00:34:22,060 your products Credit Karma company was 678 00:34:22,060 --> 00:34:26,654 formed less than 10 years ago, sold earlier in 2020 679 00:34:26,654 --> 00:34:31,030 for $5 billion to Intuit, Intuit that 680 00:34:31,030 --> 00:34:36,370 has the TurboTax, and this accounting 681 00:34:36,370 --> 00:34:37,630 software, and the like. 682 00:34:37,630 --> 00:34:45,030 But Credit Karma had 106 million individual files 683 00:34:45,030 --> 00:34:49,260 on various folks, not all of whom are their customers. 684 00:34:49,260 --> 00:34:50,610 But they cross sell. 685 00:34:50,610 --> 00:34:53,790 They had nearly a billion dollars in revenue in 2019. 686 00:34:53,790 --> 00:34:55,290 It might be on the funding side. 687 00:34:55,290 --> 00:34:59,310 You might have a new way to do securitization or your issuer 688 00:34:59,310 --> 00:35:00,307 bank partnership. 689 00:35:00,307 --> 00:35:01,140 And we talked about. 690 00:35:01,140 --> 00:35:03,780 LendingClub had an issuer bank partner. 691 00:35:03,780 --> 00:35:06,690 Now, they're trying to buy a bank. 692 00:35:06,690 --> 00:35:08,670 It might be on the funding side. 693 00:35:08,670 --> 00:35:11,750 And that's what peer-to-peer lending tried to do. 694 00:35:11,750 --> 00:35:14,970 And they haven't been as broadly successful. 695 00:35:14,970 --> 00:35:18,300 Most importantly, I would say that it's usually 696 00:35:18,300 --> 00:35:21,510 been on user experience and user interface. 697 00:35:21,510 --> 00:35:24,660 And sometimes it's that you got in through the payment 698 00:35:24,660 --> 00:35:28,710 channels, like Toast getting into the restaurant sector 699 00:35:28,710 --> 00:35:29,970 through the payment. 700 00:35:29,970 --> 00:35:32,280 Toast was a company out of Boston. 701 00:35:32,280 --> 00:35:33,900 It was really about software. 702 00:35:33,900 --> 00:35:35,760 It was about tablets and hardware 703 00:35:35,760 --> 00:35:41,160 as well, that the restaurant server had a better user 704 00:35:41,160 --> 00:35:42,000 experience. 705 00:35:42,000 --> 00:35:43,980 And the restaurant had a better experience 706 00:35:43,980 --> 00:35:46,980 in the tablet and payment side. 707 00:35:46,980 --> 00:35:49,260 And then they started to build Toast credit 708 00:35:49,260 --> 00:35:51,660 to provide those restaurants credit. 709 00:35:51,660 --> 00:35:54,210 Now, there's going to be a shakeout there, no doubt, 710 00:35:54,210 --> 00:35:58,170 in terms of this crisis, the corona crisis. 711 00:35:58,170 --> 00:36:02,560 It might be that you're breaking into some slice of risk. 712 00:36:02,560 --> 00:36:05,760 And this has been a case for a lot of companies 713 00:36:05,760 --> 00:36:09,820 that have broken into manage one risk or another better. 714 00:36:09,820 --> 00:36:12,640 And then lastly, what role are you in? 715 00:36:12,640 --> 00:36:16,260 In the mortgage markets here in the US-- and we found 716 00:36:16,260 --> 00:36:20,570 that origination has really changed. 717 00:36:20,570 --> 00:36:22,490 And we'll look at the competitive landscape. 718 00:36:22,490 --> 00:36:26,810 But companies like Quicken Loan, and PennyMac, and others 719 00:36:26,810 --> 00:36:28,160 have broken in. 720 00:36:28,160 --> 00:36:30,260 And they've broken in on the origination side. 721 00:36:30,260 --> 00:36:33,410 And that's partly because the uniqueness in the US mortgage 722 00:36:33,410 --> 00:36:34,250 market-- 723 00:36:34,250 --> 00:36:37,100 that our government-sponsored enterprises guarantee 724 00:36:37,100 --> 00:36:39,000 the bulk of the market. 725 00:36:39,000 --> 00:36:43,040 So the balance sheet credit risk is diminished. 726 00:36:43,040 --> 00:36:47,380 And Quicken Loan, and PennyMac, and others can come in. 727 00:36:47,380 --> 00:36:49,520 And probably over half the market 728 00:36:49,520 --> 00:36:52,700 is originated by companies that are broadly 729 00:36:52,700 --> 00:36:55,130 speaking disruptors. 730 00:36:55,130 --> 00:36:56,750 So again, it could be data. 731 00:36:56,750 --> 00:36:57,630 It could be funding. 732 00:36:57,630 --> 00:36:59,630 It could be the user experience, which 733 00:36:59,630 --> 00:37:04,340 is really a critical one, maybe the risks, the roles. 734 00:37:04,340 --> 00:37:06,980 Any piece of these might give an opportunity 735 00:37:06,980 --> 00:37:10,100 to break into a market or to do something different 736 00:37:10,100 --> 00:37:11,720 than the financial incumbents. 737 00:37:15,650 --> 00:37:20,140 So the earlier fintech, way back-- 738 00:37:20,140 --> 00:37:22,840 I'm going to take you to a story about an earlier fintech 739 00:37:22,840 --> 00:37:23,530 that I like. 740 00:37:23,530 --> 00:37:25,900 It's just credit cards. 741 00:37:25,900 --> 00:37:27,640 The first use of the term credit card 742 00:37:27,640 --> 00:37:31,690 was in the 1880s in a dystopian-- 743 00:37:31,690 --> 00:37:33,880 I would call it, but utopian book that 744 00:37:33,880 --> 00:37:35,830 was written by Edward Bellamy. 745 00:37:35,830 --> 00:37:37,780 It was a New York Times bestseller. 746 00:37:37,780 --> 00:37:41,170 It was a bestseller in multiple languages around the globe, 747 00:37:41,170 --> 00:37:43,570 talking about the year 2000. 748 00:37:43,570 --> 00:37:46,030 Well, Bellamy-- you could go back and look at the book. 749 00:37:46,030 --> 00:37:48,010 It's really science fiction. 750 00:37:48,010 --> 00:37:50,890 But use the term credit card. 751 00:37:50,890 --> 00:37:53,020 It's the first known use of the concept 752 00:37:53,020 --> 00:37:56,920 that you would have a card for payments. 753 00:37:56,920 --> 00:38:00,400 Well, shortly thereafter, not really because of Bellamy, 754 00:38:00,400 --> 00:38:03,880 you saw a bunch of companies starting to use charge coins 755 00:38:03,880 --> 00:38:05,020 and charge cards. 756 00:38:05,020 --> 00:38:08,980 And by the 1920s, these merchant cards-- 757 00:38:08,980 --> 00:38:12,970 you had an individual merchant providing credit and saying you 758 00:38:12,970 --> 00:38:14,860 can buy something on credit. 759 00:38:14,860 --> 00:38:17,380 You could call that a point-of-sale credit. 760 00:38:17,380 --> 00:38:20,320 Earlier fintech-- about a hundred years ago. 761 00:38:20,320 --> 00:38:26,230 But in the 1940s, one banker in Brooklyn 762 00:38:26,230 --> 00:38:28,720 never made a lot of money for themselves. 763 00:38:28,720 --> 00:38:34,900 One banker came up with the concept of a credit system 764 00:38:34,900 --> 00:38:38,170 where it was multiple merchants. 765 00:38:38,170 --> 00:38:41,410 Not one merchant, but multiple merchants. 766 00:38:41,410 --> 00:38:43,720 And that charge card-- 767 00:38:43,720 --> 00:38:49,420 75 years ago, so a long time ago, but still somewhat recent. 768 00:38:49,420 --> 00:38:52,030 And that led to the 1940s and '50s, 769 00:38:52,030 --> 00:38:55,060 all these innovations-- the first plastic card. 770 00:38:55,060 --> 00:38:58,300 BankAmericard was from a California bank. 771 00:38:58,300 --> 00:39:00,430 And that's where Visa started. 772 00:39:00,430 --> 00:39:03,850 So all of that was fintech of the time. 773 00:39:03,850 --> 00:39:05,460 And the only reason I mention it is 774 00:39:05,460 --> 00:39:08,740 if you think about what disruptions have come before 775 00:39:08,740 --> 00:39:11,260 that now we take for granted, sometimes 776 00:39:11,260 --> 00:39:13,960 that's evidence in what you might do now. 777 00:39:13,960 --> 00:39:17,590 BankAmericard was a California bank 778 00:39:17,590 --> 00:39:20,980 that was trying to partner with other banks around the country 779 00:39:20,980 --> 00:39:22,480 and partnered with other countries 780 00:39:22,480 --> 00:39:27,280 to do something that was more universal for the country. 781 00:39:27,280 --> 00:39:30,490 The Diners Club was literally about this restaurant concept. 782 00:39:30,490 --> 00:39:32,710 You would consider it almost like a general merchant 783 00:39:32,710 --> 00:39:34,720 card, an early Toast. 784 00:39:34,720 --> 00:39:36,940 The Diners Club did what maybe Toast 785 00:39:36,940 --> 00:39:39,880 is trying to do now, inside the restaurants, 786 00:39:39,880 --> 00:39:45,910 providing more use of those initially high-end restaurants 787 00:39:45,910 --> 00:39:46,840 on the East Coast. 788 00:39:49,850 --> 00:39:53,360 So what disruptions are in the value chain now? 789 00:39:53,360 --> 00:39:57,510 And particularly, this little chart-- 790 00:39:57,510 --> 00:40:02,120 I borrow from an interesting long paper on it, 791 00:40:02,120 --> 00:40:04,940 is think about the different parts of the value chain. 792 00:40:04,940 --> 00:40:07,100 Whether you're sourcing capital, you're 793 00:40:07,100 --> 00:40:08,420 actually assessing credit. 794 00:40:08,420 --> 00:40:10,430 That's the underwriting of the credit 795 00:40:10,430 --> 00:40:13,040 or actually just servicing the credit 796 00:40:13,040 --> 00:40:15,360 like you're servicing a student loan. 797 00:40:15,360 --> 00:40:18,150 It can be any part of the value chain. 798 00:40:18,150 --> 00:40:19,550 And you could go in and disrupt. 799 00:40:19,550 --> 00:40:21,890 And we're not going to dive into this chart. 800 00:40:21,890 --> 00:40:24,147 But I'll just take disbursements for a minute. 801 00:40:24,147 --> 00:40:25,730 If you look at that vertical, it could 802 00:40:25,730 --> 00:40:28,580 be digital wallets, or virtual currency, 803 00:40:28,580 --> 00:40:30,200 or the machine learning. 804 00:40:30,200 --> 00:40:34,470 If it's in credit assessment, it could be the alternative data. 805 00:40:34,470 --> 00:40:37,970 So each of these provides a little opportunity 806 00:40:37,970 --> 00:40:41,540 to disrupt the current business model. 807 00:40:41,540 --> 00:40:44,350 And so we talked about payments last class, credit. 808 00:40:44,350 --> 00:40:46,660 You really have to get, in a sense, 809 00:40:46,660 --> 00:40:49,930 granular into which part of the value chain. 810 00:40:49,930 --> 00:40:52,510 And then, how do I bring a technology to it 811 00:40:52,510 --> 00:40:54,430 that maybe the big incumbents aren't yet 812 00:40:54,430 --> 00:40:58,300 doing in a sufficiently sophisticated way? 813 00:40:58,300 --> 00:41:00,130 Or you might just bring it to one sector 814 00:41:00,130 --> 00:41:02,560 like Toast did to the restaurant sector. 815 00:41:02,560 --> 00:41:05,020 It might be sector specific. 816 00:41:05,020 --> 00:41:06,640 So where do we go? 817 00:41:06,640 --> 00:41:09,400 Well, we've already seen big techs there, 818 00:41:09,400 --> 00:41:11,350 the payment unicorns. 819 00:41:11,350 --> 00:41:13,300 There's hundreds of other payment companies 820 00:41:13,300 --> 00:41:17,480 that are building credit on top of payment. 821 00:41:17,480 --> 00:41:21,080 And sometimes a payment company is really also a credit 822 00:41:21,080 --> 00:41:26,070 company, like Brex is both payment and credit. 823 00:41:26,070 --> 00:41:28,640 AvidXchange is mostly payment, but is 824 00:41:28,640 --> 00:41:35,040 moving into credit and then some that are built just on credit. 825 00:41:35,040 --> 00:41:38,540 And so I thought I would start with the business side-- 826 00:41:38,540 --> 00:41:41,240 small, medium-sized enterprise lending. 827 00:41:41,240 --> 00:41:44,380 Again, there's no really good definition of SME. 828 00:41:44,380 --> 00:41:46,970 But the definition that these companies would take at it-- 829 00:41:46,970 --> 00:41:49,760 they would say these are companies 830 00:41:49,760 --> 00:41:53,420 that are having difficulty borrowing from the big banks. 831 00:41:53,420 --> 00:41:57,870 It's either assessing credit or providing 832 00:41:57,870 --> 00:42:03,370 that credit in a timely and a cost-effective way. 833 00:42:03,370 --> 00:42:06,640 Brex is an interesting company that started around the concept 834 00:42:06,640 --> 00:42:11,560 that, I can't get money as a startup. 835 00:42:11,560 --> 00:42:14,300 How can I even get a credit card if I had a-- 836 00:42:14,300 --> 00:42:24,220 it's a mixture of seed investing and credit card provisions. 837 00:42:24,220 --> 00:42:26,800 Some of these companies I put on here like Amazon, 838 00:42:26,800 --> 00:42:28,750 Alipay are big tech. 839 00:42:28,750 --> 00:42:30,370 I don't think you can leave them out. 840 00:42:30,370 --> 00:42:33,190 Some started in the payment side like Square 841 00:42:33,190 --> 00:42:36,280 and Stripe and Toast-- 842 00:42:36,280 --> 00:42:38,140 which I mentioned earlier-- 843 00:42:38,140 --> 00:42:39,190 PayPal. 844 00:42:39,190 --> 00:42:42,460 All provide small and medium-sized enterprise 845 00:42:42,460 --> 00:42:43,350 lending. 846 00:42:43,350 --> 00:42:48,520 Some are really just like Kabbage and Lendio, 847 00:42:48,520 --> 00:42:53,770 provide comparison, that you can go on the Lendio prop platform, 848 00:42:53,770 --> 00:42:56,190 and you can compare and contrast. 849 00:42:56,190 --> 00:42:59,200 They're more like a broker or an agent 850 00:42:59,200 --> 00:43:02,310 than actually making the lending. 851 00:43:02,310 --> 00:43:05,050 And Funding Circle is one of the only ones 852 00:43:05,050 --> 00:43:08,700 that is a little bit in the marketplace lending. 853 00:43:08,700 --> 00:43:11,100 Do I see some questions, Romain? 854 00:43:11,100 --> 00:43:13,980 I'm doing a thumbnail taste test here. 855 00:43:17,072 --> 00:43:19,030 TA: So in the chat, there's quite some activity 856 00:43:19,030 --> 00:43:20,145 about LendingClub. 857 00:43:20,145 --> 00:43:21,520 Perhaps you can provide the class 858 00:43:21,520 --> 00:43:23,680 with an overview of their business model. 859 00:43:23,680 --> 00:43:25,920 And what are the challenges they've been facing? 860 00:43:25,920 --> 00:43:26,920 GARY GENSLER: All right. 861 00:43:26,920 --> 00:43:31,030 I'm going to do that in about 10 minutes. 862 00:43:31,030 --> 00:43:35,020 So I'll hold that if I can. 863 00:43:35,020 --> 00:43:38,740 LendingClub has been more about the household sector 864 00:43:38,740 --> 00:43:41,110 than the small and medium size. 865 00:43:41,110 --> 00:43:42,010 I'll ask this. 866 00:43:42,010 --> 00:43:44,530 Has anybody in the class actually worked 867 00:43:44,530 --> 00:43:48,400 at a startup, worked at any corporation that's barred 868 00:43:48,400 --> 00:43:49,660 from one of these companies? 869 00:43:54,970 --> 00:43:57,620 TA: Alida, you've unmuted yourself. 870 00:43:57,620 --> 00:43:58,223 Yeah? 871 00:43:58,223 --> 00:44:00,640 AUDIENCE: Yeah, I was at Citibank at the time, 872 00:44:00,640 --> 00:44:05,990 that Citibank partners with C2FO as a partnered [INAUDIBLE] 873 00:44:05,990 --> 00:44:06,490 program. 874 00:44:06,490 --> 00:44:11,140 We financed some of the smaller suppliers in those programs 875 00:44:11,140 --> 00:44:13,030 by large [INAUDIBLE]. 876 00:44:13,030 --> 00:44:14,570 GARY GENSLER: So it's interesting. 877 00:44:14,570 --> 00:44:15,380 Could you share? 878 00:44:15,380 --> 00:44:21,460 Why did Citibank partner with C2FO, rather than 879 00:44:21,460 --> 00:44:23,120 make those loans themselves? 880 00:44:23,120 --> 00:44:24,480 And this is an important-- 881 00:44:24,480 --> 00:44:26,650 the relationship with the incumbents 882 00:44:26,650 --> 00:44:28,140 between the disruptors. 883 00:44:28,140 --> 00:44:30,400 Why in that one circumstance do you 884 00:44:30,400 --> 00:44:35,387 think Citi chose to partner, rather than do it on their own? 885 00:44:35,387 --> 00:44:37,720 AUDIENCE: [INAUDIBLE] an interesting model that actually 886 00:44:37,720 --> 00:44:41,550 allows the corporate to lend to its suppliers 887 00:44:41,550 --> 00:44:43,735 is the easiest way to say it would 888 00:44:43,735 --> 00:44:45,640 have been short-term firm. 889 00:44:45,640 --> 00:44:50,530 But if you look at a company and supplier base, 890 00:44:50,530 --> 00:44:53,720 you'll see that 80/20 rule applies fairly well. 891 00:44:53,720 --> 00:44:56,770 So the top 20 suppliers are generally 892 00:44:56,770 --> 00:45:00,400 supplying appropriate with the majority of their inventory. 893 00:45:00,400 --> 00:45:05,410 [INAUDIBLE] Purchasing on that bottom tail of the suppliers 894 00:45:05,410 --> 00:45:06,100 is-- 895 00:45:06,100 --> 00:45:07,860 they're all very small businesses. 896 00:45:07,860 --> 00:45:08,860 They're hard to lend to. 897 00:45:08,860 --> 00:45:14,440 It's very hard to do all the KYC requirements, which 898 00:45:14,440 --> 00:45:18,240 is really what Citibank does not like doing [INAUDIBLE].. 899 00:45:18,240 --> 00:45:20,920 And so a company like C2FO could come 900 00:45:20,920 --> 00:45:23,500 in there, partner with a corporate [INAUDIBLE],, 901 00:45:23,500 --> 00:45:27,777 and lend to or extend credit to a supplier [INAUDIBLE].. 902 00:45:27,777 --> 00:45:29,610 GARY GENSLER: So this is an important aspect 903 00:45:29,610 --> 00:45:30,940 that Alida just raised. 904 00:45:30,940 --> 00:45:33,130 Large incumbents sometimes don't feel 905 00:45:33,130 --> 00:45:36,580 that they can, in a cost-effective way, 906 00:45:36,580 --> 00:45:39,250 assess the credit and reach the distribution 907 00:45:39,250 --> 00:45:41,200 to small businesses. 908 00:45:41,200 --> 00:45:43,570 And then the disruptive companies say, well, wait, 909 00:45:43,570 --> 00:45:44,380 we could provide. 910 00:45:44,380 --> 00:45:46,090 That's a little crack in the system. 911 00:45:46,090 --> 00:45:48,850 That's something we can have more financial inclusion, 912 00:45:48,850 --> 00:45:50,740 whether it's Brex for the startups, 913 00:45:50,740 --> 00:45:56,650 C2FO for a lot of the small businesses, and the like. 914 00:45:56,650 --> 00:45:59,020 And the incumbents say all right, we can't. 915 00:45:59,020 --> 00:46:04,520 But we can, through C2FO and others, reach them. 916 00:46:04,520 --> 00:46:06,530 And then it helps down the supply chain. 917 00:46:06,530 --> 00:46:08,170 I think Ivy's hand was up, maybe? 918 00:46:08,170 --> 00:46:08,930 TA: Yes, correct. 919 00:46:08,930 --> 00:46:11,545 Ivy, go ahead. 920 00:46:11,545 --> 00:46:12,170 AUDIENCE: Yeah. 921 00:46:12,170 --> 00:46:14,600 So I use to work in securitization. 922 00:46:14,600 --> 00:46:18,480 And Brex is one of my clients and then also worked 923 00:46:18,480 --> 00:46:20,700 at a startup that uses Brex, too. 924 00:46:20,700 --> 00:46:24,770 And so I think, though, to your point of-- 925 00:46:24,770 --> 00:46:27,530 their user interface is pretty amazing. 926 00:46:27,530 --> 00:46:31,430 And they've also just have really identified 927 00:46:31,430 --> 00:46:33,920 this white space of startups. 928 00:46:33,920 --> 00:46:35,810 But I think where we got comfortable 929 00:46:35,810 --> 00:46:42,080 in terms of the diligence is the fact that they're pretty much-- 930 00:46:42,080 --> 00:46:46,160 it's a very elegant way of just having these startups making 931 00:46:46,160 --> 00:46:49,680 sure that they have literally enough cash in the account. 932 00:46:49,680 --> 00:46:51,770 So they're monitoring that. 933 00:46:51,770 --> 00:46:54,560 Basically, if you have access to these startups, 934 00:46:54,560 --> 00:46:56,150 bank account, day to day. 935 00:46:56,150 --> 00:46:57,980 And they started with startups. 936 00:46:57,980 --> 00:47:01,460 And they've been very, I think, thoughtful about which 937 00:47:01,460 --> 00:47:04,880 sectors they're going to, like life sciences, and e-commerce, 938 00:47:04,880 --> 00:47:09,110 and now having cash management, which also makes a lot of sense 939 00:47:09,110 --> 00:47:12,410 in terms of just having yield, so just wanted to offer 940 00:47:12,410 --> 00:47:14,180 a little bit more color there. 941 00:47:14,180 --> 00:47:17,150 GARY GENSLER: And Brex started with this concept 942 00:47:17,150 --> 00:47:20,780 of, how does entrepreneurs get money when you 943 00:47:20,780 --> 00:47:22,590 don't have any track record? 944 00:47:22,590 --> 00:47:23,090 Right? 945 00:47:23,090 --> 00:47:24,882 Literally, you don't have any track record. 946 00:47:24,882 --> 00:47:28,400 They had to also rely on something 947 00:47:28,400 --> 00:47:29,660 we've talked about already-- 948 00:47:29,660 --> 00:47:30,680 OpenAPI. 949 00:47:30,680 --> 00:47:31,950 They had to get data. 950 00:47:31,950 --> 00:47:33,440 And they had to do it, as you said, 951 00:47:33,440 --> 00:47:38,120 in an efficient, elegant way to get that data and get access. 952 00:47:38,120 --> 00:47:40,640 Do you have cash in your account, so to speak? 953 00:47:40,640 --> 00:47:44,240 And now, they've grown up a certain expertise 954 00:47:44,240 --> 00:47:47,380 in that startup world. 955 00:47:47,380 --> 00:47:49,490 And it's not equity that they're funding. 956 00:47:49,490 --> 00:47:53,660 It's loans, basically, against the cash flow. 957 00:47:53,660 --> 00:47:56,420 What you'll see also on here is, as I 958 00:47:56,420 --> 00:47:59,480 said, some of the big tech companies like Amazon 959 00:47:59,480 --> 00:48:01,340 and Tencent and Alipay. 960 00:48:01,340 --> 00:48:04,400 You see some of the really, now incumbent fintechs, 961 00:48:04,400 --> 00:48:08,430 as some folks would call them, like Stripe and Square 962 00:48:08,430 --> 00:48:13,940 and PayPal and Intuit that have built up a long history now, 963 00:48:13,940 --> 00:48:18,260 either in the payment space or in the tax prep and accounting 964 00:48:18,260 --> 00:48:20,660 space, as some have come from accounting. 965 00:48:20,660 --> 00:48:22,700 Some have come from the payment side 966 00:48:22,700 --> 00:48:25,370 where they're getting data and corporate business 967 00:48:25,370 --> 00:48:26,840 relationships. 968 00:48:26,840 --> 00:48:29,958 What you don't see is a lot of the challenger banks 969 00:48:29,958 --> 00:48:32,000 that we're going to talk about in our next class. 970 00:48:32,000 --> 00:48:33,740 Now, Prosper is here. 971 00:48:33,740 --> 00:48:35,390 They've started to offer some lending 972 00:48:35,390 --> 00:48:36,920 side to the corporate side. 973 00:48:36,920 --> 00:48:39,890 Most of the challenger banks and nearly all 974 00:48:39,890 --> 00:48:43,430 of the marketplace lenders that are of size 975 00:48:43,430 --> 00:48:45,350 are in the household sector, rather than 976 00:48:45,350 --> 00:48:49,260 the corporate sector, which I find of interest. 977 00:48:49,260 --> 00:48:51,950 I don't if there's a question. 978 00:48:51,950 --> 00:48:53,240 TA: We have two hands raised-- 979 00:48:53,240 --> 00:48:54,400 Camillo and then Carlos. 980 00:48:54,400 --> 00:48:55,400 GARY GENSLER: All right. 981 00:48:55,400 --> 00:48:59,180 And then we're going to go to the household sector. 982 00:48:59,180 --> 00:49:01,740 AUDIENCE: OK, this is about the household. 983 00:49:01,740 --> 00:49:05,610 I'm sure you know about this Brazilian unicorn called 984 00:49:05,610 --> 00:49:06,372 Nubank. 985 00:49:06,372 --> 00:49:07,580 GARY GENSLER: Oh, absolutely. 986 00:49:07,580 --> 00:49:07,770 Yeah. 987 00:49:07,770 --> 00:49:10,103 And we're going to be talking about Nubank a fair amount 988 00:49:10,103 --> 00:49:11,338 next Monday as well. 989 00:49:11,338 --> 00:49:11,880 AUDIENCE: OK. 990 00:49:11,880 --> 00:49:13,520 I just want to know-- 991 00:49:13,520 --> 00:49:14,780 well, maybe next class. 992 00:49:14,780 --> 00:49:18,750 Do you think that their business model about giving 993 00:49:18,750 --> 00:49:21,180 online credit cards to-- 994 00:49:21,180 --> 00:49:22,440 I don't know. 995 00:49:22,440 --> 00:49:27,450 I think it's 8.5 million people already, who have a Nubank 996 00:49:27,450 --> 00:49:30,680 credit card, is sustainable. 997 00:49:30,680 --> 00:49:34,030 Because I don't know what's their specific innovation, 998 00:49:34,030 --> 00:49:37,410 apart from accepting applications 999 00:49:37,410 --> 00:49:38,940 on line of credit cards. 1000 00:49:38,940 --> 00:49:42,280 Just I'm wondering if that's going to be-- 1001 00:49:42,280 --> 00:49:46,090 are they are going to have some [INAUDIBLE] problem? 1002 00:49:46,090 --> 00:49:48,670 GARY GENSLER: We'll dive more into Nubank in the next class. 1003 00:49:48,670 --> 00:49:50,250 But let me just generically say, I 1004 00:49:50,250 --> 00:49:55,200 think that it's the reality of startups that 1005 00:49:55,200 --> 00:49:57,690 more will fail than succeed. 1006 00:49:57,690 --> 00:50:00,540 Now, as it specifically relates to credit cards, 1007 00:50:00,540 --> 00:50:07,980 in the credit card space, the big incumbents 1008 00:50:07,980 --> 00:50:09,780 aren't going to keep the whole market. 1009 00:50:09,780 --> 00:50:13,530 And maybe that leads me for a minute. 1010 00:50:13,530 --> 00:50:16,860 I'm going to come back to mortgages in a second. 1011 00:50:16,860 --> 00:50:18,510 This is the US credit card system. 1012 00:50:18,510 --> 00:50:20,070 It's not Brazil. 1013 00:50:20,070 --> 00:50:23,280 But the big seven, what I call, or the big eight 1014 00:50:23,280 --> 00:50:25,530 being the big four or five banks-- 1015 00:50:25,530 --> 00:50:28,920 American Express, Discover, and Cap One-- 1016 00:50:28,920 --> 00:50:34,020 control 80%, 78% as of last year-- 1017 00:50:34,020 --> 00:50:35,280 credit card business. 1018 00:50:35,280 --> 00:50:37,980 There are a lot of economies of scale. 1019 00:50:37,980 --> 00:50:41,160 There's a lot of economies of scale back to managing risk 1020 00:50:41,160 --> 00:50:42,660 and balance sheet. 1021 00:50:42,660 --> 00:50:45,150 Credit cards as opposed to mortgages 1022 00:50:45,150 --> 00:50:48,510 are not guaranteed in any way by the US government. 1023 00:50:48,510 --> 00:50:51,870 It has a very different risk profile. 1024 00:50:51,870 --> 00:50:57,000 This is about a little over $1 trillion asset class market 1025 00:50:57,000 --> 00:50:57,820 in the US. 1026 00:50:57,820 --> 00:51:02,010 But 22% are smaller providers. 1027 00:51:02,010 --> 00:51:06,390 And so Amazon, for instance, partners with Synchrony Bank. 1028 00:51:06,390 --> 00:51:08,910 And Amazon has the Synchrony card. 1029 00:51:08,910 --> 00:51:11,310 Amazon also, I think, has something with JP Morgan 1030 00:51:11,310 --> 00:51:12,150 as well. 1031 00:51:12,150 --> 00:51:14,760 You'd probably say Amazon will be sustainable. 1032 00:51:14,760 --> 00:51:19,500 Amazon is such a phenomenal profit generator, 1033 00:51:19,500 --> 00:51:21,690 particularly with the crisis now. 1034 00:51:21,690 --> 00:51:24,360 I can't speak to any one startup. 1035 00:51:24,360 --> 00:51:27,780 Can they chip away at this 22%? 1036 00:51:27,780 --> 00:51:30,930 Yes, they can by using alternative data. 1037 00:51:30,930 --> 00:51:33,540 But the big seven or eight are not asleep. 1038 00:51:33,540 --> 00:51:36,230 They're not ignoring alternative data. 1039 00:51:36,230 --> 00:51:39,060 But a new startup can say, maybe we 1040 00:51:39,060 --> 00:51:41,860 can approach this in a different way 1041 00:51:41,860 --> 00:51:45,930 and particularly provide a better user interface. 1042 00:51:45,930 --> 00:51:49,680 Here in the US, what's happening is rather than credit card 1043 00:51:49,680 --> 00:51:54,030 products, they're providing personal loans. 1044 00:51:54,030 --> 00:51:56,250 But let me hold on that for a second, 1045 00:51:56,250 --> 00:52:00,220 because I want to go back to the mortgage market. 1046 00:52:00,220 --> 00:52:03,370 I mentioned this in the mortgage market. 1047 00:52:03,370 --> 00:52:05,160 These are figures from 2018. 1048 00:52:05,160 --> 00:52:09,030 These are the largest mortgage originators in the US. 1049 00:52:09,030 --> 00:52:11,040 It doesn't mean that they bought these loans 1050 00:52:11,040 --> 00:52:13,020 and held them on their balance sheet. 1051 00:52:13,020 --> 00:52:16,500 The yellow are the non-banks. 1052 00:52:16,500 --> 00:52:19,050 And PennyMac, for some reason, is not on here. 1053 00:52:19,050 --> 00:52:20,540 They should be. 1054 00:52:20,540 --> 00:52:26,670 But of the top 10, 5, the yellow are non-banks. 1055 00:52:26,670 --> 00:52:29,010 Now, do we call them fintechs? 1056 00:52:29,010 --> 00:52:29,830 Absolutely. 1057 00:52:29,830 --> 00:52:35,920 They are giving a different user interface with the public, 1058 00:52:35,920 --> 00:52:37,700 and they've just taken off. 1059 00:52:37,700 --> 00:52:39,170 Part of it is regulatory. 1060 00:52:39,170 --> 00:52:42,140 Part of it is since the 2008 crisis. 1061 00:52:42,140 --> 00:52:43,970 Holding loans on the balance sheets 1062 00:52:43,970 --> 00:52:46,460 become less attractive to the big banks. 1063 00:52:46,460 --> 00:52:50,180 In terms of their capital charges and the like, 1064 00:52:50,180 --> 00:52:52,280 part of it is also because in the US, 1065 00:52:52,280 --> 00:52:55,880 this is highly tied to the government-sponsored 1066 00:52:55,880 --> 00:52:56,990 enterprises. 1067 00:52:56,990 --> 00:53:00,560 But big disruption in the last 12 years, that about half 1068 00:53:00,560 --> 00:53:03,930 of the loans are originated by, broadly speaking, 1069 00:53:03,930 --> 00:53:08,210 yeah, the non-banks sector who are largely then laying it off 1070 00:53:08,210 --> 00:53:11,930 to the asset securitization marketplace. 1071 00:53:11,930 --> 00:53:13,640 Disruption of the past-- 1072 00:53:13,640 --> 00:53:15,290 I believe there'll still be disruption 1073 00:53:15,290 --> 00:53:17,830 in the future in this space. 1074 00:53:17,830 --> 00:53:19,960 Back to the credit card side, what we 1075 00:53:19,960 --> 00:53:21,730 were talking about there with Camillo-- 1076 00:53:21,730 --> 00:53:24,010 and I'll pause if there's other questions. 1077 00:53:24,010 --> 00:53:26,650 I just want to take a look also at China. 1078 00:53:26,650 --> 00:53:29,800 China's biggest credit card issuers-- 1079 00:53:29,800 --> 00:53:33,040 all that are building upon that UnionPay platform 1080 00:53:33,040 --> 00:53:33,760 we talked about. 1081 00:53:33,760 --> 00:53:38,530 UnionPay was started by, I think, 84 banks in China, 1082 00:53:38,530 --> 00:53:41,380 really with the People's Bank of China bringing that together. 1083 00:53:41,380 --> 00:53:46,690 UnionPay is that one backbone of their whole credit card payment 1084 00:53:46,690 --> 00:53:47,890 system. 1085 00:53:47,890 --> 00:53:52,180 Interestingly, as dominant and as strong as Alipay and WeChat 1086 00:53:52,180 --> 00:53:53,200 Pay are-- 1087 00:53:53,200 --> 00:53:55,690 and in a sense, WeChat Pay and Alipay 1088 00:53:55,690 --> 00:53:58,290 leapfrogged the banking system. 1089 00:53:58,290 --> 00:54:02,260 There's real growth going on in the credit card business, 1090 00:54:02,260 --> 00:54:04,840 but not from disruptors and startups. 1091 00:54:04,840 --> 00:54:08,850 It's like the commercial banks getting back into it. 1092 00:54:08,850 --> 00:54:10,990 Romain where there some questions? 1093 00:54:10,990 --> 00:54:12,350 TA: Yes, Alessandro? 1094 00:54:12,350 --> 00:54:15,060 GARY GENSLER: Please. 1095 00:54:15,060 --> 00:54:15,900 AUDIENCE: Yes, Gary. 1096 00:54:15,900 --> 00:54:19,710 I'd like to get your point of view on the following topic. 1097 00:54:19,710 --> 00:54:23,400 So I was thinking about how these new credit card-- 1098 00:54:23,400 --> 00:54:25,080 think that companies work. 1099 00:54:25,080 --> 00:54:27,900 And most of them, not all of them-- 1100 00:54:27,900 --> 00:54:31,080 they got to partner up with the bank, right? 1101 00:54:31,080 --> 00:54:33,820 Unless they have huge amount of cash anticipated, 1102 00:54:33,820 --> 00:54:37,587 they got to partner up with a bank that gives actual credit. 1103 00:54:37,587 --> 00:54:38,920 GARY GENSLER: Let me just pause. 1104 00:54:38,920 --> 00:54:42,270 They either have to partner with a bank, which is the issuer 1105 00:54:42,270 --> 00:54:43,680 bank partner model. 1106 00:54:43,680 --> 00:54:46,380 And we're going to get to LendingClub, I promise, 1107 00:54:46,380 --> 00:54:50,220 that has that issuer partner, that bank that's a partner. 1108 00:54:50,220 --> 00:54:54,210 Or they tap into the securitization markets. 1109 00:54:54,210 --> 00:54:56,760 And so for those who are not familiar, 1110 00:54:56,760 --> 00:54:58,920 asset securitization is the concept 1111 00:54:58,920 --> 00:55:04,130 that the securities markets are the investors in the loans, 1112 00:55:04,130 --> 00:55:06,590 rather than holding it on a bank's balance 1113 00:55:06,590 --> 00:55:09,560 sheet or a finance company's balance sheet. 1114 00:55:09,560 --> 00:55:12,980 And that innovation, asset securitization starting 1115 00:55:12,980 --> 00:55:17,480 in the mortgage markets 40-plus years ago moved 1116 00:55:17,480 --> 00:55:24,470 to the credit card markets in a robust way by the 1990s, 1117 00:55:24,470 --> 00:55:29,000 is a very real way to lay off that side, 1118 00:55:29,000 --> 00:55:32,000 meaning find somebody else to be the investors, 1119 00:55:32,000 --> 00:55:33,390 rather than have a balance sheet. 1120 00:55:33,390 --> 00:55:34,700 So back to you, Alexandro. 1121 00:55:34,700 --> 00:55:39,010 It's either a partner bank or asset securitization. 1122 00:55:39,010 --> 00:55:41,620 AUDIENCE: So in the end, these guys, 1123 00:55:41,620 --> 00:55:46,750 these fintech companies are second intermediary, right? 1124 00:55:46,750 --> 00:55:49,810 So how much money do they actually make? 1125 00:55:49,810 --> 00:55:54,100 Because I'm thinking the more and more companies we can see, 1126 00:55:54,100 --> 00:55:55,670 the fees are going to go down. 1127 00:55:55,670 --> 00:55:58,420 So competition will drive their fees down. 1128 00:55:58,420 --> 00:56:00,400 They also have to pay a fee to-- you'd 1129 00:56:00,400 --> 00:56:03,970 see they're a balance sheet bank or in the case 1130 00:56:03,970 --> 00:56:05,960 of securitization, too. 1131 00:56:05,960 --> 00:56:07,960 GARY GENSLER: So you're absolutely right. 1132 00:56:07,960 --> 00:56:13,900 But financial intermediation has multiple layers. 1133 00:56:13,900 --> 00:56:17,860 And the more advanced an economy is, usually 1134 00:56:17,860 --> 00:56:19,000 the more the layers. 1135 00:56:19,000 --> 00:56:23,440 And the more competition in the market, more the layers. 1136 00:56:23,440 --> 00:56:26,830 And you might think of layers as inefficiency. 1137 00:56:26,830 --> 00:56:28,030 It might be. 1138 00:56:28,030 --> 00:56:31,360 But often, layers would bring efficiency and competition. 1139 00:56:31,360 --> 00:56:35,650 So some financial firm is doing the origination. 1140 00:56:35,650 --> 00:56:39,760 This is brokering and selling and providing a user interface. 1141 00:56:39,760 --> 00:56:42,360 And they might not want to be the balance sheet lender. 1142 00:56:42,360 --> 00:56:44,708 They might say, I'm going to partner with the bank 1143 00:56:44,708 --> 00:56:46,000 to be the balance sheet lender. 1144 00:56:46,000 --> 00:56:48,730 What we're going to do is we're going to compete and give 1145 00:56:48,730 --> 00:56:52,840 the most remarkable, robust user interface and brokerage. 1146 00:56:52,840 --> 00:56:57,310 In the mortgage market, back to that, the Quickens, and United 1147 00:56:57,310 --> 00:57:00,470 Wholesale Mortgage, and PennyMac that aren't on here, 1148 00:57:00,470 --> 00:57:04,870 by and large, only hold the mortgage for a few weeks, 1149 00:57:04,870 --> 00:57:07,500 a few days, maybe a couple months. 1150 00:57:07,500 --> 00:57:10,030 They have a warehouse line of credit to do that. 1151 00:57:10,030 --> 00:57:12,550 And then they securitize the rest. 1152 00:57:12,550 --> 00:57:14,080 But the mortgage market in the US 1153 00:57:14,080 --> 00:57:17,170 has a very robust securitization market. 1154 00:57:17,170 --> 00:57:18,980 You asked about credit cards. 1155 00:57:18,980 --> 00:57:23,830 Credit cards-- this 22% that's competing with the rest 1156 00:57:23,830 --> 00:57:28,870 does not have as big a robust securitization market. 1157 00:57:28,870 --> 00:57:31,330 Of the trillion in the US, I think 1158 00:57:31,330 --> 00:57:36,040 the credit card securitization market is about $150 to $200 1159 00:57:36,040 --> 00:57:38,410 billion if I recall. 1160 00:57:38,410 --> 00:57:41,170 So it's harder. 1161 00:57:41,170 --> 00:57:45,550 But it might be that company, the Nubank, as Camillo asked, 1162 00:57:45,550 --> 00:57:49,090 that has a better use of underwriting, and data, 1163 00:57:49,090 --> 00:57:51,520 and so forth. 1164 00:57:51,520 --> 00:57:54,730 What somebody wouldn't give for Credit Karma's data 1165 00:57:54,730 --> 00:57:56,680 with 106 million files? 1166 00:57:56,680 --> 00:57:59,020 That's a robust data set. 1167 00:57:59,020 --> 00:58:02,120 Now, Intuit, we know, paid $5 billion. 1168 00:58:02,120 --> 00:58:06,160 So maybe we do know what somebody would pay for it 1169 00:58:06,160 --> 00:58:10,240 I wouldn't diminish being at one particular slice. 1170 00:58:10,240 --> 00:58:13,750 If you can find the slice in the value chain 1171 00:58:13,750 --> 00:58:17,260 and compete away some of the incumbent's margin, 1172 00:58:17,260 --> 00:58:21,385 credit cards are very big business-- trillion dollars 1173 00:58:21,385 --> 00:58:24,130 in the US, very big in Europe and Asia as well, 1174 00:58:24,130 --> 00:58:27,220 growing in China rapidly. 1175 00:58:27,220 --> 00:58:29,440 And there's a lot of margin. 1176 00:58:29,440 --> 00:58:31,813 I would say the thing that's competing the most-- 1177 00:58:31,813 --> 00:58:32,980 and I'm going to jump ahead. 1178 00:58:32,980 --> 00:58:35,800 But, Alexandro, stay with us for a minute-- 1179 00:58:35,800 --> 00:58:38,710 is the personal loan business. 1180 00:58:38,710 --> 00:58:42,730 Personal loans differ from credit cards 1181 00:58:42,730 --> 00:58:46,900 in an important way, is that credit cards are what's known 1182 00:58:46,900 --> 00:58:50,430 as a revolving line of credit. 1183 00:58:50,430 --> 00:58:53,430 Each purchase adds to your credit balance. 1184 00:58:53,430 --> 00:58:54,870 You have a limit. 1185 00:58:54,870 --> 00:58:58,980 If you're high, if you're super prime or a prime borrower, 1186 00:58:58,980 --> 00:59:00,030 your limit is higher. 1187 00:59:00,030 --> 00:59:03,010 If you're sub-prime, your limit is lower. 1188 00:59:03,010 --> 00:59:07,500 That business of revolving credit-- 1189 00:59:07,500 --> 00:59:10,200 about a trillion dollars in the US. 1190 00:59:10,200 --> 00:59:12,270 We now have this personal loan business. 1191 00:59:12,270 --> 00:59:15,540 It's only about one sixth the size, about $160 billion 1192 00:59:15,540 --> 00:59:17,340 in the US. 1193 00:59:17,340 --> 00:59:19,620 That personal loan business is generally 1194 00:59:19,620 --> 00:59:23,670 term financing, a specific term that you 1195 00:59:23,670 --> 00:59:28,800 have to have an installment loan and pay once every month for 36 1196 00:59:28,800 --> 00:59:33,610 months or for 48 or 60 months. 1197 00:59:33,610 --> 00:59:35,890 The underwriting risk of a term loan 1198 00:59:35,890 --> 00:59:39,490 is lower than the underwriting risk of credit card 1199 00:59:39,490 --> 00:59:42,520 business or revolving credit. 1200 00:59:42,520 --> 00:59:46,210 The personal loan business is where most of the disruptors 1201 00:59:46,210 --> 00:59:47,180 are. 1202 00:59:47,180 --> 00:59:51,820 The SoFis, and the Prospers, and the Nubanks, and so forth-- 1203 00:59:51,820 --> 00:59:56,090 they're trying to break in the personal loan 1204 00:59:56,090 --> 01:00:02,015 side as much or even more than the credit card side. 1205 01:00:02,015 --> 01:00:02,890 But I don't know if-- 1206 01:00:02,890 --> 01:00:06,675 Alexandro, did you want to follow up on anything? 1207 01:00:06,675 --> 01:00:07,550 AUDIENCE: No, no, no. 1208 01:00:07,550 --> 01:00:09,970 My point was just-- 1209 01:00:09,970 --> 01:00:11,660 I don't know if you agree on the fact 1210 01:00:11,660 --> 01:00:18,380 that we would see a massive wave of mergers 1211 01:00:18,380 --> 01:00:21,230 between these companies. 1212 01:00:21,230 --> 01:00:26,350 I mean, in my mind, there's not much room for all 1213 01:00:26,350 --> 01:00:28,370 of these hundreds of companies that are just 1214 01:00:28,370 --> 01:00:30,783 popping up like mushrooms here. 1215 01:00:30,783 --> 01:00:32,450 GARY GENSLER: I think we'll see mergers. 1216 01:00:32,450 --> 01:00:34,700 And I think we'll see failures. 1217 01:00:34,700 --> 01:00:38,000 But the question is, is there an opportunity 1218 01:00:38,000 --> 01:00:39,590 in the midst of all of that? 1219 01:00:39,590 --> 01:00:43,360 Is there an opportunity along the way? 1220 01:00:43,360 --> 01:00:45,920 We've seen in the payment space a lot of consolidation 1221 01:00:45,920 --> 01:00:48,920 and the payment system providers, the PSPs. 1222 01:00:48,920 --> 01:00:51,380 But there's still a lot of opportunity 1223 01:00:51,380 --> 01:00:54,440 for sector-specific payment companies. 1224 01:00:54,440 --> 01:00:58,010 And we've even seen that the data aggregators in the payment 1225 01:00:58,010 --> 01:01:03,260 space have started to combine and be bought 1226 01:01:03,260 --> 01:01:06,020 where that phase of things. 1227 01:01:06,020 --> 01:01:09,020 I think in the household credit space, 1228 01:01:09,020 --> 01:01:11,870 we're going to see still a lot of competition-- 1229 01:01:11,870 --> 01:01:13,107 personal loan. 1230 01:01:13,107 --> 01:01:14,690 And I think in the personal loan side, 1231 01:01:14,690 --> 01:01:17,490 they will be chipping away at some of the profit margin, 1232 01:01:17,490 --> 01:01:21,290 so will be trying to, at least, of the incumbents in the credit 1233 01:01:21,290 --> 01:01:22,340 card space. 1234 01:01:22,340 --> 01:01:25,220 And interestingly in China, the credit card space 1235 01:01:25,220 --> 01:01:28,870 is trying to chip away at what Alipay and WeChat Pay built up. 1236 01:01:28,870 --> 01:01:34,100 Because there was a reverse over there that's happened. 1237 01:01:34,100 --> 01:01:36,770 Whether they'll be completely successful-- another story. 1238 01:01:39,267 --> 01:01:40,100 AUDIENCE: Thank you. 1239 01:01:40,100 --> 01:01:42,090 GARY GENSLER: [INAUDIBLE] 1240 01:01:42,090 --> 01:01:46,330 TA: [INAUDIBLE] 1241 01:01:46,330 --> 01:01:47,470 AUDIENCE: Yeah, sorry. 1242 01:01:47,470 --> 01:01:50,200 So I have a question on that point 1243 01:01:50,200 --> 01:01:55,750 that you brought up on UnionPay being an attractive alternative 1244 01:01:55,750 --> 01:01:57,325 to Alipay and WeChat Pay. 1245 01:01:57,325 --> 01:01:59,150 GARY GENSLER: [INAUDIBLE] I'm just 1246 01:01:59,150 --> 01:02:02,560 going to say it's been growing more quickly than I might 1247 01:02:02,560 --> 01:02:05,650 have thought, that I wouldn't count out 1248 01:02:05,650 --> 01:02:08,575 credit cards in China. 1249 01:02:08,575 --> 01:02:09,450 They've been growing. 1250 01:02:09,450 --> 01:02:11,825 AUDIENCE: Would you know what were the value propositions 1251 01:02:11,825 --> 01:02:15,660 of UnionPay that liked their consumers to opt 1252 01:02:15,660 --> 01:02:17,456 to its UnionPay? 1253 01:02:17,456 --> 01:02:18,092 Yeah. 1254 01:02:18,092 --> 01:02:19,300 GARY GENSLER: Well, I'm not-- 1255 01:02:19,300 --> 01:02:23,350 I mean, maybe some of our fellow students know better than I. 1256 01:02:23,350 --> 01:02:25,090 But I think, listen, you can't count out 1257 01:02:25,090 --> 01:02:27,610 that there's a distribution channel when you have 1258 01:02:27,610 --> 01:02:31,600 84 banks and particularly the six or eight big banks in China 1259 01:02:31,600 --> 01:02:36,850 that own a piece [INAUDIBLE] and all the hundreds of millions 1260 01:02:36,850 --> 01:02:38,110 of people there. 1261 01:02:38,110 --> 01:02:39,460 They're not asleep. 1262 01:02:39,460 --> 01:02:43,630 As big tech comes in, the incumbents don't rest. 1263 01:02:43,630 --> 01:02:45,370 It's competition. 1264 01:02:45,370 --> 01:02:48,580 But they do have the advantages of incredible distribution 1265 01:02:48,580 --> 01:02:53,440 channel, meaning the depositors and clients of those banks. 1266 01:02:53,440 --> 01:02:56,680 The product itself, the revolving credit product, 1267 01:02:56,680 --> 01:03:00,580 the classic credit card product has 1268 01:03:00,580 --> 01:03:03,520 a little bit more flexibility than something just 1269 01:03:03,520 --> 01:03:05,290 on an e-money wallet. 1270 01:03:05,290 --> 01:03:08,170 And it doesn't mean Alipay and WeChat Pay 1271 01:03:08,170 --> 01:03:10,852 can't offer something that is pretty much identical 1272 01:03:10,852 --> 01:03:12,060 to a credit card [INAUDIBLE]. 1273 01:03:12,060 --> 01:03:13,060 AUDIENCE: That's right. 1274 01:03:13,060 --> 01:03:15,335 GARY GENSLER: But their balances and the like 1275 01:03:15,335 --> 01:03:16,960 might be different as well, but I'm not 1276 01:03:16,960 --> 01:03:18,450 sufficiently close to it. 1277 01:03:18,450 --> 01:03:20,580 AUDIENCE: OK, cool. 1278 01:03:20,580 --> 01:03:23,490 Thank you. 1279 01:03:23,490 --> 01:03:26,950 GARY GENSLER: And I might pull some data for next class. 1280 01:03:26,950 --> 01:03:30,010 I'll show you what I'm talking about there. 1281 01:03:30,010 --> 01:03:31,960 Personal loan business-- just to give you 1282 01:03:31,960 --> 01:03:35,530 a percentage of unsecured personal loans, who is 1283 01:03:35,530 --> 01:03:37,930 making unsecured personal loan? 1284 01:03:37,930 --> 01:03:41,320 And again, a personal loan is not tied to a credit card. 1285 01:03:41,320 --> 01:03:44,000 It's usually an installment or term loan. 1286 01:03:44,000 --> 01:03:47,780 But you can see the shift just in these five years, 1287 01:03:47,780 --> 01:03:51,740 that the disruptors are eating into the market 1288 01:03:51,740 --> 01:03:53,735 share in this space. 1289 01:03:53,735 --> 01:03:55,610 Here are some of the personal loan companies. 1290 01:03:55,610 --> 01:03:57,570 Not a lot of overlap. 1291 01:03:57,570 --> 01:03:58,920 Prosper is on both lists. 1292 01:03:58,920 --> 01:04:01,250 But not a lot of overlap with the list 1293 01:04:01,250 --> 01:04:03,700 to the small and medium size. 1294 01:04:03,700 --> 01:04:06,410 And Camillo, I'm glad I have NuBank on here. 1295 01:04:06,410 --> 01:04:08,090 But we'll come back to a few of these 1296 01:04:08,090 --> 01:04:09,800 when we talk about challenger banks-- 1297 01:04:09,800 --> 01:04:12,740 Revolut, Nubank. 1298 01:04:12,740 --> 01:04:14,720 A number of these are really what we also 1299 01:04:14,720 --> 01:04:17,780 call as challenger banks. 1300 01:04:17,780 --> 01:04:21,170 Student loans-- I could probably ask for a show of hands. 1301 01:04:21,170 --> 01:04:24,710 How many of you have a student loan by one of these? 1302 01:04:24,710 --> 01:04:29,720 And in the US, the private student loan market 1303 01:04:29,720 --> 01:04:32,090 is only a small share. 1304 01:04:32,090 --> 01:04:34,580 Student loans in the US are dominated 1305 01:04:34,580 --> 01:04:37,340 by our Department of Education. 1306 01:04:37,340 --> 01:04:40,330 Over 92% of student loans in America 1307 01:04:40,330 --> 01:04:43,970 are either guaranteed or direct loans from the Department 1308 01:04:43,970 --> 01:04:45,140 of Education. 1309 01:04:45,140 --> 01:04:47,210 But of course, the private loan market 1310 01:04:47,210 --> 01:04:50,090 where graduate students and particularly those who are not 1311 01:04:50,090 --> 01:04:52,850 US citizens are more likely in the private student loan 1312 01:04:52,850 --> 01:04:53,850 market. 1313 01:04:53,850 --> 01:04:56,190 These are probably familiar names to many of you, 1314 01:04:56,190 --> 01:05:01,220 whether you used MPower, or Prodigy, or others, basically 1315 01:05:01,220 --> 01:05:04,580 to shop for a student loan or a traditional bank 1316 01:05:04,580 --> 01:05:08,410 like SunTrust and Wells Fargo. 1317 01:05:08,410 --> 01:05:14,300 And that 8% of that market is still about $100-plus billion. 1318 01:05:14,300 --> 01:05:19,440 Because the overall student loan market is $1.6 trillion, 1319 01:05:19,440 --> 01:05:22,290 so not small numbers. 1320 01:05:22,290 --> 01:05:23,750 So marketplace lending-- 1321 01:05:23,750 --> 01:05:26,450 I did say we would get to this. 1322 01:05:26,450 --> 01:05:29,360 It's an online platform connecting 1323 01:05:29,360 --> 01:05:31,400 borrowers and investors. 1324 01:05:31,400 --> 01:05:33,970 So it's a platform in the middle, 1325 01:05:33,970 --> 01:05:36,980 started with this concept of being peer to peer. 1326 01:05:36,980 --> 01:05:38,870 And so this is a look at LendingClub 1327 01:05:38,870 --> 01:05:42,090 from their own documents from last summer. 1328 01:05:42,090 --> 01:05:47,460 LendingClub-- 3 million-plus borrowers on one side 1329 01:05:47,460 --> 01:05:52,110 of the platform economics, 200,000-plus investors 1330 01:05:52,110 --> 01:05:53,050 on the other side. 1331 01:05:53,050 --> 01:05:55,860 Now, don't think of it as 3 million and 200,000, 1332 01:05:55,860 --> 01:05:58,960 because it gets more concentrated than that. 1333 01:05:58,960 --> 01:06:01,230 But LendingClub sits in the middle, 1334 01:06:01,230 --> 01:06:04,770 between borrowers and investors, or you might 1335 01:06:04,770 --> 01:06:06,990 call lenders, but investors. 1336 01:06:06,990 --> 01:06:10,448 But they partner with issuing bank. 1337 01:06:10,448 --> 01:06:12,990 They don't want to take a lot of this on their balance sheet. 1338 01:06:12,990 --> 01:06:15,770 They take some of it onto their balance sheet. 1339 01:06:15,770 --> 01:06:21,130 But they want to basically have issuing bank partners plural, 1340 01:06:21,130 --> 01:06:25,350 because they keep some banks in competition. 1341 01:06:25,350 --> 01:06:27,190 And so what LendingClub is providing 1342 01:06:27,190 --> 01:06:31,460 is the platform and some of those issuing banks. 1343 01:06:31,460 --> 01:06:33,050 They're not the Bank of Americas, 1344 01:06:33,050 --> 01:06:34,570 but they're much smaller banks. 1345 01:06:34,570 --> 01:06:37,430 Say, all right, we don't have that front end. 1346 01:06:37,430 --> 01:06:39,770 We don't have that platform, that user experience. 1347 01:06:39,770 --> 01:06:43,470 LendingClub provides that. 1348 01:06:43,470 --> 01:06:46,960 And the investors on the other side of a LendingClub 1349 01:06:46,960 --> 01:06:51,560 are often hedge funds. 1350 01:06:51,560 --> 01:06:58,820 And asset managers are saying we can invest. 1351 01:06:58,820 --> 01:07:03,230 LendingClub is providing us a portfolio of loans. 1352 01:07:03,230 --> 01:07:04,880 And you can see the numbers here-- 1353 01:07:04,880 --> 01:07:09,440 16-month average duration, 1 and 1.6 to 7 1354 01:07:09,440 --> 01:07:11,360 and 1/2% range of returns. 1355 01:07:11,360 --> 01:07:14,480 That's a pretty wide range of returns. 1356 01:07:14,480 --> 01:07:15,410 And who are they? 1357 01:07:15,410 --> 01:07:18,973 Managed accounts means it could be an account at BlackRock 1358 01:07:18,973 --> 01:07:20,390 or Fidelity that says, we're going 1359 01:07:20,390 --> 01:07:23,030 to put a little bit of money into this credit 1360 01:07:23,030 --> 01:07:26,170 market and the like. 1361 01:07:26,170 --> 01:07:27,230 Now, Luke was right. 1362 01:07:27,230 --> 01:07:29,990 LendingClub and many of the other marketplace lenders 1363 01:07:29,990 --> 01:07:31,700 were quite a dream. 1364 01:07:31,700 --> 01:07:33,620 LendingClub happened to go public. 1365 01:07:33,620 --> 01:07:37,640 And then their market value came down quite a bit 1366 01:07:37,640 --> 01:07:40,610 as they had to prove out whether they can make money. 1367 01:07:40,610 --> 01:07:42,598 Where have they been in these last 10 years, 1368 01:07:42,598 --> 01:07:43,640 just to give you a sense? 1369 01:07:43,640 --> 01:07:48,410 In 2010, only it was $100 million of originations. 1370 01:07:48,410 --> 01:07:51,710 But it was all retail originations, by and large. 1371 01:07:51,710 --> 01:07:57,990 By 2018, the retail, which is a very small part of it-- 1372 01:07:57,990 --> 01:08:01,400 they're originating very-- quite a different bit 1373 01:08:01,400 --> 01:08:05,960 of loans, how they're originating these things. 1374 01:08:05,960 --> 01:08:07,910 And China-- I just want to mention 1375 01:08:07,910 --> 01:08:13,550 China went through a remarkable wave of peer-to-peer lending. 1376 01:08:13,550 --> 01:08:15,140 And then the People's Bank of China 1377 01:08:15,140 --> 01:08:18,410 felt, no, we've got to get control of this. 1378 01:08:18,410 --> 01:08:24,970 I mean, literally there was 2,700 peer-to-peer lending 1379 01:08:24,970 --> 01:08:28,420 platforms in China just 4 years ago 1380 01:08:28,420 --> 01:08:33,069 and most recent statistics down to about 300-plus. 1381 01:08:33,069 --> 01:08:37,990 And in November of 2019, the official sector in China 1382 01:08:37,990 --> 01:08:40,899 still said this isn't right. 1383 01:08:40,899 --> 01:08:43,720 The peer-to-peer lenders need more regulation. 1384 01:08:43,720 --> 01:08:47,229 In essence, they need bank-like regulation. 1385 01:08:47,229 --> 01:08:50,109 And what's interesting is back to LendingClub, 1386 01:08:50,109 --> 01:08:51,819 LendingClub has actually announced 1387 01:08:51,819 --> 01:08:55,029 the purchase of a bank. 1388 01:08:55,029 --> 01:08:57,609 Romain, I think I saw a hand go up. 1389 01:09:00,257 --> 01:09:01,340 TA: I don't see any, Gary. 1390 01:09:01,340 --> 01:09:03,760 GARY GENSLER: Oh, OK. 1391 01:09:03,760 --> 01:09:07,100 But there were questions earlier about LendingClub. 1392 01:09:07,100 --> 01:09:07,600 TA: Yeah. 1393 01:09:07,600 --> 01:09:09,430 So now, we have two hands raised. 1394 01:09:09,430 --> 01:09:12,439 Let's go first with Jose. 1395 01:09:12,439 --> 01:09:15,240 AUDIENCE: Yeah, so I'm not super familiar with LendingClub, 1396 01:09:15,240 --> 01:09:18,090 but I'm familiar with another one in Europe. 1397 01:09:18,090 --> 01:09:20,720 I think the way it works is a bit different. 1398 01:09:20,720 --> 01:09:23,516 I would like to hear your opinion on that model. 1399 01:09:23,516 --> 01:09:25,850 GARY GENSLER: [INAUDIBLE] 1400 01:09:25,850 --> 01:09:27,132 AUDIENCE: Sorry? 1401 01:09:27,132 --> 01:09:28,299 GARY GENSLER: I'm listening. 1402 01:09:28,299 --> 01:09:28,799 Yes. 1403 01:09:28,799 --> 01:09:30,265 AUDIENCE: So it's called Mintos. 1404 01:09:30,265 --> 01:09:31,890 I think it's the biggest one in Europe. 1405 01:09:31,890 --> 01:09:33,473 And basically, what they do is there's 1406 01:09:33,473 --> 01:09:36,920 a group of loan originators that are independent companies that 1407 01:09:36,920 --> 01:09:39,290 create these loans and give out these loans. 1408 01:09:39,290 --> 01:09:45,740 And then these [AUDIO OUT] [INAUDIBLE] loans 1409 01:09:45,740 --> 01:09:46,970 to independent investors. 1410 01:09:46,970 --> 01:09:49,950 But they guarantee the payment of the loan. 1411 01:09:49,950 --> 01:09:54,440 So if the person that asked for the loan doesn't pay, 1412 01:09:54,440 --> 01:10:00,990 the loan originator pays for that payment to the investor. 1413 01:10:00,990 --> 01:10:03,110 So basically, the risk for the investor 1414 01:10:03,110 --> 01:10:06,035 is that the loan originators go bankrupt. 1415 01:10:06,035 --> 01:10:09,862 I learned there's something similar in the US to that. 1416 01:10:09,862 --> 01:10:11,570 GARY GENSLER: Well, so what you're saying 1417 01:10:11,570 --> 01:10:15,560 is how they are managing the risks. 1418 01:10:15,560 --> 01:10:20,440 The investors are taking a credit risk 1419 01:10:20,440 --> 01:10:25,380 on the platform, the originator, rather 1420 01:10:25,380 --> 01:10:28,950 than taking a credit risk on the portfolio of loans themselves. 1421 01:10:32,910 --> 01:10:34,327 [INTERPOSING VOICES] 1422 01:10:34,327 --> 01:10:35,910 AUDIENCE: --one more layer in between. 1423 01:10:35,910 --> 01:10:37,290 So there's the loan originators. 1424 01:10:37,290 --> 01:10:39,360 And there's hundreds of companies, then 1425 01:10:39,360 --> 01:10:41,340 the platform that connects the loan 1426 01:10:41,340 --> 01:10:43,890 originators with investors. 1427 01:10:43,890 --> 01:10:48,270 And basically, the investors invest in specific loans, 1428 01:10:48,270 --> 01:10:50,872 but they are guaranteed by the loan originators. 1429 01:10:50,872 --> 01:10:52,330 GARY GENSLER: Why don't we do this? 1430 01:10:52,330 --> 01:10:54,580 Why don't you shoot me an email? 1431 01:10:54,580 --> 01:10:56,920 And I'll try to take this up in our next class. 1432 01:10:56,920 --> 01:10:59,620 And I'll look at the company more specifically. 1433 01:10:59,620 --> 01:11:03,960 But to the point, there's no reason 1434 01:11:03,960 --> 01:11:10,470 you can't find a new model as to who takes the credit risk. 1435 01:11:10,470 --> 01:11:13,740 Credit risk is inherent in lending. 1436 01:11:13,740 --> 01:11:16,860 Somebody is going to repay on time. 1437 01:11:16,860 --> 01:11:19,980 And others are going to fall into delinquency or even 1438 01:11:19,980 --> 01:11:23,400 default. And so then the structure 1439 01:11:23,400 --> 01:11:26,320 of a market, whether it's mortgages, 1440 01:11:26,320 --> 01:11:30,270 credit cards, personal loans, small businesses-- 1441 01:11:30,270 --> 01:11:34,470 the structure of a market might evolve 1442 01:11:34,470 --> 01:11:39,360 as to how to slice up who bears that credit risk. 1443 01:11:39,360 --> 01:11:40,740 And there's not just credit risk. 1444 01:11:40,740 --> 01:11:42,130 There's prepayment risk. 1445 01:11:42,130 --> 01:11:44,040 There's interest rate risk. 1446 01:11:44,040 --> 01:11:46,500 There's numerous financial risks. 1447 01:11:46,500 --> 01:11:48,510 And so what's just being highlighted by Jose-- 1448 01:11:48,510 --> 01:11:49,590 and I apologize. 1449 01:11:49,590 --> 01:11:54,030 I just don't know that model, is that the investors, rather 1450 01:11:54,030 --> 01:11:58,470 than bearing the direct credit risk of the borrowers 1451 01:11:58,470 --> 01:12:01,590 are having some of that held by others. 1452 01:12:01,590 --> 01:12:04,470 And they're bearing the risk of the intermediary 1453 01:12:04,470 --> 01:12:07,260 in between the platform. 1454 01:12:07,260 --> 01:12:10,860 And in essence, that's true in the US mortgage 1455 01:12:10,860 --> 01:12:14,030 market, a very different part, what you asked about. 1456 01:12:14,030 --> 01:12:17,550 But the US mortgage market conforming loans 1457 01:12:17,550 --> 01:12:23,790 are guaranteed by the government or by the government-sponsored 1458 01:12:23,790 --> 01:12:26,280 enterprises so that your risks then 1459 01:12:26,280 --> 01:12:28,120 are a little bit different. 1460 01:12:28,120 --> 01:12:29,460 It's not the credit risk. 1461 01:12:29,460 --> 01:12:32,610 In the US mortgage market, you have prepayment risk. 1462 01:12:32,610 --> 01:12:36,060 Will somebody pay the mortgage early 1463 01:12:36,060 --> 01:12:39,040 as interest rates might go down and so forth? 1464 01:12:39,040 --> 01:12:42,150 And then in parts of the US mortgage market that 1465 01:12:42,150 --> 01:12:44,550 are not the conforming mortgage market, 1466 01:12:44,550 --> 01:12:45,810 you did have credit risk. 1467 01:12:45,810 --> 01:12:48,070 Because the government wasn't guaranteeing. 1468 01:12:48,070 --> 01:12:49,950 And a lot of the sub-prime mortgage 1469 01:12:49,950 --> 01:12:53,253 mess that we got into in 2008 was around that. 1470 01:12:53,253 --> 01:12:55,170 But rather than taking time now, why don't you 1471 01:12:55,170 --> 01:12:56,420 shoot me an email? 1472 01:12:56,420 --> 01:13:00,370 I'll look at this specific company and come back. 1473 01:13:00,370 --> 01:13:02,400 Romain, were there other hands up? 1474 01:13:02,400 --> 01:13:04,955 TA: Yes, let's go with Akshay. 1475 01:13:04,955 --> 01:13:06,080 AUDIENCE: Hello, professor. 1476 01:13:06,080 --> 01:13:10,040 So I had no question with the business model of LendingClub. 1477 01:13:10,040 --> 01:13:14,820 So what is the role of issuing banks in this case? 1478 01:13:14,820 --> 01:13:18,470 GARY GENSLER: So issuing banks basically are 1479 01:13:18,470 --> 01:13:21,450 lending their balance sheet. 1480 01:13:21,450 --> 01:13:25,880 So let's say an issuing bank has its own availability 1481 01:13:25,880 --> 01:13:32,280 of depositors and has not built the front end to the borrowers. 1482 01:13:32,280 --> 01:13:36,360 So the issuing bank is standing in to do that. 1483 01:13:36,360 --> 01:13:41,210 In addition, they're actually papering and documenting 1484 01:13:41,210 --> 01:13:42,440 the loans. 1485 01:13:42,440 --> 01:13:44,360 So as you see on this chart here, 1486 01:13:44,360 --> 01:13:51,500 the issuing bank is sending the loans out and taking it in. 1487 01:13:51,500 --> 01:13:54,890 So there's a regulatory reason that the issuing bank is there. 1488 01:13:54,890 --> 01:13:59,210 So the issuing bank might issue the loans and hold them. 1489 01:13:59,210 --> 01:14:01,490 Or the issuing bank might issue the loans 1490 01:14:01,490 --> 01:14:03,960 and then, literally, as this chart shows, 1491 01:14:03,960 --> 01:14:05,600 resell them to LendingClub. 1492 01:14:05,600 --> 01:14:08,970 And LendingClub sells them to investors. 1493 01:14:08,970 --> 01:14:13,240 So there's a bit of-- 1494 01:14:13,240 --> 01:14:16,810 it's similar to what's called a warehouse line. 1495 01:14:16,810 --> 01:14:18,640 The issuing bank is standing there 1496 01:14:18,640 --> 01:14:23,830 ready to take loans, but then resell them. 1497 01:14:23,830 --> 01:14:27,430 Because their capability is only a certain size. 1498 01:14:27,430 --> 01:14:30,580 LendingClub says they did $10 billion of loans 1499 01:14:30,580 --> 01:14:33,250 in 2018, if I recall the number. 1500 01:14:33,250 --> 01:14:36,370 The issuing bank doesn't want to put $10 billion on. 1501 01:14:36,370 --> 01:14:38,320 But they're providing the liquidity 1502 01:14:38,320 --> 01:14:43,270 for the first few days or weeks until LendingClub then provides 1503 01:14:43,270 --> 01:14:45,880 the investor to buy the loan. 1504 01:14:45,880 --> 01:14:49,030 So it's similar to a warehouse line, 1505 01:14:49,030 --> 01:14:52,600 but it's actually a purchase and sale. 1506 01:14:52,600 --> 01:14:56,890 They purchase the loan or issue the loan and sell. 1507 01:14:56,890 --> 01:14:59,530 There's also a bit of regulation that you actually 1508 01:14:59,530 --> 01:15:01,520 have a bank involved. 1509 01:15:01,520 --> 01:15:06,220 And part of what was going on, both in the UK and the US, 1510 01:15:06,220 --> 01:15:09,220 is this marketplace. 1511 01:15:09,220 --> 01:15:11,770 Peer-to-peer lending started, is the platforms 1512 01:15:11,770 --> 01:15:14,470 didn't want to, frankly, register 1513 01:15:14,470 --> 01:15:16,660 and be regulated like banks. 1514 01:15:16,660 --> 01:15:19,180 They needed somebody else to make the loan 1515 01:15:19,180 --> 01:15:22,208 to have that interface. 1516 01:15:22,208 --> 01:15:23,690 I oversimplified. 1517 01:15:23,690 --> 01:15:26,340 And probably a lawyer would tell me I've gotten it a little bit 1518 01:15:26,340 --> 01:15:27,860 wrong. 1519 01:15:27,860 --> 01:15:30,660 TA: And then we have Adam who would like to provide 1520 01:15:30,660 --> 01:15:32,985 some insight on UnionPay. 1521 01:15:32,985 --> 01:15:33,860 GARY GENSLER: Please. 1522 01:15:33,860 --> 01:15:34,360 Please. 1523 01:15:34,360 --> 01:15:36,880 And then [INAUDIBLE] closed on alternative data. 1524 01:15:36,880 --> 01:15:37,512 AUDIENCE: Yeah. 1525 01:15:37,512 --> 01:15:39,470 In response to [INAUDIBLE]'s's earlier question 1526 01:15:39,470 --> 01:15:44,180 about UnionPay, so UnionPay is a state-owned credit and debit 1527 01:15:44,180 --> 01:15:45,770 card network, all right? 1528 01:15:45,770 --> 01:15:51,440 So the one thing that separates them from the [INAUDIBLE] 1529 01:15:51,440 --> 01:15:53,540 duopoly between Alipay and WeChat Pay, 1530 01:15:53,540 --> 01:15:56,900 which dominates 90% of the market, is that it can be, 1531 01:15:56,900 --> 01:15:58,850 well, among other things. 1532 01:15:58,850 --> 01:16:02,240 They can be used for all mobile devices and computer browsers. 1533 01:16:02,240 --> 01:16:05,210 So technology wise, they do have an advantage. 1534 01:16:05,210 --> 01:16:08,390 Because for WeChat Pay, it's quite 1535 01:16:08,390 --> 01:16:11,300 restrictive in terms of technology, 1536 01:16:11,300 --> 01:16:13,490 because they're used mostly on mobile. 1537 01:16:13,490 --> 01:16:15,890 And unlike Alipay and WeChat Pay, 1538 01:16:15,890 --> 01:16:19,580 UnionPay actually supports almost all currencies 1539 01:16:19,580 --> 01:16:22,430 and operates in many countries besides China, 1540 01:16:22,430 --> 01:16:24,740 also a feature that both Alipay and WeChat 1541 01:16:24,740 --> 01:16:29,150 Pay are struggling with, due to the peculiarities 1542 01:16:29,150 --> 01:16:31,820 of the Chinese legislation. 1543 01:16:31,820 --> 01:16:36,860 And the one thing is that what UnionPay focuses on 1544 01:16:36,860 --> 01:16:41,060 is the fact that they focus on the efforts 1545 01:16:41,060 --> 01:16:42,590 of those Chinese account holders. 1546 01:16:42,590 --> 01:16:44,810 Because most people-- in fact, the majority 1547 01:16:44,810 --> 01:16:48,870 of the people who owns a credit card will be UnionPay holders. 1548 01:16:48,870 --> 01:16:51,980 They are focusing on people who travel abroad, predominantly 1549 01:16:51,980 --> 01:16:53,750 to the US, in fact. 1550 01:16:53,750 --> 01:16:57,290 So you see a lot of shops that are 1551 01:16:57,290 --> 01:17:00,080 targeting for Chinese customers and travelers. 1552 01:17:00,080 --> 01:17:02,150 You would see that UnionPay. 1553 01:17:02,150 --> 01:17:03,710 They could actually pay by UnionPay. 1554 01:17:03,710 --> 01:17:07,340 So these are the edge that they have over Alipay and WeChat 1555 01:17:07,340 --> 01:17:07,840 Pay. 1556 01:17:07,840 --> 01:17:09,965 And that's just in response to the earlier question 1557 01:17:09,965 --> 01:17:11,358 [INAUDIBLE]. 1558 01:17:11,358 --> 01:17:12,150 GARY GENSLER: Yeah. 1559 01:17:12,150 --> 01:17:14,390 What I'm going to do is-- because we only have two 1560 01:17:14,390 --> 01:17:17,300 minutes, is I'm going to hold off and talk about alternative 1561 01:17:17,300 --> 01:17:22,560 data when we start up our next session on challenger banks 1562 01:17:22,560 --> 01:17:29,570 and the like and just close out with a little comment, 1563 01:17:29,570 --> 01:17:35,330 if I might, on just to-- 1564 01:17:35,330 --> 01:17:38,490 what I've already said in our first class on professionalism. 1565 01:17:38,490 --> 01:17:39,980 Hope this slide is there. 1566 01:17:39,980 --> 01:17:49,750 But again, is that I just want to lend to you again 1567 01:17:49,750 --> 01:17:52,510 from my years of experience. 1568 01:17:52,510 --> 01:17:56,600 We're in a very unusual time now with the corona crisis. 1569 01:17:56,600 --> 01:17:58,810 And we're even at MIT. 1570 01:17:58,810 --> 01:18:05,140 It's these Zoom classes and pass emergency, no credit emergency, 1571 01:18:05,140 --> 01:18:06,280 and the like. 1572 01:18:06,280 --> 01:18:09,160 But I would just share with you my own observation, 1573 01:18:09,160 --> 01:18:12,490 that for those of you trying to get the most out of this MIT 1574 01:18:12,490 --> 01:18:14,425 experience, it's not easy. 1575 01:18:14,425 --> 01:18:18,520 And in some ways, it's just frustrating as heck, I'm sure. 1576 01:18:18,520 --> 01:18:20,140 But again, to the extent that you 1577 01:18:20,140 --> 01:18:22,990 can, to the extent you can come prepared, and be 1578 01:18:22,990 --> 01:18:27,160 curious, and reach out to faculty members like myself, 1579 01:18:27,160 --> 01:18:30,520 and leverage off of our experience, take office hours, 1580 01:18:30,520 --> 01:18:31,330 I would do it. 1581 01:18:31,330 --> 01:18:33,880 I know this is a lousy time. 1582 01:18:33,880 --> 01:18:34,590 A lousy time. 1583 01:18:34,590 --> 01:18:37,270 I'm just reminding us all of that 1584 01:18:37,270 --> 01:18:41,750 and saying take whatever you can out of this MIT experience, 1585 01:18:41,750 --> 01:18:45,160 even if it's diminished in some way. 1586 01:18:45,160 --> 01:18:48,370 I want to make myself available again. 1587 01:18:48,370 --> 01:18:51,800 If you find the readings of interest, do them. 1588 01:18:51,800 --> 01:18:54,850 If you can't get through them because you're distracted 1589 01:18:54,850 --> 01:18:56,980 and you're looking for a job, I get that. 1590 01:18:56,980 --> 01:18:57,580 I get that. 1591 01:18:57,580 --> 01:18:59,950 I'm just saying the more you engage, 1592 01:18:59,950 --> 01:19:03,760 the more you will invest in yourselves and get out of it. 1593 01:19:03,760 --> 01:19:06,160 And on plagiarism-- and I say this just 1594 01:19:06,160 --> 01:19:09,130 to remind people again. 1595 01:19:09,130 --> 01:19:11,880 There's probably-- it's going to be hard for any of you-- 1596 01:19:11,880 --> 01:19:13,650 get no credit emergency. 1597 01:19:13,650 --> 01:19:17,190 But somebody might get no credit emergency if you submit 1598 01:19:17,190 --> 01:19:21,720 a 1,000-word paper and 600 or 800 words are plagiarized. 1599 01:19:21,720 --> 01:19:27,330 That's your pathway right into that no credit emergency. 1600 01:19:27,330 --> 01:19:29,270 It's easy to avoid, because you know 1601 01:19:29,270 --> 01:19:32,180 if you're taking a lot from something else. 1602 01:19:32,180 --> 01:19:35,990 And I just say this, because I have had those experiences. 1603 01:19:35,990 --> 01:19:37,790 I just mention it again, just because I 1604 01:19:37,790 --> 01:19:42,050 want to do you the favor of helping you make sure that even 1605 01:19:42,050 --> 01:19:45,770 in these unusual times, that you protect yourself 1606 01:19:45,770 --> 01:19:50,960 if you want to get these 9 credits on your transcript. 1607 01:19:50,960 --> 01:19:55,040 But mostly, I put this up again at this part of the semester, 1608 01:19:55,040 --> 01:20:00,000 just to say, we want to make this MIT experience as good, 1609 01:20:00,000 --> 01:20:02,280 given all the challenges as we can. 1610 01:20:02,280 --> 01:20:07,530 And we know it's a heck of a crazy time. 1611 01:20:07,530 --> 01:20:12,120 But to the extent you want me off hours or another time 1612 01:20:12,120 --> 01:20:14,740 or you've got questions that I'll further research, just let 1613 01:20:14,740 --> 01:20:15,240 me know. 1614 01:20:15,240 --> 01:20:17,623 Or if you have a fintech startup, let me know. 1615 01:20:17,623 --> 01:20:18,540 And I'll be all there. 1616 01:20:18,540 --> 01:20:19,860 And I'll read that, too. 1617 01:20:19,860 --> 01:20:21,490 I had one student recently send me 1618 01:20:21,490 --> 01:20:25,680 a whole paper on a fintech startup, just outside of this. 1619 01:20:25,680 --> 01:20:26,730 It's not an assignment. 1620 01:20:26,730 --> 01:20:28,440 But they're engaged in a startup. 1621 01:20:28,440 --> 01:20:31,765 And I'm going to review it and give some feedback.