1 00:00:02,279 --> 00:00:06,880 Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio. 2 00:00:09,720 --> 00:00:12,160 Speaker 1: This week on the podcast, I have a special guest. 3 00:00:12,320 --> 00:00:14,160 Speaker 1: His name is David en Rich, and he is a 4 00:00:14,200 --> 00:00:17,959 Speaker 1: reporter for The New York Times. But more importantly, he 5 00:00:18,120 --> 00:00:22,239 Speaker 1: is the author of The Spider Network, The wild story 6 00:00:22,360 --> 00:00:26,920 Speaker 1: of a math genius, a gang of backstabbing bankers, and 7 00:00:27,040 --> 00:00:31,680 Speaker 1: one of the greatest scams in financial history. It is 8 00:00:31,840 --> 00:00:36,720 Speaker 1: all about libor and how that scandal, which is not 9 00:00:36,840 --> 00:00:41,760 Speaker 1: even a decade old, unfolded. Uh. We are talking about 10 00:00:42,280 --> 00:00:45,839 Speaker 1: not just millions of dollars, not just billions of dollars, 11 00:00:46,320 --> 00:00:50,800 Speaker 1: but hundreds of trillions of dollars that were manipulated in 12 00:00:50,840 --> 00:00:57,800 Speaker 1: different directions for people two capture some trading profits. And 13 00:00:57,840 --> 00:01:01,720 Speaker 1: when you stop and think about all the assets that 14 00:01:01,960 --> 00:01:06,240 Speaker 1: trade based on LIEB or UH, if you have a 15 00:01:06,600 --> 00:01:09,560 Speaker 1: variable mortgage, or a car loan, or credit card loans 16 00:01:09,680 --> 00:01:13,240 Speaker 1: or student loans, you may have been paying more for 17 00:01:13,280 --> 00:01:18,320 Speaker 1: those interest payments due to some of these manipulations by 18 00:01:18,480 --> 00:01:23,440 Speaker 1: various bankers. Arguably occasionally you were paying less because they 19 00:01:23,520 --> 00:01:26,920 Speaker 1: manipulated it in the other direction. Um. The book is 20 00:01:26,959 --> 00:01:29,600 Speaker 1: really quite fascinating. I'm not finished with it yet. I'm 21 00:01:29,600 --> 00:01:32,920 Speaker 1: working my way through it, but it really reads like, uh, 22 00:01:32,959 --> 00:01:36,480 Speaker 1: you know, an Ian Fleming novel. It's it's a spy tail. 23 00:01:36,600 --> 00:01:39,759 Speaker 1: There are some fascinating characters in it. Uh. It really 24 00:01:39,840 --> 00:01:42,840 Speaker 1: is a great narrative, and David does a wonderful job 25 00:01:43,400 --> 00:01:48,600 Speaker 1: bringing some really arcane uh minutia to life in a 26 00:01:48,640 --> 00:01:52,880 Speaker 1: way that's fascinating and understandable. Uh. I think that if 27 00:01:52,920 --> 00:01:56,720 Speaker 1: you're remotely interested in the world of fixed income or 28 00:01:57,280 --> 00:02:01,120 Speaker 1: borrowing or derivatives, this is a must read and it's 29 00:02:01,160 --> 00:02:06,600 Speaker 1: gonna enter the pantheon of great financial narratives. So, with 30 00:02:06,640 --> 00:02:10,560 Speaker 1: no further ado, here is my conversation with David Enrich. 31 00:02:12,919 --> 00:02:17,519 Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio. 32 00:02:20,440 --> 00:02:23,359 Speaker 1: My guest today is David Enrich. He is a New 33 00:02:23,440 --> 00:02:28,040 Speaker 1: York Times reporter and editor UH since the summer ofen 34 00:02:28,320 --> 00:02:31,120 Speaker 1: Prior to that, he worked for The Wall Street Journal 35 00:02:31,200 --> 00:02:35,120 Speaker 1: for a decade, writing about banking and finance in the 36 00:02:35,200 --> 00:02:41,200 Speaker 1: United States. UH. He has won numerous journalism awards, including 37 00:02:41,639 --> 00:02:44,680 Speaker 1: the Overseas Press Club Award for his coverage of the 38 00:02:44,720 --> 00:02:48,800 Speaker 1: European debt crisis, the George Polk Award for coverage on 39 00:02:48,880 --> 00:02:53,560 Speaker 1: Instarter Trading. He won two Society of American Business Editors 40 00:02:53,600 --> 00:02:57,760 Speaker 1: and Writers Awards. David was part of two teams of 41 00:02:57,880 --> 00:03:01,119 Speaker 1: journal reporters who were finalists for Pool Surprises in both 42 00:03:01,160 --> 00:03:04,600 Speaker 1: two thousand and nine and two thousand and eleven. He 43 00:03:04,760 --> 00:03:09,160 Speaker 1: won the prestigious Gerald Loebe Award for Feature Writing for 44 00:03:09,240 --> 00:03:13,480 Speaker 1: his coverage on the unraveling of Tom Hayes, the expos 45 00:03:13,520 --> 00:03:18,000 Speaker 1: about the Libor scandal that eventually led to him writing 46 00:03:18,040 --> 00:03:21,800 Speaker 1: a book on it titled The Spider Network. How a 47 00:03:21,919 --> 00:03:25,600 Speaker 1: math genius and a gang of scheming bankers pulled off 48 00:03:25,720 --> 00:03:30,120 Speaker 1: one of the greatest scams in history. David Enrich, Welcome 49 00:03:30,120 --> 00:03:33,800 Speaker 1: to Bloomberg. Thank you. I'm fascinated by the library scandal. 50 00:03:34,480 --> 00:03:37,680 Speaker 1: Folks like you and I who cover this are pretty 51 00:03:37,720 --> 00:03:42,360 Speaker 1: familiar with some of the minutia and details about Libor. 52 00:03:42,800 --> 00:03:46,680 Speaker 1: But for the lay person listening to this, what exactly 53 00:03:47,000 --> 00:03:50,760 Speaker 1: is liebar and why is it so important? It's an acronym. 54 00:03:50,800 --> 00:03:54,720 Speaker 1: It stands for the London Interbank Offered Grade and it 55 00:03:54,920 --> 00:03:58,480 Speaker 1: is the world's most important number. The world's most important number. 56 00:03:58,920 --> 00:04:02,119 Speaker 1: That's quite a claim, it is. Explain why it's it's 57 00:04:02,160 --> 00:04:05,280 Speaker 1: such an important number? What what is it used for. 58 00:04:05,640 --> 00:04:08,640 Speaker 1: It sets interest rates on all sorts of debt all 59 00:04:08,680 --> 00:04:11,840 Speaker 1: over the world. So if you have an adjustable rate mortgage, 60 00:04:11,880 --> 00:04:13,440 Speaker 1: the interest rate is based on libor. If you have 61 00:04:13,440 --> 00:04:16,000 Speaker 1: a credit card, a student loan, and auto loan, it's 62 00:04:16,040 --> 00:04:18,960 Speaker 1: likely based on libor. If you are a big company 63 00:04:19,200 --> 00:04:21,520 Speaker 1: and are issuing debt, the interest rate might be based 64 00:04:21,520 --> 00:04:23,400 Speaker 1: on librar. Same if you're a town or city. They're 65 00:04:23,440 --> 00:04:26,640 Speaker 1: trillions and trillions of dollars of this stuff, trillions, trillions, 66 00:04:26,680 --> 00:04:29,240 Speaker 1: And the biggest part is not the just normal debt, 67 00:04:29,240 --> 00:04:33,719 Speaker 1: it's derivatives that are that you know. Originally companies or 68 00:04:33,839 --> 00:04:37,640 Speaker 1: investors were using them to protect themselves to hedge the 69 00:04:38,279 --> 00:04:42,960 Speaker 1: against possible fluctuations and interest rates, and later, as you 70 00:04:42,960 --> 00:04:45,880 Speaker 1: know often happens in the financial world, they became a 71 00:04:45,920 --> 00:04:49,960 Speaker 1: playground for speculators and traders. So I learned a lot 72 00:04:50,000 --> 00:04:53,640 Speaker 1: of different things from the book, one of which was 73 00:04:53,760 --> 00:04:58,640 Speaker 1: that essentially decades ago, a Greek BANKO was trying to 74 00:04:58,880 --> 00:05:02,440 Speaker 1: arrange an eighty milli million dollar loan for the shav 75 00:05:02,560 --> 00:05:05,960 Speaker 1: I Ran and the syndication process lead to a question 76 00:05:06,000 --> 00:05:09,120 Speaker 1: how are you going to set rates? And that effectively 77 00:05:09,200 --> 00:05:11,640 Speaker 1: is the origin of live or is is that right? Yeah, 78 00:05:11,720 --> 00:05:14,520 Speaker 1: that is right, and this is I really like history, 79 00:05:14,760 --> 00:05:17,960 Speaker 1: and so researching this is just fascinating for me, and 80 00:05:18,040 --> 00:05:21,839 Speaker 1: they're Uh. Originally, you know, if you think about how 81 00:05:22,040 --> 00:05:24,480 Speaker 1: does an interst rate come into being when a bank 82 00:05:24,560 --> 00:05:26,760 Speaker 1: offers a loan to someone, how do they determine what 83 00:05:26,800 --> 00:05:28,960 Speaker 1: they're going to pay? And the general rule of thumb 84 00:05:29,000 --> 00:05:31,440 Speaker 1: was that they are going to base the interest rate 85 00:05:31,440 --> 00:05:34,120 Speaker 1: they're putting on a loan based on how much it 86 00:05:34,160 --> 00:05:37,480 Speaker 1: costs the bank to borrow money. So it's it's the 87 00:05:37,600 --> 00:05:41,520 Speaker 1: borrowing rate plus some margin, which becomes a profit. Yeah, exactly, 88 00:05:41,560 --> 00:05:44,760 Speaker 1: And so obviously the banks need to have a profit, 89 00:05:44,800 --> 00:05:47,360 Speaker 1: and so they eventually normally that would be simple if 90 00:05:47,360 --> 00:05:49,640 Speaker 1: it's just one bank making a loan. But the history 91 00:05:49,680 --> 00:05:51,600 Speaker 1: of this is that at the kind of dawn of 92 00:05:51,640 --> 00:05:54,240 Speaker 1: the era where loans, big loans are being syndicated, you 93 00:05:54,279 --> 00:05:57,239 Speaker 1: had a big group of banks getting together to team 94 00:05:57,320 --> 00:05:59,680 Speaker 1: up on to make big loans. In this case, it 95 00:05:59,760 --> 00:06:01,880 Speaker 1: was a loan in eighty million dollar loan to the 96 00:06:01,880 --> 00:06:04,960 Speaker 1: Shah of Iran at the time. And uh, how do 97 00:06:05,040 --> 00:06:07,000 Speaker 1: you have different banks of different funding costs, how do 98 00:06:07,000 --> 00:06:09,360 Speaker 1: you determine the interest rate? And so the innovation here 99 00:06:09,920 --> 00:06:12,240 Speaker 1: was that you can have you can come up with 100 00:06:12,279 --> 00:06:14,880 Speaker 1: an average basically, and you can look at how much 101 00:06:14,920 --> 00:06:16,479 Speaker 1: does it if you've got ten banks on it, you 102 00:06:16,640 --> 00:06:19,479 Speaker 1: take their average funding cost and that can be the 103 00:06:19,480 --> 00:06:22,560 Speaker 1: interest rate plus a little bit. And the challenge though, 104 00:06:22,640 --> 00:06:25,479 Speaker 1: is that funding costs change and what you're if you're 105 00:06:25,520 --> 00:06:28,279 Speaker 1: making a twenty year loan, your funding costs at year 106 00:06:28,320 --> 00:06:31,159 Speaker 1: one could be very different from your funding costs at 107 00:06:31,200 --> 00:06:33,520 Speaker 1: year ten or twenty. And that is a very scary 108 00:06:33,520 --> 00:06:35,480 Speaker 1: thing for the banks because you know, if their funding 109 00:06:35,520 --> 00:06:38,839 Speaker 1: costs go up, you could be locked into a loan 110 00:06:39,040 --> 00:06:41,359 Speaker 1: that is deeply unprofitable for the bank. And so the 111 00:06:41,400 --> 00:06:44,960 Speaker 1: innovation here that they would have a mechanism where the 112 00:06:45,000 --> 00:06:47,320 Speaker 1: interest rate would fluctuate over time based on the bank's 113 00:06:47,320 --> 00:06:50,680 Speaker 1: funding costs. So so, given those kind of murky origins, 114 00:06:50,800 --> 00:06:56,520 Speaker 1: the Greek bankers syndicated loan to the shaw of Iran. 115 00:06:57,000 --> 00:07:00,279 Speaker 1: How did this become the most important number in the world. 116 00:07:00,320 --> 00:07:04,039 Speaker 1: How did this become so widely accepted everywhere? Yeah, So 117 00:07:04,080 --> 00:07:07,400 Speaker 1: in the mid nineteen eighties, the British Bankers Association, which 118 00:07:07,400 --> 00:07:10,720 Speaker 1: was a trade organization basically lobbying group b v A yeah, 119 00:07:10,760 --> 00:07:13,960 Speaker 1: the b b A for not only the big British banks, 120 00:07:14,000 --> 00:07:15,560 Speaker 1: but for many of the biggest banks in the world 121 00:07:15,560 --> 00:07:18,880 Speaker 1: that had set up shop in London. They got together 122 00:07:18,960 --> 00:07:21,120 Speaker 1: with the Bank of England, the central bank there, and 123 00:07:21,160 --> 00:07:23,840 Speaker 1: they decided the use of derivatives was really booming and 124 00:07:23,840 --> 00:07:26,760 Speaker 1: they need figured they needed a standardized way. Instead of 125 00:07:26,800 --> 00:07:29,000 Speaker 1: every time there's a loan or any type of financial 126 00:07:29,040 --> 00:07:32,160 Speaker 1: contract cobbling together this kind of ad hoc system for 127 00:07:32,600 --> 00:07:34,760 Speaker 1: determining interest rates, they figured it would be a much 128 00:07:34,840 --> 00:07:37,640 Speaker 1: better way to standardize or much better idea to standardize this, 129 00:07:37,720 --> 00:07:40,360 Speaker 1: and so live work came into existence as something that 130 00:07:40,480 --> 00:07:43,080 Speaker 1: was every day around lunch time in London, a group 131 00:07:43,120 --> 00:07:45,640 Speaker 1: of the world's biggest banks would estimate how much it 132 00:07:45,720 --> 00:07:48,720 Speaker 1: costs them to borrow money from each other. And you know, 133 00:07:48,760 --> 00:07:51,560 Speaker 1: you could do it in different currencies, so and pound, 134 00:07:51,640 --> 00:07:56,200 Speaker 1: sterling and dollars and euros, in Japanese yen, and you 135 00:07:56,200 --> 00:07:58,320 Speaker 1: can do it over a different time period. So you 136 00:07:58,360 --> 00:08:00,640 Speaker 1: know it's going to cost a bank for an amount 137 00:08:00,720 --> 00:08:03,520 Speaker 1: to borrow money for one day or a week, or 138 00:08:03,560 --> 00:08:06,080 Speaker 1: a month or a year, and the longer the duration 139 00:08:06,120 --> 00:08:09,040 Speaker 1: of that loan to hire, the interest rate generally and 140 00:08:09,200 --> 00:08:11,640 Speaker 1: you can every day. So every day, at lunchtime, a 141 00:08:11,640 --> 00:08:14,480 Speaker 1: group of the world's biggest banks gets together, someone comes 142 00:08:14,520 --> 00:08:16,720 Speaker 1: up with an estimate for theoretically how much it would 143 00:08:16,720 --> 00:08:19,520 Speaker 1: cost them to borrow money in a specific currency over 144 00:08:19,520 --> 00:08:22,400 Speaker 1: a specific time period. All those numbers get smushed together, 145 00:08:22,480 --> 00:08:24,560 Speaker 1: the high estimates and the lowest mints get booted out, 146 00:08:25,160 --> 00:08:27,960 Speaker 1: and the rest are averaged in presto, you've got labor. 147 00:08:28,520 --> 00:08:33,439 Speaker 1: That's quite fascinating. You raised a couple of really interesting 148 00:08:33,480 --> 00:08:36,200 Speaker 1: points I have to follow up on. The first is 149 00:08:36,720 --> 00:08:40,760 Speaker 1: why lunchtime almost everything else is set at the close 150 00:08:40,800 --> 00:08:43,960 Speaker 1: of business during the end of the day. Why the 151 00:08:44,000 --> 00:08:46,960 Speaker 1: middle of the banking day, the trading day would you 152 00:08:47,000 --> 00:08:49,520 Speaker 1: want to set interest rates? What what is that about? 153 00:08:49,600 --> 00:08:52,400 Speaker 1: Because this was this was developed in a pre computer era, 154 00:08:52,559 --> 00:08:55,480 Speaker 1: was the mid nineties, and to determine how much a 155 00:08:55,559 --> 00:08:58,120 Speaker 1: bank it cost a bank to borrow money, you needed 156 00:08:58,120 --> 00:09:00,360 Speaker 1: to check with various parts of the bank. So someone 157 00:09:00,559 --> 00:09:02,640 Speaker 1: this is usually a pretty low level person with kind 158 00:09:02,640 --> 00:09:05,320 Speaker 1: of the bowels of the bank, and he would come 159 00:09:05,360 --> 00:09:07,679 Speaker 1: in the morning and start making phone calls to different 160 00:09:07,679 --> 00:09:10,000 Speaker 1: parts of the bank to try and assess how much 161 00:09:10,120 --> 00:09:12,280 Speaker 1: it costs them to borrow money. And remember this isn't 162 00:09:12,360 --> 00:09:14,920 Speaker 1: one phone call, because this is most of these banks 163 00:09:14,920 --> 00:09:19,000 Speaker 1: are global at this point and they have operations all 164 00:09:19,040 --> 00:09:21,360 Speaker 1: over the world. And you know, so he has this 165 00:09:21,360 --> 00:09:25,360 Speaker 1: guy has to call the treasury desk in Tokyo, Singapore, 166 00:09:25,600 --> 00:09:28,200 Speaker 1: in New York. It's actually a full time job determining 167 00:09:28,240 --> 00:09:31,200 Speaker 1: live boards. Well it was kind of a halftime, let's say. 168 00:09:31,200 --> 00:09:34,400 Speaker 1: And it was again, this is someone who is usually 169 00:09:34,440 --> 00:09:37,800 Speaker 1: a clerk and entry level job, an aspiring trader. So 170 00:09:38,160 --> 00:09:41,640 Speaker 1: the most important number, to quote you, in the world. 171 00:09:42,120 --> 00:09:44,640 Speaker 1: A bunch of lowly clerks are running around or or 172 00:09:44,679 --> 00:09:48,040 Speaker 1: sending up their desks in London making calls everywhere. And 173 00:09:48,120 --> 00:09:50,520 Speaker 1: that's how this number gets a sound that well, and 174 00:09:50,640 --> 00:09:53,640 Speaker 1: the joke is that and the reason I wrote a 175 00:09:53,640 --> 00:09:55,520 Speaker 1: book on this, and there's been so much media coverage 176 00:09:55,559 --> 00:09:58,400 Speaker 1: on this is because it was just they were They 177 00:09:58,480 --> 00:09:59,960 Speaker 1: got to the point where they weren't even really make 178 00:10:00,000 --> 00:10:03,600 Speaker 1: and calls. This became a number that was being pulled 179 00:10:03,640 --> 00:10:06,760 Speaker 1: more or less out of thin air by bankers at 180 00:10:06,760 --> 00:10:08,640 Speaker 1: a low level. And why were they pulling it out 181 00:10:08,679 --> 00:10:11,319 Speaker 1: of thin air? They're doing it because their traders asked 182 00:10:11,320 --> 00:10:13,800 Speaker 1: them too. Because the traders had especially by the nine 183 00:10:14,080 --> 00:10:18,360 Speaker 1: nineties and early oughts, had huge amounts of money that 184 00:10:18,400 --> 00:10:21,640 Speaker 1: they were wagering on whether lib or was going to 185 00:10:21,679 --> 00:10:24,760 Speaker 1: go up or down by very tiny increment. And we're 186 00:10:24,800 --> 00:10:30,760 Speaker 1: talking about positions that are trillions of notational value, trillions, 187 00:10:31,120 --> 00:10:34,000 Speaker 1: hundreds of trillions, of hundreds of these. This is kind 188 00:10:34,040 --> 00:10:36,680 Speaker 1: of like asking how hot is the sun? Right the 189 00:10:36,679 --> 00:10:40,360 Speaker 1: the actual temperature degrees fahrenheit or celsius doesn't make any differences. 190 00:10:40,640 --> 00:10:45,400 Speaker 1: The numbers so astronomically largely it literally so, So all 191 00:10:45,440 --> 00:10:48,320 Speaker 1: of this raises the obvious question. On the one hand, 192 00:10:48,440 --> 00:10:52,760 Speaker 1: the banks are collectively setting the number. On the other hands, 193 00:10:53,160 --> 00:10:59,440 Speaker 1: they're totally interested parties who have enormous amounts of capital 194 00:10:59,520 --> 00:11:03,400 Speaker 1: running on the outcome of those numbers. How could that 195 00:11:03,480 --> 00:11:06,600 Speaker 1: ever possibly go wrong? How could there be a conflict 196 00:11:06,600 --> 00:11:09,800 Speaker 1: of interest in the banking industry. Yeah, I mean, it's 197 00:11:09,800 --> 00:11:11,600 Speaker 1: it's funny because I've been covering this at this point 198 00:11:11,600 --> 00:11:14,920 Speaker 1: for eight years, I would say, and it's that is 199 00:11:14,960 --> 00:11:17,400 Speaker 1: such a fundamental question, And it's true, it's such a 200 00:11:17,480 --> 00:11:22,480 Speaker 1: deeply embedded conflict of interest, that is, it's just completely inappropriate. 201 00:11:22,640 --> 00:11:25,800 Speaker 1: So so who who is to blame for that conflict? 202 00:11:26,200 --> 00:11:29,319 Speaker 1: Was it just happenstance the way it developed and where 203 00:11:29,320 --> 00:11:33,000 Speaker 1: were the regulators when yeah, you guys deal with hundreds 204 00:11:33,000 --> 00:11:36,080 Speaker 1: of trillions of dollars bet on the direction of libor 205 00:11:36,440 --> 00:11:39,679 Speaker 1: set yourselves, that's fine with us. Yeah, And this is 206 00:11:39,800 --> 00:11:42,880 Speaker 1: like so many other problems in the financial arena, this 207 00:11:42,960 --> 00:11:46,760 Speaker 1: is something that had fairly benign origin. And this is 208 00:11:46,800 --> 00:11:49,280 Speaker 1: something that was it really was meant to be to 209 00:11:49,400 --> 00:11:53,920 Speaker 1: simplify and increase the efficiency of very complicated and cumbersome 210 00:11:54,000 --> 00:11:57,960 Speaker 1: lending process. And gradually, over a period of a decade 211 00:11:58,040 --> 00:12:00,720 Speaker 1: or two, this rate, first of all, be came embedded 212 00:12:00,920 --> 00:12:04,280 Speaker 1: in hundreds of billions of dollars worth of American mortgages. 213 00:12:04,480 --> 00:12:06,760 Speaker 1: And it didn't start out the hundreds of billions. Yeah, 214 00:12:06,960 --> 00:12:09,360 Speaker 1: they's because way back in the day it was either 215 00:12:09,480 --> 00:12:13,400 Speaker 1: fed funds rate or some other US based number. When 216 00:12:13,440 --> 00:12:17,840 Speaker 1: did libor infiltrate there mortgages in the early nineties, and 217 00:12:17,840 --> 00:12:21,120 Speaker 1: that was partly a product of library at the time 218 00:12:21,160 --> 00:12:23,440 Speaker 1: was viewed as a very reliable way for banks to 219 00:12:23,600 --> 00:12:27,120 Speaker 1: estimate their funding costs. And it was. And and again 220 00:12:27,160 --> 00:12:29,600 Speaker 1: that's something that in theory, if it works properly, is 221 00:12:29,679 --> 00:12:31,559 Speaker 1: very good for everyone. It's good for the banks. It's 222 00:12:31,559 --> 00:12:33,839 Speaker 1: also good for the consumers because it's an efficient way. 223 00:12:34,160 --> 00:12:37,160 Speaker 1: It relieves the banks of any anxiety they might have 224 00:12:37,480 --> 00:12:40,520 Speaker 1: that if they price alone at a low interest rate, 225 00:12:40,559 --> 00:12:42,920 Speaker 1: that they're going to get burned a year or five 226 00:12:43,000 --> 00:12:45,200 Speaker 1: years later. This allows them to relieves them of all 227 00:12:45,280 --> 00:12:48,680 Speaker 1: that anxiety. And that's that allows them theoretically to loan 228 00:12:48,760 --> 00:12:50,800 Speaker 1: money at a lower interest rate. And and those loans 229 00:12:50,840 --> 00:12:54,440 Speaker 1: typically look like libor plus two percent libor plus three, 230 00:12:55,080 --> 00:12:58,720 Speaker 1: so that's their markup, that's the cost of the loan 231 00:12:59,200 --> 00:13:02,400 Speaker 1: to the borrow or it's the profit theoretically to the bank. 232 00:13:03,360 --> 00:13:05,880 Speaker 1: But it seems kind of funny that they get to 233 00:13:05,920 --> 00:13:08,200 Speaker 1: set what. Yeah, it does seem kind of funny. Did 234 00:13:08,200 --> 00:13:11,760 Speaker 1: anybody question that arrangement? Originally? Not really, And originally this 235 00:13:11,840 --> 00:13:14,559 Speaker 1: was seen as and keep in mind that the alternative 236 00:13:14,600 --> 00:13:16,920 Speaker 1: to this is that just banks are arbitrarily setting loans. 237 00:13:16,920 --> 00:13:19,800 Speaker 1: It's not something that is it's not like this is 238 00:13:19,840 --> 00:13:24,160 Speaker 1: replacing a heavily regulated kind of government imposed rates. Previously, 239 00:13:24,160 --> 00:13:26,400 Speaker 1: it was just market forces. You negotiate the best you 240 00:13:26,440 --> 00:13:28,679 Speaker 1: can for the loan, and that's it. As opposed to 241 00:13:29,320 --> 00:13:31,600 Speaker 1: libord plus or maybe it was the Fed funds rate 242 00:13:31,679 --> 00:13:34,720 Speaker 1: or something like that that was. But then again, since 243 00:13:34,800 --> 00:13:37,520 Speaker 1: that is going to change less frequently than libra wood you, 244 00:13:37,640 --> 00:13:40,800 Speaker 1: then the banks were then adding an additional buffer. So 245 00:13:40,920 --> 00:13:43,079 Speaker 1: instead of maybe libor plus two per point would be 246 00:13:43,160 --> 00:13:47,640 Speaker 1: fed funds plus three points, so the loans more expensive. Yeah, exactly, 247 00:13:47,679 --> 00:13:51,000 Speaker 1: And so this is something the big problem that wasn't 248 00:13:51,080 --> 00:13:53,240 Speaker 1: the introduction of liborar into the mortgage market. It was 249 00:13:53,280 --> 00:13:56,320 Speaker 1: the introduction of library into the derivatives market, and that 250 00:13:56,400 --> 00:13:59,720 Speaker 1: happened in the mid nineties, and that was something that 251 00:13:59,760 --> 00:14:02,920 Speaker 1: at the time the Commodity Futures Trading Commission had to 252 00:14:02,920 --> 00:14:05,600 Speaker 1: approve this because it was the Chicago Mercantile Exchange that 253 00:14:05,760 --> 00:14:09,560 Speaker 1: was looking to kind of have lib welar embedded as 254 00:14:09,559 --> 00:14:12,920 Speaker 1: a mechanism and interest rate swaps, and that was it 255 00:14:13,000 --> 00:14:15,319 Speaker 1: was seen as a way to make swap the swaps 256 00:14:15,360 --> 00:14:18,400 Speaker 1: market much more accessible and much more efficient and much 257 00:14:18,440 --> 00:14:21,040 Speaker 1: more liquid. But at the time a number of traders 258 00:14:21,040 --> 00:14:24,040 Speaker 1: warned the CFTC that if you do this, you are 259 00:14:24,080 --> 00:14:27,680 Speaker 1: inviting disaster because traders at the big banks know how 260 00:14:27,760 --> 00:14:32,880 Speaker 1: library works. There's completely unregulated by central banks or by 261 00:14:32,920 --> 00:14:36,080 Speaker 1: financial regulators, and they it's very easy if you give 262 00:14:36,080 --> 00:14:39,680 Speaker 1: banks a huge profit incentive to manipulate something. Guess what 263 00:14:39,800 --> 00:14:41,800 Speaker 1: they're going to manipulate it. So, so let's stay on 264 00:14:41,840 --> 00:14:44,600 Speaker 1: that point in the book you discussed Gary Gainsler. You 265 00:14:44,680 --> 00:14:48,920 Speaker 1: just mentioned the Commodity Futures Training Commission. Gainsler is the 266 00:14:48,960 --> 00:14:55,680 Speaker 1: person who pretty much defang the the CFTC and then 267 00:14:56,160 --> 00:14:59,920 Speaker 1: he ends up running it as the library scandal is unfolding, 268 00:15:00,400 --> 00:15:05,200 Speaker 1: and for reasons I still don't understand, falsely takes claim 269 00:15:05,360 --> 00:15:09,880 Speaker 1: for initiating an investigation into Libar. It actually predated his 270 00:15:09,960 --> 00:15:14,600 Speaker 1: tenure by year. Explain this mania because this is crazy. Also, well, 271 00:15:14,640 --> 00:15:18,200 Speaker 1: this is the regulatory pendulum has swung so wildly, and 272 00:15:18,200 --> 00:15:21,960 Speaker 1: I think it's a common misconception right now in to 273 00:15:22,040 --> 00:15:25,240 Speaker 1: look at this as a product of Democrats versus Republicans 274 00:15:25,280 --> 00:15:28,200 Speaker 1: and Democrats or Barack Obama versus Donald Trump, and that's 275 00:15:28,200 --> 00:15:30,920 Speaker 1: just not what it is. And well, and this started 276 00:15:30,920 --> 00:15:35,400 Speaker 1: in the Clinton administration. The Clinton administration oversaw one of 277 00:15:35,440 --> 00:15:39,000 Speaker 1: the great regulatory rollbacks in the of the twentieth century, 278 00:15:39,160 --> 00:15:42,160 Speaker 1: and it was Bob Reubin and Gary Gensler who are 279 00:15:42,200 --> 00:15:45,240 Speaker 1: leading that charge. Well, let me let me push back 280 00:15:45,240 --> 00:15:49,840 Speaker 1: a little bit. So so you have Um, a number 281 00:15:49,960 --> 00:15:56,200 Speaker 1: of significant Republicans in the Senate pushing pushing for this. Um, 282 00:15:56,240 --> 00:15:58,360 Speaker 1: I'm drown a blank on somebody's name. I mean Phil 283 00:15:58,400 --> 00:16:02,080 Speaker 1: Graham is so Phil Graham is really the ring leader 284 00:16:02,120 --> 00:16:07,000 Speaker 1: of all this. Uh. Reuben so so behind Graham, we 285 00:16:07,120 --> 00:16:12,280 Speaker 1: basically overturned under Clinton and Robert Reuben and Larry Summers. 286 00:16:12,280 --> 00:16:15,640 Speaker 1: I'm not gonna disagree with you. They kind of went along, 287 00:16:15,760 --> 00:16:19,240 Speaker 1: get went along to get along. We we overturned Glass Stiegel. 288 00:16:19,720 --> 00:16:23,600 Speaker 1: We passed the Commodity Futures Modernization Act, which basically said, yeah, 289 00:16:23,680 --> 00:16:27,760 Speaker 1: derivatives free for all. And we basically took the Commodity 290 00:16:27,760 --> 00:16:30,960 Speaker 1: Futures Trading Commission and turned it into a toothless tiger. 291 00:16:31,760 --> 00:16:35,160 Speaker 1: Clinton signed all these things. Some of these passed uh 292 00:16:35,280 --> 00:16:38,040 Speaker 1: the House like three to one. Right now, that s 293 00:16:39,080 --> 00:16:41,400 Speaker 1: there was a consensus in both parties at the time 294 00:16:41,880 --> 00:16:46,080 Speaker 1: that the key or one of the keys to economic 295 00:16:46,120 --> 00:16:50,800 Speaker 1: growth and too uh kind of economic growth spreading globally 296 00:16:50,840 --> 00:16:53,120 Speaker 1: in the US maintaining its competitive advantage when came to 297 00:16:53,120 --> 00:16:57,800 Speaker 1: financial services was to embrace a really aggressive leisay fair 298 00:16:58,160 --> 00:17:02,200 Speaker 1: attitude towards all walks of financial life. And look, it's 299 00:17:02,240 --> 00:17:05,040 Speaker 1: clearly not only the Clinton administration. They but you know, 300 00:17:05,119 --> 00:17:08,600 Speaker 1: the the administration and power in any given year wields 301 00:17:08,640 --> 00:17:10,720 Speaker 1: a tremendous amount of clout on these things. And if 302 00:17:10,920 --> 00:17:14,000 Speaker 1: if Bob Reuben, a guy who is coming from the 303 00:17:14,040 --> 00:17:18,159 Speaker 1: upper echelons of Goldman Sax, wasn't uh cheerleader of this, 304 00:17:18,240 --> 00:17:21,560 Speaker 1: it wouldn't have happened. And the and Gary Gensler as well, 305 00:17:21,600 --> 00:17:25,639 Speaker 1: another Goldwen Sax guy. So there ends up the city. 306 00:17:25,920 --> 00:17:31,159 Speaker 1: So he he oversaw the repeal of um Glass Steagle, 307 00:17:31,320 --> 00:17:33,320 Speaker 1: which paved the way for the creation of the modern 308 00:17:33,320 --> 00:17:36,440 Speaker 1: city Group, which was travelers and travelers and city corps. 309 00:17:36,520 --> 00:17:39,840 Speaker 1: And it then lo and behold. After leaving immediately gets 310 00:17:39,880 --> 00:17:42,399 Speaker 1: hired in a very lucrative contract to do not a 311 00:17:42,400 --> 00:17:47,040 Speaker 1: whole lot at city Group. So in any case, the 312 00:17:47,119 --> 00:17:49,440 Speaker 1: Gensler at the Gensler in the Treasure Derment in the 313 00:17:49,440 --> 00:17:53,040 Speaker 1: Clinton administration was one of the proponents of essentially neutering 314 00:17:53,080 --> 00:17:56,960 Speaker 1: the CFDC, not having it the powerful force for the 315 00:17:56,960 --> 00:18:01,600 Speaker 1: regulation of derivatives. He then in the Obama era, is 316 00:18:01,720 --> 00:18:06,239 Speaker 1: eager too. He sees the winds shifting, We've just had 317 00:18:06,240 --> 00:18:09,680 Speaker 1: the financial crisis. He's eager for a senior administration position 318 00:18:10,119 --> 00:18:13,320 Speaker 1: and the opposition to him on Capitol Hill was intense 319 00:18:13,359 --> 00:18:16,800 Speaker 1: because he was so deeply embedded with the Rubin wing 320 00:18:16,800 --> 00:18:21,240 Speaker 1: of the Democratic Party. And he underwent a remarkable makeover. 321 00:18:21,320 --> 00:18:23,240 Speaker 1: And Bernie Sanders was one guy on the on the 322 00:18:23,280 --> 00:18:26,160 Speaker 1: Hill who had been a vigorous opponent of Gensler getting 323 00:18:26,160 --> 00:18:30,560 Speaker 1: any powerful position, and Gensler just pulled this remarkable about face, 324 00:18:30,600 --> 00:18:34,000 Speaker 1: and to his credit, unlike most politicians, he admitted that 325 00:18:34,040 --> 00:18:37,520 Speaker 1: he had been catastrophically wrong in the Clinton administration, in 326 00:18:37,560 --> 00:18:39,680 Speaker 1: the Clinton era, and he had just gotten it wrong. 327 00:18:39,720 --> 00:18:41,600 Speaker 1: He and he said he had learned a lesson and 328 00:18:41,720 --> 00:18:47,200 Speaker 1: was embracing very enthusiastically this pro regulation, pro government view 329 00:18:47,280 --> 00:18:50,040 Speaker 1: of the financial world. And so he came into the CFDC, 330 00:18:50,200 --> 00:18:54,119 Speaker 1: which at the time was this kind of scrappy, underfunded 331 00:18:54,640 --> 00:18:58,280 Speaker 1: backwater of an agency in Washington, and did everything he 332 00:18:58,320 --> 00:19:02,119 Speaker 1: could to he he wants scalps. He wanted to he 333 00:19:02,160 --> 00:19:06,280 Speaker 1: wanted to see the CFDC developing a reputation for being 334 00:19:06,400 --> 00:19:10,359 Speaker 1: one of the uh toughest, scariest gun slingers on Wall Street. 335 00:19:10,480 --> 00:19:13,879 Speaker 1: And what became this investigation into Library that became the 336 00:19:13,880 --> 00:19:17,000 Speaker 1: perfect vehicle for him. What what's so astonishing is a 337 00:19:17,080 --> 00:19:21,199 Speaker 1: lot of the people who set up the financial crisis, 338 00:19:22,040 --> 00:19:26,720 Speaker 1: uh during the Clinton administration. And let's hold the Republicans aside, 339 00:19:26,840 --> 00:19:29,760 Speaker 1: guys like Phil Graham. But when you look at the Democrats, 340 00:19:30,280 --> 00:19:34,159 Speaker 1: you have you have Laurence Somers eventually goes on to 341 00:19:34,200 --> 00:19:36,959 Speaker 1: get a Chairman of the c e A for Obama. 342 00:19:37,320 --> 00:19:40,879 Speaker 1: Tim Geithner, who was New York Fed Chief, eventually becomes 343 00:19:40,920 --> 00:19:45,800 Speaker 1: Treasury Secretary. Gensler gets appointed to the agency that he 344 00:19:45,800 --> 00:19:50,120 Speaker 1: helped to dismantle. It's really pretty astonishing if you look 345 00:19:50,160 --> 00:19:53,560 Speaker 1: at the fields of of aviation or medicine. When a 346 00:19:53,600 --> 00:19:56,760 Speaker 1: plane crashes or there's a surgical problem, you don't send 347 00:19:56,840 --> 00:19:58,840 Speaker 1: the same pilot back to tell you what went wrong. 348 00:19:58,840 --> 00:20:01,280 Speaker 1: You don't send the same s rgin to do a 349 00:20:01,320 --> 00:20:04,760 Speaker 1: post mortem. Someone else with fresh eyes comes in. That 350 00:20:04,880 --> 00:20:09,320 Speaker 1: is not what we saw take place during the financial crisis. No, 351 00:20:09,440 --> 00:20:11,120 Speaker 1: it's totally true. You had a lot of the same 352 00:20:11,119 --> 00:20:13,520 Speaker 1: old characters coming in, and a lot of them Geitner 353 00:20:13,560 --> 00:20:15,280 Speaker 1: is an exception to this, I think, but a lot 354 00:20:15,320 --> 00:20:17,200 Speaker 1: of them hailed from All Street and those are these 355 00:20:17,200 --> 00:20:19,800 Speaker 1: are the same guys who had not only not stocked 356 00:20:19,800 --> 00:20:22,000 Speaker 1: the financial crisis, but in a number of cases either 357 00:20:22,119 --> 00:20:24,680 Speaker 1: worsened it or profited from it, and take your pick. 358 00:20:24,720 --> 00:20:28,560 Speaker 1: I don't know which of those is worse. And uh, Again, 359 00:20:29,160 --> 00:20:32,600 Speaker 1: in fairness to people like Summers and Getzler, I think 360 00:20:32,680 --> 00:20:35,680 Speaker 1: there is a human capacity to learn from one's mistakes. 361 00:20:35,920 --> 00:20:41,240 Speaker 1: And arguably the experience of having screwed up royally and 362 00:20:41,800 --> 00:20:44,560 Speaker 1: watching the financial world burn as a result in part 363 00:20:44,680 --> 00:20:48,240 Speaker 1: of youuter mistakes is probably a pretty sobering educational moment. 364 00:20:49,160 --> 00:20:51,119 Speaker 1: And look that everyone got it wrong. It's not just 365 00:20:51,200 --> 00:20:53,840 Speaker 1: these guys, right, the media got it wrong. Everybody got 366 00:20:53,840 --> 00:20:55,399 Speaker 1: it wrong. Lots of people, a lot of people got 367 00:20:55,440 --> 00:20:57,639 Speaker 1: it wrong. You know, there were plenty of people who 368 00:20:57,720 --> 00:21:01,760 Speaker 1: were complaining about it and warning about it. I just 369 00:21:02,040 --> 00:21:05,800 Speaker 1: I've always found it fascinating that, wait, there aren't people 370 00:21:05,880 --> 00:21:09,600 Speaker 1: who weren't major contributors to the crisis to take the 371 00:21:09,720 --> 00:21:13,400 Speaker 1: role of C. E. H A or Treasury secretary. I've 372 00:21:13,440 --> 00:21:16,480 Speaker 1: always learned when you really screw up, hey, you know 373 00:21:16,600 --> 00:21:20,080 Speaker 1: you're not going to get that promotion. Apparently DC in 374 00:21:20,080 --> 00:21:22,840 Speaker 1: Wall Street that that doesn't seem to Yeah. I mean, 375 00:21:22,960 --> 00:21:25,080 Speaker 1: one of the revelations to me in writing this book 376 00:21:25,160 --> 00:21:28,399 Speaker 1: is that most of the things on Wall Street and 377 00:21:28,440 --> 00:21:30,400 Speaker 1: in the financial world, and I think in politics too, 378 00:21:30,920 --> 00:21:33,879 Speaker 1: it boils down to incentives. And of course people's people 379 00:21:33,920 --> 00:21:37,280 Speaker 1: are actually pretty rational actors if you can figure out 380 00:21:37,320 --> 00:21:40,440 Speaker 1: what's motivating them to do what they're doing. And so 381 00:21:41,000 --> 00:21:43,120 Speaker 1: you see this any awhere, from kind of a low 382 00:21:43,200 --> 00:21:46,320 Speaker 1: level trader starting out in Wall Street to someone at 383 00:21:46,320 --> 00:21:49,480 Speaker 1: the upper echelons of a bank like Gary Ginsler, Bob Rubin, 384 00:21:49,600 --> 00:21:51,359 Speaker 1: or or if you put them in government service, the 385 00:21:51,400 --> 00:21:54,280 Speaker 1: same thing. So if they they're responding to the incentives, 386 00:21:54,280 --> 00:22:00,120 Speaker 1: whether it's compensation incentives or feedback or just approval ratings 387 00:22:00,240 --> 00:22:04,480 Speaker 1: or things like that, and they they have everyone incentives matter, 388 00:22:04,720 --> 00:22:06,560 Speaker 1: and they explained that we see and I think that's 389 00:22:06,560 --> 00:22:10,280 Speaker 1: why to me, when the next crisis inevitably happens in 390 00:22:10,320 --> 00:22:13,000 Speaker 1: the next scandal inevitably and will it will. It's a 391 00:22:13,080 --> 00:22:15,399 Speaker 1: question of when and where. But when it does, I 392 00:22:15,400 --> 00:22:17,359 Speaker 1: think we're going to look back and see that a 393 00:22:17,400 --> 00:22:19,159 Speaker 1: lot of the lessons we should have learned from the 394 00:22:19,160 --> 00:22:22,000 Speaker 1: financial crisis in terms of shaping incentives in a way 395 00:22:22,000 --> 00:22:28,080 Speaker 1: to encourage sober, careful, prudent behavior, we're not really heated. 396 00:22:28,119 --> 00:22:31,800 Speaker 1: We instead just imposed erected all these new regulations that 397 00:22:31,880 --> 00:22:34,399 Speaker 1: are just designed for the sake of regulations, they're not 398 00:22:34,440 --> 00:22:37,119 Speaker 1: actually looking very closely at what motivates people to behave 399 00:22:37,160 --> 00:22:39,600 Speaker 1: the way that they do. So let's talk a little 400 00:22:39,600 --> 00:22:42,919 Speaker 1: bit about Tom Hayes, the man in the middle of this. Uh, 401 00:22:43,040 --> 00:22:45,879 Speaker 1: you actually won a Globe Award for your coverage of 402 00:22:46,480 --> 00:22:50,960 Speaker 1: the unraveling of Tom Hayes. Who was Tom Hayes And 403 00:22:51,040 --> 00:22:53,600 Speaker 1: how did he find himself in the middle of the 404 00:22:53,640 --> 00:22:59,080 Speaker 1: library scandal? So? Tom Hayes is mildly autistic mathematician. He 405 00:23:00,200 --> 00:23:02,320 Speaker 1: was a trader at some of the world's biggest banks. 406 00:23:02,320 --> 00:23:05,639 Speaker 1: He was a guy who, like most mathematicians who are 407 00:23:05,680 --> 00:23:08,080 Speaker 1: mildly autistic and gett into banking, was very good at 408 00:23:08,119 --> 00:23:12,159 Speaker 1: creating models, detecting patterns, things like that. Not very not 409 00:23:12,240 --> 00:23:15,160 Speaker 1: just very good at detecting patterns. People described him as 410 00:23:15,280 --> 00:23:17,639 Speaker 1: just he was a genius, all right, just brilliant at this. 411 00:23:17,680 --> 00:23:19,720 Speaker 1: He was a genius, and he was one of the 412 00:23:19,720 --> 00:23:23,480 Speaker 1: best traders that a lot of his colleagues had ever seen. 413 00:23:23,560 --> 00:23:28,840 Speaker 1: He also was someone who was very well trained to 414 00:23:29,200 --> 00:23:32,440 Speaker 1: do what traders do best, especially in a decade ago, 415 00:23:32,520 --> 00:23:36,359 Speaker 1: which was to look for tiny, little inefficiencies and find 416 00:23:36,400 --> 00:23:39,399 Speaker 1: ways to exploit them. And that could mean having a 417 00:23:39,440 --> 00:23:43,199 Speaker 1: faster trading system, it could mean having better intelligence, It 418 00:23:43,200 --> 00:23:47,800 Speaker 1: could mean having stupider clients. It could mean finding ways 419 00:23:47,880 --> 00:23:52,679 Speaker 1: to manipulate something that you are betting on the outcome of. 420 00:23:52,880 --> 00:23:55,800 Speaker 1: And so so let's talk about stupider clients for a second, 421 00:23:55,840 --> 00:23:59,800 Speaker 1: because this comes up in the book with there's a 422 00:23:59,800 --> 00:24:02,600 Speaker 1: whole list of characters, and there are really some very 423 00:24:02,280 --> 00:24:07,360 Speaker 1: colorful characters. What is the relationship of the brokers who 424 00:24:07,359 --> 00:24:11,200 Speaker 1: are working with the traders and how do people identify 425 00:24:11,560 --> 00:24:15,239 Speaker 1: smarter and dumber clients. Yeah, so the brokers serve this 426 00:24:15,400 --> 00:24:19,160 Speaker 1: role as the great middleman in the banking industry. And 427 00:24:19,560 --> 00:24:22,520 Speaker 1: when two traders, when bank a trader bank A and 428 00:24:22,520 --> 00:24:24,719 Speaker 1: a trader bank B both want to do a transaction, 429 00:24:25,080 --> 00:24:27,280 Speaker 1: they're often not talking to each other. They're talking to 430 00:24:27,320 --> 00:24:30,640 Speaker 1: a broker who's in the middle and realizes that trader 431 00:24:30,640 --> 00:24:33,040 Speaker 1: bank A wants to buy something and trader bank B 432 00:24:33,240 --> 00:24:34,800 Speaker 1: is looking to sell the same thing, and so they'll 433 00:24:34,800 --> 00:24:37,560 Speaker 1: serve as the middleman for that service. They take a 434 00:24:37,720 --> 00:24:41,119 Speaker 1: cut of the the value of the transaction, and that's fine. 435 00:24:41,520 --> 00:24:45,199 Speaker 1: The broker serve another role though, which is uh information 436 00:24:45,240 --> 00:24:50,119 Speaker 1: brokers essentially, and they pedal gossip and they are paid 437 00:24:50,600 --> 00:24:54,000 Speaker 1: in large part to develop relationships with these traders. And 438 00:24:54,119 --> 00:24:56,440 Speaker 1: the way they do that. I love this thing. It's 439 00:24:56,480 --> 00:25:00,320 Speaker 1: that they have. There's a ratio of how or a 440 00:25:00,440 --> 00:25:04,239 Speaker 1: percentage of the revenue that each trader generates you are 441 00:25:04,280 --> 00:25:08,439 Speaker 1: supposed to as a broker recycle that back to the trader. 442 00:25:08,640 --> 00:25:12,360 Speaker 1: Define define recycle in real life? What is entertainment? It's 443 00:25:12,400 --> 00:25:17,600 Speaker 1: called which is just a giant teeny budget ranks, food, 444 00:25:17,960 --> 00:25:21,639 Speaker 1: strip clubs, and and and if you've got some of 445 00:25:21,680 --> 00:25:25,680 Speaker 1: these traders who are generating uh millions and millions of 446 00:25:25,720 --> 00:25:30,919 Speaker 1: dollars a year in brokerage fees, spending ten of that 447 00:25:31,359 --> 00:25:34,280 Speaker 1: on steak dinners and nice drinks is very hard. But 448 00:25:34,359 --> 00:25:37,680 Speaker 1: it's not just steak dinners and nice draders. You tell 449 00:25:37,800 --> 00:25:40,600 Speaker 1: some stories. This is g rated, but you tell some 450 00:25:40,720 --> 00:25:43,479 Speaker 1: stories in the book. These guys are animals. Now they 451 00:25:43,520 --> 00:25:46,200 Speaker 1: get creative, They get very creative about ways to spend 452 00:25:46,280 --> 00:25:49,399 Speaker 1: hundreds of thousands of dollars a year on a particular person. 453 00:25:49,480 --> 00:25:51,879 Speaker 1: And so what does that mean? That means drugs, it 454 00:25:51,880 --> 00:25:55,920 Speaker 1: means women, it means trips to various places, it means 455 00:25:55,960 --> 00:26:00,000 Speaker 1: just all sorts of ludicrous misbehavior. And this is something 456 00:26:00,040 --> 00:26:02,960 Speaker 1: him that again is the book singles out a number 457 00:26:02,960 --> 00:26:05,240 Speaker 1: of individuals for being involved in this, but this is 458 00:26:05,359 --> 00:26:09,639 Speaker 1: widespread industry practice at the time. And Hayes, Tom Hayes 459 00:26:09,720 --> 00:26:11,920 Speaker 1: was not a guy who liked going to strip clubs. 460 00:26:11,920 --> 00:26:13,720 Speaker 1: He was not a big drinker. His idea of a 461 00:26:13,720 --> 00:26:17,040 Speaker 1: fun night out was going to KFC, getting a bucket 462 00:26:17,040 --> 00:26:20,600 Speaker 1: of fried chicken, sitting at home eating it while watching 463 00:26:20,600 --> 00:26:22,840 Speaker 1: Steinfeld reruns. And so this is not a guy who 464 00:26:22,880 --> 00:26:26,080 Speaker 1: you can easily. He's a huge trader, but it was 465 00:26:26,200 --> 00:26:28,159 Speaker 1: very hard, and the brokers were dying to do business 466 00:26:28,200 --> 00:26:29,800 Speaker 1: with him because of the huge volumes he was doing. 467 00:26:30,000 --> 00:26:31,840 Speaker 1: But this is not someone who is very easy to 468 00:26:31,920 --> 00:26:34,400 Speaker 1: spend your ten percent of the commissions on. And so 469 00:26:35,119 --> 00:26:38,159 Speaker 1: the brokers found another way to reward him, which was 470 00:26:38,200 --> 00:26:43,159 Speaker 1: that Tom Hayes was making huge, huge bets on the 471 00:26:43,200 --> 00:26:46,560 Speaker 1: direction of interest rates, which meant that he had a huge, 472 00:26:46,760 --> 00:26:49,879 Speaker 1: huge steak in the direction of library every day. And 473 00:26:49,960 --> 00:26:52,760 Speaker 1: Tom Hayes on a given day would have millions and 474 00:26:52,800 --> 00:26:56,119 Speaker 1: millions of dollars riding on whether libra or went up 475 00:26:56,200 --> 00:26:59,439 Speaker 1: or down by a basis point, which is a one 476 00:27:00,119 --> 00:27:03,199 Speaker 1: percentage point. So a tiny, little move that no one 477 00:27:03,200 --> 00:27:06,199 Speaker 1: would ever notice. Tom Hayes not only would notice, but 478 00:27:06,280 --> 00:27:09,840 Speaker 1: cared deeply about live were moving in these tiny little increments. 479 00:27:10,240 --> 00:27:12,920 Speaker 1: And so that's where the brokers came in For Tom Hayes. 480 00:27:13,080 --> 00:27:16,760 Speaker 1: He realized and the brokers realized that libras set not 481 00:27:17,040 --> 00:27:19,280 Speaker 1: Tom Hayes at this time worked at UBSA. Was not 482 00:27:19,359 --> 00:27:21,280 Speaker 1: set by the market, but it's set by the by 483 00:27:21,280 --> 00:27:23,960 Speaker 1: the Tom Hayes works at one bank. And so Tom Hayes, 484 00:27:24,119 --> 00:27:26,800 Speaker 1: as with standard industry practice at the time, the traders 485 00:27:26,800 --> 00:27:29,440 Speaker 1: who were making wagers based on the direction of interest 486 00:27:29,520 --> 00:27:32,320 Speaker 1: rates would call up the little clerk in the bowels 487 00:27:32,320 --> 00:27:34,959 Speaker 1: of the bank and say, hey, mate, I need libor 488 00:27:35,040 --> 00:27:38,080 Speaker 1: up today. Can you please move UBS submission up by 489 00:27:38,320 --> 00:27:39,800 Speaker 1: as much as you can or move it down by 490 00:27:39,800 --> 00:27:41,320 Speaker 1: as much as you can. Depend it was that. It 491 00:27:41,400 --> 00:27:45,040 Speaker 1: was that, It was that. Yeah, it's very explicit. People 492 00:27:45,040 --> 00:27:47,119 Speaker 1: are very open about it. They were encouraged to do it. 493 00:27:47,359 --> 00:27:49,720 Speaker 1: This was under the under the umbrella at the time 494 00:27:49,760 --> 00:27:53,640 Speaker 1: of banks trying to improve the coordination of different parts 495 00:27:53,640 --> 00:27:56,080 Speaker 1: of the bank working together, all playing in the same direction. 496 00:27:56,160 --> 00:27:59,200 Speaker 1: And what role does the broker's play with these clerks? 497 00:27:59,200 --> 00:28:02,400 Speaker 1: So the broker's the broker's role is that they Tom 498 00:28:02,400 --> 00:28:04,320 Speaker 1: Hayes can tell the guy at UBS his colleague, to 499 00:28:04,359 --> 00:28:06,760 Speaker 1: move lib Rar uper down. What Tom Hayes can't do 500 00:28:06,840 --> 00:28:10,280 Speaker 1: quite as easily is called City Group or JP Morrigan, 501 00:28:10,320 --> 00:28:13,320 Speaker 1: a royal bank of the other ten banks. And because 502 00:28:13,359 --> 00:28:14,840 Speaker 1: he doesn't know these guys and why would they listen 503 00:28:14,880 --> 00:28:16,840 Speaker 1: to him anyway, but he can call in a favorite 504 00:28:16,840 --> 00:28:19,080 Speaker 1: with the brokers. And so that he had brokers at 505 00:28:19,119 --> 00:28:21,560 Speaker 1: eye Cap which is the biggest, and some other firms 506 00:28:21,640 --> 00:28:26,400 Speaker 1: as well, just every single day routinely going out into 507 00:28:26,440 --> 00:28:29,080 Speaker 1: the market and telling all of their context that all 508 00:28:29,119 --> 00:28:32,000 Speaker 1: these other banks move live or upper down. And it 509 00:28:32,080 --> 00:28:35,359 Speaker 1: was basically to benefit Tom Hayes's trading positions and the 510 00:28:35,359 --> 00:28:37,840 Speaker 1: trading positions of Tom Hayes's colleagues. Was this unique to 511 00:28:37,920 --> 00:28:40,920 Speaker 1: Hayes and and Ubs was the standard practice, well, it 512 00:28:40,960 --> 00:28:44,080 Speaker 1: was standard practice to be manipulating lib Or. Hayes was 513 00:28:44,160 --> 00:28:47,240 Speaker 1: a really clever guy and a really relentless guy and 514 00:28:47,280 --> 00:28:49,640 Speaker 1: took this to a new level. So the introduction of 515 00:28:49,680 --> 00:28:53,680 Speaker 1: the brokers was something that Hayes. Hayes pioneered and that 516 00:28:53,800 --> 00:28:55,560 Speaker 1: was really his innovation. That was the way that he 517 00:28:55,720 --> 00:28:58,760 Speaker 1: got an edge and Everyone always talked about getting an 518 00:28:58,840 --> 00:29:01,600 Speaker 1: edge on the trading floor, and heyesn't found one. You 519 00:29:01,640 --> 00:29:05,239 Speaker 1: were in London in the mid two thousand's. How did 520 00:29:05,240 --> 00:29:07,560 Speaker 1: you find your way to London? How how does a 521 00:29:07,600 --> 00:29:10,400 Speaker 1: Wall Street General reporter based in New York ends up 522 00:29:10,400 --> 00:29:12,880 Speaker 1: in London. It was actually the late two thousands and 523 00:29:12,880 --> 00:29:16,440 Speaker 1: the financial crisis here in the US had ended. Banks 524 00:29:16,440 --> 00:29:19,320 Speaker 1: are getting back to normal more or less boring stuff, 525 00:29:19,360 --> 00:29:22,480 Speaker 1: but a financial crisis was just dawning in Europe. I 526 00:29:22,520 --> 00:29:25,520 Speaker 1: had never lived overseas and was eager for an adventure, 527 00:29:25,800 --> 00:29:28,680 Speaker 1: and London seemed like an adventure. So so in late 528 00:29:28,720 --> 00:29:31,280 Speaker 1: twenties at this point, it's a decade ago. I think 529 00:29:31,320 --> 00:29:34,840 Speaker 1: it was early early thirties. So now you're in London 530 00:29:34,920 --> 00:29:37,680 Speaker 1: for a couple of years. You're covering finance, You're covering 531 00:29:37,720 --> 00:29:40,440 Speaker 1: the banks. The middle of the night, you get a 532 00:29:40,520 --> 00:29:44,240 Speaker 1: text from a phone that you don't recognize. The number 533 00:29:44,280 --> 00:29:48,040 Speaker 1: of comes in tell us about that. So I was covering. 534 00:29:48,560 --> 00:29:50,240 Speaker 1: I had been covering the library or what it was 535 00:29:50,280 --> 00:29:53,080 Speaker 1: now known as the Library scandal. And government had investigated 536 00:29:53,800 --> 00:29:57,200 Speaker 1: all these banks and in a couple of cases, including 537 00:29:57,240 --> 00:30:00,240 Speaker 1: with UBS, which was Tom Hayes's former employer had reached 538 00:30:00,240 --> 00:30:02,840 Speaker 1: these huge settlements where the banks had to pay hundreds 539 00:30:02,840 --> 00:30:04,960 Speaker 1: of millions, if not billions of dollars and penalties and 540 00:30:05,040 --> 00:30:07,120 Speaker 1: admitted that they had been part of this global scheme 541 00:30:07,360 --> 00:30:10,800 Speaker 1: to manipulate interest. How many banks wrote? How much money? 542 00:30:10,840 --> 00:30:13,600 Speaker 1: And well, ultimately it was more than a dozen banks 543 00:30:13,760 --> 00:30:16,640 Speaker 1: and probably five or six or seven or eight or 544 00:30:16,720 --> 00:30:19,320 Speaker 1: nine or ten billion dollars in penalties, A lot huge, 545 00:30:19,640 --> 00:30:25,400 Speaker 1: widespread is this? This is in at the very end 546 00:30:25,440 --> 00:30:30,160 Speaker 1: of For the first time, a guy was actually a guy, 547 00:30:30,200 --> 00:30:33,160 Speaker 1: an individual, a person was held accountable for this, and 548 00:30:33,160 --> 00:30:35,400 Speaker 1: that guy was Tom Hayes. He was arrested in the 549 00:30:35,480 --> 00:30:38,160 Speaker 1: UK and he was criminally charged here in the un 550 00:30:38,840 --> 00:30:41,280 Speaker 1: Remember he was the first person to be charged. And 551 00:30:42,080 --> 00:30:45,320 Speaker 1: my boss at the time, a guy named Bruce or 552 00:30:45,360 --> 00:30:46,880 Speaker 1: While who was a great editor at the Wall Street 553 00:30:46,920 --> 00:30:50,280 Speaker 1: Journal UH wanted me to write a profile Tom Hayes. 554 00:30:50,360 --> 00:30:53,080 Speaker 1: And of course that seemed like a thankless task. Hayes 555 00:30:53,120 --> 00:30:55,360 Speaker 1: had been you know, he'd been criminally charged. This guy's 556 00:30:55,400 --> 00:30:58,600 Speaker 1: not going to talk. And so after much toing and frowing, 557 00:30:58,680 --> 00:31:02,560 Speaker 1: I agreed to do this and found a woman who 558 00:31:03,040 --> 00:31:05,640 Speaker 1: was his former business school classmate and got her to 559 00:31:05,680 --> 00:31:08,400 Speaker 1: talk to me, and it started painting this picture. Nothing 560 00:31:08,440 --> 00:31:10,600 Speaker 1: was known about Tom Hayes at this point he other 561 00:31:10,640 --> 00:31:13,320 Speaker 1: than that he was a very successful trader who had 562 00:31:13,320 --> 00:31:19,360 Speaker 1: said some really stupid, uh seemingly damning stuff in againstant messages. 563 00:31:19,560 --> 00:31:22,760 Speaker 1: And this woman, though, painted a much more interesting, nuanced 564 00:31:22,800 --> 00:31:25,000 Speaker 1: picture of Tom as someone who was mildly autistic. He 565 00:31:25,080 --> 00:31:27,280 Speaker 1: was a nerd. He was just doing what everyone else 566 00:31:27,320 --> 00:31:30,560 Speaker 1: was doing, it seemed like uh. And I convinced her 567 00:31:30,560 --> 00:31:33,000 Speaker 1: to pass on my phone number to Tom Hayes and 568 00:31:33,080 --> 00:31:35,080 Speaker 1: she said, of course, there's no way he's gonna call you. 569 00:31:35,160 --> 00:31:37,440 Speaker 1: There's his lawyers won't let him, blah blah blah. And 570 00:31:37,480 --> 00:31:39,960 Speaker 1: I was sitting at home that night on the sofa 571 00:31:40,000 --> 00:31:42,800 Speaker 1: watching TV with my wife and I got a text 572 00:31:42,800 --> 00:31:45,240 Speaker 1: message from an unknown number and it said this goes 573 00:31:45,360 --> 00:31:48,240 Speaker 1: much much higher than me. Not even the Justice Department 574 00:31:48,240 --> 00:31:50,240 Speaker 1: knows the full story. And it was Tom Hayes, and 575 00:31:50,320 --> 00:31:53,040 Speaker 1: I could not believe it. He agreed then to meet 576 00:31:53,040 --> 00:31:56,360 Speaker 1: me the next day. Uh. He said, I'll meebe if 577 00:31:56,360 --> 00:31:57,640 Speaker 1: I can trust you, And I said, of course you 578 00:31:57,680 --> 00:32:00,800 Speaker 1: can trust me. I'm a journalist and it and he 579 00:32:01,120 --> 00:32:04,160 Speaker 1: told me he'd be standing in Victoria station, which is 580 00:32:04,160 --> 00:32:06,720 Speaker 1: a big busy train station in London outside the Burger 581 00:32:06,800 --> 00:32:08,880 Speaker 1: King were in a brown leather jacket, and of course 582 00:32:08,880 --> 00:32:10,280 Speaker 1: no one who knows what this guy looks like at 583 00:32:10,280 --> 00:32:14,280 Speaker 1: this point, and I, as you can imagine, was pretty 584 00:32:14,320 --> 00:32:18,560 Speaker 1: excited about that. I kind of pictured myself as Bob Woodward. 585 00:32:20,400 --> 00:32:22,720 Speaker 1: And unfortunately he canceled the next morning because his wife 586 00:32:22,720 --> 00:32:24,800 Speaker 1: had found his phone and realized he was off to 587 00:32:24,800 --> 00:32:27,040 Speaker 1: meet a journalist and his wife is a lawyer, and 588 00:32:27,800 --> 00:32:30,800 Speaker 1: uh decided that was not a wise thing to do. 589 00:32:31,080 --> 00:32:33,680 Speaker 1: But that was the start of what became a year's 590 00:32:33,720 --> 00:32:36,360 Speaker 1: long relationship I had with Tom Hayes. That and this 591 00:32:36,560 --> 00:32:40,480 Speaker 1: initially started over text messages, but ultimately and I was 592 00:32:40,520 --> 00:32:43,760 Speaker 1: spending what seemed like the majority of my waking hours 593 00:32:43,800 --> 00:32:45,320 Speaker 1: either with him or on the phone with him, and 594 00:32:45,400 --> 00:32:47,640 Speaker 1: eventually his wife as well, and they just let me 595 00:32:47,680 --> 00:32:51,560 Speaker 1: inside their life for uh, pretty substantial period of time 596 00:32:51,560 --> 00:32:56,200 Speaker 1: from early until mid when Tom Hayes eventually went on 597 00:32:56,280 --> 00:32:59,760 Speaker 1: trial for manipulating live board. And so that was the 598 00:32:59,760 --> 00:33:03,280 Speaker 1: bag for this Walser journal series. The unraveling of Tom 599 00:33:03,280 --> 00:33:06,080 Speaker 1: Hayes is that I watched this guy who had become 600 00:33:06,200 --> 00:33:10,080 Speaker 1: kind of this unlikely public face of financial crime. Uh 601 00:33:10,120 --> 00:33:13,760 Speaker 1: and I watched him his life disintegrate. It was fascinating 602 00:33:13,800 --> 00:33:17,640 Speaker 1: and kind of upsetting. So Hayes eventually loses the case, 603 00:33:17,680 --> 00:33:21,200 Speaker 1: gets what was it, a fourteen year sentence. So there's 604 00:33:21,240 --> 00:33:25,560 Speaker 1: a section in the book it's jaw dropping his former bosses, 605 00:33:25,600 --> 00:33:27,680 Speaker 1: his associates, all the traders he worked with, all the 606 00:33:27,680 --> 00:33:31,240 Speaker 1: brokers he worked with. Nobody else gets into trouble. How 607 00:33:31,320 --> 00:33:33,640 Speaker 1: is that not only do they not get into trouble, 608 00:33:33,880 --> 00:33:36,160 Speaker 1: they're all doing fine, They're all still working in the industry, 609 00:33:36,160 --> 00:33:38,640 Speaker 1: they're all still making millions of dollars. How did this 610 00:33:38,720 --> 00:33:43,040 Speaker 1: one guy become the full guy and everybody else skates 611 00:33:43,080 --> 00:33:46,360 Speaker 1: away scott free? I mean, there are two basic reasons, 612 00:33:46,400 --> 00:33:50,040 Speaker 1: too literal reasons. That one is that Hayes was stupid 613 00:33:50,160 --> 00:33:52,280 Speaker 1: and naive, and he did everything in writing. So there's 614 00:33:52,320 --> 00:33:55,920 Speaker 1: this rich trove of documentary evidence that showed Hayes in 615 00:33:56,320 --> 00:33:59,640 Speaker 1: text messages or chat rooms or sometimes unrecorded phone lines. 616 00:34:00,240 --> 00:34:02,040 Speaker 1: Please move lie War up from me. I have a 617 00:34:02,080 --> 00:34:04,360 Speaker 1: lot of money riding over and over and over again, 618 00:34:04,480 --> 00:34:08,799 Speaker 1: thousands of times. Well, and the second reason is that 619 00:34:08,920 --> 00:34:13,000 Speaker 1: prosecutors and regulators are a little bit lazy. They wanted 620 00:34:13,160 --> 00:34:16,080 Speaker 1: to nail some people, but you know, they don't really 621 00:34:16,120 --> 00:34:17,719 Speaker 1: want to take risks. They want to go after the 622 00:34:17,760 --> 00:34:20,000 Speaker 1: sure thing, and the sure thing in this case was 623 00:34:20,040 --> 00:34:23,000 Speaker 1: Tom Hayes. This isn't, i think, probably an unlosable case 624 00:34:23,080 --> 00:34:26,760 Speaker 1: for them, and they went after him. And what's mystifying 625 00:34:26,800 --> 00:34:28,839 Speaker 1: to me is what happened next, which is that they 626 00:34:28,880 --> 00:34:31,960 Speaker 1: did they criminally charged a small handful of other people 627 00:34:32,000 --> 00:34:35,399 Speaker 1: of his confederates, all of whom got acquitted, but they 628 00:34:35,480 --> 00:34:39,440 Speaker 1: really didn't go after anyone higher us. And you know, 629 00:34:39,560 --> 00:34:42,760 Speaker 1: this is mystifying a little bit frustrating to me because 630 00:34:43,040 --> 00:34:46,480 Speaker 1: there's as much evidence that there's against Tom Hayes, there's 631 00:34:46,520 --> 00:34:49,880 Speaker 1: also a lot of evidence that shows Hayes's bosses and 632 00:34:50,000 --> 00:34:53,359 Speaker 1: his boss's bosses and his boss's boss's bosses not only 633 00:34:53,719 --> 00:34:56,520 Speaker 1: knowing about and condoning what he was doing at the time, 634 00:34:56,560 --> 00:34:59,640 Speaker 1: but in some cases participating alongside him. And were they 635 00:34:59,719 --> 00:35:02,640 Speaker 1: doing it as extensively and as aggressively as Hays and 636 00:35:02,719 --> 00:35:05,919 Speaker 1: as blatantly as He's absolutely not, but these are people 637 00:35:05,920 --> 00:35:09,719 Speaker 1: who should have known better, and the regulation prosecutors, I 638 00:35:09,800 --> 00:35:13,239 Speaker 1: think most of these are smart, ambitious people and they 639 00:35:13,320 --> 00:35:17,319 Speaker 1: should recognize how the actions that they take going after 640 00:35:17,400 --> 00:35:19,560 Speaker 1: certain people in the industry. Those are have the potential 641 00:35:19,640 --> 00:35:22,719 Speaker 1: be very powerful deterrent messages, and this is a huge 642 00:35:22,760 --> 00:35:25,279 Speaker 1: missed opportunity there they could have. I think they could 643 00:35:25,280 --> 00:35:26,920 Speaker 1: have brought a lot more cases than they did. So 644 00:35:27,080 --> 00:35:29,520 Speaker 1: Jesse Eisinger's book, which I can't say the title on 645 00:35:29,920 --> 00:35:32,959 Speaker 1: of on the air the Chicken Blank Club talks about 646 00:35:33,040 --> 00:35:35,840 Speaker 1: the comby That phrase comes from the Kobe speech about 647 00:35:35,960 --> 00:35:41,560 Speaker 1: the prosecutors who are chickens lazy and only take easy cases. 648 00:35:42,040 --> 00:35:44,439 Speaker 1: But it didn't sound like a lot in your book, 649 00:35:44,520 --> 00:35:47,799 Speaker 1: the picture you paint, it doesn't sound like these are 650 00:35:47,880 --> 00:35:50,839 Speaker 1: all that different. Maybe the Hayes case was a lay down, 651 00:35:51,280 --> 00:35:54,480 Speaker 1: but there seemed like a huge paper trail for another 652 00:35:54,719 --> 00:35:57,880 Speaker 1: dozen people, maybe another fifty people. Yeah, there are a 653 00:35:57,960 --> 00:36:01,279 Speaker 1: lot of people who have of who are caught up 654 00:36:01,320 --> 00:36:04,080 Speaker 1: in this, and they're to me. At first of all, 655 00:36:04,080 --> 00:36:06,040 Speaker 1: I love Jesse Eisinger's book. Everyone should read it. I 656 00:36:06,080 --> 00:36:08,000 Speaker 1: think it's a perfect compliment to the Spider Network in 657 00:36:08,080 --> 00:36:10,239 Speaker 1: the sense that the Spider Network show is one of 658 00:36:10,280 --> 00:36:12,839 Speaker 1: these cases where there was all this evidence and most 659 00:36:12,880 --> 00:36:15,080 Speaker 1: of it just didn't get used. In Jesse's book, does 660 00:36:15,080 --> 00:36:17,200 Speaker 1: a really good job of explaining some of the dynamics 661 00:36:17,239 --> 00:36:21,400 Speaker 1: inside the Justice department for why prosecutors are sometimes kind 662 00:36:21,440 --> 00:36:25,480 Speaker 1: of cowardly and um in this case. And I think 663 00:36:25,640 --> 00:36:29,120 Speaker 1: part of the issue is that these are complicated cases. 664 00:36:29,960 --> 00:36:33,279 Speaker 1: It takes a lot to bring a case, and but 665 00:36:33,400 --> 00:36:36,279 Speaker 1: there's enormous resistance in the financial world, and a lot 666 00:36:36,320 --> 00:36:39,800 Speaker 1: of these prosecutors are they really don't want to lose. 667 00:36:40,360 --> 00:36:44,799 Speaker 1: And to me, the power of the prosecutors have here 668 00:36:45,360 --> 00:36:48,440 Speaker 1: is the simple act of staging a perp walk, of 669 00:36:48,600 --> 00:36:51,719 Speaker 1: going and arresting a senior executive at a bank or 670 00:36:51,800 --> 00:36:55,320 Speaker 1: another big yeah, that would have in parading them in 671 00:36:55,360 --> 00:36:58,560 Speaker 1: front of the TV cameras and making them go into 672 00:36:58,640 --> 00:37:01,440 Speaker 1: court and face the jury of appears, and how the 673 00:37:01,520 --> 00:37:03,360 Speaker 1: fear of God put in them that they might not 674 00:37:03,560 --> 00:37:06,400 Speaker 1: lose some money or might lose some reputation, might lose 675 00:37:06,400 --> 00:37:09,840 Speaker 1: their job, but might lose their freedom. That's scary. And 676 00:37:10,120 --> 00:37:13,000 Speaker 1: if that prospect of the possibility of actually going to 677 00:37:13,160 --> 00:37:17,239 Speaker 1: jail was hanging over people's heads, I think that would 678 00:37:17,239 --> 00:37:19,120 Speaker 1: do a lot to change behavior. And we talked earlier 679 00:37:19,160 --> 00:37:22,680 Speaker 1: about incentives and how people respond to the incentives are given. 680 00:37:23,000 --> 00:37:27,160 Speaker 1: Both positivetives exactly, both positive and negatives. So money is 681 00:37:27,200 --> 00:37:33,760 Speaker 1: a positive incentive, but prospect of serious, life changing personal 682 00:37:33,880 --> 00:37:39,080 Speaker 1: consequences is another incentive, to say the least. Uh. Let 683 00:37:39,120 --> 00:37:42,600 Speaker 1: me let me sum up this conversation with the quote 684 00:37:42,640 --> 00:37:44,960 Speaker 1: from the book, and I want you to respond to it. 685 00:37:45,800 --> 00:37:50,200 Speaker 1: There is a tension between quote long term effective functioning 686 00:37:50,280 --> 00:37:55,000 Speaker 1: of the financial markets on one hands, I'm now paraphrasing you, uh, 687 00:37:55,080 --> 00:37:58,880 Speaker 1: and on the other hand, optimizing the current value of 688 00:37:59,000 --> 00:38:04,200 Speaker 1: your securities portfolio. How do you uh square that circle? 689 00:38:04,360 --> 00:38:08,719 Speaker 1: How do you resolve the tension between those two clearly 690 00:38:09,040 --> 00:38:14,239 Speaker 1: potentially conflicting motivations. So between just long term and short term, well, 691 00:38:14,400 --> 00:38:18,600 Speaker 1: it's it's long term functioning of the financial markets. You know, 692 00:38:19,200 --> 00:38:22,560 Speaker 1: during the subprime crisis, there were these bonuses that people 693 00:38:22,640 --> 00:38:25,719 Speaker 1: called I'll be gone, You'll be gone, bonuses that by 694 00:38:25,760 --> 00:38:28,040 Speaker 1: the time it blew up, hey will be three jobs away. 695 00:38:28,640 --> 00:38:32,719 Speaker 1: It seemed that the short term totally trump the long term. 696 00:38:33,120 --> 00:38:36,560 Speaker 1: But that's not what I'm asking about here. This is 697 00:38:37,880 --> 00:38:42,319 Speaker 1: the actual functioning of the finance markets. So we don't 698 00:38:42,360 --> 00:38:45,279 Speaker 1: have a situation where the crepent markets just freeze. How 699 00:38:45,400 --> 00:38:52,240 Speaker 1: can that inherent tension between functioning markets and optimizing portfolios. 700 00:38:52,440 --> 00:38:56,080 Speaker 1: Can that be resolved? Probably not. And the one of 701 00:38:56,120 --> 00:38:58,319 Speaker 1: the things I found interesting recently though, is that there 702 00:38:58,360 --> 00:39:00,480 Speaker 1: are a lot of banks out there these days. Banks 703 00:39:00,600 --> 00:39:03,480 Speaker 1: used to be the model that was in vogue was 704 00:39:03,560 --> 00:39:05,719 Speaker 1: to be this financial supermarket, and that included, you know, 705 00:39:05,800 --> 00:39:07,800 Speaker 1: you have a retail bank, a credit card business, a 706 00:39:07,840 --> 00:39:10,839 Speaker 1: mortgage business, a wealth management business, but most of all, 707 00:39:10,880 --> 00:39:13,480 Speaker 1: the big revenue driver were these investment banks that a 708 00:39:13,560 --> 00:39:15,800 Speaker 1: lot of it not just prop trading, although that was 709 00:39:15,880 --> 00:39:18,040 Speaker 1: part of it. It was, but there was a huge 710 00:39:18,719 --> 00:39:24,920 Speaker 1: business that sprung up around serving or making trades uh 711 00:39:25,040 --> 00:39:28,560 Speaker 1: in the wake of or around the business of servicing 712 00:39:28,600 --> 00:39:31,279 Speaker 1: big clients and big, big institutions. And one of the 713 00:39:31,360 --> 00:39:33,399 Speaker 1: things I found interest in recently that that turned into 714 00:39:33,440 --> 00:39:35,440 Speaker 1: a very risky business, by the way, because you know 715 00:39:35,640 --> 00:39:38,040 Speaker 1: that a lot of the there's a tremendous amount of 716 00:39:38,080 --> 00:39:40,880 Speaker 1: volatility in the markets, and yes, you can make huge profits, 717 00:39:40,880 --> 00:39:42,800 Speaker 1: but you can also make huge losses when the markets 718 00:39:42,840 --> 00:39:45,360 Speaker 1: turn if you don't handle it perfectly. And one of 719 00:39:45,360 --> 00:39:47,960 Speaker 1: the things I found very interesting now is that if 720 00:39:48,000 --> 00:39:51,440 Speaker 1: you look at the banks that investors think are the 721 00:39:51,560 --> 00:39:54,960 Speaker 1: best deals, those are not banks that bear any resemblance 722 00:39:55,360 --> 00:39:58,160 Speaker 1: to what was in vogue ten years ago. You're looking 723 00:39:58,160 --> 00:40:01,000 Speaker 1: at banks, and the UK has some really interesting examples 724 00:40:01,040 --> 00:40:03,800 Speaker 1: of these banks like Lloyd's and Royal Bank of Scotland 725 00:40:03,840 --> 00:40:07,440 Speaker 1: that are these just there as boring as can be. 726 00:40:07,600 --> 00:40:09,840 Speaker 1: They're just banks that do what banks used to do 727 00:40:09,920 --> 00:40:13,080 Speaker 1: in the nineteen fifties, which is they take deposits, they 728 00:40:13,160 --> 00:40:15,960 Speaker 1: make loans, and it's that simple. And it turns out 729 00:40:16,040 --> 00:40:19,160 Speaker 1: that if you do that properly in an economy that's 730 00:40:19,200 --> 00:40:23,200 Speaker 1: pretty strong, that's an enormously profitable business and it's safe, 731 00:40:23,840 --> 00:40:27,600 Speaker 1: and it's uh conservative, and it also is valuable to 732 00:40:27,920 --> 00:40:31,359 Speaker 1: not just the the shareholders and executives, but to an 733 00:40:31,400 --> 00:40:33,880 Speaker 1: economy as a whole. And I think, to me, this 734 00:40:34,000 --> 00:40:35,920 Speaker 1: is gonna sound old fashioned, and I think a lot 735 00:40:35,920 --> 00:40:37,800 Speaker 1: of people in the banking industry probably will view this 736 00:40:38,040 --> 00:40:41,839 Speaker 1: as naive and just a little too quaint for their taste. 737 00:40:41,880 --> 00:40:46,080 Speaker 1: But looking at things through the prism of is there 738 00:40:46,160 --> 00:40:51,400 Speaker 1: some value social economic value to what you're doing? To 739 00:40:51,560 --> 00:40:54,920 Speaker 1: me that would have that's a pretty good filter for 740 00:40:55,280 --> 00:41:00,160 Speaker 1: activity that is not really good for shareholders either. The 741 00:41:00,480 --> 00:41:03,759 Speaker 1: huge risks the banks are customed to taking those turn 742 00:41:03,800 --> 00:41:08,000 Speaker 1: out badly way too often. So how did RBS run 743 00:41:08,120 --> 00:41:12,840 Speaker 1: into trouble because they are in deep trouble. RBS is 744 00:41:12,880 --> 00:41:15,200 Speaker 1: actually doing pretty well right now with the reality and 745 00:41:15,320 --> 00:41:19,680 Speaker 1: they they were with the world's worst bank for up 746 00:41:19,800 --> 00:41:22,839 Speaker 1: until a couple of years ago, and they managed. They 747 00:41:22,920 --> 00:41:26,120 Speaker 1: had been on this acquisition spree. They were every single 748 00:41:26,280 --> 00:41:29,839 Speaker 1: crisis there was RBS steps in the middle everything. When 749 00:41:29,920 --> 00:41:31,480 Speaker 1: there are a lot of banks that fit that mold right. 750 00:41:31,719 --> 00:41:36,200 Speaker 1: UBS is another good example, City Group, Deutschebank unbelievable, and 751 00:41:36,440 --> 00:41:39,799 Speaker 1: all these banks and and and well it's far ago. 752 00:41:39,880 --> 00:41:42,640 Speaker 1: I mean, we can it's hard to name banks that 753 00:41:42,760 --> 00:41:46,439 Speaker 1: haven't made these catastrophic mistakes. Chase JP Morgan is really 754 00:41:46,520 --> 00:41:49,760 Speaker 1: the exception. Yeah, and Goldman too to a certain extent. 755 00:41:49,840 --> 00:41:53,160 Speaker 1: I think, um, they've certainly had their blunders, but they 756 00:41:54,160 --> 00:41:57,600 Speaker 1: they're not. Those are banks that have been much more 757 00:41:57,680 --> 00:42:02,399 Speaker 1: conservative and I think better. Manager Stanley arguably sidestep much 758 00:42:02,440 --> 00:42:06,200 Speaker 1: of the debacle. We have been speaking to David Enrich 759 00:42:06,360 --> 00:42:10,040 Speaker 1: about the Spider Network. If you enjoy this conversation, be 760 00:42:10,120 --> 00:42:12,520 Speaker 1: sure and check out our podcast extras, where we keep 761 00:42:12,600 --> 00:42:17,640 Speaker 1: the tapes rolling and continued discussing all things Liebor. We 762 00:42:17,800 --> 00:42:21,319 Speaker 1: love your comments, feedback and suggestions right to us. At 763 00:42:22,160 --> 00:42:25,319 Speaker 1: m IB podcast at Bloomberg dot net, where we keep 764 00:42:25,360 --> 00:42:28,200 Speaker 1: the tape rolling and continue discussing all things lie Bar. 765 00:42:28,640 --> 00:42:34,000 Speaker 1: You can find that wherever finer podcasts are sold SoundCloud, Overcast, 766 00:42:34,440 --> 00:42:37,799 Speaker 1: Apple iTunes, and of course Bloomberg dot com. You can 767 00:42:37,920 --> 00:42:40,799 Speaker 1: check out my daily column on Bloomberg View dot com. 768 00:42:41,480 --> 00:42:45,560 Speaker 1: Follow me on Twitter at Rid Halts. I'm Barry Rit Halts. 769 00:42:45,840 --> 00:43:02,760 Speaker 1: You're listening to Masters in Business on Bloomberg Radio. Welcome 770 00:43:02,800 --> 00:43:05,239 Speaker 1: to the podcast, David. Thank you so much for doing this. 771 00:43:05,560 --> 00:43:08,920 Speaker 1: I found I'm only halfway through the book, but I 772 00:43:08,960 --> 00:43:14,560 Speaker 1: found it to be absolutely fascinating, and it unfolds like 773 00:43:14,719 --> 00:43:18,759 Speaker 1: a spy novel. It's it's really amazing characters and all 774 00:43:18,880 --> 00:43:22,600 Speaker 1: these things going on, and you're kind of astonished along 775 00:43:22,640 --> 00:43:24,880 Speaker 1: the way that wait, can they really do that? That? 776 00:43:25,160 --> 00:43:28,200 Speaker 1: That seems like that doesn't make any sense? How much 777 00:43:28,320 --> 00:43:32,239 Speaker 1: fun was this to research and write? So much fun 778 00:43:32,600 --> 00:43:35,399 Speaker 1: it was. It was the most fun I've ever had 779 00:43:35,800 --> 00:43:39,320 Speaker 1: as a journalist. Honestly, I found I found getting to 780 00:43:39,400 --> 00:43:44,360 Speaker 1: know these characters fascinating. I found the historical research fascinating. 781 00:43:44,680 --> 00:43:46,839 Speaker 1: I actually really enjoyed the writing part two. I felt 782 00:43:46,880 --> 00:43:52,400 Speaker 1: like I got h It was a peaceful, creative process 783 00:43:52,440 --> 00:43:56,719 Speaker 1: for me, and I just was happy as a clam. 784 00:43:57,280 --> 00:44:00,600 Speaker 1: So you you get to know the hay his family, 785 00:44:01,480 --> 00:44:06,880 Speaker 1: you spend almost a year with them, than from to 786 00:44:07,040 --> 00:44:12,879 Speaker 1: that early through middle of so and close to two 787 00:44:12,880 --> 00:44:15,719 Speaker 1: and a half years. Are you surprised that he's the 788 00:44:15,800 --> 00:44:18,919 Speaker 1: only person who ended up going to jail for this. I'm, 789 00:44:19,520 --> 00:44:23,080 Speaker 1: on the one hand, surprised because that doesn't seem right 790 00:44:23,320 --> 00:44:24,879 Speaker 1: or fair. There were a few other people who got 791 00:44:25,000 --> 00:44:28,440 Speaker 1: very small jail sentence is not not part of his ring, 792 00:44:28,640 --> 00:44:30,640 Speaker 1: but part of other people at other banks that were 793 00:44:31,719 --> 00:44:34,160 Speaker 1: engaged and have similar behavior, but the jail sentences were 794 00:44:35,280 --> 00:44:38,040 Speaker 1: tiny fractions of what he received. On the other hand, though, 795 00:44:38,040 --> 00:44:40,680 Speaker 1: I'm not that surprised. And one of the things that 796 00:44:41,360 --> 00:44:45,080 Speaker 1: I think has fueled the current populace movement, certainly fueled 797 00:44:45,080 --> 00:44:48,560 Speaker 1: the rises of Bernie Sanders and Donald Trump in is 798 00:44:48,600 --> 00:44:51,160 Speaker 1: the sense that Wall Street got away with murder and 799 00:44:51,719 --> 00:44:54,080 Speaker 1: no one was held no no individuals were held accountable, 800 00:44:54,120 --> 00:44:58,040 Speaker 1: while so many people in the public lost their jobs, 801 00:44:58,200 --> 00:45:00,960 Speaker 1: or their homes or their savings as a result of this. 802 00:45:01,000 --> 00:45:03,719 Speaker 1: And I think there's that's that feeling that's been out 803 00:45:03,760 --> 00:45:08,319 Speaker 1: there since the financial crisis that's it lends itself to demagoguery, 804 00:45:08,360 --> 00:45:12,600 Speaker 1: and it's often oversimplified and not very nuanced, but there's 805 00:45:12,680 --> 00:45:16,680 Speaker 1: a big kernel of truth that behind that, And drain 806 00:45:16,760 --> 00:45:19,759 Speaker 1: the swamp is an effective slogan. Drain the swamps and 807 00:45:19,800 --> 00:45:24,040 Speaker 1: effective slogan. And the fear that Wall Street is taking 808 00:45:24,080 --> 00:45:26,880 Speaker 1: advantage and people are everyone is in the pocket of 809 00:45:26,880 --> 00:45:29,839 Speaker 1: Wall Street, whether it's politicians or proseutors. That's again, it's 810 00:45:29,880 --> 00:45:32,560 Speaker 1: not that simple, but there is some truth to that, 811 00:45:32,760 --> 00:45:36,200 Speaker 1: and there's no to me, there's no more powerful manifestation 812 00:45:36,280 --> 00:45:41,600 Speaker 1: of that than looking at the almost uniformly low level, 813 00:45:43,640 --> 00:45:48,440 Speaker 1: slightly dysfunctional, almost autistic guys who bear the brunt of 814 00:45:49,719 --> 00:45:53,160 Speaker 1: the criminal accountability for actions committed during the financial crisis. 815 00:45:53,160 --> 00:45:55,840 Speaker 1: It's not just haz And there's people involved in London 816 00:45:55,880 --> 00:45:58,880 Speaker 1: Whale that are kind of like a little on the spectrum. 817 00:45:58,880 --> 00:46:00,719 Speaker 1: I don't know them, but that's just the sense I get. 818 00:46:00,920 --> 00:46:02,920 Speaker 1: The guy who has been account held accountable for the 819 00:46:03,000 --> 00:46:06,080 Speaker 1: flash crash in is a guy who is like a 820 00:46:06,200 --> 00:46:08,960 Speaker 1: little bit on the spectrum. There's this is a pattern. 821 00:46:10,040 --> 00:46:13,480 Speaker 1: So what was the most shocking thing you discovered while 822 00:46:13,520 --> 00:46:16,440 Speaker 1: you were researching this? To me, that it was not 823 00:46:16,840 --> 00:46:18,760 Speaker 1: it is not something it's going to make a sexy headline, 824 00:46:18,760 --> 00:46:23,359 Speaker 1: but it was really the degree to which culture at 825 00:46:23,400 --> 00:46:27,399 Speaker 1: banks matters and has real world impacts. As someone who's 826 00:46:27,440 --> 00:46:29,000 Speaker 1: been covering the banking industry in the U S and 827 00:46:29,000 --> 00:46:32,359 Speaker 1: the UK for many years, I'd kind of dismissed as 828 00:46:32,480 --> 00:46:36,920 Speaker 1: hogwash this notion of culture that consultants and banking executives 829 00:46:36,960 --> 00:46:39,640 Speaker 1: pay lip service too. But I actually realized that it's true, 830 00:46:39,719 --> 00:46:42,080 Speaker 1: and there's the culture at the institutions where Tom Hayes 831 00:46:42,120 --> 00:46:47,920 Speaker 1: worked was one where envelope pushing was not just acceptable, 832 00:46:47,960 --> 00:46:52,040 Speaker 1: but it was explicitly encouraged, explicitly and explicitly encouraged. And 833 00:46:52,120 --> 00:46:55,279 Speaker 1: the senior executives at a number of these institutions, not 834 00:46:55,360 --> 00:46:58,879 Speaker 1: just where Hayes worked, but across the industry were doing 835 00:46:58,960 --> 00:47:01,239 Speaker 1: things not just with their trading but also just what 836 00:47:01,320 --> 00:47:06,880 Speaker 1: their socialized doing things that are just out of controlled drinking, womanizing, drugs, 837 00:47:07,040 --> 00:47:10,640 Speaker 1: things like that that we that you can't help. But 838 00:47:10,680 --> 00:47:13,560 Speaker 1: look at the behavior of a top executive as a 839 00:47:13,719 --> 00:47:16,120 Speaker 1: as an underling in an organization and take a cue 840 00:47:16,239 --> 00:47:18,040 Speaker 1: from that person. If that person is doing stuff that 841 00:47:18,520 --> 00:47:22,080 Speaker 1: is just nuts, you're gonna get the message that it's 842 00:47:22,120 --> 00:47:26,080 Speaker 1: okay to be nuts. So so you can identify a 843 00:47:26,200 --> 00:47:30,560 Speaker 1: distinct cultural difference from bank to bank, executive to executive, 844 00:47:31,680 --> 00:47:35,399 Speaker 1: even if not pushing the envelope means our profit level 845 00:47:35,480 --> 00:47:37,600 Speaker 1: is going to be a little less. That that works 846 00:47:37,640 --> 00:47:40,359 Speaker 1: its way through the entire troops. Absolutely, And I think 847 00:47:40,400 --> 00:47:42,640 Speaker 1: that we're talking earlier about how some some of the 848 00:47:42,680 --> 00:47:46,239 Speaker 1: banks have survived whethered crasies pretty well. Are the like 849 00:47:46,520 --> 00:47:48,799 Speaker 1: and JP Morgan is a good example, and it's an 850 00:47:48,880 --> 00:47:52,080 Speaker 1: enormously profitable institution. It's made many, many mistakes, of course, 851 00:47:52,719 --> 00:47:56,200 Speaker 1: but that's an institution where it's okay to leave some 852 00:47:56,320 --> 00:47:58,680 Speaker 1: money on the table sometimes. But they don't. They don't 853 00:47:58,680 --> 00:48:02,759 Speaker 1: seem to make existent mistakes like like Lehman did, like 854 00:48:02,960 --> 00:48:06,440 Speaker 1: There did, like City Bank there. Apparently the list of 855 00:48:06,520 --> 00:48:11,239 Speaker 1: banks that have made existential mistakes is much longer than 856 00:48:11,280 --> 00:48:12,920 Speaker 1: a list of banks that have it. And I can 857 00:48:13,960 --> 00:48:16,360 Speaker 1: I really can't think and not all of them, not 858 00:48:16,520 --> 00:48:21,920 Speaker 1: all of the mistakes became existential because thanks largely taxpayers, 859 00:48:22,040 --> 00:48:25,560 Speaker 1: but there was I mean, it's it's really hard for 860 00:48:25,640 --> 00:48:30,320 Speaker 1: me to think of a bank that really managed risks 861 00:48:30,400 --> 00:48:32,840 Speaker 1: well and would have been fine without government intervention. And 862 00:48:33,000 --> 00:48:36,399 Speaker 1: that's that's again there's a lot of external circumstances to play, 863 00:48:36,400 --> 00:48:39,360 Speaker 1: and there's good luck and bad luck. But the reality 864 00:48:39,440 --> 00:48:44,480 Speaker 1: is these banks were financial institutions in general, were responding 865 00:48:44,520 --> 00:48:49,040 Speaker 1: to press again, incentives from shareholders too, and uh the 866 00:48:49,080 --> 00:48:52,440 Speaker 1: analyst community to amp up profits as quickly as possible 867 00:48:52,520 --> 00:48:54,279 Speaker 1: quarter after quarter, and the best way to do that 868 00:48:54,360 --> 00:48:56,879 Speaker 1: is to take more risks. And that works really well 869 00:48:57,080 --> 00:49:00,720 Speaker 1: until it doesn't. So before I get to my favorite questions, 870 00:49:00,760 --> 00:49:03,520 Speaker 1: I have to ask you a little bit about um, 871 00:49:03,800 --> 00:49:07,719 Speaker 1: your writing process, because it really is kind of fascinating. 872 00:49:08,040 --> 00:49:10,080 Speaker 1: How did you find your way to the Wall Street 873 00:49:10,120 --> 00:49:12,440 Speaker 1: Journal that was back in oh seven before the crisis? 874 00:49:12,560 --> 00:49:15,000 Speaker 1: Is that right? It was? I started at the journal 875 00:49:15,840 --> 00:49:18,400 Speaker 1: in December of two thousand seven, so the crisis was 876 00:49:18,800 --> 00:49:21,080 Speaker 1: right as the recession was started. Yeah, right, is saying 877 00:49:21,320 --> 00:49:24,520 Speaker 1: that was right? I started right after Chuck Princeton Standard 878 00:49:24,560 --> 00:49:26,840 Speaker 1: Neial lost their jobs at the Maryland City Group. And 879 00:49:28,080 --> 00:49:30,120 Speaker 1: I've been working at down John's News Wires, which is 880 00:49:30,520 --> 00:49:33,840 Speaker 1: uh same same parent company for a few years in 881 00:49:34,160 --> 00:49:38,319 Speaker 1: Washington and in New York, and prior to that had 882 00:49:38,320 --> 00:49:41,440 Speaker 1: been doing other journalisms. And you were in Washington covering 883 00:49:42,120 --> 00:49:45,239 Speaker 1: not banks. What were you covering? I was covering politics. 884 00:49:46,000 --> 00:49:48,239 Speaker 1: My first job out of college was working for this 885 00:49:48,360 --> 00:49:51,200 Speaker 1: little wire service. It was kind of Washington d C 886 00:49:51,360 --> 00:49:53,400 Speaker 1: bureau for a bunch of regional newspapers. So I was 887 00:49:53,719 --> 00:49:57,319 Speaker 1: I was covering d C for a newspaper in Wisconsin. 888 00:49:58,239 --> 00:50:01,040 Speaker 1: One in Amarillo, Texas where they which is home to, 889 00:50:01,440 --> 00:50:04,800 Speaker 1: uh the manufacturer of the V twenty two osprey. You 890 00:50:04,840 --> 00:50:08,080 Speaker 1: know there's plane. At the time they were this is 891 00:50:08,080 --> 00:50:10,080 Speaker 1: in the early two thousands, they were they kept crashing 892 00:50:10,080 --> 00:50:11,560 Speaker 1: and they kept inviting me to go down there and 893 00:50:11,600 --> 00:50:14,240 Speaker 1: write on one, and I thought they were They were crazy. 894 00:50:15,120 --> 00:50:18,040 Speaker 1: They fly now you see them around actually in the 895 00:50:18,200 --> 00:50:20,480 Speaker 1: UK uses them all the time there. You see them 896 00:50:20,600 --> 00:50:24,600 Speaker 1: flying around London. They were really considered wildly over priced, 897 00:50:24,640 --> 00:50:26,560 Speaker 1: bone dog one of that. I don't remember the price. 898 00:50:26,640 --> 00:50:28,359 Speaker 1: I just remember the fact that they kept crashing. They 899 00:50:28,400 --> 00:50:31,880 Speaker 1: weren't safe at all. They would like they would crash 900 00:50:31,960 --> 00:50:34,719 Speaker 1: like ten at the time. That's not a good ratio, 901 00:50:34,800 --> 00:50:37,040 Speaker 1: that's a bad number. So so you find your way 902 00:50:37,040 --> 00:50:40,840 Speaker 1: to the journal, you stop covering politics, do you immediately 903 00:50:41,040 --> 00:50:44,000 Speaker 1: start covering banks out of that work? Yeah, I started 904 00:50:44,040 --> 00:50:47,640 Speaker 1: covering finance at Dow Jones at news Wires, and I 905 00:50:47,719 --> 00:50:50,759 Speaker 1: had no idea. I had fallen asleep for most my 906 00:50:50,960 --> 00:50:55,839 Speaker 1: icon classes in college finance experience. Uh. But my first 907 00:50:55,920 --> 00:50:59,680 Speaker 1: job at Dow Jones was actually, uh, my primary goal 908 00:50:59,840 --> 00:51:01,880 Speaker 1: was to I had to read all these SEC filings 909 00:51:02,000 --> 00:51:04,840 Speaker 1: and so I kind of taught myself what a balanced 910 00:51:04,880 --> 00:51:07,560 Speaker 1: she is when income statement is how companies make disclosures, 911 00:51:07,600 --> 00:51:11,000 Speaker 1: and that proved to be a really useful skill. Um, 912 00:51:11,760 --> 00:51:13,760 Speaker 1: and I learned a lot about the industries, but more important, 913 00:51:13,760 --> 00:51:15,880 Speaker 1: I learned how to do research, which is kind of 914 00:51:15,960 --> 00:51:20,120 Speaker 1: the lifeblood of any good business reporter. So you're covering 915 00:51:20,239 --> 00:51:24,440 Speaker 1: Tom Hayes for the Journal. You're you're one of five. 916 00:51:24,920 --> 00:51:26,680 Speaker 1: You know, you're one of the journalists responsible for the 917 00:51:26,760 --> 00:51:29,520 Speaker 1: five part series that led to the lobe A ward. 918 00:51:29,960 --> 00:51:34,000 Speaker 1: What made you say, um, let's turn this into a book. 919 00:51:34,920 --> 00:51:36,600 Speaker 1: It was, you know what it was? It was that 920 00:51:36,840 --> 00:51:39,239 Speaker 1: in that five part series, and that was I don't know, 921 00:51:39,320 --> 00:51:41,120 Speaker 1: it's like seven or eight thousand words, which is really 922 00:51:41,200 --> 00:51:45,759 Speaker 1: long by newspaper journalist standards, manning journalist standards. And I 923 00:51:46,160 --> 00:51:48,239 Speaker 1: looked at what I had as I wrote that, and 924 00:51:48,400 --> 00:51:50,680 Speaker 1: there was just I had so much more material and 925 00:51:50,719 --> 00:51:53,719 Speaker 1: I felt like I was having to really leave so 926 00:51:53,840 --> 00:51:57,040 Speaker 1: much on the cutting room floor, And that was the 927 00:51:57,200 --> 00:51:59,160 Speaker 1: narrative in that story to me, and I think a 928 00:51:59,200 --> 00:52:00,880 Speaker 1: lot of readers as well, with really powerful and it 929 00:52:01,239 --> 00:52:05,120 Speaker 1: was putting a human face on someone who had been 930 00:52:05,200 --> 00:52:07,640 Speaker 1: caricatured as a villain and it you know, it turns 931 00:52:07,680 --> 00:52:10,600 Speaker 1: out we all have a lot in common, and you know, 932 00:52:10,719 --> 00:52:12,439 Speaker 1: once you get to know someone, you can really relate 933 00:52:12,480 --> 00:52:14,480 Speaker 1: to them more. And to me, that was this is 934 00:52:14,640 --> 00:52:17,839 Speaker 1: a great character, a great narrative arc, and a great 935 00:52:17,880 --> 00:52:22,200 Speaker 1: opportunity to bring some of this finance stuff to a 936 00:52:22,280 --> 00:52:25,600 Speaker 1: mass audience, because the finance industry over the past twenty 937 00:52:25,680 --> 00:52:27,200 Speaker 1: years has done a really good job at kind of 938 00:52:27,239 --> 00:52:31,360 Speaker 1: cloaking itself in opacity and making it seem like the 939 00:52:31,440 --> 00:52:34,880 Speaker 1: stuff they're doing is so complicated and so important that 940 00:52:35,160 --> 00:52:37,719 Speaker 1: no mere mortal can actually understand it. And you know what, 941 00:52:37,880 --> 00:52:40,720 Speaker 1: that's nonsense. There by the way, that is a feature, 942 00:52:40,840 --> 00:52:43,640 Speaker 1: not a bug. When things are simple and transparent, you 943 00:52:43,719 --> 00:52:46,880 Speaker 1: can't charge know that, that's completely right. They they have 944 00:52:47,080 --> 00:52:49,440 Speaker 1: thrived on this lack of transparency and this kind of 945 00:52:49,760 --> 00:52:52,840 Speaker 1: the mystification of the banking industry. They've thrived on it, 946 00:52:53,000 --> 00:52:56,160 Speaker 1: and that drives me crazy, and it so to me 947 00:52:56,320 --> 00:52:59,160 Speaker 1: this was how do you get people to actually read 948 00:52:59,160 --> 00:53:01,200 Speaker 1: a book about finance. A One way is to make 949 00:53:01,280 --> 00:53:05,160 Speaker 1: it read like a spy miss spin and it does 950 00:53:05,320 --> 00:53:08,560 Speaker 1: and and that's gratified theories. That was the goal. And 951 00:53:09,120 --> 00:53:11,040 Speaker 1: at the same time, you can get people to eat 952 00:53:11,080 --> 00:53:14,759 Speaker 1: some of their like carrots and spinach sneak sneaking in 953 00:53:14,840 --> 00:53:17,160 Speaker 1: And I feel like there's I used my parents, who 954 00:53:18,160 --> 00:53:20,480 Speaker 1: don't know what's tremends amount about finance as kind of 955 00:53:20,920 --> 00:53:26,400 Speaker 1: guinea pigs, and uh, that was a laborious process that 956 00:53:26,480 --> 00:53:28,320 Speaker 1: might not have been great for my relationship with my parents, 957 00:53:28,400 --> 00:53:30,920 Speaker 1: But so funny you say that my wife is an 958 00:53:31,000 --> 00:53:33,640 Speaker 1: art teacher, my mother is a real estate agent. And 959 00:53:33,719 --> 00:53:36,279 Speaker 1: when I'm trying to explain anything in finance, if I 960 00:53:36,360 --> 00:53:41,120 Speaker 1: can get if I could create an explanation that both 961 00:53:41,200 --> 00:53:43,680 Speaker 1: of them easily get, I know you're in business, I 962 00:53:43,800 --> 00:53:45,920 Speaker 1: know I understand it, and I know I can explain. 963 00:53:46,040 --> 00:53:47,400 Speaker 1: That was one of the interesting things for me is 964 00:53:47,480 --> 00:53:51,359 Speaker 1: that that act of trying to explain things, either trying 965 00:53:51,400 --> 00:53:55,080 Speaker 1: to write them in really simple terms or explain them 966 00:53:55,120 --> 00:53:57,640 Speaker 1: to human beings like my book editor, for example. The 967 00:53:57,719 --> 00:53:59,200 Speaker 1: act of doing that, I I had at this point 968 00:53:59,480 --> 00:54:02,640 Speaker 1: been covering banks for since like two thousand and four, 969 00:54:02,760 --> 00:54:05,920 Speaker 1: I think, so this is more than a decade. And uh, 970 00:54:06,200 --> 00:54:08,080 Speaker 1: I thought I did know the industry quite well. But 971 00:54:08,200 --> 00:54:09,880 Speaker 1: the act of trying to explain to someone what an 972 00:54:09,920 --> 00:54:12,400 Speaker 1: interest rate swap is, what a derivative is, what does 973 00:54:12,440 --> 00:54:14,640 Speaker 1: the bank actually do that that was a sobering moment 974 00:54:14,680 --> 00:54:16,840 Speaker 1: for me because I realized that as well as I 975 00:54:16,920 --> 00:54:19,640 Speaker 1: knew this industry and as many you know, hundreds if 976 00:54:19,680 --> 00:54:22,800 Speaker 1: not thousands of stories had written about it, I it 977 00:54:22,960 --> 00:54:25,839 Speaker 1: was very hard to explain these things, and I don't 978 00:54:25,880 --> 00:54:27,839 Speaker 1: think I understood them fully. So I was gonna say 979 00:54:27,880 --> 00:54:31,080 Speaker 1: the old line is, if you really want to understand something, 980 00:54:31,440 --> 00:54:33,840 Speaker 1: teach it, because if you could teach it, then you really, 981 00:54:34,080 --> 00:54:36,239 Speaker 1: you really get it. So I found myself in writing 982 00:54:36,280 --> 00:54:38,759 Speaker 1: this book. There's a section on what a derivative is 983 00:54:38,760 --> 00:54:41,400 Speaker 1: and what an interest rate swap is, and I remember 984 00:54:41,440 --> 00:54:43,960 Speaker 1: sitting down to write writing it. Sitting down to write it, 985 00:54:44,000 --> 00:54:46,800 Speaker 1: and I realized I was writing just nonsense. It was gibberish, 986 00:54:47,080 --> 00:54:49,719 Speaker 1: and it was a very obvious reflection of my lack 987 00:54:49,800 --> 00:54:51,719 Speaker 1: of nuanced understanding of it. So I had to go 988 00:54:51,880 --> 00:54:54,759 Speaker 1: back and I found a bunch of professors who had 989 00:54:54,840 --> 00:54:58,040 Speaker 1: were former traders to kind of walk me through it, 990 00:54:58,200 --> 00:55:01,840 Speaker 1: and I just read a hot and arrived at a 991 00:55:01,880 --> 00:55:04,480 Speaker 1: point where I did understand. And honestly, a lot of 992 00:55:04,560 --> 00:55:07,040 Speaker 1: this stuff is not that complicated when you boil it 993 00:55:07,080 --> 00:55:09,279 Speaker 1: down to its essence. It's that Wall Street does a 994 00:55:09,400 --> 00:55:14,040 Speaker 1: very good job of cloaking everything and acronyms and jargon 995 00:55:14,640 --> 00:55:17,359 Speaker 1: and you know, just doubling the complexity for the sake 996 00:55:17,400 --> 00:55:21,560 Speaker 1: of complexity itself. So augusteen, you leave the Wall Street Journal, 997 00:55:21,600 --> 00:55:24,880 Speaker 1: you go to the New York Times. What motivated that change? 998 00:55:25,000 --> 00:55:27,880 Speaker 1: And and what is it like working at the Gray Lady? Um? 999 00:55:28,239 --> 00:55:30,160 Speaker 1: What motivated that changes? I've been at the Journal for 1000 00:55:30,200 --> 00:55:33,440 Speaker 1: a long time. I love the water. Yeah, and I've 1001 00:55:33,480 --> 00:55:35,320 Speaker 1: been there for at the Journal for a decade, And 1002 00:55:35,400 --> 00:55:36,960 Speaker 1: if you count my time at DOWD John's before that, 1003 00:55:37,040 --> 00:55:38,640 Speaker 1: it was closer to fifth and that was a that 1004 00:55:38,840 --> 00:55:42,640 Speaker 1: was a decade where a lot of stuff was happening. Yeah, 1005 00:55:43,000 --> 00:55:45,000 Speaker 1: I mean a lot of stuff externally, was the entire 1006 00:55:45,040 --> 00:55:47,839 Speaker 1: financial crisis, a lot of stuff internally. Murdoch bought the place, 1007 00:55:48,480 --> 00:55:50,799 Speaker 1: and look, I love the Wall Street Journal day day 1008 00:55:50,880 --> 00:55:53,239 Speaker 1: in and day out, do great stuff. In fact, this 1009 00:55:53,680 --> 00:55:55,560 Speaker 1: may or may not be a coincidence, but since I left, 1010 00:55:55,600 --> 00:55:58,960 Speaker 1: they've just been on this tear, one awesome scoop after another. 1011 00:55:59,040 --> 00:56:02,000 Speaker 1: So I'm not sure that's because I left her despite me, 1012 00:56:02,440 --> 00:56:07,920 Speaker 1: but there's but the time, I hope not. The times 1013 00:56:08,000 --> 00:56:11,600 Speaker 1: is great. We are um in the midst of trying 1014 00:56:11,640 --> 00:56:15,040 Speaker 1: to kind of expand and revitalize our business and finance 1015 00:56:15,160 --> 00:56:17,840 Speaker 1: do so I'm the finance editor, so I run a 1016 00:56:17,920 --> 00:56:21,920 Speaker 1: team of I think nine or ten reporters and we're hiring, 1017 00:56:22,640 --> 00:56:27,520 Speaker 1: uh so, everything from banking and Wall Street and markets 1018 00:56:27,880 --> 00:56:35,120 Speaker 1: to UM, insurance, business, public pensions, um, the whole range 1019 00:56:35,239 --> 00:56:40,160 Speaker 1: of everything. So it's fun, it's busy, it's uh you know, 1020 00:56:40,400 --> 00:56:41,680 Speaker 1: this is I think we might be entering a new 1021 00:56:41,719 --> 00:56:43,719 Speaker 1: turbulent era. So there'll be lots more to write about. 1022 00:56:43,840 --> 00:56:46,520 Speaker 1: So let's get to my favorite questions. I asked these 1023 00:56:46,600 --> 00:56:50,040 Speaker 1: of all my guests, tell me the most important thing 1024 00:56:50,280 --> 00:56:55,400 Speaker 1: that people don't know about you. I have been bald 1025 00:56:56,760 --> 00:57:00,080 Speaker 1: since I was fifteen years old. Fifteen Mikey here that 1026 00:57:00,320 --> 00:57:02,960 Speaker 1: so my head of research a couple of years ago 1027 00:57:03,200 --> 00:57:05,960 Speaker 1: and he's early thirties, just said, the hell with it. 1028 00:57:06,080 --> 00:57:09,040 Speaker 1: I'm just gonna start shaving. Well, that's smart. He gave 1029 00:57:09,120 --> 00:57:11,200 Speaker 1: up on it, Dave, as early as and often as 1030 00:57:11,239 --> 00:57:14,600 Speaker 1: you can. There's nothing is? So what was that like 1031 00:57:14,719 --> 00:57:18,000 Speaker 1: in high school? I can't the words. I'd get bleeped out. 1032 00:57:18,040 --> 00:57:21,320 Speaker 1: It's awful kidding me? So not? And and you were 1033 00:57:21,600 --> 00:57:24,200 Speaker 1: just at the edge of the Michael Jordan era. So 1034 00:57:24,640 --> 00:57:27,200 Speaker 1: you wanted to be like Mike or it? You just said, 1035 00:57:28,520 --> 00:57:30,720 Speaker 1: is there is? Well, I yeah, shaved my head, but 1036 00:57:30,800 --> 00:57:32,720 Speaker 1: that was not because I wanted to be like Mike. 1037 00:57:32,840 --> 00:57:38,240 Speaker 1: That's because I was going bald, isn't. Wow? That's amazing. 1038 00:57:38,800 --> 00:57:42,480 Speaker 1: Um Who were some of your early mentors who influenced 1039 00:57:42,920 --> 00:57:47,040 Speaker 1: your research and writing styles? Um My dad certainly did. 1040 00:57:47,080 --> 00:57:50,080 Speaker 1: He's a professor and was he teaching What does he teach? 1041 00:57:50,200 --> 00:57:54,840 Speaker 1: He teaches law at Northeastern University in Boston. Um My, 1042 00:57:55,400 --> 00:57:57,520 Speaker 1: and my mom actually was a mentor, and not in 1043 00:57:57,680 --> 00:57:59,800 Speaker 1: terms of writing, but in terms she's a psychologist. And 1044 00:58:00,640 --> 00:58:04,280 Speaker 1: I've found that the one of the most important things 1045 00:58:04,280 --> 00:58:07,760 Speaker 1: about being a successful journalist is the inability to get 1046 00:58:07,760 --> 00:58:10,120 Speaker 1: people to talk to you, people who often aren't supposed 1047 00:58:10,120 --> 00:58:12,200 Speaker 1: to talk to you, get them to think that it's 1048 00:58:12,240 --> 00:58:13,720 Speaker 1: in their best interests to do so, and the best 1049 00:58:13,760 --> 00:58:15,520 Speaker 1: way to do that is to kind of understand where 1050 00:58:15,520 --> 00:58:18,200 Speaker 1: they're coming from and show empathy and listen. Well, and 1051 00:58:18,280 --> 00:58:21,680 Speaker 1: those are traits that my mom really taught me. But uh, 1052 00:58:21,800 --> 00:58:25,439 Speaker 1: I mean there's throughout college. And I said a number 1053 00:58:25,440 --> 00:58:29,439 Speaker 1: of great professors who taught me that, you know, don't 1054 00:58:29,520 --> 00:58:35,000 Speaker 1: use adverbs, don't write passive sentences, use action verbs, things 1055 00:58:35,080 --> 00:58:40,240 Speaker 1: like that. Don't okay, don't use adverbs, no passive action words, 1056 00:58:40,320 --> 00:58:45,320 Speaker 1: short sentences, direct use you know, don't use a three 1057 00:58:45,320 --> 00:58:48,800 Speaker 1: syllable word when a one syllable word, we'll do. There's 1058 00:58:48,920 --> 00:58:53,480 Speaker 1: a one syllable word for syllable beat. Oh, I like 1059 00:58:53,680 --> 00:58:57,960 Speaker 1: that very good. Um tell us the journalists who influenced 1060 00:58:58,040 --> 00:59:02,320 Speaker 1: the way you approach covering a topic, Um, the kind 1061 00:59:02,320 --> 00:59:05,880 Speaker 1: of great inspirations And for me, at least in business 1062 00:59:05,960 --> 00:59:08,080 Speaker 1: journalism or this is not gonna surprise. I mean, Michael 1063 00:59:08,160 --> 00:59:11,800 Speaker 1: Lewis is one of the great. Uh, nobody focuses on 1064 00:59:12,080 --> 00:59:17,480 Speaker 1: characters in finance the way he does. Absolutely, he's easily 1065 00:59:17,520 --> 00:59:20,040 Speaker 1: the best there is at that and it's just inspiring. 1066 00:59:20,360 --> 00:59:22,880 Speaker 1: And to me, actually, my favorite writing of his is 1067 00:59:22,880 --> 00:59:26,000 Speaker 1: actually not in the finance basaying Moneyball is a book 1068 00:59:26,200 --> 00:59:30,600 Speaker 1: that and change I'm a huge baseball fan, and change 1069 00:59:30,640 --> 00:59:33,040 Speaker 1: the way I watched baseball and thinking about baseball, which 1070 00:59:33,120 --> 00:59:35,080 Speaker 1: is saying a lot because I at that point, I 1071 00:59:35,120 --> 00:59:37,160 Speaker 1: can't remember when that came out, early two thousand's probably, 1072 00:59:37,360 --> 00:59:41,280 Speaker 1: and I at that point it's spent my entire life 1073 00:59:41,320 --> 00:59:44,040 Speaker 1: obsessing over the Boston Red sucks. And to then see 1074 00:59:44,920 --> 00:59:47,000 Speaker 1: to view it through this entirely different prison, it's something 1075 00:59:47,600 --> 00:59:51,120 Speaker 1: really exceptionally powerful. And that's essentially a book about stats, right, 1076 00:59:51,160 --> 00:59:53,200 Speaker 1: I was gonna I was gonna push back and say 1077 00:59:54,520 --> 00:59:58,920 Speaker 1: it shares a tremendous amount with the rise of quants 1078 00:59:58,960 --> 01:00:01,400 Speaker 1: and finance and rise and quants. It's, oh, we have 1079 01:00:01,480 --> 01:00:04,160 Speaker 1: computers and we understand math. Here's how to make the 1080 01:00:04,240 --> 01:00:07,000 Speaker 1: segment better. It just doesn't matter which the subject is. 1081 01:00:07,560 --> 01:00:09,600 Speaker 1: And he does a masterful job. Have you ever read 1082 01:00:09,960 --> 01:00:11,840 Speaker 1: The blind Side of Him? I love The blind Side 1083 01:00:11,840 --> 01:00:15,440 Speaker 1: as well. It's actually his funniest book. I think is 1084 01:00:15,560 --> 01:00:19,000 Speaker 1: just laugh out loud segments and it's obviously a very 1085 01:00:19,040 --> 01:00:22,520 Speaker 1: personal book. Without spoiling any of it for anyone. Um, 1086 01:00:22,800 --> 01:00:25,960 Speaker 1: since we're talking about books, well before we talk about books, 1087 01:00:25,960 --> 01:00:27,760 Speaker 1: anyone else in the media you want to reference, Yeah, 1088 01:00:27,800 --> 01:00:29,680 Speaker 1: there are two others. One is Jim Stewart, who is 1089 01:00:29,720 --> 01:00:33,280 Speaker 1: now a columnist Thieves, Thieves, Den of Thieves and like 1090 01:00:33,320 --> 01:00:35,200 Speaker 1: a zillion other books, but that was the one that 1091 01:00:35,360 --> 01:00:39,200 Speaker 1: really Yeah, that was an amazing book and he's I'm 1092 01:00:39,320 --> 01:00:41,680 Speaker 1: really proud. That's why my one of the many great 1093 01:00:41,720 --> 01:00:43,400 Speaker 1: things about working at the Times these days is he's 1094 01:00:43,440 --> 01:00:46,000 Speaker 1: a colleague of mine and I get to bounce ideas 1095 01:00:46,040 --> 01:00:49,919 Speaker 1: off him and sometimes the same with me. And that's saying. 1096 01:00:49,960 --> 01:00:51,920 Speaker 1: And the one other personal mention is not a journalist 1097 01:00:52,520 --> 01:00:54,760 Speaker 1: is but it used to be is Karrik Mullencamp, who 1098 01:00:54,960 --> 01:00:57,040 Speaker 1: is uh, the guy who when he was a Wall 1099 01:00:57,080 --> 01:01:01,640 Speaker 1: Street journal reporter basically uncovered the lie Worlar scandal and 1100 01:01:01,800 --> 01:01:04,800 Speaker 1: real not like he uncovered like there was an investigation 1101 01:01:04,840 --> 01:01:07,720 Speaker 1: going on, but he did the number crunction in the 1102 01:01:07,800 --> 01:01:11,480 Speaker 1: analysis and something sourcing and yeah, blew the whistle on 1103 01:01:11,560 --> 01:01:14,760 Speaker 1: it essentially, And that, to me is the most profound 1104 01:01:14,800 --> 01:01:17,160 Speaker 1: example I've seen in business journalism in a really long 1105 01:01:17,280 --> 01:01:22,200 Speaker 1: time of a newspaper story or a news story changing 1106 01:01:22,240 --> 01:01:27,040 Speaker 1: the world. So, since we mentioned uh, money ball, what 1107 01:01:27,200 --> 01:01:32,040 Speaker 1: are some of your favorite books finance, nonfinance, fiction, nonfiction? 1108 01:01:32,160 --> 01:01:34,600 Speaker 1: What what do you really like Um, I really like 1109 01:01:34,840 --> 01:01:38,400 Speaker 1: the business genre. Actually, and there's We've mentioned Michael Lewis, 1110 01:01:38,480 --> 01:01:41,440 Speaker 1: We've mentioned Denil Thus by Jim Stewart, When Genius Failed 1111 01:01:41,440 --> 01:01:46,840 Speaker 1: by Roger Lonstein is uh is a great one. The 1112 01:01:46,960 --> 01:01:48,960 Speaker 1: thing I like about I like books that have a 1113 01:01:49,040 --> 01:01:52,720 Speaker 1: narrative arc, so whether that's fiction or nonfiction. And Um, 1114 01:01:53,840 --> 01:01:56,600 Speaker 1: to me, that's it's really I mean, I got out. 1115 01:01:56,600 --> 01:01:58,280 Speaker 1: I have no idea how to write a write a novel, 1116 01:01:58,360 --> 01:02:00,880 Speaker 1: but there's in in think that's a lot of way 1117 01:02:00,960 --> 01:02:03,720 Speaker 1: is harder than writing nonfiction, but nonfiction doing in a 1118 01:02:03,840 --> 01:02:06,480 Speaker 1: compelling way. I mean, I've done this one tonight. It's hard, 1119 01:02:06,800 --> 01:02:09,800 Speaker 1: and it's really hard. And being able to find character 1120 01:02:09,880 --> 01:02:11,240 Speaker 1: and get them to open up to you, and being 1121 01:02:11,240 --> 01:02:13,800 Speaker 1: able to tell their stories in a way that not 1122 01:02:14,000 --> 01:02:17,840 Speaker 1: only engages readers, but it's also honest and it really 1123 01:02:17,920 --> 01:02:20,560 Speaker 1: reflects what's going on in a non superficial way. That's 1124 01:02:20,600 --> 01:02:23,240 Speaker 1: hard and it's so powerful when you can get it right. 1125 01:02:23,360 --> 01:02:26,880 Speaker 1: Give us one more. Another recent one is I'm gonna 1126 01:02:26,920 --> 01:02:28,960 Speaker 1: butcher her name, but Sheila from The New York Or 1127 01:02:29,040 --> 01:02:32,240 Speaker 1: her book Black Edge on Stevie is a great one. Yeah. Um, 1128 01:02:32,480 --> 01:02:36,360 Speaker 1: that's that's a really interesting title. Alright, let's uh, let's 1129 01:02:36,440 --> 01:02:41,640 Speaker 1: talk a bit about financial journalism. What excites you right 1130 01:02:41,760 --> 01:02:44,360 Speaker 1: now that's going on in the world of financial media. 1131 01:02:45,080 --> 01:02:47,320 Speaker 1: We're just finding new ways to tell stories. I mean, 1132 01:02:47,360 --> 01:02:51,280 Speaker 1: the notion of a story as something with a lead 1133 01:02:51,880 --> 01:02:56,080 Speaker 1: and a nutgraph and uh, just all sort of garbage 1134 01:02:56,120 --> 01:02:59,880 Speaker 1: in the middle that runs eight words. That's gone, I mean, 1135 01:03:00,080 --> 01:03:02,120 Speaker 1: is not gone. It needs to be gone. It's going away, 1136 01:03:02,760 --> 01:03:05,840 Speaker 1: and we're trying to And again, the New York Times 1137 01:03:05,920 --> 01:03:07,720 Speaker 1: is not at all alone. As the journal is doing this, 1138 01:03:07,920 --> 01:03:10,080 Speaker 1: Bloomberg does is everyone is doing this, but trying to 1139 01:03:10,120 --> 01:03:13,400 Speaker 1: find creative ways to engage readers who are increasingly reading 1140 01:03:13,440 --> 01:03:16,920 Speaker 1: everything on their phone is hard and really disruptive, but 1141 01:03:16,960 --> 01:03:18,360 Speaker 1: it's actually a lot of fun. And you can be 1142 01:03:19,360 --> 01:03:21,760 Speaker 1: at the big media organizations that are investing a lot 1143 01:03:21,840 --> 01:03:25,280 Speaker 1: and hiring really talented people that are not just writers 1144 01:03:25,360 --> 01:03:29,440 Speaker 1: but are also graphics people or computer programmers or audio 1145 01:03:29,520 --> 01:03:33,160 Speaker 1: people or video people and doing clever, creative stuff. It's 1146 01:03:33,200 --> 01:03:36,480 Speaker 1: this whole new world that is not what I grew 1147 01:03:36,560 --> 01:03:40,000 Speaker 1: up in, And as long as you have tolerance for 1148 01:03:40,720 --> 01:03:44,400 Speaker 1: experimentation and occasional failure, it's a lot of fun. The 1149 01:03:44,640 --> 01:03:48,280 Speaker 1: so let's go down the list of these big interactive 1150 01:03:48,400 --> 01:03:52,200 Speaker 1: digital stories, The New York Times, the Wall Street Journal, Bloomberg, 1151 01:03:52,520 --> 01:03:57,960 Speaker 1: Washington Post. There have been some amazing things, and if 1152 01:03:58,000 --> 01:04:01,360 Speaker 1: that's the future of journalism, you have to be encouraged, right, Yeah, 1153 01:04:01,360 --> 01:04:03,440 Speaker 1: I think the future of journalism is really bright right now. 1154 01:04:03,480 --> 01:04:06,360 Speaker 1: I mean there's uh, look, what doesn't work is giving 1155 01:04:06,400 --> 01:04:10,560 Speaker 1: away commoditized content for free. That's like, that's not a 1156 01:04:10,640 --> 01:04:13,160 Speaker 1: business model. So but I think everyone gets that at 1157 01:04:13,240 --> 01:04:15,720 Speaker 1: this point. There's not There's plenty of commoditized stuff out 1158 01:04:15,760 --> 01:04:18,200 Speaker 1: there that will be free, but that's not a business 1159 01:04:18,280 --> 01:04:21,640 Speaker 1: model that that's not sustainable. Well, it doesn't generate revenue, right, No, 1160 01:04:21,840 --> 01:04:23,080 Speaker 1: I don't want I'm not going to pay for that, 1161 01:04:23,280 --> 01:04:25,720 Speaker 1: are you? Probably not? Like you need to pay for 1162 01:04:26,160 --> 01:04:29,240 Speaker 1: The New York Times, the Washington Post, the Wall Street Journal, 1163 01:04:29,320 --> 01:04:33,840 Speaker 1: the Financial Times, and a handful of magazines like The 1164 01:04:33,920 --> 01:04:37,360 Speaker 1: New York are in the Atlantic. But it's high quality, 1165 01:04:37,400 --> 01:04:40,760 Speaker 1: expensive content, and I think that's something. I mean, I 1166 01:04:40,840 --> 01:04:44,200 Speaker 1: think that's probably much more media than the average person 1167 01:04:44,280 --> 01:04:47,200 Speaker 1: is going to consume. But there's I think people do 1168 01:04:47,680 --> 01:04:51,000 Speaker 1: in this day and age. I think there's the notion 1169 01:04:51,040 --> 01:04:53,360 Speaker 1: of fake news has resonated a lot, and people are 1170 01:04:54,080 --> 01:04:55,920 Speaker 1: they want to know what's really going on in the world. 1171 01:04:55,960 --> 01:04:58,920 Speaker 1: These are like dangerous times, regardless of your ideology, and 1172 01:04:59,640 --> 01:05:02,200 Speaker 1: people are willing to pay. And it's not just news, 1173 01:05:02,280 --> 01:05:03,880 Speaker 1: by the way, and sports coverage is going through this 1174 01:05:03,960 --> 01:05:07,240 Speaker 1: renaissance where there's all these kind of localized businesses, localized 1175 01:05:07,240 --> 01:05:09,200 Speaker 1: business models that are popping up all over the country 1176 01:05:09,240 --> 01:05:11,760 Speaker 1: where people that's something people really care about. I care 1177 01:05:11,800 --> 01:05:14,320 Speaker 1: about that, and I subscribe to the Boston Globe for 1178 01:05:14,400 --> 01:05:16,960 Speaker 1: the sole reason that I want their sports coverage. And 1179 01:05:17,200 --> 01:05:19,160 Speaker 1: that's something that that's very valuable to me, and I 1180 01:05:19,240 --> 01:05:21,280 Speaker 1: think a lot of people. You just need to do 1181 01:05:21,400 --> 01:05:24,360 Speaker 1: things that are valuable and not commoditized and people will 1182 01:05:24,360 --> 01:05:26,960 Speaker 1: pay for tell us about a time you failed and 1183 01:05:27,120 --> 01:05:31,200 Speaker 1: what you learned from the experience. Man, I fail almost 1184 01:05:31,280 --> 01:05:33,920 Speaker 1: every day. It's something really yeah, don't. I mean, I 1185 01:05:34,000 --> 01:05:39,400 Speaker 1: make mistakes all the time. There's uh, seriously, I make 1186 01:05:39,560 --> 01:05:41,960 Speaker 1: decisions that turn out not to be very good. I 1187 01:05:43,440 --> 01:05:45,280 Speaker 1: I mean, I have two little kids also, so that 1188 01:05:45,480 --> 01:05:48,640 Speaker 1: is just a huge recipe for one failure after another 1189 01:05:48,680 --> 01:05:51,800 Speaker 1: as a new parent. That's uh, you know, I I 1190 01:05:52,360 --> 01:05:54,760 Speaker 1: do it all the time. I think the key is 1191 01:05:54,840 --> 01:05:58,280 Speaker 1: to just be able to yeah, own their mistake and 1192 01:05:58,320 --> 01:06:00,320 Speaker 1: move on. All right. That makes a lot of sense 1193 01:06:00,360 --> 01:06:01,960 Speaker 1: to me. What do you do for fun? What do 1194 01:06:02,000 --> 01:06:04,800 Speaker 1: you do out of the office to kick back, relax, 1195 01:06:05,520 --> 01:06:11,000 Speaker 1: stay physically or mentally sharp. I have two little kids, 1196 01:06:11,080 --> 01:06:15,240 Speaker 1: so I play with them, I take them outside, I 1197 01:06:15,920 --> 01:06:19,400 Speaker 1: ride a bike, I read a lot, listen to music, 1198 01:06:19,840 --> 01:06:23,680 Speaker 1: go on vacation. I'd love to travel. Um. Yeah, I 1199 01:06:23,760 --> 01:06:26,000 Speaker 1: just was down in Georgia, which we've never been to, 1200 01:06:26,200 --> 01:06:31,520 Speaker 1: and as a work of vacation, vacation we just stay 1201 01:06:31,560 --> 01:06:34,680 Speaker 1: in Georgia. We were in Savannah and then Jekyll Island 1202 01:06:35,360 --> 01:06:38,160 Speaker 1: of Lovely Places. Jacki Island is where the fed the 1203 01:06:38,240 --> 01:06:44,680 Speaker 1: idea from Jacki Island, very favorite famous book. Um, if 1204 01:06:44,880 --> 01:06:47,479 Speaker 1: a millennial came to you and said they were thinking 1205 01:06:47,520 --> 01:06:50,240 Speaker 1: about a career in journalism or writing, what sort of 1206 01:06:50,280 --> 01:06:53,919 Speaker 1: advice would you give them. Develop a skill that sets 1207 01:06:53,960 --> 01:06:57,560 Speaker 1: you apart, whether that is being really good at game 1208 01:06:57,600 --> 01:06:59,840 Speaker 1: people to talk to you, or being really good at writing, 1209 01:07:00,520 --> 01:07:05,040 Speaker 1: or learning some uh some element of computer programming, or 1210 01:07:05,200 --> 01:07:09,880 Speaker 1: developing expertise in audio or video stuff. Don't go the 1211 01:07:10,080 --> 01:07:12,720 Speaker 1: route of just aiming to be at the Wall Street 1212 01:07:12,760 --> 01:07:16,320 Speaker 1: Journal or the New York Times, go develop some specialization. 1213 01:07:17,000 --> 01:07:20,200 Speaker 1: And our final question, uh, tell us what you wish 1214 01:07:20,280 --> 01:07:23,760 Speaker 1: you knew about the world of banking and finance and 1215 01:07:23,960 --> 01:07:27,640 Speaker 1: libor fifteen years ago, I wish someone had told me 1216 01:07:27,920 --> 01:07:30,360 Speaker 1: that everyone is going to try and make it seem 1217 01:07:30,440 --> 01:07:32,880 Speaker 1: much more complicated than it really is. When you boiled 1218 01:07:32,920 --> 01:07:36,480 Speaker 1: down to the essence, it's pretty understandable for someone with 1219 01:07:36,600 --> 01:07:40,320 Speaker 1: a brain. That's as good an answers as I've ever heard. 1220 01:07:40,920 --> 01:07:43,560 Speaker 1: We have been speaking with David Enrich of The New 1221 01:07:43,640 --> 01:07:47,200 Speaker 1: York Times. If you enjoy this conversation, be sure and 1222 01:07:47,280 --> 01:07:49,480 Speaker 1: look up an inch or down an inch on Apple 1223 01:07:49,600 --> 01:07:51,920 Speaker 1: iTunes and you could see any of the other hundred 1224 01:07:51,960 --> 01:07:56,400 Speaker 1: and ninety three or so such conversations we've had previously. 1225 01:07:57,080 --> 01:08:01,440 Speaker 1: We love your comments, feedback and suggest Jen's right to 1226 01:08:01,680 --> 01:08:05,560 Speaker 1: us at m IB podcast at Bloomberg dot Net. I 1227 01:08:05,960 --> 01:08:08,800 Speaker 1: would be remiss if I did not thank my crack 1228 01:08:08,960 --> 01:08:12,760 Speaker 1: staff who helped put together the show every week. Medita 1229 01:08:12,840 --> 01:08:18,040 Speaker 1: Parwana is our producer slash audio engineer. Taylor Riggs is 1230 01:08:18,160 --> 01:08:23,040 Speaker 1: our booker slash producer. Michael bat Nick Bolts and Slate 1231 01:08:23,120 --> 01:08:27,599 Speaker 1: twenties not quite not quite so he had twelve good 1232 01:08:27,680 --> 01:08:30,360 Speaker 1: years on you um is our head of research who 1233 01:08:30,400 --> 01:08:33,679 Speaker 1: helps me assemble a lot of the details and questions 1234 01:08:33,760 --> 01:08:38,759 Speaker 1: and really makes these shows what they are. I'm Barry Ridholtz. 1235 01:08:38,920 --> 01:08:42,559 Speaker 1: You're listening to Masters in Business on Bloomberg Radio.