1 00:00:08,080 --> 00:00:11,200 Speaker 1: Hello, and welcome to another edition of the Odd Lots Podcast. 2 00:00:11,280 --> 00:00:15,080 Speaker 1: I'm Joe Wisenthal, Managing editor at Bloomberg Markets, and I'm 3 00:00:15,120 --> 00:00:19,480 Speaker 1: Tracy Alloway, Executive editor at Bloomberg Markets. So, Joe, I'm 4 00:00:19,480 --> 00:00:23,200 Speaker 1: really excited about our guest for today's show. He is 5 00:00:23,400 --> 00:00:26,960 Speaker 1: one of my all time favorite banking analysts, a guy 6 00:00:27,000 --> 00:00:31,840 Speaker 1: called David Hendler. Why do you like this, uh analysts 7 00:00:31,880 --> 00:00:34,199 Speaker 1: so much? What is it about his work that separates 8 00:00:34,280 --> 00:00:37,440 Speaker 1: him from other banking analysts? All right, Well, David was 9 00:00:37,560 --> 00:00:41,880 Speaker 1: known for working at this research shop called Credit Sites. 10 00:00:41,960 --> 00:00:43,519 Speaker 1: I don't know if you've heard of them. They have 11 00:00:43,640 --> 00:00:47,159 Speaker 1: a bit of a Parish bias, some people would say. 12 00:00:47,400 --> 00:00:49,839 Speaker 1: But what David did really well is in the run 13 00:00:49,920 --> 00:00:52,600 Speaker 1: up to the financial crisis, he spotted a whole bunch 14 00:00:52,640 --> 00:00:55,160 Speaker 1: of the risks in the banking system that not that 15 00:00:55,200 --> 00:00:58,600 Speaker 1: many other people saw. And then after the financial crisis, 16 00:00:58,640 --> 00:01:00,680 Speaker 1: he was one of the banking analysts putting out some 17 00:01:00,880 --> 00:01:05,600 Speaker 1: really really interesting research out on the business of being 18 00:01:05,720 --> 00:01:09,680 Speaker 1: a bank, what was permanently broken and what could be fixed. Yeah, 19 00:01:09,720 --> 00:01:13,000 Speaker 1: this has become a really big topic. People have been 20 00:01:13,000 --> 00:01:14,959 Speaker 1: talking for the about this for a while, but in 21 00:01:15,000 --> 00:01:17,640 Speaker 1: the last several months, it seems like there's been this 22 00:01:17,720 --> 00:01:21,360 Speaker 1: big surge in people talking about this question of is 23 00:01:21,400 --> 00:01:25,800 Speaker 1: the traditional banking business model structurally flawed? In other words, 24 00:01:26,040 --> 00:01:29,959 Speaker 1: not just a slow recovery from the financial crisis, but 25 00:01:30,120 --> 00:01:34,080 Speaker 1: some sort of permanent impairment. Right, This is the classic 26 00:01:34,480 --> 00:01:38,800 Speaker 1: structural versus cyclical debate. Are things like fixed income the 27 00:01:38,800 --> 00:01:41,839 Speaker 1: bond trading business is going to come back or has 28 00:01:41,920 --> 00:01:46,640 Speaker 1: something permanently changed that means they're basically dead forever? And 29 00:01:47,000 --> 00:01:49,960 Speaker 1: we're definitely going to ask David how he feels about that. Well, 30 00:01:50,120 --> 00:01:53,560 Speaker 1: this is a huge question because there's so much writing 31 00:01:53,760 --> 00:01:56,240 Speaker 1: on the health of the bank, so much money is 32 00:01:56,280 --> 00:01:59,000 Speaker 1: in the banking sector, so much wealth, and so this 33 00:01:59,080 --> 00:02:01,800 Speaker 1: question of can the banks actually recover or they doomed 34 00:02:01,800 --> 00:02:04,440 Speaker 1: to be much smaller than they were on the early 35 00:02:04,560 --> 00:02:08,400 Speaker 1: part of the century is absolutely massive. So I'm looking 36 00:02:08,400 --> 00:02:21,160 Speaker 1: forward to getting the answer. All right. Here is David Hendler. 37 00:02:21,200 --> 00:02:23,920 Speaker 1: He is the former banking analyst at Credit Sites and 38 00:02:24,000 --> 00:02:26,880 Speaker 1: he is now founder and principle at his own risk 39 00:02:27,000 --> 00:02:30,639 Speaker 1: advisor of Viola. David, thanks so much for being with us. 40 00:02:31,320 --> 00:02:34,600 Speaker 1: Thank you for your time. So I supposed to be 41 00:02:35,000 --> 00:02:39,600 Speaker 1: begin You built this reputation as the guy who saw 42 00:02:39,639 --> 00:02:42,359 Speaker 1: a lot of the risks coming before the financial crisis. 43 00:02:42,639 --> 00:02:45,919 Speaker 1: How did you manage to do that? That's funny you 44 00:02:45,960 --> 00:02:49,640 Speaker 1: should ask um. Basically, I started on the bye side 45 00:02:49,680 --> 00:02:54,200 Speaker 1: at a conservative life insurance company, New York Life, and 46 00:02:54,560 --> 00:02:59,000 Speaker 1: they taught me some very good old age investment principles, 47 00:03:00,240 --> 00:03:05,920 Speaker 1: you know, where credit analysis was emphasized and uh, you know, 48 00:03:06,000 --> 00:03:12,360 Speaker 1: being I guess cautionary or skeptical when uh, you know, 49 00:03:12,600 --> 00:03:17,520 Speaker 1: new issue bonds were sold two investors as sucial investors 50 00:03:17,600 --> 00:03:19,520 Speaker 1: or secondary bonds were sold to be you know, a 51 00:03:19,520 --> 00:03:23,200 Speaker 1: little skeptical and not just take the up case, you know, 52 00:03:23,280 --> 00:03:25,480 Speaker 1: stress tested for the down case and then if you 53 00:03:25,520 --> 00:03:30,760 Speaker 1: felt comfortable and the spreads were and yields were you know, amenable, 54 00:03:30,880 --> 00:03:32,959 Speaker 1: you you know, you would do the deal. So I 55 00:03:33,000 --> 00:03:35,160 Speaker 1: think it's my early days on the by side in 56 00:03:35,200 --> 00:03:39,480 Speaker 1: the early to mid eighties. So what did you see 57 00:03:39,640 --> 00:03:44,880 Speaker 1: prior to the crisis, specifically that others were missing? Well, 58 00:03:44,920 --> 00:03:50,320 Speaker 1: I had been doing UH bank and finance analysis probably 59 00:03:50,600 --> 00:03:53,040 Speaker 1: for close to twenty years, So I saw a couple 60 00:03:53,040 --> 00:03:58,440 Speaker 1: of cycles. I saw the nine eighties energy bust, in 61 00:03:58,560 --> 00:04:04,320 Speaker 1: real estate bust and EXUS New England, California, and the 62 00:04:04,520 --> 00:04:08,200 Speaker 1: SNL debacle of the nineteen eighties, and I and and 63 00:04:08,240 --> 00:04:11,920 Speaker 1: then I saw, um, you know, the tech wreck of 64 00:04:11,960 --> 00:04:17,520 Speaker 1: the early two thousand, so I kind of understood how 65 00:04:18,240 --> 00:04:20,720 Speaker 1: things that look too good to be true usually were. 66 00:04:20,800 --> 00:04:23,400 Speaker 1: And you try to try to get ahead of the 67 00:04:23,520 --> 00:04:28,039 Speaker 1: decline by you know, writing reports and warning your customers 68 00:04:28,080 --> 00:04:32,279 Speaker 1: are investor base about the upcoming difficulties. Then as it 69 00:04:32,320 --> 00:04:34,880 Speaker 1: plays out, try to figure out if there's a risk 70 00:04:34,920 --> 00:04:40,200 Speaker 1: adjusted return opportunity on the on the upside. Once you know, 71 00:04:40,240 --> 00:04:43,400 Speaker 1: most people see it and they sell out, and they're 72 00:04:43,680 --> 00:04:46,920 Speaker 1: overly worried because you know, I just thought it never 73 00:04:46,920 --> 00:04:48,800 Speaker 1: could be this way before. Kind of like, you know, 74 00:04:48,839 --> 00:04:51,120 Speaker 1: the real estate markets are so strong in New York 75 00:04:51,200 --> 00:04:54,480 Speaker 1: City in the luxury area and people think it will 76 00:04:54,520 --> 00:04:58,520 Speaker 1: never go down. I think that's a negative signal there, David, 77 00:04:58,560 --> 00:05:01,719 Speaker 1: did any of your report before the crisis get you 78 00:05:01,760 --> 00:05:03,920 Speaker 1: into trouble? Because some of the stuff you were saying 79 00:05:03,960 --> 00:05:08,679 Speaker 1: back then was really controversial. What do you mean by trouble? 80 00:05:10,320 --> 00:05:13,320 Speaker 1: I mean I would say that at times at times, um, 81 00:05:13,360 --> 00:05:17,600 Speaker 1: you know, companies they wouldn't like it, and they would 82 00:05:17,680 --> 00:05:20,200 Speaker 1: call me about it or quote people that I worked 83 00:05:20,200 --> 00:05:24,000 Speaker 1: for about it. And you know usually, um, you know, 84 00:05:24,760 --> 00:05:27,080 Speaker 1: we just heard him out and that was it. Um. 85 00:05:27,960 --> 00:05:30,960 Speaker 1: So you know there was there was some friction. You know, 86 00:05:31,160 --> 00:05:34,919 Speaker 1: investors didn't do that. I would say, I say it 87 00:05:34,960 --> 00:05:38,560 Speaker 1: was more you know, the companies I covered. Let's uh, 88 00:05:38,720 --> 00:05:41,840 Speaker 1: let's spin it forward today. Right now, we're in this 89 00:05:41,920 --> 00:05:45,400 Speaker 1: period where people aren't so much concerned about a banking 90 00:05:45,560 --> 00:05:49,720 Speaker 1: collapse or anything like that, but concerned that the business 91 00:05:49,760 --> 00:05:52,320 Speaker 1: model of the major banks is just sort of in 92 00:05:52,800 --> 00:05:55,719 Speaker 1: either a permanently low state or a state of sort 93 00:05:55,760 --> 00:05:58,760 Speaker 1: of long decline, and that the business model that was 94 00:05:58,839 --> 00:06:02,680 Speaker 1: thriving pre crisis will never come back. What's your take 95 00:06:02,760 --> 00:06:05,680 Speaker 1: on that? And why are we seeing such a difficult 96 00:06:05,760 --> 00:06:08,760 Speaker 1: time for banks to hit goals of profitability? We see 97 00:06:08,760 --> 00:06:13,160 Speaker 1: these continued layoffs. What's going on now right Well, you know, 98 00:06:14,400 --> 00:06:18,160 Speaker 1: my thirty odd year career watching the bank sector in 99 00:06:18,200 --> 00:06:21,840 Speaker 1: the US, primarily, I mean there there wasn't really many 100 00:06:21,920 --> 00:06:25,760 Speaker 1: years that you would call normal. There's always like booms 101 00:06:25,800 --> 00:06:31,440 Speaker 1: and busts and maybe some quiet periods in between. So 102 00:06:31,800 --> 00:06:33,880 Speaker 1: I think what's happening is, you know, we have a 103 00:06:33,920 --> 00:06:38,320 Speaker 1: demographic shift from the baby boom whars, who are on 104 00:06:38,400 --> 00:06:42,440 Speaker 1: average fifty eight years old and they're retiring, and maybe 105 00:06:42,440 --> 00:06:44,800 Speaker 1: they don't have enough money to retire, So what's going 106 00:06:44,839 --> 00:06:47,440 Speaker 1: to happen with them? Can they put all their money 107 00:06:47,440 --> 00:06:49,839 Speaker 1: in the stock market now because the bond market doesn't 108 00:06:49,839 --> 00:06:53,520 Speaker 1: have enough interest yield to support their minimum living standards? 109 00:06:53,560 --> 00:06:55,920 Speaker 1: I don't know. I think it's kind of risky. So 110 00:06:56,200 --> 00:06:59,200 Speaker 1: I think you know you have that shift as well 111 00:06:59,200 --> 00:07:02,440 Speaker 1: as the Millennias, who have a certain way of life 112 00:07:02,480 --> 00:07:06,880 Speaker 1: that you know, favors urban dwellers, walkable commutes. But you 113 00:07:06,920 --> 00:07:11,040 Speaker 1: know what, it's getting expensive. And they heard lately that 114 00:07:11,240 --> 00:07:14,360 Speaker 1: on another media source that maybe the suburbs is a 115 00:07:14,400 --> 00:07:17,640 Speaker 1: better deal. Um, And you're seeing in a lot of 116 00:07:17,640 --> 00:07:22,080 Speaker 1: suburbs they're making little town centers that simulate sort of 117 00:07:22,080 --> 00:07:26,840 Speaker 1: a Brooklyn, you know, parts of New York City experience, 118 00:07:26,880 --> 00:07:28,440 Speaker 1: and you can get on the train and go into 119 00:07:28,480 --> 00:07:31,320 Speaker 1: the real thing once in a while. So, um, I 120 00:07:31,400 --> 00:07:34,560 Speaker 1: think you know that demographic shift is shifting how banking 121 00:07:34,960 --> 00:07:40,680 Speaker 1: is pitched distributed. You know, people don't go into the 122 00:07:40,680 --> 00:07:44,120 Speaker 1: branch anymore that these there are smartphones to make deposits, 123 00:07:44,120 --> 00:07:47,960 Speaker 1: so nobody really knows the bank anymore except it's an 124 00:07:47,960 --> 00:07:50,760 Speaker 1: app or something. So I think you know that's one 125 00:07:50,960 --> 00:07:55,600 Speaker 1: change that's reducing employment. Um, I think it increases risk 126 00:07:55,640 --> 00:07:58,720 Speaker 1: if you don't really know people on a humans fashion 127 00:07:58,840 --> 00:08:01,120 Speaker 1: like face to face. I think there's a lot of 128 00:08:02,840 --> 00:08:05,040 Speaker 1: threats like runs on the banks because you don't really 129 00:08:05,080 --> 00:08:07,200 Speaker 1: know anybody. When you get panick, you need to talk 130 00:08:07,200 --> 00:08:09,800 Speaker 1: to someone, but you never did, so how do you 131 00:08:09,880 --> 00:08:12,720 Speaker 1: do it? You know? I think that's one trend. You know. 132 00:08:12,760 --> 00:08:18,960 Speaker 1: The other trend is big data disintermediating back of offices UM, 133 00:08:19,200 --> 00:08:23,360 Speaker 1: computer type systems types as well as you know, different 134 00:08:23,360 --> 00:08:32,679 Speaker 1: types of loan officers UM. So you know, big data, cloud, bitcoin, blockchain. 135 00:08:32,840 --> 00:08:36,120 Speaker 1: You know, that's all reducing So it's like a human 136 00:08:36,760 --> 00:08:39,480 Speaker 1: thud cuts everywhere you look, there's some sort of threat 137 00:08:39,559 --> 00:08:42,720 Speaker 1: change and um, you know. Then there's a lot of 138 00:08:42,720 --> 00:08:46,439 Speaker 1: credit building up again in credit cards. We just pierced 139 00:08:46,640 --> 00:08:50,040 Speaker 1: one trillion and outstandings for the first time. I think 140 00:08:50,040 --> 00:08:53,680 Speaker 1: it's gonna double in size as the millennials use the 141 00:08:53,720 --> 00:08:58,120 Speaker 1: credit cards to realize their dreams by borrowing money, and 142 00:08:58,120 --> 00:08:59,800 Speaker 1: a lot of them are gonna get into trouble. They're 143 00:08:59,800 --> 00:09:04,400 Speaker 1: just humans like everybody other generations. So, um, commercial real 144 00:09:04,480 --> 00:09:07,199 Speaker 1: estate I think is gonna have some problems multi family, 145 00:09:07,240 --> 00:09:11,200 Speaker 1: which everyone thinks is a ticket to gold. It's I've 146 00:09:11,200 --> 00:09:15,080 Speaker 1: seen it in my own buying and selling in different 147 00:09:15,280 --> 00:09:18,600 Speaker 1: craze periods in the eighties and nineties and two thousands. 148 00:09:18,600 --> 00:09:20,960 Speaker 1: So you know, trees don't grow to the sky, and 149 00:09:21,000 --> 00:09:22,959 Speaker 1: you have to see when it's overdone and try to 150 00:09:23,000 --> 00:09:25,200 Speaker 1: get people to focus on it, because when they have 151 00:09:25,240 --> 00:09:26,959 Speaker 1: a house and it's going up at price, they don't 152 00:09:26,960 --> 00:09:29,240 Speaker 1: want to hear a story that housing is going down. 153 00:09:29,840 --> 00:09:32,120 Speaker 1: It hurts their own personal pocketbook. They just don't want 154 00:09:32,120 --> 00:09:35,800 Speaker 1: to face the reality. What about interest rate risk, David, 155 00:09:35,800 --> 00:09:38,000 Speaker 1: I remember this is something you talked a lot about 156 00:09:38,120 --> 00:09:41,360 Speaker 1: a few years ago, and since then, you know, rates 157 00:09:41,360 --> 00:09:43,880 Speaker 1: have stayed pretty low. We had one rate hike from 158 00:09:43,920 --> 00:09:46,720 Speaker 1: the Fed. We're talking about another one possibly this month 159 00:09:46,800 --> 00:09:50,840 Speaker 1: or next. Is that a risk for the banks? Well, 160 00:09:51,640 --> 00:09:56,360 Speaker 1: I think what's happened is rates have stayed low so 161 00:09:56,480 --> 00:09:58,040 Speaker 1: long that some of the things I talked about a 162 00:09:58,040 --> 00:10:02,880 Speaker 1: few years ago, they kind of um the yields rolled 163 00:10:02,880 --> 00:10:06,079 Speaker 1: into a lower environment, whether it was the investment securities, 164 00:10:06,160 --> 00:10:11,240 Speaker 1: the cash securities like MBS mortgage backed securities, or you know, 165 00:10:11,400 --> 00:10:15,760 Speaker 1: different types of derivatives that simulate you know, investment views 166 00:10:15,880 --> 00:10:20,559 Speaker 1: or mbs, So I think, uh, you know, rates banks 167 00:10:20,640 --> 00:10:22,640 Speaker 1: maybe you know, take a little bit more risk on 168 00:10:22,679 --> 00:10:25,000 Speaker 1: the on the cash side, it's hard to simulate it 169 00:10:25,160 --> 00:10:28,520 Speaker 1: as much on the synthetic derivative side. It's kind of 170 00:10:28,520 --> 00:10:31,760 Speaker 1: played out in a way. But you know, when rates rise, 171 00:10:32,040 --> 00:10:34,800 Speaker 1: you know, nobody really knows how sensitive deposits are to 172 00:10:34,880 --> 00:10:38,559 Speaker 1: hire rates. So far, with the basis point move, that 173 00:10:38,800 --> 00:10:43,520 Speaker 1: has not been you know, a huge outmigration from bank deposits. 174 00:10:43,559 --> 00:10:47,440 Speaker 1: But we'll see how it goes, if how gradual the 175 00:10:47,520 --> 00:10:51,800 Speaker 1: fet is um the pace and how you know deposits 176 00:10:51,840 --> 00:10:55,000 Speaker 1: react as deposits could read price faster than bank loans 177 00:10:55,000 --> 00:10:59,720 Speaker 1: could be or securities yields. What about the decline of 178 00:10:59,760 --> 00:11:03,439 Speaker 1: these trading businesses, So we continue to see the major 179 00:11:03,840 --> 00:11:06,160 Speaker 1: Wall Street banks slim the ranks of their trading. They 180 00:11:06,160 --> 00:11:08,120 Speaker 1: always talk this was a bad quarter for trading and 181 00:11:08,160 --> 00:11:11,200 Speaker 1: there wasn't a volatility. Is that business ever going to 182 00:11:11,679 --> 00:11:14,880 Speaker 1: thrive in a big way again? It's going back to 183 00:11:15,040 --> 00:11:22,160 Speaker 1: its core purpose, which is capital creation to grow businesses 184 00:11:22,400 --> 00:11:27,720 Speaker 1: or consumer asset classes less speculative by far less speculative. 185 00:11:28,200 --> 00:11:31,040 Speaker 1: So I you know, under the current regime, Dot Frank 186 00:11:31,160 --> 00:11:35,560 Speaker 1: BOSEL three and all the implementations. And know what we 187 00:11:35,640 --> 00:11:40,199 Speaker 1: saw in the you know two thousands. You know, you're 188 00:11:40,200 --> 00:11:42,040 Speaker 1: not going to see for a while whether that gets 189 00:11:42,120 --> 00:11:46,280 Speaker 1: rolled back with different political movements, whether it's Bernie Sanders 190 00:11:46,360 --> 00:11:49,600 Speaker 1: or Donald Trump or even Hillary Clinton. You know, we'll 191 00:11:49,640 --> 00:11:53,120 Speaker 1: see um. But for the time being, you know, trading 192 00:11:53,200 --> 00:11:56,720 Speaker 1: desks have been derisked. Um. You know, if you want to, 193 00:11:57,520 --> 00:12:00,520 Speaker 1: you know, gamble, you know, you gotta do it in 194 00:12:01,080 --> 00:12:06,199 Speaker 1: non regulated markets or sports fantasy leagues or so you 195 00:12:06,200 --> 00:12:08,880 Speaker 1: would say. The main problem, the reason those desks aren't 196 00:12:08,880 --> 00:12:16,000 Speaker 1: as profitable, essentially they've been stripped of their ability to gamble. Correct, David, 197 00:12:16,040 --> 00:12:18,400 Speaker 1: give us a snapshot of what the Bank of the 198 00:12:18,440 --> 00:12:20,960 Speaker 1: future is going to look like, say in ten or 199 00:12:21,000 --> 00:12:23,240 Speaker 1: twenty years, is it going to be recognizable to what 200 00:12:23,280 --> 00:12:27,280 Speaker 1: we have today. Well, it's gonna I was just anticipating 201 00:12:27,280 --> 00:12:28,760 Speaker 1: that question. I think it's gonna be a little like 202 00:12:28,840 --> 00:12:33,559 Speaker 1: you know, you know, Johnson Space Control, Mission control. You're 203 00:12:33,559 --> 00:12:38,480 Speaker 1: gonna have you know, a few dozen really smart guys 204 00:12:38,520 --> 00:12:41,160 Speaker 1: and women running the bank, and then a lot of 205 00:12:41,200 --> 00:12:45,920 Speaker 1: it's going to be automated and cloud distributed. You're not 206 00:12:45,960 --> 00:12:47,880 Speaker 1: gonna have you know, you're gonna have you may have 207 00:12:47,920 --> 00:12:51,960 Speaker 1: more robotic investment management. I mean the by sides really 208 00:12:52,000 --> 00:12:54,280 Speaker 1: at risk. I think there was a story about Fink 209 00:12:54,440 --> 00:12:57,680 Speaker 1: at black Rock saying there's would be a wave of 210 00:12:57,720 --> 00:13:03,080 Speaker 1: consolidation and asset management. UM. So you know, people the 211 00:13:03,120 --> 00:13:07,439 Speaker 1: younger generation is more comfortable doing businesses on a smartphone 212 00:13:07,600 --> 00:13:10,640 Speaker 1: or Skype or whatever. So it's gonna be a lot 213 00:13:10,760 --> 00:13:16,480 Speaker 1: less people pushing out even more credit. Um. But there's 214 00:13:16,600 --> 00:13:19,760 Speaker 1: risks because you know, the best way to you do 215 00:13:20,040 --> 00:13:23,240 Speaker 1: credit businesses is to look at someone's eye and decided 216 00:13:23,280 --> 00:13:26,040 Speaker 1: that person really gonna pay me back. And I'm not 217 00:13:26,200 --> 00:13:30,080 Speaker 1: sure if fintech has solved that. Yeah, it doesn't sound 218 00:13:30,120 --> 00:13:33,679 Speaker 1: like then you're very optimistic about some of they's new 219 00:13:33,679 --> 00:13:38,480 Speaker 1: marketplace lenders or other attempts to make lending more efficient. 220 00:13:38,520 --> 00:13:41,360 Speaker 1: If you think there's still a value in looking at 221 00:13:41,400 --> 00:13:45,120 Speaker 1: someone in the eye, yeah, I would agree, or being 222 00:13:45,160 --> 00:13:48,560 Speaker 1: in the same room and having a context about what's 223 00:13:48,600 --> 00:13:50,640 Speaker 1: going on. So you know, fintech is going to go 224 00:13:50,679 --> 00:13:54,199 Speaker 1: through an evolution of fits and starts of discovery of 225 00:13:54,240 --> 00:13:57,280 Speaker 1: what sort of works and maybe it being overdone and 226 00:13:57,320 --> 00:13:59,280 Speaker 1: it doesn't work. And I think we're starting to see 227 00:14:00,040 --> 00:14:03,040 Speaker 1: some models, you know, break down a little, even though 228 00:14:03,040 --> 00:14:05,760 Speaker 1: there was a lot of fanfare for things like lending 229 00:14:05,800 --> 00:14:10,280 Speaker 1: club UM and others, you know, where the algorithms don't 230 00:14:10,320 --> 00:14:14,360 Speaker 1: capture the human element precisely, and uh, they get carried 231 00:14:14,360 --> 00:14:20,760 Speaker 1: away standing credit automatically. Are there any technologies you mentioned 232 00:14:20,800 --> 00:14:23,400 Speaker 1: mobile it's going to be a key avenue banking. You 233 00:14:23,440 --> 00:14:27,120 Speaker 1: mentioned the cloud. Are there any technology other technologies that 234 00:14:27,160 --> 00:14:29,360 Speaker 1: you are actually quite bullish on or that you think 235 00:14:29,360 --> 00:14:31,840 Speaker 1: will be really important? I mean maybe yeah, some of 236 00:14:31,880 --> 00:14:34,000 Speaker 1: the lending clubs won't live up to the hype. But 237 00:14:34,280 --> 00:14:36,160 Speaker 1: are there areas that you think right now are being 238 00:14:36,240 --> 00:14:39,880 Speaker 1: underestimated that are going to change the nature of finance? Well, 239 00:14:39,880 --> 00:14:43,600 Speaker 1: I think you know, where you can make mundane practices 240 00:14:45,200 --> 00:14:51,320 Speaker 1: more efficient and less intrusive on somebody's lifestyle, like you know, 241 00:14:51,440 --> 00:14:55,080 Speaker 1: quick pay or Venmo or PayPal. You know, I think 242 00:14:55,280 --> 00:14:58,560 Speaker 1: things like that have been I think successful, Like more 243 00:14:58,600 --> 00:15:02,120 Speaker 1: on the transaction process s side, where going to the 244 00:15:02,160 --> 00:15:04,840 Speaker 1: bank and getting your past book stamped with interest, which 245 00:15:04,880 --> 00:15:07,440 Speaker 1: is what I did when I as a kid, you know, 246 00:15:07,560 --> 00:15:11,520 Speaker 1: on my paper route, say, um, depositing that check. You know, 247 00:15:11,520 --> 00:15:13,880 Speaker 1: you just don't need to do that anymore, so I 248 00:15:13,920 --> 00:15:23,120 Speaker 1: think there's you know, lifestyle efficiency, productivity applications and activities 249 00:15:23,160 --> 00:15:26,680 Speaker 1: that you know, make banking just easier on everybody. What 250 00:15:26,760 --> 00:15:30,080 Speaker 1: about blockchain you mentioned that earlier. Do you think I mean, 251 00:15:30,080 --> 00:15:32,280 Speaker 1: there's a lot of hype about that, but I haven't 252 00:15:32,400 --> 00:15:36,240 Speaker 1: really grasped how that's going to change things. Do you 253 00:15:36,360 --> 00:15:41,080 Speaker 1: see a significant role for that technology in finance? I mean, 254 00:15:41,120 --> 00:15:43,440 Speaker 1: I'm not an expert in it, but you know it's 255 00:15:43,520 --> 00:15:49,120 Speaker 1: trying to make things more transparent for the ledger of 256 00:15:49,160 --> 00:15:55,320 Speaker 1: different activities, whether it's trading or you know, payment systems. 257 00:15:55,480 --> 00:16:00,000 Speaker 1: We have massive amounts of payments going one way or another. Um, 258 00:16:00,160 --> 00:16:03,120 Speaker 1: so I think it's going to help on the efficiency side. 259 00:16:03,520 --> 00:16:07,400 Speaker 1: And uh, you know what's happening with banking, and I 260 00:16:07,480 --> 00:16:10,600 Speaker 1: said this in different reports and different talks, is that 261 00:16:11,240 --> 00:16:14,400 Speaker 1: it's really becoming a commoditized business. We have to brand 262 00:16:14,480 --> 00:16:19,480 Speaker 1: it to get loyalty so that you could reuse the product, 263 00:16:20,360 --> 00:16:25,200 Speaker 1: the investment the product across more users and people. So 264 00:16:25,360 --> 00:16:27,680 Speaker 1: you know, you need a strong brand. And when you 265 00:16:27,720 --> 00:16:31,479 Speaker 1: have brands, you have to deliver on the brand concepts. 266 00:16:31,480 --> 00:16:35,240 Speaker 1: So you know, banks like Chase should continue to do well. 267 00:16:35,520 --> 00:16:38,640 Speaker 1: Banks like City self to prove themselves again, even though 268 00:16:38,680 --> 00:16:41,360 Speaker 1: they kind of with the first big bank to do 269 00:16:41,800 --> 00:16:44,920 Speaker 1: mass marketing of credit cards back in the seventies and eighties, 270 00:16:45,360 --> 00:16:49,280 Speaker 1: Bank of America's trying to get that brand of you know, 271 00:16:49,360 --> 00:16:55,600 Speaker 1: reliability across mortgages and credit cards and you know other activities. 272 00:16:55,640 --> 00:16:58,520 Speaker 1: So um, I think that's the key. Do you have 273 00:16:58,560 --> 00:17:02,479 Speaker 1: a brand and then you leverage the efficiency that technology 274 00:17:02,520 --> 00:17:06,880 Speaker 1: presents to your customer base. So it's brand and human element. 275 00:17:07,200 --> 00:17:09,359 Speaker 1: David Hendler, thank you very much for joining us. I 276 00:17:09,359 --> 00:17:12,359 Speaker 1: think there's gonna be a fascinating debate and conversation to 277 00:17:12,480 --> 00:17:14,560 Speaker 1: track in the coming years, and we hope you'll come 278 00:17:14,600 --> 00:17:17,520 Speaker 1: back at some point for a update on how things evolved. 279 00:17:17,680 --> 00:17:26,679 Speaker 1: Thanks so much, Thank you, Tracy. I think this is 280 00:17:26,720 --> 00:17:30,640 Speaker 1: going to be a really interesting topic that we're going 281 00:17:30,680 --> 00:17:33,440 Speaker 1: to be talking about from many years. And I feel 282 00:17:33,480 --> 00:17:37,680 Speaker 1: like this is an area the future of the bank 283 00:17:37,760 --> 00:17:40,719 Speaker 1: that everyone is sort of clawing around for an answer, 284 00:17:40,720 --> 00:17:43,240 Speaker 1: and I just don't feel like, uh, I just feel 285 00:17:43,240 --> 00:17:44,800 Speaker 1: like there's gonna be like a huge mystery we're all 286 00:17:44,800 --> 00:17:48,560 Speaker 1: gonna be talking about. Well, I suppose in ten or 287 00:17:48,600 --> 00:17:51,720 Speaker 1: twenty years we'll have to reconvene all thoughts and figure 288 00:17:51,760 --> 00:17:54,040 Speaker 1: out where we've come out. But I do like the 289 00:17:54,080 --> 00:17:59,200 Speaker 1: idea from David of having bankers sort of like pilot 290 00:17:59,200 --> 00:18:02,800 Speaker 1: the Starship bank, right, like everyone, you just have a 291 00:18:02,800 --> 00:18:04,480 Speaker 1: couple of people who are sitting in front of a 292 00:18:04,520 --> 00:18:07,120 Speaker 1: computer and they sort of control it and direct this 293 00:18:07,400 --> 00:18:11,160 Speaker 1: massive organization, and you don't need as many people anymore. 294 00:18:11,200 --> 00:18:14,320 Speaker 1: But the other interesting thing he brought up was the 295 00:18:14,359 --> 00:18:18,320 Speaker 1: trade off. Right, if everything is electronic and you're not 296 00:18:18,400 --> 00:18:22,840 Speaker 1: really interacting with people in person anymore, is that bad 297 00:18:22,880 --> 00:18:26,880 Speaker 1: for credit management? Yeah? Yeah, exactly. It seems like there's 298 00:18:26,960 --> 00:18:29,080 Speaker 1: kind of a contradiction. So on the one hand, you 299 00:18:29,160 --> 00:18:33,680 Speaker 1: have the person sitting behind the Starship enterprise with all 300 00:18:33,720 --> 00:18:36,720 Speaker 1: this technology around them, But on the other hand, as 301 00:18:36,720 --> 00:18:40,920 Speaker 1: you pointed out, there's still no better way to assess 302 00:18:40,960 --> 00:18:45,399 Speaker 1: someone's credit viability that talking to them and actually getting 303 00:18:45,440 --> 00:18:48,080 Speaker 1: to know them. So it feels like this is something 304 00:18:48,280 --> 00:18:50,080 Speaker 1: we're going to be wrestling with for a while. I mean, 305 00:18:50,080 --> 00:18:53,040 Speaker 1: we talked about a couple episodes ago what's going on 306 00:18:53,280 --> 00:18:56,399 Speaker 1: with Lending Club and the attempts to use big data 307 00:18:56,520 --> 00:19:00,320 Speaker 1: or whatever to assist credit worthiness, But it doesn't sound 308 00:19:01,200 --> 00:19:04,560 Speaker 1: like that issue has been solved yet. It still sounds 309 00:19:04,600 --> 00:19:07,080 Speaker 1: like there's a contradiction here. No, I don't think anyone's 310 00:19:07,080 --> 00:19:09,920 Speaker 1: cracked it just yet. So we'll have plenty of stuff 311 00:19:09,960 --> 00:19:12,119 Speaker 1: to have plenty of talk about, and I look forward 312 00:19:12,160 --> 00:19:15,920 Speaker 1: to Odd Lots episodes in the year twenty thirty six 313 00:19:15,920 --> 00:19:18,560 Speaker 1: where we see how this all developed. All right, I'll 314 00:19:18,600 --> 00:19:21,320 Speaker 1: see you then. Thanks everyone for listening to the latest 315 00:19:21,320 --> 00:19:24,400 Speaker 1: episode of the Odd Lots Podcast. I'm Joe Wisn't All. 316 00:19:24,440 --> 00:19:26,919 Speaker 1: You could follow me on Twitter at the Stalwart and 317 00:19:26,960 --> 00:19:30,040 Speaker 1: I'm Tracy Alloway. I'm on Twitter at Tracy Alloway. Thanks 318 00:19:30,080 --> 00:19:30,560 Speaker 1: for listening.