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Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.

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Speaker 2: Hello and welcome to another episode of the Odd Lots podcast.

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Speaker 3: I'm Jill Wisenthal, and I'm Tracy Alloway.

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Speaker 2: Racy, how good at Excel?

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Speaker 4: Are you.

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Speaker 3: Not good? Compared to a lot of people who listen

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Speaker 3: to this podcast? I would imagine, I mean, I can

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Speaker 3: do some basic stuff like auto some and you know

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Speaker 3: so some.

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Speaker 5: No, it's not.

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Speaker 3: That's like literally clicking a button. I can write like

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Speaker 3: a couple formulas in the little command prompt. But I

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Speaker 3: think everyone can.

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Speaker 2: I could write some really rudimentary formasts, but I never

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Speaker 2: really I got to the degree that some people are.

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Speaker 2: But the good news is I saw that I have

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Speaker 2: to learn it. We don't have to learn I saw

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Speaker 2: that Claude code they have or Claude they have some

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Speaker 2: extension where you just talk to Excel and and you say, like,

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Speaker 2: you know, build this kind of formula and make these

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Speaker 2: changes and import this. I haven't played around with it,

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Speaker 2: so not one hundred percent sure would work. And to

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Speaker 2: be honest, because by limited Excel skills, I wouldn't even

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Speaker 2: be able to verify if it worked in the first place.

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Speaker 2: But my sense is, you know that maybe that seems

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Speaker 2: like a maybe that's changing.

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Speaker 3: I would guess that it works pretty well. And imagine

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Speaker 3: if you're someone who's been working probably in finance for

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Speaker 3: like twenty years, and you became known as not and

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Speaker 3: I don't want to say Excel spreadsheet monkey, Excel spreadsheet gorilla,

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Speaker 3: like you know, someone really admired for their Excel skills

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Speaker 3: and suddenly you've been disrupted totally.

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Speaker 2: Wellst Sometimes you see these things online where like they

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Speaker 2: show this stuff like oh, the investment bank investment analysts

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Speaker 2: or junior analysts just got put out of a job,

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Speaker 2: and like there's a go I'm pretty sure there's more

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Speaker 2: to the job. So I do know that, like building

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Speaker 2: models and so forth, there's an important thing in finance

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Speaker 2: and Wall Street in various capacities. I'm pretty sure that's

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Speaker 2: not the entire job. I'm pretty sure automating Excel was

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Speaker 2: only part of it. But nonetheless, technical skills are technical skills,

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Speaker 2: and if that changes, who knows, maybe the job could change.

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Speaker 1: Well.

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Speaker 3: The question I've always had about Wall Street is how

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Speaker 3: much of it is driven by your own personality and

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Speaker 3: sort of client facing skills versus I am a brilliant

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Speaker 3: analysis who is not only able to come up with

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Speaker 3: amazing ideas for mergers and acquisitions, sort of you know,

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Speaker 3: working girls style, where like Melanie Griffith is in an

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Speaker 3: elevator and is like, I know your company needs to

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Speaker 3: start with whatever, versus like I'm just really good at

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Speaker 3: hopnobbing with executives.

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Speaker 2: It's probably a mix, right, That would be my guess

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Speaker 2: that there's someone is really good at this company that

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Speaker 2: is parking lot, so this the city could buy another

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Speaker 2: parking lot company and so forth, and then another person

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Speaker 2: who's really good at staying out and taking the class

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Speaker 2: to a nice dinner. I don't think you could really

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Speaker 2: or I don't really want to have a conversation, but

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Speaker 2: the degree to which AI is going to disrupt all

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Speaker 2: of these white jobs until I have a better handle

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Speaker 2: what the white color jobs are in the first place,

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Speaker 2: I feel like we are.

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Speaker 3: How important are excel skills actually in this business?

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Speaker 2: What is the sort of distribution of skills that it

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Speaker 2: takes to thrive in some of these capacities. Anyway, very

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Speaker 2: excited to say, we really do have the perfect guest

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Speaker 2: to talk about some of this. Someone we talked to

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Speaker 2: last year and that was about sort of the history

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Speaker 2: of investment banking over the last several decades and the

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Speaker 2: sort of connection between global capitalism investment banking. We wanted

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Speaker 2: to have them back on the show because as an

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Speaker 2: investment banking veteran, someone who can maybe talk about the

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Speaker 2: inside and how people work and how the culture change

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Speaker 2: and how technology changes. So we're going to be speaking

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Speaker 2: with return guests. Scott Baki is the former longtime CEO

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Speaker 2: of the investment bank Greenhill, the author of the recent

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Speaker 2: book Surviving Wall Street and it comes back on odd Lot.

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Speaker 2: So Scott, thank you so much for coming back with us.

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Speaker 2: It's great to be back.

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Speaker 4: Thank you.

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Speaker 2: What are you for listeners who, in case they didn't

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Speaker 2: listen to the previous one, which they should. What did

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Speaker 2: your career span on Wall Street? When did you first

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Speaker 2: get into it? And you know how well give us

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Speaker 2: the sort of the thirty second Scott book career bio. Well,

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Speaker 2: I feel like.

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Speaker 4: I started at the very beginning of really the explosion

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Speaker 4: of the investment banking business. You know, as I said

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Speaker 4: in my book, when I graduated from Wharton, I did

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Speaker 4: not know what an investment banker was. I knew exactly

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Speaker 4: one person from our entire class who got a job

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Speaker 4: on Wall Street. So it was a very small place.

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Speaker 4: Back then, M and A was very rare. Here were

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Speaker 4: we talking about nineteen eighty one. Okay, you know, it's

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Speaker 4: your interest rates peaked. It's the you know, stock market

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Speaker 4: was had been flat for more than a decade. You know,

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Speaker 4: private equity is a phrase didn't even exist. Hedge fund

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Speaker 4: didn't exist. I mean, it was a very very different role.

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Speaker 4: By the way, it wasn't even legal to buy back

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Speaker 4: your own stock back then. That that happened a year later.

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Speaker 4: It was viewed as market manipulation to do that. So

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Speaker 4: the whole thing of sort of playing with balance sheets,

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Speaker 4: putting companies together and so on. I mean, there had

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Speaker 4: been a bit of that in the nineteen sixties, mostly

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Speaker 4: around building conglomerates, which I think in part was because

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Speaker 4: they couldn't buy back stock. Because if you're generating cash

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Speaker 4: to do with it, you could be it t a

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Speaker 4: big industrial company, and so I think I'll buy the Hartford,

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Speaker 4: a big insurance company. You know, today people would think

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Speaker 4: that's a crazy idea, but that was kind of the

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Speaker 4: predecessor to what became, you know, the M and A

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Speaker 4: and transaction business around you know, maximizing shareholder value. That

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Speaker 4: that really began, I would say, right at the beginning

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Speaker 4: of my career.

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Speaker 3: Perfect, this is already a fascinating conversation, I have to say,

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Speaker 3: so I imagine this dynamic would have changed throughout your career.

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Speaker 3: But how much of the investment banking business is the

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Speaker 3: bankers approaching clients and saying we have an idea for you,

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Speaker 3: versus the clients coming to the bankers and saying we

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Speaker 3: have a problem, such as we have all this cash

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Speaker 3: and we can't you know, buy back our shares or

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Speaker 3: we want to do something with it to reduce our

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Speaker 3: cost of capital or whatever.

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Speaker 4: You know, that changed an awful lot of our time

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Speaker 4: because it's the beginning. There were lots of companies and

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Speaker 4: very few investment bankers, and so they didn't get a

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Speaker 4: visit all that often, and so when they did, the

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Speaker 4: bank would try to bring, you know, ideas and maybe

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Speaker 4: they hadn't heard before. You know, Now there's thousands and

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Speaker 4: thousands of investment bankers, many many different firms of many

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Speaker 4: different types, and they're all maintaining relationships. So it really

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Speaker 4: turns into more of a dialogue where you don't you

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Speaker 4: don't just you know, you never met the client before

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Speaker 4: your show up say hey, I think you should buy

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Speaker 4: this company down the street and wow, that's a great idea.

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Speaker 4: I hadn't heard that before, and they do it. It's

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Speaker 4: more like you have an ongoing dialogue with a client.

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Speaker 4: You figure out what they want to do, what they're

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Speaker 4: you know, kind of what their appetite to their board is,

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Speaker 4: what their balance sheets like, how their business is going,

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Speaker 4: how they feel about their share price, you know, what

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Speaker 4: what they think is kind of the next big thing

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Speaker 4: for them, And over time you come to an idea.

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Speaker 4: Almost mutually.

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Speaker 2: I would say, what were you good at in the

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Speaker 2: early eighties or the people that you went to work

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Speaker 2: with very early on, what would you say you had

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Speaker 2: in common? Why? Why did uh you know? Why was

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Speaker 2: it a fit for you?

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Speaker 4: For me, I was probably a little bit different since

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Speaker 4: it came from a legal background than some. I mean,

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Speaker 4: there were some people who were you know, the ex

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Speaker 4: and by the way, Excel wasn't even around then. It

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Speaker 4: was Lotus one, two three. Who are the you know

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Speaker 4: Excel jockeys who built these you know, enormous models and

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Speaker 4: so one and I did a bit of that myself.

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Speaker 4: I think my strength was more in sort of structuring, conceptualizing, negotiating,

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Speaker 4: you know, marketing, talking to CEOs and boards. It was

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Speaker 4: more of that kind of uh in many ways, the

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Speaker 4: qualitative skills, the math. You can pick up what you

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Speaker 4: need fairly quickly. And you know, I sometimes tell, you know,

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Speaker 4: people of like my my son's generation, he's he's thirty

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Speaker 4: years old. I tell his people at his pure level,

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Speaker 4: I see, you know, the great rubicon a cross in

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Speaker 4: the world of you know, Wall Street and related fields

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Speaker 4: is when you get to the point where there's somebody

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Speaker 4: smart working for you. You're you're You're no longer yeah,

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Speaker 4: you're You're no longer the one, you know, training some

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Speaker 4: complete newbie. You're no longer the one doing it all yourself.

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Speaker 4: You're the one who's doing a bit of conceptualizing and

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Speaker 4: giving into a very smart person who's going to stay

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Speaker 4: late at night and build you a beautiful model.

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Speaker 3: I want to ask you what it was actually like

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Speaker 3: working a sort of junior banker in the eighties. But

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Speaker 3: before I do, what's with all the people with legal

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Speaker 3: degrees going into banking in the nineteen eighties, Because you

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Speaker 3: weren't the only one. I think there were a few

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Speaker 3: other famous compatriots at the time. Lloyd blank Find for instance,

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Speaker 3: stands out. But what was it about having done a

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Speaker 3: law degree that translated into banking?

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Speaker 4: Back then, there were many who made the move, And

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Speaker 4: as a matter of fact, while I was interviewing the

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Speaker 4: New York Times, Sunday magazine had a cover story called

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Speaker 4: lawyers Becoming Bankers. I mean, it really was a big phenomenon,

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Speaker 4: and I think literally the reason was the business exploded suddenly.

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Speaker 4: There's just massive amounts of transaction activity. There aren't that

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Speaker 4: many investment bankers. You're not just going to hire more

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Speaker 4: people who are twenty two years old and train them.

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Speaker 4: You need someone who's twenty six or twenty eight or

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Speaker 4: thirty years old who actually has kind of been around

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Speaker 4: the business. They may have some skills to learn, but

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Speaker 4: they bring other skills to the table, and so they

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Speaker 4: brought into bank the lawyers, including myself, is kind of

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Speaker 4: a way of sort of ramping up the scale of

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Speaker 4: the team rather than just saying we're going to just

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Speaker 4: hire more twenty two year olds and train them. But

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Speaker 4: you didn't have a time for that, you know, there's

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Speaker 4: so much such a growth in transaction activity. That's why

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Speaker 4: a lot of lawyers made that move.

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Speaker 2: Well you mentioned just now you're like, okay, it's nice

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Speaker 2: to be in the position where you can conceptualize something.

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Speaker 2: And then the really you know, the smart wiz kids

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Speaker 2: stays up all night building the model? Are they staying

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Speaker 2: up all night?

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Speaker 1: Like?

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Speaker 2: This is the This is sort of one of the

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Speaker 2: big questions that people have is like, what is it

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Speaker 2: about the business that demands these sort of in some

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Speaker 2: case extreme hours laid into the night. Why can't they

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Speaker 2: just do it during the day? I clock out at five?

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Speaker 4: Very good question, you know, I think one in this

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Speaker 4: this kind of relates to, you know, the future of

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Speaker 4: AI and efficiency and investment banking and so on as well.

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Speaker 4: I think maybe the dirty little secret of the industry

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Speaker 4: in terms of how the sausage is actually made, is

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Speaker 4: that the actual building of the model, the creation of

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Speaker 4: the math that says why it makes sense or doesn't

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Speaker 4: make sense to buy something that certain share price, that

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Speaker 4: that takes a limited amount of time, the fiddling with

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Speaker 4: the PowerPoint pages that expressed that information so it makes

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Speaker 4: just the right points and just the right way and

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Speaker 4: just the right color seam, and you know, just the

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Speaker 4: right things in italics and other things in bold and

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Speaker 4: things like that. You know, bankers tend to be perfectionists,

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Speaker 4: and so they will fiddle with that for a very

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Speaker 4: long time and a lot of times. I mean, if

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Speaker 4: you ask people who are in the early part of

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Speaker 4: their careers, like, what are you really doing when you're

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Speaker 4: there late at night, it's very often it's fine tuning

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Speaker 4: math that was done long ago.

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Speaker 3: There's also a schedule misalignment, I guess, because you get

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Speaker 3: the feedback from your boss at like five or six pm,

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Speaker 3: right and like at the end of their day, and

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Speaker 3: then you have to stay up really late to make

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Speaker 3: all the changes and get them on their desk in

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Speaker 3: the morning. But okay, perfectionism long hours. Was that the

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Speaker 3: case when you were initially entering the industry in the eighties,

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Speaker 3: very much so, But not with PowerPoint, with something else?

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Speaker 4: Well, that's true. I mean it literally was. I don't know,

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Speaker 4: I'm not sure it was called anything. I think it

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Speaker 4: was like a typed page, you know, of numbers.

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Speaker 3: You know.

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Speaker 4: It was kind of the early, the early version where

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Speaker 4: there wasn't all the software that put it in pretty

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Speaker 4: pictures and so Matia look that that came along with

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Speaker 4: the you know, pie charts, and bar charts and things

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Speaker 4: like that. You know fairly early, but it wasn't nearly

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Speaker 4: as kind of beautiful, is it. And I mean now

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Speaker 4: it almost looks like you know what Vanity Fair magazine

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Speaker 4: used to look like, right you open up's got beautiful

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Speaker 4: color and pictures and charts and and all that sort

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Speaker 4: of thing. But people always worked very long hours. That

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Speaker 4: was always the sort of ethos of the industry that

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Speaker 4: there's a lot of work to be done. We wanted

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Speaker 4: to be perfect, and hey, if you can make it

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Speaker 4: a little bit better by staying another half hour, you

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Speaker 4: stay another half hour.

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Speaker 3: So how much of that do you think was driven

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Speaker 3: by genuine client demand in the sense that you know,

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Speaker 3: a client presumably would be not very impressed if you

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Speaker 3: saw that a bullet point was slightly misaligned in a

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Speaker 3: PowerPoint presentation or something like that, versus driven by the

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Speaker 3: institution itself and a soret. I don't want to say

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Speaker 3: hazing culture, but there is a sense that, you know,

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Speaker 3: we all have to work long hours. I worked long

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Speaker 3: hours at the beginning of my career. It's expected that

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Speaker 3: now you are going to work long hours yourself.

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Speaker 4: I think if you go back to the beginning really

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Speaker 4: the nineteen eighties. I think it grew initially out of

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Speaker 4: neither of those things. I think it grew out of

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Speaker 4: the fact that business was growing so fast and you

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Speaker 4: had a limited sized team, and you had twice as

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Speaker 4: many deals to work on as last year, and next

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Speaker 4: year you had fifty percent more than that, and I

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Speaker 4: mean it was a really extraordinary growth, and so there

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Speaker 4: just like weren't enough hands on deck that you could,

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Speaker 4: you know, go home at seven o'clock at night. Now,

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Speaker 4: over time, that generation of bankers, including myself, you know,

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Speaker 4: they bore the scars of those years throughout their careers,

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Speaker 4: and so yes, there probably was in the industry some

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Speaker 4: element of hey I worked like this, You're going to

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Speaker 4: work like this. But initially it was just a genuine

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Speaker 4: business issue of hey, there's so much business to do,

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Speaker 4: so a few of us here to do it. We

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Speaker 4: have to work very lately get it done.

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Speaker 2: What about the element of essentially banking, Like many other fields,

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Speaker 2: including academia but also law, you know, there's like a

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Speaker 2: pyramid element where there's like a very small number or

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Speaker 2: relatively small number of extraordinarily good slash remunerative jobs at

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Speaker 2: the top at a large base of junior analysts and

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Speaker 2: so forth, and how much is it a sort of

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Speaker 2: emergent competition amongst the junior bankers or whatever such that

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Speaker 2: it's not even necessarily some directive to put it in

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Speaker 2: crazy hours. But there's a big field of people and

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Speaker 2: they want to get up to the next rung, and

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Speaker 2: there's fewer spots to the next rung, and that creates

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Speaker 2: that mechanism of intense competition, the desire to sort.

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Speaker 4: Of over please, you know, to just go over the top.

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Speaker 4: And yeah, that's that certainly is there as well. I

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Speaker 4: remember back I don't know why I remember this, but

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Speaker 4: back you know, kind of in the late eighties. I

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Speaker 4: was probably in late twenties at that time, not even

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Speaker 4: a vice president yet at Morgan Stanley. I remember we

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Speaker 4: had this meeting once with the head of investment banking

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Speaker 4: at Morgan Stanley, the guy named Joe Fog very very

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Speaker 4: sort of, very sort of tough guy of that era,

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Speaker 4: and we're sitting around the table. I don't know, there

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Speaker 4: must have been twenty some associates in New York at

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Speaker 4: that time something like that, and people are asking them

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Speaker 4: the question, hey, you know, we have someone you know

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Speaker 4: who covers the retail industry, someone who covers the industrials,

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Speaker 4: someone who covers you know, insurance companies, Like, what what

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Speaker 4: are we going to grow up into? You know, what

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Speaker 4: are the roles going to be for us? And so

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Speaker 4: people did try very hard to differentiate themselves. Now, of course,

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Speaker 4: what none of us around that table knew is this

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Speaker 4: business was going to be like a hundred times bigger.

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Speaker 4: So it wasn't like, oh, we have somebody to cover

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Speaker 4: the retail industry, So I guess that's not an opportunity

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Speaker 4: for me. No, there was going to come a day

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Speaker 4: when you would have twenty five people covering the retail industry.

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Speaker 4: But there's always been that sense of, you know, few

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Speaker 4: opportunities at the top, even when it wasn't true, you know,

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Speaker 4: even when there was going to be more opportunity.

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Speaker 3: So I imagine quite a bit of the work you

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Speaker 3: were doing in the nineteen eighties is what we would

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Speaker 3: now characterize as pretty rote work in the sense that,

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Speaker 3: you know, we didn't have computers, we didn't have Bloomberg

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Speaker 3: terminals that would show the share price or a bond quote.

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Speaker 3: You would have to like actually call someone up and

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Speaker 3: get that.

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Speaker 4: Inn which that's right now. Who owned that company, but

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Speaker 4: Bloomberg put it out of business a long time ago.

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Speaker 3: Shout out to the Bloomberg terminal. I guess, but you know,

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Speaker 3: you went through a wave of disruption, basically, And yet

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Speaker 3: it seems that the work of physically going somewhere to

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Speaker 3: find corporate papers or physically calling someone up to get

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Speaker 3: a share price quote, that was replaced with work of

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Speaker 3: a different kind. Can you explain how that substitution kind

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Speaker 3: of happened.

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Speaker 4: I think it was replaced with going from the sort

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Speaker 4: of very intermittent meetings with a limited number of clients

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Speaker 4: to talk about ideas to a place the industry is

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Speaker 4: today where you go very very regularly to almost every

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Speaker 4: company on the planet of any real size. Right You're

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Speaker 4: someone is there, and you're there with analysis of their industry,

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Speaker 4: their performance, their stock price, their competitors, what's for sale,

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Speaker 4: what might be for sale, and so it's more like

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Speaker 4: a saturation coverage. It's you know, it's a little bit.

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Speaker 4: I think investment making is very very different from consulting,

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Speaker 4: but you know, but where it has some similarity is

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Speaker 4: this kind of try, this attempt and desire to sort

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Speaker 4: of almost get inside the business and really know your

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Speaker 4: client's business, and that was not something that was even

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Speaker 4: attempted back in the nineteen eighties. But that's what all

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Speaker 4: those people are doing with all those extra hours.

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Speaker 2: Now you mentioned you in the early eighties, you couldn't

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Speaker 2: have anticipated that the industry was going to grow one

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Speaker 2: hundred folder whatever it was. And this is one of

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Speaker 2: those things where perhaps from any indo people, many in

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Speaker 2: the public like wise, finance so big? Why why is

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Speaker 2: there so much money in this area? Finance doesn't produce anything?

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Speaker 2: Why why is this? Why has this grown so much?

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Speaker 2: How would you articulate that to someone? Why fundamentally, there

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Speaker 2: is just so much demand for financial services at the

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Speaker 2: corporate level, and so much more than there was, say

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Speaker 2: forty years ago or forty five years ago.

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Speaker 4: Look, I think there there are literally it's no exaggeration

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Speaker 4: to say that there really was an ethical change that

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Speaker 4: the world of sort of post World War two. You know,

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Speaker 4: big companies building conglomerates, you know, work at the same

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Speaker 4: place for thirty five years like my father did. And

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Speaker 4: you know, not a massive amount of intense competition, not

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Speaker 4: a lot of mergers, kind of stable, stable companies and

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Speaker 4: and and you know, maybe that meant slow growth at

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Speaker 4: some point, and maybe that was part of a problem.

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Speaker 4: But in the early eighties you had really a lot

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Speaker 4: of things change. I think corporate culture changed a lot.

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Speaker 4: You know, Jack Els took over from a guy named

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Speaker 4: Greg Jones who was very involved at pen where I went,

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Speaker 4: you know, a very very different kind of character. You know,

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Speaker 4: the the tax law changed. You know, capital gains got

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Speaker 4: started getting taxed differently from ordinary income. The tax rates

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Speaker 4: got cut quite a lot. Deregulation increase, the kind of

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Speaker 4: pressure on unions, you know, Reagan breaking the Air Traffic

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Speaker 4: Controllers union, the ability to buy back stock, even the

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Speaker 4: sort of theoretical notion of you know, what is a

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Speaker 4: company for, right, Milton Friedman said, the company's sole purposes

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Speaker 4: to make money. You know. Professor at Harvard Business School

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Speaker 4: named Michael Jensen wrote all these these stories or analysis

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Speaker 4: about why, you know, you had to maxim my shareholder

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Speaker 4: value and you can't serve two masters, so that has

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Speaker 4: to be the only thing you're you're trying to do.

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Speaker 4: And you know, and he had this long running debate

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Speaker 4: with my first boss, Marty Lipton, founder of Walked Out

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Speaker 4: Lipton about you know, should a company serve you know,

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Speaker 4: the community its employees, it's customers, et cetera. And that

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Speaker 4: all those things mixed together really made for a tremendous

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Speaker 4: focus on transactions. How do you maximize values with more

401
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Speaker 4: shares outstanding or less outstanding? Is it combining with this

402
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Speaker 4: other company? Is it spinning off a business you've already got.

403
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Speaker 4: Maybe this year it's spinning it off, maybe four years

404
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Speaker 4: later it's buying it back. You know, this this game

405
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Speaker 4: really in a way, and hedge funds grew up to

406
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Speaker 4: sort of play that game, to bet on that game,

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Speaker 4: and investment bankers grew up to really you know, drive

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Speaker 4: the transaction activity from that. So the industry that you

409
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Speaker 4: know again was very very small back in the in

410
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Speaker 4: the seventies, and you know, as you turned into that

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Speaker 4: sort of Reagan era when all those rules changed, just

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Speaker 4: really exploded it. And you know, the number of transactions

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Speaker 4: to you know, has been very very high and growing

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Speaker 4: for a long time. I think the interesting question is

415
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Speaker 4: does that go on forever? But it's not like it

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Speaker 4: was there forever. If you're if you're you know the

417
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Speaker 4: age I am, and you started what I did, you

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Speaker 4: sort of feel like it did. But if you look

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Speaker 4: just a tiny bit further back in history you realize, no,

420
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Speaker 4: this is all new.

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Speaker 3: This might be a dumb question. But in terms of

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Speaker 3: the urge to do something as a corporate manager or executive,

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Speaker 3: did you notice a difference between public and private companies.

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Speaker 3: Was that urgency or pressure more apparent at publicly traded ones.

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Speaker 4: Yes, because they had you know, there was this thing

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Speaker 4: that became known as the market for corporate control. Right

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Speaker 4: if you if you don't buy into my mantra of

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Speaker 4: maximizing shareholder value, and therefore you don't, I will bid

429
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Speaker 4: for your company, and I will maximize shareholder value, and

430
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Speaker 4: the difference between the value today and the value later

431
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Speaker 4: is going to be mine. And so there was pressure

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Speaker 4: on public companies. Of course, private companies, you know, there

433
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Speaker 4: were a lot of sort of family owned companies that

434
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Speaker 4: had a longer term point of view and some that

435
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Speaker 4: are still there, you know, the Mars family, you know,

436
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Speaker 4: some companies like that are huge Cargill, some really big

437
00:20:52,080 --> 00:20:54,919
Speaker 4: ones that have remained you know, kind of steadfastly private.

438
00:20:54,960 --> 00:20:57,840
Speaker 4: But today, of course, private company really means private equity

439
00:20:57,840 --> 00:21:00,399
Speaker 4: owned company, you know, and that has grown you know what,

440
00:21:00,560 --> 00:21:04,359
Speaker 4: thirty thousand plus companies owned by that sector of a

441
00:21:04,359 --> 00:21:06,800
Speaker 4: bit of a log jam right now, and they really

442
00:21:06,840 --> 00:21:09,520
Speaker 4: are the masters of that universe. They're the masters of

443
00:21:09,560 --> 00:21:11,199
Speaker 4: trying to maximize shareholder value.

444
00:21:11,320 --> 00:21:13,480
Speaker 3: Actually we should talk about that because this is the

445
00:21:13,480 --> 00:21:15,639
Speaker 3: other thing that's happened in investment banking is you have

446
00:21:15,760 --> 00:21:18,800
Speaker 3: had the rise of private equity and also hedge funds,

447
00:21:18,840 --> 00:21:22,960
Speaker 3: which are in some ways, you know, competing directly with bankers.

448
00:21:23,080 --> 00:21:25,000
Speaker 3: One of the things you sometimes hear, actually when it

449
00:21:25,000 --> 00:21:27,959
Speaker 3: comes to the junior bankers actually working really long hours,

450
00:21:28,040 --> 00:21:29,800
Speaker 3: is this idea that well, we all know they're going

451
00:21:29,880 --> 00:21:32,560
Speaker 3: to go join Blackstone in like two years anyway, so

452
00:21:32,600 --> 00:21:34,920
Speaker 3: we have to squeeze out as much as we can

453
00:21:35,000 --> 00:21:39,080
Speaker 3: from them before that actually happens. How did that actually

454
00:21:39,280 --> 00:21:41,920
Speaker 3: change the business? And I guess, like how much pressure

455
00:21:42,000 --> 00:21:45,960
Speaker 3: did that generate on the banks to respond and I

456
00:21:45,960 --> 00:21:49,040
Speaker 3: guess retool their own offerings and response.

457
00:21:49,560 --> 00:21:52,520
Speaker 4: Well, private equity really became the biggest client base for

458
00:21:52,560 --> 00:21:54,920
Speaker 4: the whole industry, right and that also was a very

459
00:21:55,040 --> 00:21:57,919
Speaker 4: very small, nascent industry. You go back to the you know,

460
00:21:57,960 --> 00:22:00,360
Speaker 4: the early days, like Morgan Stanley had to its first

461
00:22:00,359 --> 00:22:02,520
Speaker 4: private equity fund. It was I can't remember exactly. I

462
00:22:02,520 --> 00:22:05,080
Speaker 4: think it was like a forty four zero million dollar

463
00:22:05,200 --> 00:22:07,680
Speaker 4: fund and you go back to KKR's initial fund. I

464
00:22:07,680 --> 00:22:10,200
Speaker 4: mean people used to do leverage buyouts with like you know,

465
00:22:10,400 --> 00:22:12,879
Speaker 4: buy a ten million dollar company with one hundred thousand

466
00:22:12,880 --> 00:22:16,040
Speaker 4: dollars down and by and by by the rest with debt,

467
00:22:17,119 --> 00:22:20,320
Speaker 4: right we put together, I think you may have missed

468
00:22:20,359 --> 00:22:23,879
Speaker 4: the opportunity. Unfortunately, prices went up from there. But you know,

469
00:22:23,920 --> 00:22:26,119
Speaker 4: these things kind of fed fed on themselves, had some

470
00:22:26,200 --> 00:22:29,520
Speaker 4: early success, and so really in the nineteen eighties beginning

471
00:22:29,600 --> 00:22:32,200
Speaker 4: then you had the rise of the private equity industry.

472
00:22:32,400 --> 00:22:34,600
Speaker 4: You know, these huge players that for a long time,

473
00:22:34,840 --> 00:22:37,800
Speaker 4: you know, did very very well taking companies private, you know,

474
00:22:37,920 --> 00:22:39,800
Speaker 4: kind of doing a number of things to boost their

475
00:22:39,840 --> 00:22:42,359
Speaker 4: returns and then putting them back out into the public.

476
00:22:42,960 --> 00:22:45,800
Speaker 4: That that has also changed quite a lot where the

477
00:22:45,840 --> 00:22:49,040
Speaker 4: industry is looking at, you know, all kinds of private capital, right.

478
00:22:49,080 --> 00:22:51,840
Speaker 4: I mean, you know, Blackstone really pioneered this model of oh,

479
00:22:51,880 --> 00:22:54,000
Speaker 4: let's do real estate, let's do hedge funds, let's do

480
00:22:54,040 --> 00:22:58,320
Speaker 4: private credit, and so you expanded to so many different fields.

481
00:22:58,320 --> 00:23:02,520
Speaker 4: But that that really fundamentally changed Wall Street because the

482
00:23:02,640 --> 00:23:05,439
Speaker 4: rise of the private equity to created a client that

483
00:23:05,560 --> 00:23:07,720
Speaker 4: was kind of in the kind of permanently in the

484
00:23:07,720 --> 00:23:10,920
Speaker 4: transaction business, right, not like a public fortune one hundred

485
00:23:11,000 --> 00:23:13,160
Speaker 4: five hundred company that might do a deal every year

486
00:23:13,200 --> 00:23:15,600
Speaker 4: or two or three. You know, these were firms that

487
00:23:15,720 --> 00:23:18,760
Speaker 4: did you know, ten or twenty deals a year, and

488
00:23:18,800 --> 00:23:21,600
Speaker 4: so they were became the most important clients.

489
00:23:21,920 --> 00:23:27,479
Speaker 3: They're raising Dutch is raising money. I got thank you.

490
00:23:27,920 --> 00:23:30,639
Speaker 3: I stole that from Lloyd Fling. Fine. Actually, oh I

491
00:23:30,640 --> 00:23:32,440
Speaker 3: feel bad. I've been reading his book, which is why

492
00:23:32,480 --> 00:23:34,159
Speaker 3: I keep mentioning him that good one.

493
00:23:34,359 --> 00:23:36,600
Speaker 2: Okay, you get a little bit further into your career

494
00:23:36,800 --> 00:23:39,439
Speaker 2: and you get a sort of role where perhaps you

495
00:23:39,480 --> 00:23:41,600
Speaker 2: get to think a little big picture and you have

496
00:23:41,640 --> 00:23:44,680
Speaker 2: to more junior people are the ones staying up late,

497
00:23:44,720 --> 00:23:47,359
Speaker 2: et cetera. Talk to us a little bit about recruiting,

498
00:23:47,400 --> 00:23:49,359
Speaker 2: and I met this is an area of course today

499
00:23:49,400 --> 00:23:52,160
Speaker 2: that there's probably a lot of anxiety for people going

500
00:23:52,160 --> 00:23:54,719
Speaker 2: into the biz. But talk to us a little bit

501
00:23:54,720 --> 00:23:58,160
Speaker 2: about like, Okay, some things obviously can be taught. Math

502
00:23:58,240 --> 00:24:03,239
Speaker 2: can probably generally be taught. Put aligning bullet points on

503
00:24:03,320 --> 00:24:06,520
Speaker 2: a PowerPoint. I think that could probably be taught. Though

504
00:24:06,560 --> 00:24:10,479
Speaker 2: fastidiousness and attention to detail maybe inherently, maybe not how

505
00:24:10,520 --> 00:24:12,159
Speaker 2: would you talk to us a little bit about how

506
00:24:12,640 --> 00:24:14,240
Speaker 2: how you found people at the writ fit, how you

507
00:24:14,600 --> 00:24:15,679
Speaker 2: what that process was like.

508
00:24:16,000 --> 00:24:18,679
Speaker 4: Well, that also, of course has changed dramatically as the

509
00:24:18,680 --> 00:24:21,000
Speaker 4: industry has grown. If you go back to early days,

510
00:24:21,160 --> 00:24:23,760
Speaker 4: we recruited a very few schools. I mean it really

511
00:24:23,840 --> 00:24:25,959
Speaker 4: was sort of the Ivy League and maybe a few others,

512
00:24:26,800 --> 00:24:28,520
Speaker 4: and it was for a small number of jobs, so

513
00:24:28,600 --> 00:24:30,239
Speaker 4: there were plenty of students there for that. Now, when

514
00:24:30,240 --> 00:24:33,439
Speaker 4: the industry really exploded, those schools weren't producing enough people.

515
00:24:33,800 --> 00:24:35,760
Speaker 4: And I can say in the early days of Greenhill

516
00:24:35,840 --> 00:24:38,200
Speaker 4: we had in terms of like what knowledge these these

517
00:24:38,240 --> 00:24:40,280
Speaker 4: young people had, we had a little bit of a

518
00:24:40,720 --> 00:24:43,639
Speaker 4: strategy of you know, let's take half of the class

519
00:24:44,080 --> 00:24:46,000
Speaker 4: just kids who are really smart. You know, but they

520
00:24:46,000 --> 00:24:48,680
Speaker 4: can do math, they can speak, they can write, they

521
00:24:48,800 --> 00:24:50,600
Speaker 4: just got great grades all the way through. They're really

522
00:24:50,600 --> 00:24:53,560
Speaker 4: really smart. And let's take the other half as people

523
00:24:53,560 --> 00:24:56,879
Speaker 4: who actually have some substance of knowledge that's useful. You know,

524
00:24:56,920 --> 00:24:59,159
Speaker 4: they went to Wharton. There are other great business schools

525
00:24:59,119 --> 00:25:01,640
Speaker 4: about University Gina had one. We recruited a lot from

526
00:25:01,720 --> 00:25:05,760
Speaker 4: a University of Texas, Indiana, University, University of Michigan, and

527
00:25:05,800 --> 00:25:07,480
Speaker 4: so we'd kind of do half and half in figure.

528
00:25:07,560 --> 00:25:09,399
Speaker 4: You know, the kid who majored in finance at Wharton

529
00:25:09,400 --> 00:25:12,600
Speaker 4: can teach the kid who majored in English at Yale.

530
00:25:13,000 --> 00:25:16,920
Speaker 4: Now today, what's changed is that the typical student wherever

531
00:25:17,000 --> 00:25:20,000
Speaker 4: he or she sits, as they're in their senior year

532
00:25:20,040 --> 00:25:22,720
Speaker 4: of college. I mean, they've had like four internships by now,

533
00:25:23,000 --> 00:25:26,919
Speaker 4: they've taken various online courses. They come in so ready

534
00:25:26,960 --> 00:25:30,040
Speaker 4: to roll, even if they majored in something that's completely

535
00:25:30,119 --> 00:25:34,679
Speaker 4: unrelated to what Wall Street actually does. So you're getting

536
00:25:34,720 --> 00:25:37,639
Speaker 4: someone who's almost trained before they even arrived. Now you

537
00:25:37,680 --> 00:25:39,920
Speaker 4: give them a lot more training, of course, but it's

538
00:25:39,960 --> 00:25:41,560
Speaker 4: not the kind of thing where you bring in an

539
00:25:41,600 --> 00:25:43,760
Speaker 4: English major, you know, as we did in the early

540
00:25:43,840 --> 00:25:46,320
Speaker 4: days and teach them like here, here's what a stock

541
00:25:46,440 --> 00:25:48,479
Speaker 4: is and here's what a bond is. You know, these

542
00:25:48,520 --> 00:25:50,840
Speaker 4: students have been working on that since they were in

543
00:25:50,920 --> 00:25:53,719
Speaker 4: high school. I'm maybe I'm sorry to say I think

544
00:25:53,760 --> 00:25:55,639
Speaker 4: they should probably doing other things in high school. But

545
00:25:55,840 --> 00:25:58,600
Speaker 4: you know, it's become a very very competitive world, right

546
00:25:58,600 --> 00:26:02,159
Speaker 4: even though there's many, many more opportunities for students to

547
00:26:02,160 --> 00:26:04,080
Speaker 4: get a job on Wall Street today as they come

548
00:26:04,119 --> 00:26:07,040
Speaker 4: out of college at the same time, it's very very competitive.

549
00:26:07,240 --> 00:26:09,760
Speaker 2: Was there like a point where you started noticing that

550
00:26:10,119 --> 00:26:13,080
Speaker 2: or like around when that change, because it certainly tracks

551
00:26:13,119 --> 00:26:14,800
Speaker 2: that you like meet young people and they're like, oh

552
00:26:14,840 --> 00:26:16,960
Speaker 2: my god, like, how do they know all this stuff

553
00:26:17,000 --> 00:26:19,640
Speaker 2: and about things that maybe it's the Internet or something,

554
00:26:19,680 --> 00:26:21,399
Speaker 2: the things that I certainly didn't know about when I

555
00:26:21,400 --> 00:26:24,000
Speaker 2: was in high school really even college in many instances.

556
00:26:24,040 --> 00:26:27,119
Speaker 2: But I'm curious when you started when you started noticing that.

557
00:26:27,400 --> 00:26:30,679
Speaker 4: I think maybe in the sort of the post dot

558
00:26:30,720 --> 00:26:34,080
Speaker 4: com bubble bursting kind of in the early two thousands,

559
00:26:34,080 --> 00:26:36,199
Speaker 4: when business really started to pick up again and you

560
00:26:36,240 --> 00:26:38,800
Speaker 4: had those several great years leading into what, of course

561
00:26:38,840 --> 00:26:41,920
Speaker 4: became the financial crisis, But there was such an increase

562
00:26:42,040 --> 00:26:45,560
Speaker 4: in opportunity then, and there was and now everyone was

563
00:26:45,560 --> 00:26:47,200
Speaker 4: in on the secret, right, I mean, they could read

564
00:26:47,200 --> 00:26:50,280
Speaker 4: about the industry, they could understand the you know, compensation

565
00:26:50,440 --> 00:26:54,080
Speaker 4: structures and the potential for themselves to get ahead in life.

566
00:26:54,080 --> 00:26:57,240
Speaker 4: And and so these students started kind of working backwards like, Okay,

567
00:26:57,280 --> 00:26:59,160
Speaker 4: I wanted to get a first year analyst job.

568
00:26:59,160 --> 00:26:59,719
Speaker 2: How do I do that?

569
00:27:00,080 --> 00:27:03,440
Speaker 4: What internship should I get after you know, freshman year? Well,

570
00:27:03,440 --> 00:27:05,120
Speaker 4: you can't get a very good one then, but maybe

571
00:27:05,119 --> 00:27:07,960
Speaker 4: you can get something tangentially, you know, do you know

572
00:27:08,040 --> 00:27:11,000
Speaker 4: somebody works as a stockbroker, Can you be a you know,

573
00:27:11,359 --> 00:27:13,600
Speaker 4: work in the mail room there or something after software,

574
00:27:13,640 --> 00:27:14,959
Speaker 4: or maybe you can do a little better than that.

575
00:27:15,000 --> 00:27:17,440
Speaker 4: After junior year, maybe you can get you know, something

576
00:27:17,480 --> 00:27:19,520
Speaker 4: better than that. And by time you show up, you know,

577
00:27:19,560 --> 00:27:22,640
Speaker 4: as a college junior looking for that first year analyst

578
00:27:22,720 --> 00:27:25,280
Speaker 4: job at Goldman Sachs, you know, you've got like five

579
00:27:25,400 --> 00:27:27,399
Speaker 4: names on your resume that look like, wow, this this

580
00:27:27,440 --> 00:27:29,640
Speaker 4: person's been around the industry a long time, even though

581
00:27:29,640 --> 00:27:31,960
Speaker 4: they're twenty one years old at the point, at that

582
00:27:32,040 --> 00:27:32,920
Speaker 4: point scary.

583
00:27:33,560 --> 00:27:35,200
Speaker 3: Do you think as many people are going to want

584
00:27:35,240 --> 00:27:38,199
Speaker 3: to go in finance given that, I mean, we've already

585
00:27:38,200 --> 00:27:41,120
Speaker 3: been through shifts in the popularity of finance as a career.

586
00:27:41,200 --> 00:27:44,320
Speaker 3: So at one point it was the place that you

587
00:27:44,359 --> 00:27:46,360
Speaker 3: wanted to go to if you were like a Harvard

588
00:27:46,400 --> 00:27:48,679
Speaker 3: grad or whatever, and then it became tech for a

589
00:27:48,680 --> 00:27:52,639
Speaker 3: little while, and now there's all this anxiety over AI

590
00:27:52,880 --> 00:27:56,760
Speaker 3: disrupting particularly analytical jobs. Do you think it's going to

591
00:27:56,760 --> 00:27:58,160
Speaker 3: be as popular a choice.

592
00:27:59,040 --> 00:28:02,480
Speaker 4: I think it will. It will evolve and fluctuate and

593
00:28:03,200 --> 00:28:07,240
Speaker 4: probably decline over time. Just the industry is all about cycles, right,

594
00:28:07,240 --> 00:28:10,440
Speaker 4: Markets are all about cycles. I mean, we've had an

595
00:28:10,440 --> 00:28:13,920
Speaker 4: incredible run, incredible run. Okay, the you know, COVID was

596
00:28:13,960 --> 00:28:16,040
Speaker 4: a little bit of a hiccup right where markets sort

597
00:28:16,040 --> 00:28:18,399
Speaker 4: of plummeted and things slowed down, but then you know,

598
00:28:18,560 --> 00:28:21,880
Speaker 4: it exploded in activity in just a matter of months later.

599
00:28:21,920 --> 00:28:24,280
Speaker 4: So it's been a long run really since the financial

600
00:28:24,320 --> 00:28:28,639
Speaker 4: crisis of you know, really wonderful times largely on Wall Street.

601
00:28:28,720 --> 00:28:30,399
Speaker 4: And you know at some point there's going to be

602
00:28:31,080 --> 00:28:33,560
Speaker 4: you know, a retrenchment from that. There's going to be

603
00:28:33,560 --> 00:28:35,719
Speaker 4: some kind of decline. Who you know, who knows. Maybe

604
00:28:35,960 --> 00:28:38,760
Speaker 4: maybe maybe a war set you know, turns things around,

605
00:28:38,760 --> 00:28:41,800
Speaker 4: maybe a private credit problem turns things around. But something

606
00:28:41,840 --> 00:28:44,720
Speaker 4: will happen, I think can sort of dampen the interest again,

607
00:28:44,960 --> 00:28:47,320
Speaker 4: just as happened, you know, with the dot com crash

608
00:28:47,400 --> 00:29:02,680
Speaker 4: or the financial crisis.

609
00:29:04,440 --> 00:29:07,120
Speaker 2: Let's talk a little bit more about technology and the

610
00:29:07,160 --> 00:29:11,000
Speaker 2: technological changes that you saw in your career. So okay,

611
00:29:11,200 --> 00:29:14,000
Speaker 2: mentioned like you're using Lotus one two three in the beginning,

612
00:29:14,000 --> 00:29:16,960
Speaker 2: which I have some memory of Lotus one two three

613
00:29:17,000 --> 00:29:21,040
Speaker 2: and ease of data retrieval is so much is so

614
00:29:21,160 --> 00:29:23,800
Speaker 2: much different now. But talk to us about okay, twenty

615
00:29:23,880 --> 00:29:27,080
Speaker 2: twenty four, but in recent years and some of the

616
00:29:27,080 --> 00:29:31,720
Speaker 2: other ways, like what what other technological innovations came out,

617
00:29:31,920 --> 00:29:35,520
Speaker 2: What time consuming activities did they shrink to your zero?

618
00:29:35,720 --> 00:29:38,960
Speaker 2: And then what new things did people do on top

619
00:29:39,080 --> 00:29:41,040
Speaker 2: Once Okay, the technology is here, you don't have to

620
00:29:41,080 --> 00:29:43,840
Speaker 2: allocate your time to this. You're now going to allocate

621
00:29:43,840 --> 00:29:45,920
Speaker 2: your time to that. Talk to us what else you saw?

622
00:29:46,080 --> 00:29:46,320
Speaker 3: Sure?

623
00:29:46,640 --> 00:29:49,200
Speaker 4: Yeah, I mean look in the early days, like even

624
00:29:49,240 --> 00:29:51,760
Speaker 4: if companies weren't even that of their own share price, right,

625
00:29:51,800 --> 00:29:54,600
Speaker 4: I mean, not everybody had a Bloomberg terminal or CNBC

626
00:29:55,000 --> 00:29:56,760
Speaker 4: you know screen on their on their desk. If you're

627
00:29:56,800 --> 00:30:00,800
Speaker 4: sitting in Dayton, Ohio. Uh so you didn't know. As bankers,

628
00:30:00,880 --> 00:30:03,160
Speaker 4: you know, you could bring very little information and it

629
00:30:03,200 --> 00:30:05,200
Speaker 4: was new to the client. It was interesting to the client.

630
00:30:05,560 --> 00:30:05,720
Speaker 1: You know.

631
00:30:05,800 --> 00:30:08,920
Speaker 4: Over time, we used to do a lot of laborious

632
00:30:08,960 --> 00:30:12,080
Speaker 4: work to create sort of a comparable companies analysis. Here

633
00:30:12,080 --> 00:30:15,040
Speaker 4: are the ten companies in your business segment. You know,

634
00:30:15,120 --> 00:30:17,760
Speaker 4: you trade at this pe multiple or this ebit don multiple,

635
00:30:17,760 --> 00:30:19,400
Speaker 4: and here's where the other guys trade, and here's how

636
00:30:19,400 --> 00:30:22,160
Speaker 4: their leverage is different than yours, and here's how their

637
00:30:22,200 --> 00:30:24,440
Speaker 4: stock is performed. And that used to be a tremendous

638
00:30:24,440 --> 00:30:27,080
Speaker 4: amount of work. You know, Now really a machine can

639
00:30:27,160 --> 00:30:30,120
Speaker 4: largely do that, and a lot of the other kind

640
00:30:30,160 --> 00:30:33,360
Speaker 4: of creation of sort of standard charts on you know,

641
00:30:33,400 --> 00:30:35,600
Speaker 4: on what's going on in the industry, even what's going

642
00:30:35,640 --> 00:30:38,080
Speaker 4: on in your company can be done very very quickly.

643
00:30:38,200 --> 00:30:41,280
Speaker 4: So I think, you know, the pyramid I have to

644
00:30:41,320 --> 00:30:43,960
Speaker 4: think is going to get less fat at the bottom

645
00:30:44,440 --> 00:30:47,480
Speaker 4: because you're going to be really leveraging technology to do

646
00:30:47,520 --> 00:30:49,840
Speaker 4: a lot of things that used to be somebody sitting

647
00:30:49,880 --> 00:30:52,240
Speaker 4: up all up all night trying to find out, you know,

648
00:30:52,240 --> 00:30:55,120
Speaker 4: what pe multiple Coca Cola was trading at, and now

649
00:30:55,400 --> 00:30:56,920
Speaker 4: you know it's that you can get it at the

650
00:30:57,080 --> 00:30:57,800
Speaker 4: touch of a finger.

651
00:30:58,480 --> 00:31:01,520
Speaker 3: Does the edge in that scenario? You know, if it's

652
00:31:01,520 --> 00:31:04,320
Speaker 3: not about how much knowledge you're accumulating and can share

653
00:31:04,360 --> 00:31:07,280
Speaker 3: with your client, is the edge more on the execution

654
00:31:07,480 --> 00:31:11,560
Speaker 3: side of things, just the knowledge or the client's belief

655
00:31:11,720 --> 00:31:14,880
Speaker 3: that you, out of everyone else in the IB business,

656
00:31:15,040 --> 00:31:17,360
Speaker 3: is going to be able to execute like a smooth deal.

657
00:31:18,000 --> 00:31:20,920
Speaker 4: I think that's true to some degree, And you know,

658
00:31:20,920 --> 00:31:23,160
Speaker 4: particularly amongst sort of the so called independent firms like

659
00:31:23,200 --> 00:31:25,400
Speaker 4: green Hill was for a long time and many others

660
00:31:25,440 --> 00:31:28,800
Speaker 4: are today. But I think among the larger you know

661
00:31:28,880 --> 00:31:30,960
Speaker 4: group of competitors, I think a lot it's going to

662
00:31:31,000 --> 00:31:34,080
Speaker 4: come down to what else is in the relationship. You know,

663
00:31:34,520 --> 00:31:37,560
Speaker 4: are you are you and their revolving credit facility? To

664
00:31:37,600 --> 00:31:40,000
Speaker 4: do you do their bond offering? Are you doing equity

665
00:31:40,080 --> 00:31:41,120
Speaker 4: research for them?

666
00:31:41,680 --> 00:31:41,800
Speaker 2: Uh?

667
00:31:42,040 --> 00:31:44,240
Speaker 4: Are you know, are you touching them and just every

668
00:31:44,240 --> 00:31:46,680
Speaker 4: are you doing their hedging? Are you, you know, talking

669
00:31:46,720 --> 00:31:49,880
Speaker 4: them about currency, talking them about commodity prices? And so

670
00:31:50,440 --> 00:31:53,040
Speaker 4: I do think it it may That's why I think

671
00:31:53,080 --> 00:31:55,600
Speaker 4: sort of the one stop shopping is kind of a

672
00:31:55,680 --> 00:31:59,440
Speaker 4: little more appealing again because if if nobody, if nobody

673
00:31:59,480 --> 00:32:02,080
Speaker 4: really has the magic anymore, right of the magic is

674
00:32:02,160 --> 00:32:04,760
Speaker 4: now a fingertips uh, and you know me even a

675
00:32:04,800 --> 00:32:06,400
Speaker 4: lot of things like you can you can you don't

676
00:32:06,400 --> 00:32:07,800
Speaker 4: even need to do the Excel model. I mean, you

677
00:32:08,080 --> 00:32:11,600
Speaker 4: can say into a in the AI, if you have

678
00:32:11,680 --> 00:32:13,560
Speaker 4: this stream of cash flows to this period of time,

679
00:32:13,680 --> 00:32:15,880
Speaker 4: this discount, right, what's the number? I mean, it will

680
00:32:15,880 --> 00:32:17,680
Speaker 4: give it to you without you typing a single number

681
00:32:17,720 --> 00:32:21,680
Speaker 4: under the page. But I think that with everyone having

682
00:32:21,720 --> 00:32:24,520
Speaker 4: access equal access to that information. I think it will

683
00:32:24,560 --> 00:32:27,360
Speaker 4: come down to, yeah, maybe are you smarter than the

684
00:32:27,360 --> 00:32:30,680
Speaker 4: other guys? Can you execute better? But probably in most cases,

685
00:32:30,960 --> 00:32:32,920
Speaker 4: you know, what else are you doing for me? And hey,

686
00:32:32,920 --> 00:32:34,600
Speaker 4: I could give this to anyone, but I'm gonna give

687
00:32:34,600 --> 00:32:34,959
Speaker 4: it to you.

688
00:32:35,680 --> 00:32:39,240
Speaker 2: How much Tracy alluded to this at the very beginning,

689
00:32:39,240 --> 00:32:42,560
Speaker 2: But you know how much of the job is being

690
00:32:42,600 --> 00:32:45,400
Speaker 2: a good hang, being a good hang at the golf course,

691
00:32:45,960 --> 00:32:49,480
Speaker 2: knowing being able to get a good dinner reservation. It's seriously, no,

692
00:32:49,840 --> 00:32:52,040
Speaker 2: for real, like this is like I don't think you know,

693
00:32:52,120 --> 00:32:53,760
Speaker 2: this is where I when I think about if I

694
00:32:53,840 --> 00:32:55,400
Speaker 2: were this, I don't think i'd be very good at that.

695
00:32:55,560 --> 00:32:57,600
Speaker 2: I like start looking at my watch or you on anger,

696
00:32:57,640 --> 00:33:01,120
Speaker 2: so mostly I start looking at my phone's looking board,

697
00:33:01,200 --> 00:33:03,800
Speaker 2: et cetera. The endurance, that's true.

698
00:33:03,920 --> 00:33:06,520
Speaker 3: It's very obvious when Joe is bored talking to you,

699
00:33:06,600 --> 00:33:07,160
Speaker 3: I speak from a.

700
00:33:07,200 --> 00:33:09,320
Speaker 2: Gast So this is not this should not be my field.

701
00:33:09,360 --> 00:33:12,160
Speaker 2: But talk to us about that element and just the

702
00:33:12,200 --> 00:33:15,480
Speaker 2: sort of people skills and all there.

703
00:33:16,080 --> 00:33:18,520
Speaker 4: Now, of course that's at quite the high level, right,

704
00:33:18,640 --> 00:33:21,000
Speaker 4: It doesn't matter how you know, how fun you are

705
00:33:21,040 --> 00:33:24,120
Speaker 4: to be with as a senior associate at JP Morgan.

706
00:33:24,720 --> 00:33:27,440
Speaker 4: That's not necessarily going to win the business. But maybe

707
00:33:27,480 --> 00:33:30,720
Speaker 4: your boss's boss, you know, whether he's in the right

708
00:33:30,760 --> 00:33:33,400
Speaker 4: golf clubs and inviting clients and you know, getting to

709
00:33:33,400 --> 00:33:35,520
Speaker 4: know them on a personal level. Look, there's always going

710
00:33:35,560 --> 00:33:38,400
Speaker 4: to be that element to the business, but that that's

711
00:33:38,440 --> 00:33:41,520
Speaker 4: a pretty small piece. And of course everyone has that too, right,

712
00:33:41,840 --> 00:33:43,800
Speaker 4: I mean, you can one up others. You can bring

713
00:33:43,840 --> 00:33:46,120
Speaker 4: somebody to the Masters, you can, you know, rather than

714
00:33:46,160 --> 00:33:48,680
Speaker 4: to a you know, a country club on Long Island.

715
00:33:48,760 --> 00:33:52,160
Speaker 4: You know, you can. There's there's different levels of sort

716
00:33:52,200 --> 00:33:54,560
Speaker 4: of client entertainment, but you know that that's Look, it's

717
00:33:54,600 --> 00:33:55,880
Speaker 4: important to build relationships.

718
00:33:55,960 --> 00:33:56,600
Speaker 2: It always is.

719
00:33:57,120 --> 00:33:59,880
Speaker 4: I think what you know, whether you're talking about sort

720
00:33:59,920 --> 00:34:06,800
Speaker 4: of personal wealth management or corporate financial management, what the

721
00:34:07,000 --> 00:34:09,719
Speaker 4: what the advisors have to realize is like everyone in

722
00:34:09,760 --> 00:34:12,000
Speaker 4: the world is calling on this guy and trying to

723
00:34:12,040 --> 00:34:14,320
Speaker 4: get you know, either his personal money to manage or

724
00:34:14,360 --> 00:34:17,040
Speaker 4: trying to manage his corporate affairs and help him do

725
00:34:17,200 --> 00:34:19,960
Speaker 4: acquisitions and so on. I mean, it's not That's another

726
00:34:20,000 --> 00:34:22,000
Speaker 4: thing really that changed a lot in the industry. Used

727
00:34:22,000 --> 00:34:24,880
Speaker 4: to be that people, you know, firms had clients like

728
00:34:24,880 --> 00:34:26,680
Speaker 4: like you, No, that's my client and this one is

729
00:34:26,719 --> 00:34:31,680
Speaker 4: your client. Now they're just all clients and everyone's clients everyone, right,

730
00:34:31,719 --> 00:34:34,359
Speaker 4: And it's kind of a free for all where you've

731
00:34:34,360 --> 00:34:36,440
Speaker 4: got a lot of parties out there, you know, in

732
00:34:36,520 --> 00:34:39,759
Speaker 4: you being special because you invite somebody to you know

733
00:34:39,880 --> 00:34:41,440
Speaker 4: something and get to know them butt, I mean everyone

734
00:34:41,440 --> 00:34:43,040
Speaker 4: else is doing that too, And as a matter of fact,

735
00:34:43,080 --> 00:34:46,680
Speaker 4: if you don't have the relationship, you're probably more prone

736
00:34:46,719 --> 00:34:48,560
Speaker 4: to do that because you're trying to break in, you know,

737
00:34:48,600 --> 00:34:49,520
Speaker 4: get to know them.

738
00:34:50,880 --> 00:34:53,239
Speaker 3: You mentioned this word earlier in the conversation, but can

739
00:34:53,280 --> 00:34:56,560
Speaker 3: you explain culture to us? Explain all culture to us? No,

740
00:34:56,680 --> 00:34:58,640
Speaker 3: the investment banking culture, because this is one thing that

741
00:34:58,680 --> 00:35:02,560
Speaker 3: we hear all the time time from you know, especially executives,

742
00:35:02,960 --> 00:35:06,279
Speaker 3: former executives at investment banks, this idea that well, we

743
00:35:06,400 --> 00:35:10,160
Speaker 3: have a culture that is different to someone else's culture.

744
00:35:10,360 --> 00:35:14,000
Speaker 3: And whenever you hear them summarize the culture, it's almost

745
00:35:14,040 --> 00:35:17,480
Speaker 3: always like we're client facing and it's all. I've never

746
00:35:17,520 --> 00:35:20,440
Speaker 3: heard a bank say it's not about the client. Actually,

747
00:35:20,480 --> 00:35:23,399
Speaker 3: our culture is about something else. What does culture mean

748
00:35:23,560 --> 00:35:24,520
Speaker 3: in investment banking?

749
00:35:26,560 --> 00:35:30,120
Speaker 4: I think it's probably fair to say every firm aspires

750
00:35:30,160 --> 00:35:33,840
Speaker 4: to the same culture. Right, you aspire to be driven

751
00:35:33,920 --> 00:35:39,040
Speaker 4: by excellence and attention to detail and client service, and

752
00:35:38,800 --> 00:35:43,520
Speaker 4: and you produce that great coverage through team work and

753
00:35:43,680 --> 00:35:47,960
Speaker 4: training and mentorship. I mean, every everyone aspires to all that.

754
00:35:48,360 --> 00:35:51,480
Speaker 4: There are though different cultures. There are some places I

755
00:35:51,480 --> 00:35:54,040
Speaker 4: think are much harder to work than others, although I

756
00:35:54,040 --> 00:35:56,360
Speaker 4: think the industry has become a little more in common.

757
00:35:56,400 --> 00:35:58,560
Speaker 4: I mean, I think there was there was a day

758
00:35:58,600 --> 00:36:01,440
Speaker 4: when you know, the difference inture between like a Morgan

759
00:36:01,520 --> 00:36:03,680
Speaker 4: Stanley and a bear Stearns was was vast.

760
00:36:03,680 --> 00:36:05,400
Speaker 2: I would say more about that, like what would have

761
00:36:05,400 --> 00:36:05,719
Speaker 2: been the d.

762
00:36:06,680 --> 00:36:08,480
Speaker 4: You know, there were some firms that sort of you know,

763
00:36:08,520 --> 00:36:11,520
Speaker 4: the word scrappy sometimes gets thrown around on Wall Street, right,

764
00:36:11,560 --> 00:36:14,560
Speaker 4: and if you're if you're the elite firm, like say,

765
00:36:14,760 --> 00:36:16,760
Speaker 4: you know back in the day, Morgan Stanley and Golden

766
00:36:16,800 --> 00:36:18,839
Speaker 4: Sacks were. Of course there's still elite firms in any

767
00:36:18,840 --> 00:36:22,160
Speaker 4: ways today, but you know, as opposed to someone who's

768
00:36:22,239 --> 00:36:24,799
Speaker 4: kind of scrappy trying to get business that maybe you

769
00:36:24,840 --> 00:36:27,359
Speaker 4: wouldn't do. I mean, there were there was a day

770
00:36:27,560 --> 00:36:29,360
Speaker 4: One of the interesting things not to bring up the

771
00:36:29,400 --> 00:36:32,160
Speaker 4: Epstein files, but but you know, there was a day

772
00:36:32,239 --> 00:36:35,279
Speaker 4: when when there firms had a lot of rigor over

773
00:36:35,360 --> 00:36:38,879
Speaker 4: who they would do business with, you know, and I

774
00:36:38,960 --> 00:36:41,160
Speaker 4: know that you know, Morgan Stanley, that was the case.

775
00:36:41,160 --> 00:36:42,719
Speaker 4: I think at Gold and Sacks that was the case.

776
00:36:42,760 --> 00:36:45,960
Speaker 4: I mean, look, they were in the law firm business.

777
00:36:46,080 --> 00:36:48,960
Speaker 4: There were there were firms that didn't like hostile takeovers.

778
00:36:48,960 --> 00:36:50,520
Speaker 4: You know, they thought that, oh, that that's kind of

779
00:36:50,640 --> 00:36:53,040
Speaker 4: unseemly for us to be trying to buy somebody else's

780
00:36:53,080 --> 00:36:55,520
Speaker 4: business on a hostile basis. And so these firms that

781
00:36:55,560 --> 00:36:57,440
Speaker 4: you know, you could put in the category of scrappy

782
00:36:57,840 --> 00:36:59,480
Speaker 4: were the ones that were trying to be a little

783
00:36:59,520 --> 00:37:01,319
Speaker 4: more like, hey, if the client wants that help, I'm

784
00:37:01,320 --> 00:37:02,799
Speaker 4: going to give the client that help. Or if the

785
00:37:02,800 --> 00:37:05,640
Speaker 4: client has a little bit of a that's right and

786
00:37:05,840 --> 00:37:08,799
Speaker 4: and well, and also by you know, maybe doing a

787
00:37:08,920 --> 00:37:12,120
Speaker 4: transaction for someone as a client that maybe of you know,

788
00:37:12,480 --> 00:37:14,239
Speaker 4: back in the day, I'm Morgan stand there, gomal Sex

789
00:37:14,280 --> 00:37:17,600
Speaker 4: wouldn't have worked for now you've got a credential that industry. Now,

790
00:37:17,640 --> 00:37:20,160
Speaker 4: now you've done a media deal. Now maybe you can

791
00:37:20,200 --> 00:37:22,480
Speaker 4: do the next media deal. Maybe you can swim upstream

792
00:37:22,920 --> 00:37:25,879
Speaker 4: toward the more prestigious clients. So so, I think at

793
00:37:25,880 --> 00:37:28,400
Speaker 4: one point the cultures were a lot more different than

794
00:37:28,440 --> 00:37:29,080
Speaker 4: they are today.

795
00:37:29,120 --> 00:37:31,160
Speaker 2: I think it's kind of flattened.

796
00:37:31,360 --> 00:37:34,880
Speaker 4: I think, you know, look, this is probably a function

797
00:37:34,960 --> 00:37:38,239
Speaker 4: of scale of activity, and of things like technology, and

798
00:37:38,280 --> 00:37:40,600
Speaker 4: of things like you know, just so much open information

799
00:37:40,680 --> 00:37:44,040
Speaker 4: on everything. You know, everyone can sort of copy everyone else, right,

800
00:37:44,040 --> 00:37:46,640
Speaker 4: It's pretty obvious what a good culture is higher smart

801
00:37:46,680 --> 00:37:49,520
Speaker 4: young people. Train them well, treat them decently, and they'll

802
00:37:49,520 --> 00:37:51,680
Speaker 4: grow up to be you know, good good bankers. You know,

803
00:37:51,719 --> 00:37:55,800
Speaker 4: pay attention to your clients, have integrity, you know, et cetera.

804
00:37:55,960 --> 00:37:59,400
Speaker 4: You'll build a good business. But that those aren't secrets, right,

805
00:37:59,400 --> 00:38:00,359
Speaker 4: everybody knows those.

806
00:38:00,880 --> 00:38:03,279
Speaker 2: I have a question. It's sort of this on long

807
00:38:03,320 --> 00:38:07,319
Speaker 2: standing puzzle within finance. It might be relevant this year

808
00:38:07,360 --> 00:38:10,200
Speaker 2: because there's some very big companies that might come public.

809
00:38:10,600 --> 00:38:13,840
Speaker 2: Why does the IPO process as we know it exist

810
00:38:14,040 --> 00:38:16,640
Speaker 2: and persist? Because this is one of the long standing

811
00:38:16,640 --> 00:38:20,560
Speaker 2: academic things. Why is there frequently a pop Why did

812
00:38:20,600 --> 00:38:24,520
Speaker 2: the companies have to pay large fees to underwriters, particularly

813
00:38:24,560 --> 00:38:27,799
Speaker 2: given you'd think the Internet could just just have an auction, right,

814
00:38:27,840 --> 00:38:30,040
Speaker 2: an auction out the allocation of shares you want and

815
00:38:30,080 --> 00:38:33,120
Speaker 2: then get the market price instantly and so forth. And

816
00:38:33,200 --> 00:38:35,080
Speaker 2: yet this has been tried for a very long time,

817
00:38:35,120 --> 00:38:36,719
Speaker 2: and going back to the dot com here or there

818
00:38:36,719 --> 00:38:40,120
Speaker 2: have been attempts to disintermediate the traditional IPO process with

819
00:38:40,200 --> 00:38:44,040
Speaker 2: almost no success backs tried. That seems to be sort

820
00:38:44,080 --> 00:38:47,880
Speaker 2: of not a particularly counter signal. Perhaps, How would you

821
00:38:47,960 --> 00:38:50,600
Speaker 2: describe the persistence of the IPO.

822
00:38:51,239 --> 00:38:53,680
Speaker 4: Well, you know, first of all, the public start with

823
00:38:53,680 --> 00:38:56,120
Speaker 4: public companies, right, that's what you have after you do

824
00:38:56,120 --> 00:38:58,799
Speaker 4: on IPO. You know, that market really has shrunk. I

825
00:38:58,800 --> 00:39:00,680
Speaker 4: mean it fell in half. The number of public companies

826
00:39:00,680 --> 00:39:02,719
Speaker 4: in America fell in half the in the twenty five

827
00:39:02,800 --> 00:39:05,319
Speaker 4: years or so that our firm was an independent firm.

828
00:39:06,480 --> 00:39:08,440
Speaker 4: So that I don't think that's a good thing. I

829
00:39:08,480 --> 00:39:11,200
Speaker 4: think it's a good positive thing to have more companies

830
00:39:11,200 --> 00:39:14,120
Speaker 4: in the public realm, where there's more information and more

831
00:39:14,200 --> 00:39:16,239
Speaker 4: under you know, transparency to what they do and so on.

832
00:39:16,800 --> 00:39:19,480
Speaker 4: But I think to go from the world of private

833
00:39:19,520 --> 00:39:22,120
Speaker 4: where nobody really knows much about your company to public,

834
00:39:22,239 --> 00:39:25,399
Speaker 4: I think having a lot of you know, a lot

835
00:39:25,400 --> 00:39:29,400
Speaker 4: of sort of activity around that, you know, a big

836
00:39:29,800 --> 00:39:32,280
Speaker 4: almost like pr campaign, you know, lots.

837
00:39:34,080 --> 00:39:36,080
Speaker 2: Kind of video and stand up there on the thing

838
00:39:36,360 --> 00:39:40,120
Speaker 2: and like, yeah, yeah, exactly. It is a bit like that.

839
00:39:40,160 --> 00:39:42,000
Speaker 4: I mean, I remember for our own IPO back in

840
00:39:42,320 --> 00:39:45,680
Speaker 4: two thousand and four, we had like sixty something one

841
00:39:45,719 --> 00:39:48,440
Speaker 4: on one meetings as well as big group meetings and

842
00:39:48,480 --> 00:39:50,840
Speaker 4: places like New York and Boston and so on. But

843
00:39:50,840 --> 00:39:53,319
Speaker 4: if you're trying to get known by a lot of

844
00:39:53,360 --> 00:39:55,840
Speaker 4: investors in a real hurry, you kind of need to

845
00:39:55,880 --> 00:39:58,520
Speaker 4: go through something like that. And you know, and that's

846
00:39:58,560 --> 00:40:00,360
Speaker 4: not like the industry has been some sort of a

847
00:40:00,520 --> 00:40:03,360
Speaker 4: you know, uh, fees are fixed and there's nothing you

848
00:40:03,360 --> 00:40:04,919
Speaker 4: can do about it. I mean, for a long long time,

849
00:40:04,920 --> 00:40:07,080
Speaker 4: an IPO was I remember it was seven percent. That

850
00:40:07,120 --> 00:40:10,960
Speaker 4: was an underwriting commission, you know. I remember we worked

851
00:40:11,280 --> 00:40:13,759
Speaker 4: and advised a Visa when it did what was then

852
00:40:13,760 --> 00:40:16,160
Speaker 4: the biggest IPO in two thousand and probably seven or

853
00:40:16,200 --> 00:40:19,080
Speaker 4: something like that, and that was like a fraction of

854
00:40:19,120 --> 00:40:21,080
Speaker 4: a percent, you know. So the end of it is

855
00:40:21,200 --> 00:40:25,120
Speaker 4: it sort of succumbs to competition, right, And somebody says, Okay, yeah,

856
00:40:24,719 --> 00:40:28,600
Speaker 4: if I'm doing a classic early year Silicon Valley IPO

857
00:40:28,640 --> 00:40:31,200
Speaker 4: and we're raising one hundred million dollars, yes, I think

858
00:40:31,200 --> 00:40:33,480
Speaker 4: a seven million dollar fee is fair for that, And

859
00:40:33,480 --> 00:40:35,480
Speaker 4: probably your competitors feel that way too. It's a lot

860
00:40:35,520 --> 00:40:38,200
Speaker 4: of work, it's a little bit risky. But when you're doing,

861
00:40:38,360 --> 00:40:40,960
Speaker 4: you know, an ip that's in the hundreds of millions,

862
00:40:41,000 --> 00:40:44,200
Speaker 4: the billions, and maybe today the tens or hundreds of billions,

863
00:40:44,600 --> 00:40:46,560
Speaker 4: you know, the fees will be very, very small and

864
00:40:46,640 --> 00:40:48,680
Speaker 4: driven by pretty ferocious competition.

865
00:40:48,760 --> 00:40:52,040
Speaker 3: I'm sure did you say Greenhill iPod in two thousand

866
00:40:52,080 --> 00:40:55,839
Speaker 3: and four. Yes, So that's kind of late, right for well,

867
00:40:56,239 --> 00:40:58,320
Speaker 3: certainly in the context of like some of the larger

868
00:40:58,440 --> 00:41:01,239
Speaker 3: investment banks, because I think by then even Goldman had

869
00:41:01,480 --> 00:41:02,160
Speaker 3: had gone from.

870
00:41:02,000 --> 00:41:03,600
Speaker 4: A vestorship in nineteen ninety nine.

871
00:41:03,680 --> 00:41:06,440
Speaker 3: Yeah, So what was the sort of push pull process

872
00:41:06,440 --> 00:41:09,360
Speaker 3: of actually going public for you? What were the considerations?

873
00:41:09,480 --> 00:41:12,000
Speaker 4: Well, for us, it was that there had been a

874
00:41:12,040 --> 00:41:14,680
Speaker 4: long I mean, obviously some bigger firms like Morgan Stanley

875
00:41:14,680 --> 00:41:16,920
Speaker 4: went public in nineteen eighty six, and I think Goldman

876
00:41:17,000 --> 00:41:20,440
Speaker 4: in ninety nine or something like that. But you know,

877
00:41:20,520 --> 00:41:23,160
Speaker 4: for a firm like Hours that was kind of a smaller,

878
00:41:23,280 --> 00:41:26,719
Speaker 4: more focused firm, the long history of that was that

879
00:41:26,760 --> 00:41:29,520
Speaker 4: you normally sold the firm, and even in its fairly

880
00:41:29,560 --> 00:41:32,160
Speaker 4: early days, you'd kind of build something, you know, prove

881
00:41:32,239 --> 00:41:33,920
Speaker 4: you had a team, Priva, had a brand, prove, you

882
00:41:33,960 --> 00:41:36,279
Speaker 4: had some clients, and you'd go out and sell the firm.

883
00:41:36,320 --> 00:41:38,960
Speaker 4: There were many, many cases that happened, and you know,

884
00:41:39,000 --> 00:41:41,120
Speaker 4: we viewed the IPO as an alternative, and IPO is

885
00:41:41,120 --> 00:41:44,279
Speaker 4: a way to realize the value you had created, but

886
00:41:44,360 --> 00:41:47,640
Speaker 4: also keep what you thought of the special culture. To

887
00:41:47,680 --> 00:41:50,120
Speaker 4: go back to that word, you didn't want to change things,

888
00:41:50,120 --> 00:41:51,960
Speaker 4: You don't want to give up control, et cetera. And

889
00:41:52,040 --> 00:41:53,920
Speaker 4: so that that was really what drove us to go

890
00:41:54,000 --> 00:41:55,640
Speaker 4: public and I think many others as well.

891
00:41:56,080 --> 00:41:59,920
Speaker 3: So when but also in an IPO process, you're raising capital, right,

892
00:42:00,560 --> 00:42:04,759
Speaker 3: what what does capital actually mean for a boutique advisory

893
00:42:04,800 --> 00:42:05,920
Speaker 3: firm Light Green Hill?

894
00:42:06,480 --> 00:42:09,279
Speaker 4: You know, you're you're often that used to be the case.

895
00:42:09,280 --> 00:42:11,759
Speaker 4: That was the original idea that you go public to

896
00:42:11,880 --> 00:42:15,400
Speaker 4: raise capital, and to some extent that's still true. But

897
00:42:15,480 --> 00:42:18,800
Speaker 4: you look at even take these mega you know technology companies,

898
00:42:18,800 --> 00:42:20,759
Speaker 4: stay do they do they need capital? They can raise

899
00:42:20,800 --> 00:42:22,880
Speaker 4: all the capital they want the private markets. So it

900
00:42:22,920 --> 00:42:27,560
Speaker 4: really has evolved from that to wanting liquidity. I would say,

901
00:42:27,600 --> 00:42:28,839
Speaker 4: you want to have a you want to have a

902
00:42:28,920 --> 00:42:32,120
Speaker 4: marker that says here's what my company is worth. Uh,

903
00:42:32,200 --> 00:42:33,919
Speaker 4: and you want to have the liquidity to be able

904
00:42:33,920 --> 00:42:36,560
Speaker 4: to transact at that price in any given day. So

905
00:42:36,760 --> 00:42:40,880
Speaker 4: I think that has driven more I pos in recent

906
00:42:41,000 --> 00:42:44,359
Speaker 4: years than the kind of the earlier notion of wow,

907
00:42:44,400 --> 00:42:46,399
Speaker 4: we need to build a new factory, or we need

908
00:42:46,440 --> 00:42:48,920
Speaker 4: to you know, invest a lot to build an overseas

909
00:42:48,960 --> 00:42:50,840
Speaker 4: business or launch a new brand, so we need to

910
00:42:50,840 --> 00:42:52,080
Speaker 4: do an IPO to raise money.

911
00:42:52,440 --> 00:42:55,000
Speaker 2: Has something changed in the IPO front? Now? I'm just

912
00:42:55,440 --> 00:42:59,359
Speaker 2: maybe I missed it, But I feel like several years ago,

913
00:42:59,640 --> 00:43:02,520
Speaker 2: maybe the mid twenty tens, I still used to hear

914
00:43:02,680 --> 00:43:05,960
Speaker 2: read a lot of stories about so and so won

915
00:43:06,000 --> 00:43:08,359
Speaker 2: the Uber deal, right, or so and so and this

916
00:43:08,400 --> 00:43:10,400
Speaker 2: would be a big thing and they like their flush

917
00:43:10,480 --> 00:43:13,239
Speaker 2: left on the swan or the perspectives.

918
00:43:12,840 --> 00:43:15,560
Speaker 3: Whatever getting or something yeah, and stuff like.

919
00:43:15,520 --> 00:43:17,680
Speaker 2: That used to and how I feel like, I don't

920
00:43:17,800 --> 00:43:20,359
Speaker 2: has something changed there or that's still a thing. Okay,

921
00:43:20,400 --> 00:43:21,560
Speaker 2: that's still that's still a thing.

922
00:43:21,600 --> 00:43:23,360
Speaker 4: You still want to be on the left and but

923
00:43:23,640 --> 00:43:26,120
Speaker 4: you know what, what also, again, the industry became very

924
00:43:26,200 --> 00:43:28,880
Speaker 4: very big, very very competitive, and so you know, it

925
00:43:28,960 --> 00:43:31,520
Speaker 4: used to be like there was one lead underwriter and

926
00:43:31,520 --> 00:43:34,000
Speaker 4: then you got into well, you're the global lead. You're

927
00:43:34,040 --> 00:43:35,080
Speaker 4: the co global lead.

928
00:43:35,120 --> 00:43:40,040
Speaker 2: You're the lead laugh, massive lead. Like everyone everyone gets

929
00:43:40,080 --> 00:43:40,640
Speaker 2: to be a lead.

930
00:43:40,960 --> 00:43:43,320
Speaker 4: It's it's like getting an A at Harvard. I understand

931
00:43:43,320 --> 00:43:45,080
Speaker 4: the pipation for.

932
00:43:45,600 --> 00:43:50,120
Speaker 2: Trophies for the Uber one, like there wasn't There was

933
00:43:50,160 --> 00:43:53,520
Speaker 2: a banker who became an Uber driver. There was remember

934
00:43:53,520 --> 00:43:55,960
Speaker 2: that because he wanted to show that he and like,

935
00:43:56,000 --> 00:43:58,200
Speaker 2: I get it. It's like that's cool. He like really

936
00:43:58,280 --> 00:44:00,600
Speaker 2: like got it. He really took the job seriously and

937
00:44:00,640 --> 00:44:02,600
Speaker 2: he Joe for Uber and stuff like that. But still

938
00:44:02,600 --> 00:44:04,920
Speaker 2: in my mind, I was like, does this really make

939
00:44:04,920 --> 00:44:07,080
Speaker 2: a difference from ubers. They're just selling some shares that

940
00:44:07,120 --> 00:44:11,000
Speaker 2: they're moving on, like it's cute. People used to do

941
00:44:11,040 --> 00:44:11,680
Speaker 2: that sort of thing.

942
00:44:12,160 --> 00:44:14,359
Speaker 4: I think. By the way, I can't remember his name.

943
00:44:14,400 --> 00:44:16,759
Speaker 4: He was kind of slightly after my time, I think,

944
00:44:16,800 --> 00:44:19,440
Speaker 4: but he is. That banker is still at Morgan Stanley

945
00:44:19,480 --> 00:44:21,560
Speaker 4: and is I'm sure going to be the one driving

946
00:44:21,640 --> 00:44:26,400
Speaker 4: the pursuit of Elon Musk's large IPOs to come we should.

947
00:44:28,400 --> 00:44:30,640
Speaker 2: Yeah, he became. He was also he became the Uber

948
00:44:30,880 --> 00:44:33,120
Speaker 2: He became an Uber driver for a while. Yeah, he was.

949
00:44:33,520 --> 00:44:34,319
Speaker 3: He was a big deal.

950
00:44:34,360 --> 00:44:36,680
Speaker 2: And that definitely in the mix today with some of

951
00:44:36,680 --> 00:44:38,080
Speaker 2: these big potential IPOs.

952
00:44:38,120 --> 00:44:40,880
Speaker 3: We should actually talk about league tables, though, because I

953
00:44:40,920 --> 00:44:44,320
Speaker 3: feel like this is sort of perhaps an inordinate amount

954
00:44:44,520 --> 00:44:48,200
Speaker 3: of what an investment banker's life is actually about. And

955
00:44:48,280 --> 00:44:50,520
Speaker 3: back when I was covering the banks, the league tables

956
00:44:50,520 --> 00:44:53,560
Speaker 3: were the things I probably got called up about the most.

957
00:44:53,719 --> 00:44:55,480
Speaker 3: You know, lots of banks explaining to me why the

958
00:44:55,520 --> 00:44:58,560
Speaker 3: league table rankings were not, in fact an accurate reflection

959
00:44:59,120 --> 00:45:02,280
Speaker 3: of their business. How much do those actually matter?

960
00:45:04,280 --> 00:45:06,719
Speaker 4: I think whether you're frankly, if you're number one or

961
00:45:06,760 --> 00:45:09,560
Speaker 4: number four, number seven, you know, we're number nine or

962
00:45:09,560 --> 00:45:14,000
Speaker 4: eleven even, you probably have a pretty equal chance at

963
00:45:14,040 --> 00:45:17,279
Speaker 4: pursuing something. But look, the bankers, do you know, do

964
00:45:17,480 --> 00:45:20,080
Speaker 4: aggressively fight to try to be number one in some

965
00:45:20,360 --> 00:45:23,759
Speaker 4: in something? Right? And but but again with the with

966
00:45:23,840 --> 00:45:27,120
Speaker 4: the increase in just availability of information and transparency, I mean,

967
00:45:27,160 --> 00:45:29,080
Speaker 4: it used to be that, you know, there was a

968
00:45:29,080 --> 00:45:33,080
Speaker 4: lot of gamesmanship around the league tables. You know, you'd say, well,

969
00:45:33,120 --> 00:45:35,719
Speaker 4: we're number one in in uh you know, and I

970
00:45:35,800 --> 00:45:39,080
Speaker 4: pos and you'd look into the footnotes and it would say,

971
00:45:39,120 --> 00:45:42,200
Speaker 4: you know, this includes all deals for you know, radio

972
00:45:42,200 --> 00:45:44,680
Speaker 4: stations with a market cap more than a two hundred

973
00:45:44,680 --> 00:45:46,919
Speaker 4: and fifty million dollars. And you know, if you're trying

974
00:45:46,920 --> 00:45:49,240
Speaker 4: to pitch some media deal or something, and you always

975
00:45:49,280 --> 00:45:51,200
Speaker 4: have some way to slice and dice, like us I

976
00:45:51,239 --> 00:45:55,399
Speaker 4: pos uk, I pos this industry, this deal size. Now

977
00:45:55,400 --> 00:45:57,799
Speaker 4: it's kind of all out there and it's uh, you know,

978
00:45:58,040 --> 00:46:01,520
Speaker 4: but there's there's ten or a dozens that are very,

979
00:46:01,600 --> 00:46:04,600
Speaker 4: very competitive, and the fact that one ranks number one

980
00:46:04,680 --> 00:46:05,879
Speaker 4: versus four is not a big deal.

981
00:46:06,080 --> 00:46:10,080
Speaker 2: It's hilarious. Michael Grimes, he not only drove for Uber,

982
00:46:10,680 --> 00:46:14,680
Speaker 2: he mastered the online game Farmville before Facebook's IPO. They

983
00:46:14,719 --> 00:46:17,640
Speaker 2: spent hours playing that and hey, if that paid off

984
00:46:17,680 --> 00:46:19,359
Speaker 2: for him, good for him. And now he is bad

985
00:46:19,360 --> 00:46:20,920
Speaker 2: because it looks like he'll probably be a.

986
00:46:20,920 --> 00:46:25,239
Speaker 3: Lot of people master Farmville for free with right, he.

987
00:46:26,000 --> 00:46:28,560
Speaker 2: Turned it into something, and I guess it's likely to

988
00:46:28,600 --> 00:46:31,279
Speaker 2: be involved or perhaps positioning himself for a potential role

989
00:46:31,280 --> 00:46:35,200
Speaker 2: into SpaceX IPO. Final question for me, But I'm just curious,

990
00:46:35,280 --> 00:46:37,520
Speaker 2: So like, Okay, we don't know what the future is

991
00:46:37,560 --> 00:46:39,680
Speaker 2: going to look like, but I'm curious, like people you're

992
00:46:39,719 --> 00:46:43,640
Speaker 2: talking to or things you're seeing the AI question, and

993
00:46:43,680 --> 00:46:46,839
Speaker 2: there's some obvious things today anyone knows that you can

994
00:46:46,880 --> 00:46:51,200
Speaker 2: do a very good comp analysis already with almost no knowledge,

995
00:46:51,280 --> 00:46:53,160
Speaker 2: like what are some comps here? And well, maybe that's

996
00:46:53,200 --> 00:46:55,160
Speaker 2: not the kind of output that you would show to

997
00:46:55,200 --> 00:46:57,200
Speaker 2: a client, but it might get your ninety five percent

998
00:46:57,200 --> 00:47:00,480
Speaker 2: of the way there. And so that's that's extraordinary about

999
00:47:01,560 --> 00:47:04,120
Speaker 2: excel files and stuff like that. What else, like, what

1000
00:47:04,160 --> 00:47:06,960
Speaker 2: does it feel like AI is going to do to

1001
00:47:07,040 --> 00:47:09,360
Speaker 2: this space or what would be your guess or where

1002
00:47:09,360 --> 00:47:12,600
Speaker 2: today would you imagine we're already seeing AI change the

1003
00:47:12,680 --> 00:47:13,760
Speaker 2: nature of the job.

1004
00:47:14,040 --> 00:47:16,040
Speaker 4: No one really knows the answer to that question. Of course,

1005
00:47:16,239 --> 00:47:18,719
Speaker 4: is such a fast moving technology. But look, I do

1006
00:47:18,800 --> 00:47:23,320
Speaker 4: think it will change a lot about how bankers interact

1007
00:47:23,360 --> 00:47:26,080
Speaker 4: with clients because the information now is going to go

1008
00:47:26,239 --> 00:47:29,200
Speaker 4: from you know, from kind of available, but you have

1009
00:47:29,239 --> 00:47:31,280
Speaker 4: to sort of work to dig it out to available

1010
00:47:31,400 --> 00:47:33,640
Speaker 4: just literally your fingertips, and by the way, not just

1011
00:47:33,680 --> 00:47:36,200
Speaker 4: to you the banker, but also to your client. So

1012
00:47:36,400 --> 00:47:41,040
Speaker 4: I think differentiating yourself as a banker inside one of

1013
00:47:41,080 --> 00:47:43,320
Speaker 4: these firms or as one of these firms relative to

1014
00:47:43,360 --> 00:47:45,480
Speaker 4: your peers trying to win the IPO, trying to win

1015
00:47:45,520 --> 00:47:47,080
Speaker 4: the M and A deal, trying to win the bond

1016
00:47:47,120 --> 00:47:50,080
Speaker 4: offering is going to be more complicated. You'll you'll have

1017
00:47:50,200 --> 00:47:53,279
Speaker 4: you'll be more efficient in preparing your materials, You'll be

1018
00:47:53,320 --> 00:47:57,080
Speaker 4: more efficient in communicating with that client and delivering you know, interesting,

1019
00:47:57,200 --> 00:48:00,560
Speaker 4: insightful information to them. But a lot of that information

1020
00:48:00,719 --> 00:48:03,080
Speaker 4: is going to look it's going to be commodity like.

1021
00:48:03,680 --> 00:48:06,400
Speaker 4: And so the real challenge is going to be, you know,

1022
00:48:06,400 --> 00:48:09,200
Speaker 4: if a client has access to all the information you do,

1023
00:48:09,239 --> 00:48:11,720
Speaker 4: when they're getting all the feeds of you know, various

1024
00:48:11,760 --> 00:48:13,719
Speaker 4: data they like and so on, and you have a

1025
00:48:13,800 --> 00:48:15,560
Speaker 4: one hour meeting with that client, how are you going

1026
00:48:15,640 --> 00:48:17,880
Speaker 4: to use that meeting? That one hour meeting. You know

1027
00:48:18,320 --> 00:48:20,480
Speaker 4: that they already know a lot as you're walking in there,

1028
00:48:20,480 --> 00:48:22,400
Speaker 4: So how do you use that? It's got to be

1029
00:48:22,440 --> 00:48:27,080
Speaker 4: more about you know, the human dimension, the tactics, why

1030
00:48:27,120 --> 00:48:30,000
Speaker 4: this company may be more amenable to a deal now

1031
00:48:30,040 --> 00:48:31,799
Speaker 4: than they were in the past. You know, things like

1032
00:48:31,840 --> 00:48:34,719
Speaker 4: that that are more about psychology really than about math.

1033
00:48:35,320 --> 00:48:38,400
Speaker 3: I feel like the trend is towards extroverts with large

1034
00:48:38,440 --> 00:48:39,120
Speaker 3: balance sheets.

1035
00:48:39,160 --> 00:48:43,840
Speaker 2: I suppose yes. All right, Scott bo, thank you so

1036
00:48:43,920 --> 00:48:46,440
Speaker 2: much for coming back on the podcast. We love catching

1037
00:48:46,480 --> 00:48:47,799
Speaker 2: up with you, and now we got to do it again.

1038
00:48:48,200 --> 00:48:49,520
Speaker 4: I would love to it's a great probably.

1039
00:48:49,600 --> 00:48:50,080
Speaker 2: Thank you.

1040
00:48:50,280 --> 00:49:03,640
Speaker 5: That's great, Tracy.

1041
00:49:03,680 --> 00:49:04,680
Speaker 2: I love talking to Scott.

1042
00:49:04,719 --> 00:49:05,640
Speaker 3: I yeah, that's great.

1043
00:49:05,880 --> 00:49:09,960
Speaker 2: I'm glad. I'm glad we met Scott. I think just

1044
00:49:10,040 --> 00:49:12,160
Speaker 2: this idea and it came up at the very end

1045
00:49:12,200 --> 00:49:16,040
Speaker 2: about the information asymmetry just being gone, and it feels like,

1046
00:49:16,200 --> 00:49:18,600
Speaker 2: you know, that's not something that is just true with

1047
00:49:18,680 --> 00:49:21,120
Speaker 2: AI now, right, but it feels like there is a

1048
00:49:21,200 --> 00:49:24,719
Speaker 2: version of this story that you could say, going back

1049
00:49:24,719 --> 00:49:28,120
Speaker 2: for the last forty five years, in which decline degradation

1050
00:49:28,280 --> 00:49:31,120
Speaker 2: of the information edge that a bank would have had

1051
00:49:31,120 --> 00:49:34,400
Speaker 2: over its clients for all kinds of different largely you know,

1052
00:49:34,680 --> 00:49:36,439
Speaker 2: technological changes since then.

1053
00:49:36,840 --> 00:49:39,439
Speaker 3: Yeah, I mean I found that conversation fascinating. I guess

1054
00:49:39,480 --> 00:49:44,280
Speaker 3: the two takeaways for me are the first technological revolution

1055
00:49:44,640 --> 00:49:46,799
Speaker 3: in investment banking and the idea that, well, we don't

1056
00:49:46,840 --> 00:49:50,400
Speaker 3: have to spend as many hours like actually pulling physical

1057
00:49:50,960 --> 00:49:54,000
Speaker 3: sec filings or something like that, or looking up quotes

1058
00:49:54,120 --> 00:49:58,320
Speaker 3: on a quotron or whatever, and what replaced that work

1059
00:49:58,480 --> 00:50:02,600
Speaker 3: was more meetings. Right. I feel like humans can always.

1060
00:50:02,920 --> 00:50:05,080
Speaker 2: Find a reason to meet with each other exactly.

1061
00:50:05,840 --> 00:50:08,759
Speaker 3: I know, it's crazy, isn't it ridiculous?

1062
00:50:08,840 --> 00:50:12,640
Speaker 2: Humans just love touching base and any am I maybe

1063
00:50:12,680 --> 00:50:16,440
Speaker 2: I'm revealing my own your own biases, my own biases.

1064
00:50:16,800 --> 00:50:19,120
Speaker 3: I think it's I think it's very good that we

1065
00:50:19,160 --> 00:50:21,200
Speaker 3: have an extrovert and an introvert on the show. We

1066
00:50:21,239 --> 00:50:24,000
Speaker 3: got both sides, both sides of the story. But the

1067
00:50:24,000 --> 00:50:27,760
Speaker 3: other thing I was thinking is the trend towards bigger,

1068
00:50:27,920 --> 00:50:32,320
Speaker 3: bigger balance sheets, more services, the one stop shop idea.

1069
00:50:32,880 --> 00:50:36,000
Speaker 3: And it feels to me like, Okay, if you can't

1070
00:50:36,120 --> 00:50:39,239
Speaker 3: have an informational edge anymore, and if you do have

1071
00:50:39,320 --> 00:50:42,399
Speaker 3: this sort of flattening of culture for various reasons, because

1072
00:50:42,400 --> 00:50:45,440
Speaker 3: everyone's getting smarter and smarter about what a good culture

1073
00:50:45,480 --> 00:50:48,560
Speaker 3: actually looks like and they're able to sort of execute

1074
00:50:48,560 --> 00:50:52,080
Speaker 3: on it in various ways, then it is it feels

1075
00:50:52,080 --> 00:50:53,960
Speaker 3: to me like it's very much going to be fought

1076
00:50:54,040 --> 00:50:55,840
Speaker 3: just on size and scale.

1077
00:50:56,440 --> 00:50:59,880
Speaker 2: You know, I don't think share buybacks are evil to

1078
00:51:00,040 --> 00:51:02,120
Speaker 2: a lot of people do, but it is interesting. We

1079
00:51:02,120 --> 00:51:04,520
Speaker 2: could just go back back. So interesting fact, like I

1080
00:51:04,520 --> 00:51:06,960
Speaker 2: always forget that that they haven't been around that long,

1081
00:51:07,200 --> 00:51:10,160
Speaker 2: that they were seeing as market manipulation at one point,

1082
00:51:10,600 --> 00:51:12,680
Speaker 2: we could just ban them. I mean, the fact that

1083
00:51:13,400 --> 00:51:16,520
Speaker 2: capitalism worked fine for a very long time without share back.

1084
00:51:16,760 --> 00:51:20,279
Speaker 2: Share buybacks would probably be probably wouldn't be the end

1085
00:51:20,320 --> 00:51:20,720
Speaker 2: of the world.

1086
00:51:20,760 --> 00:51:22,920
Speaker 3: We should do another episode on this, but that reminds me.

1087
00:51:23,320 --> 00:51:26,360
Speaker 3: The other thing I was thinking was this idea that like, well,

1088
00:51:26,680 --> 00:51:30,440
Speaker 3: we had an entire I mean multiple industries really that

1089
00:51:30,520 --> 00:51:35,560
Speaker 3: grew up whose entire sense of purpose was about doing transactions. Right,

1090
00:51:35,600 --> 00:51:37,400
Speaker 3: So you have the traditional Wall Street banks, but then

1091
00:51:37,440 --> 00:51:40,880
Speaker 3: you had private equity and private credit, and so you

1092
00:51:41,000 --> 00:51:44,160
Speaker 3: just have this explosion in deals.

1093
00:51:44,239 --> 00:51:45,920
Speaker 2: I wonder, if Michael Grimes is going to ride on

1094
00:51:45,960 --> 00:51:49,279
Speaker 2: a rocket to get the lot to space, he's gonna

1095
00:51:49,320 --> 00:51:52,680
Speaker 2: he's gonna do a little space joy ride. So to

1096
00:51:52,680 --> 00:51:53,200
Speaker 2: get that.

1097
00:51:53,400 --> 00:51:53,920
Speaker 5: It was one thing.

1098
00:51:53,960 --> 00:51:56,040
Speaker 2: Oh you know what I thought was also very interesting,

1099
00:51:56,600 --> 00:51:59,440
Speaker 2: and I think this says a lot about culture in

1100
00:51:59,520 --> 00:52:03,080
Speaker 2: general on just banking. The idea that at one point,

1101
00:52:03,760 --> 00:52:06,040
Speaker 2: for better or worse, and maybe for better, and that

1102
00:52:06,080 --> 00:52:09,799
Speaker 2: there were like clients that the banks wouldn't touch, but

1103
00:52:09,880 --> 00:52:12,799
Speaker 2: they end that they're like, no, we're above this, this

1104
00:52:12,880 --> 00:52:14,239
Speaker 2: is not what we do here.

1105
00:52:14,320 --> 00:52:17,520
Speaker 3: Well, some of them had investigators, like on staff to

1106
00:52:17,560 --> 00:52:19,680
Speaker 3: go out and investigate potential clients.

1107
00:52:19,800 --> 00:52:22,759
Speaker 2: I think that's really interesting and a certain level of

1108
00:52:23,040 --> 00:52:24,759
Speaker 2: you know what we're going to leave some money off

1109
00:52:24,760 --> 00:52:27,600
Speaker 2: the table because this is not what we do here.

1110
00:52:28,080 --> 00:52:30,960
Speaker 2: We have standards and so forth. And I do feel

1111
00:52:31,000 --> 00:52:36,000
Speaker 2: like these days it's just money. It's just across the board,

1112
00:52:36,680 --> 00:52:39,839
Speaker 2: it's just accumulating more and more money, and so the

1113
00:52:39,880 --> 00:52:43,000
Speaker 2: idea of some money isn't good enough for here, Like

1114
00:52:43,040 --> 00:52:46,120
Speaker 2: it does not feel like that's a thing anymore. Maybe. Well,

1115
00:52:46,320 --> 00:52:49,879
Speaker 2: I think a lot of people would say in retrospect,

1116
00:52:49,960 --> 00:52:52,200
Speaker 2: people they should have had better standards about who they

1117
00:52:52,200 --> 00:52:52,759
Speaker 2: do business with.

1118
00:52:52,920 --> 00:52:55,920
Speaker 3: Yeah, it feels much more a moral now. And I

1119
00:52:55,960 --> 00:52:58,080
Speaker 3: mean that in the sense that like there's a possibility

1120
00:52:58,080 --> 00:53:01,200
Speaker 3: that people hide behind that say, like, well, we shouldn't

1121
00:53:01,239 --> 00:53:05,279
Speaker 3: be making qualitative decisions about our clients. We're just here to,

1122
00:53:05,920 --> 00:53:09,239
Speaker 3: you know, share the good gospel of capitalism. Yeah, all right,

1123
00:53:09,280 --> 00:53:10,120
Speaker 3: shall we leave it there.

1124
00:53:10,280 --> 00:53:11,040
Speaker 2: Let's leave it there.

1125
00:53:11,160 --> 00:53:13,440
Speaker 3: This has been another episode of the Odd Lots podcast.

1126
00:53:13,560 --> 00:53:16,680
Speaker 3: I'm Tracy Alloway. You can follow me at Tracy Alloway.

1127
00:53:16,480 --> 00:53:19,160
Speaker 2: And I'm Jill Wisenthal. You can follow me at the Stalwart.

1128
00:53:19,360 --> 00:53:22,480
Speaker 2: Follow our producers Carmen Rodriguez at Carman armand desh Ol

1129
00:53:22,480 --> 00:53:26,360
Speaker 2: Bennett at Dashbot and Kilbrooks at Kilbrooks more odd Laws content.

1130
00:53:26,440 --> 00:53:28,600
Speaker 2: Go to Bloomberg dot com slash odd Lots with the

1131
00:53:28,680 --> 00:53:31,000
Speaker 2: daily newsletter and all of our episodes, and you can

1132
00:53:31,080 --> 00:53:32,919
Speaker 2: chat about all of these topics twenty four to seven

1133
00:53:33,000 --> 00:53:36,240
Speaker 2: in our discord Discord dot gg slash odlines.

1134
00:53:36,600 --> 00:53:38,640
Speaker 3: And if you enjoy odd Lots, if you like it

1135
00:53:38,760 --> 00:53:41,640
Speaker 3: when we talk about the business and culture of investment banking,

1136
00:53:41,719 --> 00:53:44,160
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1137
00:53:44,200 --> 00:53:47,520
Speaker 3: podcast platform. And remember, if you are a Bloomberg subscriber,

1138
00:53:47,600 --> 00:53:50,399
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1139
00:53:50,719 --> 00:53:52,880
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1140
00:53:52,920 --> 00:53:56,120
Speaker 3: on Apple Podcasts and follow the instructions there. Thanks for

1141
00:53:56,239 --> 00:54:21,960
Speaker 3: listening in in