1 00:00:02,560 --> 00:00:06,840 Speaker 1: This is Bloomberg Business Week from Bloomberg Radio. I'm Jason Kelly. 2 00:00:06,840 --> 00:00:10,039 Speaker 1: Welcome to the Bloomberg Business Week Extra. It's our weekly podcast, 3 00:00:10,039 --> 00:00:13,200 Speaker 1: bringing you an in depth interview you won't hear anywhere else. 4 00:00:13,280 --> 00:00:14,600 Speaker 1: This week, I had the chance to sit down with 5 00:00:14,640 --> 00:00:18,320 Speaker 1: Hans Morris. He's the managing partner of NICA Partners. He's 6 00:00:18,320 --> 00:00:22,160 Speaker 1: had a wide ranging career across the world of finance. 7 00:00:22,200 --> 00:00:24,960 Speaker 1: Started on Wall Street. He was the president of Visa 8 00:00:25,280 --> 00:00:29,320 Speaker 1: hung out a shingle really when fintech wasn't even a thing. 9 00:00:29,720 --> 00:00:34,600 Speaker 1: Here's that conversation. So Hans Morris, managing partner of NICA Partners, 10 00:00:34,640 --> 00:00:38,400 Speaker 1: let's talk about the news. Your third fund completed, your 11 00:00:38,440 --> 00:00:43,800 Speaker 1: biggest so far. Why now and a pretty substantial sugga money. Yeah. Well, 12 00:00:43,840 --> 00:00:46,319 Speaker 1: I think to me it's a continuation of what we 13 00:00:46,440 --> 00:00:48,800 Speaker 1: started five years ago, and so we started smaller. It 14 00:00:48,960 --> 00:00:52,479 Speaker 1: was it's hardy to raise my fund. But we had 15 00:00:52,479 --> 00:00:55,640 Speaker 1: a very specific idea, which was we're just gonna focus 16 00:00:55,640 --> 00:00:59,680 Speaker 1: on fintech, and I think the space we occupy is 17 00:00:59,720 --> 00:01:04,360 Speaker 1: we're at helping entrepreneurs figure out the financial system, which 18 00:01:04,400 --> 00:01:06,600 Speaker 1: is quite daunted. You have a great idea, but how 19 00:01:06,680 --> 00:01:09,640 Speaker 1: much capital will take, what regulatory process? How do you 20 00:01:09,680 --> 00:01:14,080 Speaker 1: plug into that system? So we found that UM entrepreneurs 21 00:01:14,720 --> 00:01:17,600 Speaker 1: value that and and and I think that also other 22 00:01:18,400 --> 00:01:21,600 Speaker 1: other venture firms value it. So so many cases we 23 00:01:21,640 --> 00:01:23,839 Speaker 1: have some great firms bring us in help and because 24 00:01:23,840 --> 00:01:25,920 Speaker 1: I think we can, we can help a company be 25 00:01:26,000 --> 00:01:29,640 Speaker 1: more successful. And since then, obviously fintech has gone from 26 00:01:29,720 --> 00:01:34,280 Speaker 1: a tiny little portion of the venture community to a 27 00:01:34,280 --> 00:01:37,360 Speaker 1: big portion right now. And we can talk more about this, 28 00:01:37,400 --> 00:01:39,199 Speaker 1: but I think you know when I started, I actually 29 00:01:39,240 --> 00:01:42,039 Speaker 1: wrote a blog post in two thousand and fourteen, and 30 00:01:42,080 --> 00:01:45,640 Speaker 1: there were a few hundred fintech companies and if you 31 00:01:45,680 --> 00:01:48,080 Speaker 1: went back even ten years earlier, probably a dozen right 32 00:01:48,200 --> 00:01:50,880 Speaker 1: that got VC funding. And now we just did this 33 00:01:51,080 --> 00:01:53,200 Speaker 1: rough calculation because I don't know if you could really count, 34 00:01:53,240 --> 00:01:57,320 Speaker 1: we estimate about fifteen thousand fintech firms have gotten funding 35 00:01:57,320 --> 00:01:59,880 Speaker 1: around the world. What was the catalyst to give it 36 00:02:00,120 --> 00:02:04,400 Speaker 1: that sort of acceleration, Well, A big part of I 37 00:02:04,440 --> 00:02:08,120 Speaker 1: think is technology changed, and what what's important? What were 38 00:02:08,120 --> 00:02:11,480 Speaker 1: the big drivers? I think that the UM certainly the 39 00:02:11,520 --> 00:02:13,720 Speaker 1: fact that you could say, all right, your phone is 40 00:02:13,720 --> 00:02:15,880 Speaker 1: now the supercomputers in your pocket. You don't have to 41 00:02:15,880 --> 00:02:19,200 Speaker 1: have that inside the bank was a very big change 42 00:02:19,240 --> 00:02:23,440 Speaker 1: that took place. And similarly, the the advent of the 43 00:02:23,480 --> 00:02:28,080 Speaker 1: cloud in aws suddenly dramatically cut down the infrastructure requirements. 44 00:02:28,080 --> 00:02:31,040 Speaker 1: It wouldn't cost tens of millions of dollars of investment 45 00:02:31,120 --> 00:02:33,239 Speaker 1: to get to scale. You could you could do it 46 00:02:33,240 --> 00:02:36,400 Speaker 1: by the drink. I think the financial crisis have big 47 00:02:36,440 --> 00:02:40,320 Speaker 1: impact really all the incumbent companies, every bank and insurance company. 48 00:02:40,680 --> 00:02:43,440 Speaker 1: They had to cut out all their you know, ideal 49 00:02:43,520 --> 00:02:46,519 Speaker 1: labs and innovation groups. All that got eliminated, and all 50 00:02:46,560 --> 00:02:49,880 Speaker 1: the focus was on what was really a major global 51 00:02:50,040 --> 00:02:54,320 Speaker 1: reregulation cycle. So analogus what happened after the ninet thirties, 52 00:02:54,360 --> 00:02:56,680 Speaker 1: and this happens you know, in waves, I think, and 53 00:02:57,160 --> 00:02:59,880 Speaker 1: so they were just dealing with that. I meanwhile, you 54 00:02:59,880 --> 00:03:02,560 Speaker 1: had these big changes in technology and then a key 55 00:03:02,639 --> 00:03:05,520 Speaker 1: thing and I think this is something that isn't as 56 00:03:05,520 --> 00:03:08,160 Speaker 1: well understood, and I think it's still an open question. 57 00:03:08,200 --> 00:03:10,680 Speaker 1: So I'm not sure, I fell I can't predict the 58 00:03:10,680 --> 00:03:14,560 Speaker 1: answer on this, but I think the nature of trust 59 00:03:14,919 --> 00:03:18,320 Speaker 1: has changed because if you think about this issue, like 60 00:03:18,639 --> 00:03:22,040 Speaker 1: would you give some app on the internet your logging 61 00:03:22,120 --> 00:03:27,000 Speaker 1: credentials to your bank account? Right? No, No, tens of 62 00:03:27,080 --> 00:03:30,600 Speaker 1: millions of people do just that. And uh, and it 63 00:03:30,720 --> 00:03:33,000 Speaker 1: used to be that you would it would take tremendous 64 00:03:33,000 --> 00:03:37,080 Speaker 1: infrastructure to build that brand to be trusted. And I 65 00:03:37,120 --> 00:03:40,800 Speaker 1: think that the the expectation now that consumers and businesses 66 00:03:40,840 --> 00:03:43,760 Speaker 1: have is of a call, like a tech curation, like 67 00:03:43,800 --> 00:03:46,160 Speaker 1: an experience that you expect, and if you don't get 68 00:03:46,200 --> 00:03:49,080 Speaker 1: that and you're entering the same password or you're answering 69 00:03:49,080 --> 00:03:53,600 Speaker 1: stupid questions, there's too frustrating, it's redundant you that reduces 70 00:03:53,680 --> 00:03:56,800 Speaker 1: your trust. And yet that experience characterizes many of the 71 00:03:56,880 --> 00:03:59,000 Speaker 1: legacy companies and they're trying to change all that, but 72 00:03:59,040 --> 00:04:02,760 Speaker 1: it's hard. I meanwhile, copies with these fantastic experiences, you're 73 00:04:02,800 --> 00:04:06,400 Speaker 1: on boarded in thirty seconds and all things are very simple. 74 00:04:06,840 --> 00:04:10,480 Speaker 1: So that builds trust, which would have taken a decade 75 00:04:10,520 --> 00:04:13,680 Speaker 1: to do years ago. So how do you invest against that? 76 00:04:13,800 --> 00:04:17,839 Speaker 1: How do you understand this ecosystem that's growing so fast 77 00:04:18,000 --> 00:04:22,039 Speaker 1: as you demonstrated with those figures, How do you pick 78 00:04:22,120 --> 00:04:25,640 Speaker 1: the winners? How do you even find the right companies, 79 00:04:25,880 --> 00:04:28,760 Speaker 1: especially at a nascent stage, which is where you want 80 00:04:28,760 --> 00:04:33,560 Speaker 1: to get them? So like I wouldn't say we make 81 00:04:33,600 --> 00:04:35,479 Speaker 1: a lot of mistakes. I tell people that, you know, 82 00:04:35,520 --> 00:04:39,080 Speaker 1: we have the best anti portfolio, and anti portfolio is 83 00:04:39,200 --> 00:04:41,560 Speaker 1: the is the companies you didn't invest in. And I 84 00:04:41,600 --> 00:04:44,600 Speaker 1: think we have the best, the best in the business 85 00:04:44,600 --> 00:04:47,560 Speaker 1: because we have like Robin Hood and Carter and Platt 86 00:04:47,600 --> 00:04:52,599 Speaker 1: and Marcata and Chime and uh, lots of great companies 87 00:04:52,640 --> 00:04:54,279 Speaker 1: that we didn't invest in. So we miss it that 88 00:04:54,440 --> 00:04:57,280 Speaker 1: you saw and passed. We passed, yea, And sometimes we 89 00:04:57,400 --> 00:05:00,120 Speaker 1: passed because we thought what they were trying to do 90 00:05:00,360 --> 00:05:03,400 Speaker 1: we saw. I think I think there's actually a valid 91 00:05:03,640 --> 00:05:06,200 Speaker 1: issue that sometimes if you know too much about a subject, 92 00:05:06,960 --> 00:05:12,520 Speaker 1: you might see the impediments to success, whereas if you 93 00:05:12,520 --> 00:05:14,600 Speaker 1: don't know very much about it, you just make a 94 00:05:14,680 --> 00:05:17,160 Speaker 1: bet on the people and figure it. Then they'll figure 95 00:05:17,200 --> 00:05:19,880 Speaker 1: it out, which so uh and I think that did 96 00:05:19,880 --> 00:05:23,520 Speaker 1: in fact characterize our you know, mistake that we made. 97 00:05:23,560 --> 00:05:25,920 Speaker 1: And sometimes we also said it's too expensive, the value 98 00:05:25,960 --> 00:05:28,839 Speaker 1: should be fifty million instead of you know, seventy and 99 00:05:28,960 --> 00:05:31,800 Speaker 1: so we passed now the companies Tenion or some thing, 100 00:05:31,880 --> 00:05:34,479 Speaker 1: and so we definitely make a lot of mistakes. But 101 00:05:34,560 --> 00:05:39,599 Speaker 1: what we I think we start with often start with 102 00:05:39,640 --> 00:05:43,760 Speaker 1: a premise about what we're looking for. So there's lots 103 00:05:43,800 --> 00:05:46,120 Speaker 1: of problems in the financial system and and we can 104 00:05:46,200 --> 00:05:48,440 Speaker 1: pick you know, if we go back to two thousand fourteen, 105 00:05:48,480 --> 00:05:53,320 Speaker 1: for example, we were very focused on the what a 106 00:05:53,400 --> 00:05:55,800 Speaker 1: mess the mortgage business was. And one of the one 107 00:05:55,839 --> 00:05:59,240 Speaker 1: of the problems in mortgage technology is the systems are 108 00:05:59,279 --> 00:06:02,400 Speaker 1: all very old and they were not Also, they weren't 109 00:06:02,440 --> 00:06:05,359 Speaker 1: built by technologists. They were you know, people running mortgage 110 00:06:05,360 --> 00:06:09,000 Speaker 1: companies were often sometimes bankers, but often salespeople. You know, 111 00:06:09,040 --> 00:06:13,960 Speaker 1: countrywide form by a salesman, and so nothing now there 112 00:06:14,040 --> 00:06:17,479 Speaker 1: was no real tech innovation at all in the generation 113 00:06:17,720 --> 00:06:21,000 Speaker 1: in mortgage. But we also felt that the most success 114 00:06:21,000 --> 00:06:23,840 Speaker 1: there's a lot of uh, a lot of problems of 115 00:06:23,880 --> 00:06:26,440 Speaker 1: being a mortgage company is regulated, requires capital, and it 116 00:06:26,560 --> 00:06:30,279 Speaker 1: also um there's a lot of volatility and originations because 117 00:06:30,320 --> 00:06:31,960 Speaker 1: of pre payment. So we said, we want to invest 118 00:06:32,000 --> 00:06:34,680 Speaker 1: in a mortgage company, we won't invest in an enterprise 119 00:06:34,839 --> 00:06:38,520 Speaker 1: software company that's addressing this. So who's the top Silicon 120 00:06:38,640 --> 00:06:43,240 Speaker 1: Valley team focused on this, and we found a group 121 00:06:43,240 --> 00:06:46,320 Speaker 1: of entrepreneurs that had had been a palanteer that had 122 00:06:46,520 --> 00:06:49,000 Speaker 1: done the mortgage project, a palenteer that they did for 123 00:06:49,080 --> 00:06:51,840 Speaker 1: JP Morgan and Bank of America and they came away saying, Hey, 124 00:06:51,839 --> 00:06:53,880 Speaker 1: this place is this is a this is nuts. This 125 00:06:53,960 --> 00:06:58,040 Speaker 1: whole thing works. We could definitely build this better. And 126 00:06:58,279 --> 00:07:00,240 Speaker 1: that's Blend. So that's that's a company we have used 127 00:07:00,279 --> 00:07:02,039 Speaker 1: in So we were looking, we looked at all kinds 128 00:07:02,040 --> 00:07:03,760 Speaker 1: of coming and we said, this is this is the 129 00:07:03,800 --> 00:07:06,960 Speaker 1: team and UM that's become now you know, very big 130 00:07:07,000 --> 00:07:10,160 Speaker 1: company and they have UM they just raised money from 131 00:07:10,160 --> 00:07:13,320 Speaker 1: General and Acute close to billion dollars and they're really 132 00:07:13,400 --> 00:07:17,360 Speaker 1: becoming i think, not just the enterprise solution for mortgage origination, 133 00:07:17,400 --> 00:07:21,560 Speaker 1: for digital mortgage origination, but really for UM all kinds 134 00:07:21,600 --> 00:07:25,680 Speaker 1: of of of loan originations and count originations. Tell me 135 00:07:25,680 --> 00:07:29,440 Speaker 1: about the appetite from the limited partner perspective, from the pensions, 136 00:07:29,480 --> 00:07:33,640 Speaker 1: the endowments, the sovereign funds, the family offices growing. What 137 00:07:33,720 --> 00:07:36,560 Speaker 1: was your experience raising money this time versus the previous 138 00:07:36,600 --> 00:07:39,760 Speaker 1: two funds. You know, it's interesting on that point because 139 00:07:40,920 --> 00:07:43,720 Speaker 1: we didn't have and we still don't have. We've only 140 00:07:43,720 --> 00:07:46,680 Speaker 1: had one partial exit and we got another one coming. 141 00:07:46,760 --> 00:07:49,800 Speaker 1: But the but we don't have twenty year track records 142 00:07:49,800 --> 00:07:53,440 Speaker 1: showing how great we are in all these different environments. 143 00:07:53,480 --> 00:07:58,000 Speaker 1: So I'd say many of the endowments and pension funds 144 00:07:58,240 --> 00:08:01,040 Speaker 1: who looked at us, we got good feedback, but they 145 00:08:01,080 --> 00:08:05,080 Speaker 1: passed UH. And so really our core investors are in 146 00:08:05,160 --> 00:08:07,040 Speaker 1: many cases that we have some insurance companies who do 147 00:08:07,040 --> 00:08:10,320 Speaker 1: have some sovereign wealth funds UH and one sovereign wealth 148 00:08:10,360 --> 00:08:14,320 Speaker 1: fund UM. But many cases they're investing with us because 149 00:08:14,360 --> 00:08:16,440 Speaker 1: we have a good I think they like our business 150 00:08:16,480 --> 00:08:18,800 Speaker 1: model a lot like our like our position in the market, 151 00:08:19,440 --> 00:08:20,880 Speaker 1: and we have very good I think we have very 152 00:08:20,880 --> 00:08:25,200 Speaker 1: good portfolio construction, so you can be optimistic about future 153 00:08:25,200 --> 00:08:27,520 Speaker 1: exits and returns. But a lot of them invested with 154 00:08:27,560 --> 00:08:29,760 Speaker 1: us because they want the lens on the future of fintech. 155 00:08:30,160 --> 00:08:34,240 Speaker 1: And I think, what what is UH, maybe not unique AboutUs, 156 00:08:34,240 --> 00:08:36,720 Speaker 1: because there's something really good investors in this space too. 157 00:08:36,760 --> 00:08:40,400 Speaker 1: But we now get about twenty five inbound companies a week, 158 00:08:41,000 --> 00:08:44,000 Speaker 1: about half of which are very good references, you know, 159 00:08:44,040 --> 00:08:46,440 Speaker 1: from a from a founder we know, or from another 160 00:08:46,640 --> 00:08:51,679 Speaker 1: top tier VC investor, and so we have just tremendous 161 00:08:52,160 --> 00:08:55,520 Speaker 1: deal flow. And yeah, we turned we missed things, as 162 00:08:55,559 --> 00:08:58,640 Speaker 1: I said, but we often it's rare that we didn't 163 00:08:58,640 --> 00:09:00,920 Speaker 1: see it. And so the fact that we UH and 164 00:09:00,960 --> 00:09:04,400 Speaker 1: we we spent a lot of our effort in engaging 165 00:09:04,440 --> 00:09:07,080 Speaker 1: our LPs. We want them to know what we're looking 166 00:09:07,080 --> 00:09:08,800 Speaker 1: at while we're looking at it. So we actually have 167 00:09:08,800 --> 00:09:11,400 Speaker 1: a monthly call where we talk about that or something. 168 00:09:11,760 --> 00:09:13,640 Speaker 1: We have two meetings a year, not one. So a 169 00:09:13,679 --> 00:09:16,559 Speaker 1: lot of people I would say, perhaps I allively look 170 00:09:16,559 --> 00:09:18,280 Speaker 1: at the LP meeting is sort of a pain and 171 00:09:18,320 --> 00:09:20,080 Speaker 1: they don't look forward to it. We I actually really 172 00:09:20,160 --> 00:09:23,439 Speaker 1: like it. We have very good kind of repport engagement 173 00:09:23,480 --> 00:09:26,280 Speaker 1: with them trying to do that right. So let's go 174 00:09:26,360 --> 00:09:30,160 Speaker 1: back a little ways. Tell me about the initial idea, 175 00:09:30,240 --> 00:09:35,080 Speaker 1: because it's interesting to look at your background. You know, 176 00:09:35,360 --> 00:09:41,120 Speaker 1: you were a banker, you worked in a company, you 177 00:09:41,200 --> 00:09:43,559 Speaker 1: were the president of Visa, mean, you obviously saw this 178 00:09:44,000 --> 00:09:47,040 Speaker 1: technology and financial services from a very high level at 179 00:09:47,040 --> 00:09:49,679 Speaker 1: one of the most important companies in the world, and 180 00:09:49,720 --> 00:09:51,880 Speaker 1: then you sort of switched over to be more of 181 00:09:52,160 --> 00:09:56,680 Speaker 1: an investor. Walk me through that evolution. Well, when I started, 182 00:09:56,720 --> 00:09:58,960 Speaker 1: I was a banker and I started at the Old 183 00:09:59,080 --> 00:10:02,000 Speaker 1: Smith Barney actually, so then Sandy Wild bought that in 184 00:10:03,080 --> 00:10:05,160 Speaker 1: and there was a one of the things that really 185 00:10:05,160 --> 00:10:07,920 Speaker 1: a big impact of me. There was a emerging of 186 00:10:08,000 --> 00:10:09,920 Speaker 1: talent there are a lot of talents of people there already, 187 00:10:09,960 --> 00:10:13,160 Speaker 1: but but you had Sandy Wild. But Jamie Diamond was 188 00:10:13,200 --> 00:10:16,960 Speaker 1: the twenty nine year old CFO. Frank Bisignano worked in 189 00:10:17,000 --> 00:10:20,960 Speaker 1: operations at the beginning, didn't even run operations. Jay Fishman, 190 00:10:21,000 --> 00:10:25,040 Speaker 1: a fantastic person, became chairman of Travelers UM. Charlie Sharf, 191 00:10:25,520 --> 00:10:27,439 Speaker 1: who now runs bank in New York, was the head 192 00:10:27,440 --> 00:10:31,080 Speaker 1: of planning and analysis working for Jamie. So it was 193 00:10:31,120 --> 00:10:36,160 Speaker 1: a remarkable talent factory, and you learned how to manage. 194 00:10:36,720 --> 00:10:39,560 Speaker 1: And I was a banker, but I end up being 195 00:10:39,640 --> 00:10:41,959 Speaker 1: made head of the group, the Financial Institutions group, and 196 00:10:42,000 --> 00:10:45,520 Speaker 1: I was twenty nine. So that and and I we 197 00:10:45,640 --> 00:10:48,480 Speaker 1: ended up focusing It wasn't called vintech, but we focused 198 00:10:48,520 --> 00:10:51,959 Speaker 1: on this thesis which which still is my thesis, should 199 00:10:51,960 --> 00:10:55,920 Speaker 1: be her thesis, which is declining information. Most of the 200 00:10:55,960 --> 00:10:59,600 Speaker 1: profit pools and financial services are based upon a competitive 201 00:10:59,600 --> 00:11:02,640 Speaker 1: event of information. Right, So if you're trading bonds, or 202 00:11:02,679 --> 00:11:06,480 Speaker 1: you're investing money, or you're ensuring lives UH, or you're 203 00:11:06,600 --> 00:11:08,880 Speaker 1: making loans, if you don't have a competitive avantage, if 204 00:11:08,880 --> 00:11:12,240 Speaker 1: there's perfect information, there's no margin. So margin goes away, 205 00:11:12,280 --> 00:11:16,000 Speaker 1: and so then the nature of your relationship instead of 206 00:11:16,080 --> 00:11:18,480 Speaker 1: the profit pool coming from that competitive advantage. The competitive 207 00:11:18,480 --> 00:11:22,280 Speaker 1: advantage some cases is a byproduct of that information, so 208 00:11:22,320 --> 00:11:24,120 Speaker 1: the data coming out of it might be used in 209 00:11:24,160 --> 00:11:27,480 Speaker 1: another way. Google would be an example that like they 210 00:11:27,720 --> 00:11:30,320 Speaker 1: get all search data, they don't sell search data. They 211 00:11:30,320 --> 00:11:33,040 Speaker 1: sell advertising based on search data. So there's there's a 212 00:11:33,120 --> 00:11:36,559 Speaker 1: derivative of the data can be monetized. But also it 213 00:11:36,600 --> 00:11:40,040 Speaker 1: could be just in terms of organizing choices and and 214 00:11:40,280 --> 00:11:45,240 Speaker 1: statement ng or or um holding assets or managing decisions, 215 00:11:45,280 --> 00:11:49,520 Speaker 1: help people make good decisions. So that's how financial services changed. 216 00:11:49,679 --> 00:11:53,800 Speaker 1: We thought back in the late eighties, I had this thesis, Okay, 217 00:11:53,840 --> 00:11:56,640 Speaker 1: this is uh, I call it the Holy War. Information 218 00:11:56,679 --> 00:11:58,800 Speaker 1: is dramatically changing each of these things. We want to 219 00:11:58,840 --> 00:12:02,199 Speaker 1: back the winners. So we back Capital one and we 220 00:12:02,240 --> 00:12:04,760 Speaker 1: took Capital one public. We did all all kinds of 221 00:12:04,840 --> 00:12:06,880 Speaker 1: M and a work and investment bank were the first 222 00:12:06,920 --> 00:12:10,240 Speaker 1: data we saw. The one of my colleagues actually saw 223 00:12:10,320 --> 00:12:13,240 Speaker 1: this idea that the A T M networks could become 224 00:12:13,559 --> 00:12:16,520 Speaker 1: payment networks and debit networks, and so we pretty much 225 00:12:16,679 --> 00:12:21,440 Speaker 1: sold all those companies. We privatized NASDAC, we UM represent 226 00:12:21,520 --> 00:12:24,199 Speaker 1: MasterCard on a lot of transactions, did the IPO PayPal, 227 00:12:24,559 --> 00:12:28,120 Speaker 1: So that was always my interesting say. And then I 228 00:12:28,120 --> 00:12:30,080 Speaker 1: got into management jobs and so I didn't I wasn't 229 00:12:30,080 --> 00:12:33,000 Speaker 1: doing banks. So for about seven years I was in 230 00:12:33,080 --> 00:12:35,840 Speaker 1: this very complicated place because we we bought Solemn Brothers 231 00:12:35,880 --> 00:12:38,760 Speaker 1: and we merged with City, and then I became the 232 00:12:38,800 --> 00:12:41,240 Speaker 1: chief operating officer for the investment bank, which was like, 233 00:12:41,679 --> 00:12:46,120 Speaker 1: you know, some disaster happening every day and uh and 234 00:12:46,160 --> 00:12:48,679 Speaker 1: then uh, and then I became CFO for the institutional 235 00:12:48,720 --> 00:12:50,720 Speaker 1: part of the City. And then a big, big thing, 236 00:12:51,400 --> 00:12:55,119 Speaker 1: huge impact on me is I got uh, Frank Busignando 237 00:12:55,200 --> 00:12:58,480 Speaker 1: became the head of the transaction services business and so 238 00:12:58,520 --> 00:13:00,480 Speaker 1: they so teken off. So she had been running start 239 00:13:00,559 --> 00:13:03,880 Speaker 1: reporting to me, and I thought, I knew a lot 240 00:13:04,000 --> 00:13:07,400 Speaker 1: about this because I've been doing all financial services technology 241 00:13:07,520 --> 00:13:10,800 Speaker 1: for two decades. And when I realized I had no 242 00:13:10,880 --> 00:13:14,679 Speaker 1: idea how complicated was. As someone says, like, okay, converted 243 00:13:14,840 --> 00:13:18,160 Speaker 1: to a conversion of this system to some other system, 244 00:13:18,240 --> 00:13:22,120 Speaker 1: how does that actually work? I didn't know of the 245 00:13:22,200 --> 00:13:25,080 Speaker 1: kind of thousands of systems, figure out what are going 246 00:13:25,120 --> 00:13:27,440 Speaker 1: to be the winning systems in in the global in 247 00:13:27,480 --> 00:13:31,400 Speaker 1: the globe bank and created a decision method to assess 248 00:13:31,480 --> 00:13:35,840 Speaker 1: and and and make choices, and so that definitely affected me. 249 00:13:35,880 --> 00:13:38,240 Speaker 1: So I think that when I meet with companies now 250 00:13:38,559 --> 00:13:41,880 Speaker 1: that's sitting there like, how does it actually work? And 251 00:13:41,920 --> 00:13:44,680 Speaker 1: why is this so hard? And I think I have 252 00:13:44,720 --> 00:13:47,040 Speaker 1: a very deep appreciation for that. For five years, I 253 00:13:47,080 --> 00:13:49,280 Speaker 1: was doing that and then I got the call when 254 00:13:49,360 --> 00:13:53,560 Speaker 1: Visa was privatizing, and and you know, I really remember 255 00:13:53,679 --> 00:13:55,760 Speaker 1: telling my wife about it because she said, oh, moved 256 00:13:55,800 --> 00:13:58,600 Speaker 1: to California and leave Wall Street and everything, and I said, 257 00:13:58,600 --> 00:14:01,640 Speaker 1: you know, I mean I didn't predict. I left Wall 258 00:14:01,640 --> 00:14:04,120 Speaker 1: Street in June two thousand seven, So that might be 259 00:14:04,160 --> 00:14:08,160 Speaker 1: my epitaph will be predicted the final I did not 260 00:14:08,240 --> 00:14:11,480 Speaker 1: predict the financial crisis, but I did predict. I said, 261 00:14:11,920 --> 00:14:14,840 Speaker 1: you know what, this is the market leader almost two 262 00:14:14,880 --> 00:14:19,280 Speaker 1: thirds market share in electronic payments globally. And I said, 263 00:14:20,080 --> 00:14:24,040 Speaker 1: I said, that's just a winner. And I just I 264 00:14:24,080 --> 00:14:26,280 Speaker 1: got you know, I think we should do it. And 265 00:14:26,280 --> 00:14:28,800 Speaker 1: it was really a great decision for me because even 266 00:14:28,840 --> 00:14:30,920 Speaker 1: though I didn't get the CEO job, but I I 267 00:14:31,000 --> 00:14:34,040 Speaker 1: learned a lot, uh and I um, you know, I'm 268 00:14:34,040 --> 00:14:35,880 Speaker 1: proud of what what I did there and what the 269 00:14:35,880 --> 00:14:40,520 Speaker 1: company did and It also plugged me into San Francisco, 270 00:14:40,560 --> 00:14:42,760 Speaker 1: which I really didn't get. And when Nike, as you 271 00:14:42,920 --> 00:14:46,840 Speaker 1: point out before we're talking NICAS stands for New York California. 272 00:14:46,840 --> 00:14:50,560 Speaker 1: And the idea when I formed it was that Wall 273 00:14:50,560 --> 00:14:53,000 Speaker 1: Street didn't really understand Silicon Valley and Silicon Valley didn't 274 00:14:53,040 --> 00:14:55,800 Speaker 1: understand financial system. So we could bridge these two things 275 00:14:56,040 --> 00:14:58,800 Speaker 1: that would be valuable. It'd be helpful to the entrepreneurs, 276 00:14:58,880 --> 00:15:01,320 Speaker 1: but it also be helpful to O investors. And so 277 00:15:01,400 --> 00:15:03,960 Speaker 1: that came from living there. I lived there, I wouldn't 278 00:15:03,920 --> 00:15:06,360 Speaker 1: have known that in the same way. So then also 279 00:15:06,440 --> 00:15:09,000 Speaker 1: after southa visa UM, I didn't get the CEO job, 280 00:15:09,040 --> 00:15:13,520 Speaker 1: and I went to General Atlantic and and I learned 281 00:15:13,520 --> 00:15:15,680 Speaker 1: a lot there too. I must say I thought I 282 00:15:15,720 --> 00:15:18,760 Speaker 1: knew a lot about investing and UM and they have 283 00:15:18,960 --> 00:15:22,360 Speaker 1: a you know, a remarkable culture and incredible track record, 284 00:15:22,400 --> 00:15:26,560 Speaker 1: and uh so I learned a lot about investing and 285 00:15:27,120 --> 00:15:29,760 Speaker 1: and the issue though for me, was that they tend 286 00:15:29,800 --> 00:15:32,720 Speaker 1: to invest later in and you know, they were at 287 00:15:32,720 --> 00:15:34,920 Speaker 1: that point looking to invest let's say a hundred or 288 00:15:34,920 --> 00:15:37,080 Speaker 1: two hundred million dollars into a company, or four hundred 289 00:15:37,120 --> 00:15:40,320 Speaker 1: million dollars into a company, and I felt that given 290 00:15:40,360 --> 00:15:44,600 Speaker 1: these changes that were quite dramatic and evident in financial services, 291 00:15:44,680 --> 00:15:47,880 Speaker 1: that we needed to to invest earlier, and that wasn't 292 00:15:47,960 --> 00:15:51,600 Speaker 1: their model. So um So, anyway, that's when I said, well, 293 00:15:51,640 --> 00:15:53,880 Speaker 1: I'm gonna go start my own right company and give 294 00:15:53,880 --> 00:15:55,560 Speaker 1: it a shot. And so how do you put together 295 00:15:55,600 --> 00:15:58,000 Speaker 1: a team for something like that? What are you looking 296 00:15:58,120 --> 00:16:00,960 Speaker 1: for and where do you find the oaks that ultimately 297 00:16:01,080 --> 00:16:04,760 Speaker 1: formed the core Because, as you say, you grew up 298 00:16:04,800 --> 00:16:07,720 Speaker 1: in some very distinct cultures in a lot of ways. 299 00:16:07,720 --> 00:16:09,760 Speaker 1: I mean the name checking you did about you know, 300 00:16:10,200 --> 00:16:12,480 Speaker 1: working at Smith Barney back in the day. I mean 301 00:16:12,480 --> 00:16:16,840 Speaker 1: you're talking about some of the leaders of modern finance 302 00:16:17,400 --> 00:16:19,360 Speaker 1: at this point. So what do you take from that? 303 00:16:19,400 --> 00:16:21,920 Speaker 1: What do you take from Visa and especially this New 304 00:16:22,000 --> 00:16:26,520 Speaker 1: York California thing to blend all of those ethos? Well, 305 00:16:26,560 --> 00:16:31,240 Speaker 1: you know, we try to make it different from the beginning. 306 00:16:31,680 --> 00:16:33,640 Speaker 1: And actually I'll send it to if you want. I 307 00:16:33,640 --> 00:16:35,320 Speaker 1: have I have a one page I put together out 308 00:16:35,360 --> 00:16:40,000 Speaker 1: what in December November two thousand thirteen. What are we 309 00:16:40,040 --> 00:16:42,560 Speaker 1: trying to do? Yeah? And actually reads pretty well. I start, 310 00:16:42,560 --> 00:16:44,560 Speaker 1: we do a team offside every quarder. I always start 311 00:16:44,560 --> 00:16:49,240 Speaker 1: with us and because uh, one thing we said is, uh, 312 00:16:49,280 --> 00:16:52,800 Speaker 1: what do the companies need? And what I felt is 313 00:16:52,880 --> 00:16:57,560 Speaker 1: if we assemble a group of very respected investors and partners, 314 00:16:58,120 --> 00:17:01,400 Speaker 1: that could be a unique model that could really create values. 315 00:17:01,440 --> 00:17:03,680 Speaker 1: So we started this idea which we now call our 316 00:17:03,840 --> 00:17:07,040 Speaker 1: l P A s our Limited Partner Advisors. And I 317 00:17:07,040 --> 00:17:08,959 Speaker 1: don't think anyone else has ever done this before. So 318 00:17:09,000 --> 00:17:11,480 Speaker 1: that was our source of capital where individuals who were experts. 319 00:17:11,720 --> 00:17:15,879 Speaker 1: So in fact, we we combined, we brought together that 320 00:17:15,920 --> 00:17:19,879 Speaker 1: expertise and and uh and made a network to communicate 321 00:17:19,920 --> 00:17:23,560 Speaker 1: that expertise to companies. But that was our capital base 322 00:17:23,640 --> 00:17:27,840 Speaker 1: where all these people and some really amazing people. Well, 323 00:17:27,880 --> 00:17:31,440 Speaker 1: and on that point, what's so interesting is that historically, 324 00:17:32,400 --> 00:17:36,000 Speaker 1: as much as private equity firms talk about, you know, 325 00:17:36,000 --> 00:17:38,720 Speaker 1: broadly defined talk about you know, these are our partners 326 00:17:38,720 --> 00:17:42,879 Speaker 1: and things like that, they are at some to some extent, 327 00:17:43,200 --> 00:17:47,600 Speaker 1: at arm's length. Right, there's not necessarily the intimate relationship 328 00:17:47,720 --> 00:17:50,280 Speaker 1: that that you're describing or what it sounds likescribing. Well, 329 00:17:50,280 --> 00:17:54,520 Speaker 1: actually this was pretty radical idea. Our first investment committee 330 00:17:55,000 --> 00:17:58,320 Speaker 1: was formed with me plus these five other people that 331 00:17:58,359 --> 00:18:00,880 Speaker 1: we called our investment partners, but they weren't full time. 332 00:18:00,880 --> 00:18:03,879 Speaker 1: They didn't work in the GP. But the group was 333 00:18:04,960 --> 00:18:07,560 Speaker 1: Brian Finn, who had been the president Credit Sweet, Charlie 334 00:18:07,560 --> 00:18:10,480 Speaker 1: Songhurst who have been head of strategy at Microsoft and 335 00:18:10,680 --> 00:18:14,199 Speaker 1: very plugged in Silicon Valley, Osama Bader who built the 336 00:18:14,200 --> 00:18:17,760 Speaker 1: Google wallet, and I've been at PayPal and then started 337 00:18:17,800 --> 00:18:21,360 Speaker 1: a company called Point, Max Levchin, who co founded PayPal, 338 00:18:21,680 --> 00:18:25,160 Speaker 1: founded a company called a Firm Um and then Tom Niglas, 339 00:18:25,240 --> 00:18:28,399 Speaker 1: who who I knew from Solomon Brothers where he had 340 00:18:28,400 --> 00:18:29,800 Speaker 1: been the c I. Oh, but then he had been 341 00:18:29,840 --> 00:18:34,600 Speaker 1: the CIO at Citadel for eighteen years. So it was intentionally. 342 00:18:34,680 --> 00:18:36,520 Speaker 1: If you think about that split, there's a bunch of 343 00:18:37,000 --> 00:18:38,879 Speaker 1: it's kind of New York in California. That was the 344 00:18:38,920 --> 00:18:43,000 Speaker 1: idea actually and UM and then we added we added 345 00:18:43,000 --> 00:18:45,800 Speaker 1: we now have I think fifty five l p a 346 00:18:46,000 --> 00:18:49,960 Speaker 1: s and it includes every year. You could take that group, 347 00:18:50,000 --> 00:18:55,080 Speaker 1: but I don't know, uh, Larry Summers or or or 348 00:18:55,280 --> 00:18:58,159 Speaker 1: two star vall around the risk practice at McKenzie or 349 00:18:58,480 --> 00:19:01,679 Speaker 1: Judd Lynnville Rank Global Cards at a City Group or 350 00:19:01,680 --> 00:19:06,920 Speaker 1: to Myopolis ran CFTC and CFTC. So it's it's an 351 00:19:07,040 --> 00:19:10,240 Speaker 1: amazing group. And as I say, someone is a phone 352 00:19:10,240 --> 00:19:13,879 Speaker 1: call away from the truth, right and uh and and 353 00:19:14,480 --> 00:19:17,919 Speaker 1: you know, so you can bring up a complex obscure 354 00:19:18,000 --> 00:19:21,680 Speaker 1: topic like how would regulators react to this, or how 355 00:19:21,680 --> 00:19:25,000 Speaker 1: would or what should a company do in this circumstance, 356 00:19:25,080 --> 00:19:30,960 Speaker 1: or what exactly is the problem in um OTC clearing 357 00:19:31,119 --> 00:19:34,280 Speaker 1: or you know, equity derivatives, like someone will be able 358 00:19:34,320 --> 00:19:38,320 Speaker 1: to analyze that problem with precision. And then I think 359 00:19:38,359 --> 00:19:41,040 Speaker 1: one of the most important things is I call precision introductions. 360 00:19:41,040 --> 00:19:42,760 Speaker 1: So it's one thing to do, like an email introke. 361 00:19:43,119 --> 00:19:45,480 Speaker 1: You could say, this is the person that owns the 362 00:19:45,920 --> 00:19:49,119 Speaker 1: decision that's going to be made, right, that's very valuable 363 00:19:49,160 --> 00:19:51,199 Speaker 1: to a company. And I could say my year, all right, 364 00:19:51,359 --> 00:19:54,439 Speaker 1: before I let you go, what's the one biggest idea 365 00:19:54,520 --> 00:19:57,680 Speaker 1: you've heard about fintech that sort of knocked you back 366 00:19:58,240 --> 00:20:04,359 Speaker 1: in terms of a theory that is ultimately investable? The 367 00:20:04,400 --> 00:20:09,840 Speaker 1: one idea that knocks me back, there's you know, I mean, 368 00:20:11,040 --> 00:20:14,840 Speaker 1: it's it's rare that you see a truly unique idea 369 00:20:14,840 --> 00:20:16,760 Speaker 1: if you're twenty five a week. Many of them are 370 00:20:16,840 --> 00:20:21,320 Speaker 1: variations on things sing before I think propel that's a 371 00:20:21,359 --> 00:20:23,880 Speaker 1: really that was a really unique idea. And when um 372 00:20:23,920 --> 00:20:28,000 Speaker 1: the entrepreneur came out of Facebook, Jimmy Chen, and he 373 00:20:28,000 --> 00:20:30,120 Speaker 1: he wanted to create an app to help people who 374 00:20:30,119 --> 00:20:34,200 Speaker 1: are on food stamps manage their lives better. So basically 375 00:20:34,240 --> 00:20:36,639 Speaker 1: became an app that helps you sort out what your 376 00:20:36,680 --> 00:20:41,240 Speaker 1: benefits are and it becomes a regular, almost daily form 377 00:20:41,240 --> 00:20:44,359 Speaker 1: of interaction for about three million people. And then he 378 00:20:44,400 --> 00:20:48,200 Speaker 1: wants to say, we're gonna that group navigate the financial system. 379 00:20:48,280 --> 00:20:51,200 Speaker 1: So they're definitely people who have, you know, some setback 380 00:20:51,200 --> 00:20:53,400 Speaker 1: in life. But how can you can we give them 381 00:20:53,480 --> 00:20:55,640 Speaker 1: a debit card that is in their interest and then 382 00:20:55,680 --> 00:20:57,480 Speaker 1: what are the other things that we could offer in 383 00:20:57,560 --> 00:21:01,640 Speaker 1: terms of financial services that are valuable them. Sounds really 384 00:21:02,600 --> 00:21:05,880 Speaker 1: great idea of CEO, and uh, we love working with them. 385 00:21:05,920 --> 00:21:09,520 Speaker 1: That was Hans Morris, managing partner of Nika Partners, a 386 00:21:09,600 --> 00:21:13,919 Speaker 1: longtime investor and banker in the world of money. You've 387 00:21:13,960 --> 00:21:16,199 Speaker 1: been listening to Bloomberg Business Week Extra, be sure to 388 00:21:16,240 --> 00:21:19,160 Speaker 1: tune into Bloomberg Business Week Radio. That's live Monday through 389 00:21:19,200 --> 00:21:21,879 Speaker 1: Friday at two pm Wall Street Time. I'm Jason Kelly. 390 00:21:22,119 --> 00:21:23,040 Speaker 1: This is Bloomberg