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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is Master's in

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Speaker 1: Business with Barry rid Hoolts on Bloomberg Radio.

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Speaker 2: This week on the podcast What a Fascinating Conversation, Iva

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Speaker 2: Shang co founded legal List while she was in Harvard

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Speaker 2: and then subsequently dropped out with her co founder to

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Speaker 2: launch what essentially became an alternative credit fund that specialized

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Speaker 2: in litigation financing along with two other types of credit

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Speaker 2: related to litigation outcomes. Really a fascinating combination of legal

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Speaker 2: insight and technology. Initially, this began just by scraping the

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Speaker 2: State of Massachusetts judicial websites, all the different cases that

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Speaker 2: were there, the different motions, who the lawyers were on

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Speaker 2: each side, and they had no idea what they were

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Speaker 2: going to do with this data until eventually they go

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Speaker 2: to Y combinator and general counsel there says no, you

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Speaker 2: have a gold mine here, and it's you have to

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Speaker 2: focus on financing the litigation cases with a high probability

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Speaker 2: of a successful outcome, but where the planiff doesn't have

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Speaker 2: the capital to see it through and are up against

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Speaker 2: the deep pocketed defendant who could just wait them out.

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Speaker 2: I found even to be just very interesting and I'm

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Speaker 2: intrigued by the business model. They created really a white

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Speaker 2: space that a handful of multistrat funds might have been

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Speaker 2: doing something with, but there really wasn't a dedicated old

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Speaker 2: credit fund, especially one with nearly a billion dollars in

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Speaker 2: client assets, focusing on I found this to be really

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Speaker 2: fascinating and I think you will also, with no further

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Speaker 2: ado my discussion with Legalists.

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Speaker 1: Eva Shang, thank you so much for having me.

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Speaker 2: So let's just go to Cambridge and talk about you

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Speaker 2: drop out of Harvard at the age of twenty to

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Speaker 2: start an alternative investment funds. What were you thinking?

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Speaker 1: That's a great question. So back in the day, my

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Speaker 1: co founder, Christian was actually the one who came up

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Speaker 1: with the first seedlings of the idea to start Legalist.

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Speaker 1: And what happened was he was very interested in data scraping,

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Speaker 1: and he had taken some classes with a CS professor

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Speaker 1: who did data scraping, and one day he decided to

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Speaker 1: scrape the Massachusetts State Court record website. Now, this is

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Speaker 1: a website that had cost the state seventy million dollars

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Speaker 1: to make, and it was extremely janky, and his intent

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Speaker 1: was just to download all the information and then see

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Speaker 1: what he could do with it. But keep in mind

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Speaker 1: he didn't have access to any of the standard web

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Speaker 1: scraping equipment. He didn't have access to Amazon Web Services

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Speaker 1: or cloud hosting. So he just bought these two mini's,

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Speaker 1: which are like Mac computers that don't have a little rouse,

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Speaker 1: yes exactly, and he just set them up and started

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Speaker 1: trying to download and scrape all the information. Now, as

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Speaker 1: it turns out, he was downloading at too high of

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Speaker 1: a pace, and so Harvard caught on to the fact

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Speaker 1: that there were just massive gigabytes of information passing through

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Speaker 1: to this one dorm room in Dunster, and so he

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Speaker 1: came to me and said, Uh, would you mind if

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Speaker 1: I just put these computers in your dorm room and

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Speaker 1: then they can sit in your corner and then scrape

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Speaker 1: using your Internet. And I was like, what's going on here?

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Speaker 1: And so that's kind of how I got roped into

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Speaker 1: this business where we decided to form a corporation and

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Speaker 1: our intent was just to download the data and then

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Speaker 1: question mark question mark.

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Speaker 2: So so you had no idea where this was going

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Speaker 2: to go.

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Speaker 1: Initially, we had no idea.

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Speaker 2: Let's see what happens. And that's just with the with Massachusetts, right,

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Speaker 2: will you also involved in y Combinator while you were

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Speaker 2: at Harvard as well?

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Speaker 1: Yes, So we got into y Combinator the summer of

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Speaker 1: twenty sixteen just off of this legal analytics idea. And

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Speaker 1: after we got into y Combinator, basically the very first day,

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Speaker 1: the general counsel, who kind of keeps a watch over

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Speaker 1: all the legal tech companies, pulls us aside and is like,

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Speaker 1: I don't think your business idea is very good. I

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Speaker 1: don't think this legal analytics thing is going to work

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Speaker 1: out for you. Lawyers hate to pay for things. They

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Speaker 1: like to get paid for things. I don't think you

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Speaker 1: should be doing this. And we were like, well, we

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Speaker 1: just got here, so we're going to do our old idea,

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Speaker 1: thank you very much. But throughout the course of the summer,

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Speaker 1: he kept on saying to us, you should really consider

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Speaker 1: getting into this area called litigation finance. And eventually we

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Speaker 1: realize the same thing that he did, which is that

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Speaker 1: lawyers don't like to pay for things. And we were like, okay,

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Speaker 1: so what should we do. And basically what he said was,

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Speaker 1: if you're able to have this real time coverage of

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Speaker 1: all these hard to access court dockets, than what you

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Speaker 1: could do theoretically is pick out the cases that are

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Speaker 1: going really really well and invest in those so you

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Speaker 1: can take your own portfolio.

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Speaker 2: That raises the question, if they're going really really well,

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Speaker 2: why would anybody want to take outside funding when they

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Speaker 2: want to see it through and maximize their returns. Or

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Speaker 2: are these so expensive that even the cases that are

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Speaker 2: going well need a little outside financial help.

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Speaker 1: So I think when people think about litigation, they imagine

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Speaker 1: how it is in the movies, where you file a

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Speaker 1: case and then you go to trial the next day

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Speaker 1: and then judge here's your case. So in reality, what

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Speaker 1: happens is, you know, let's just take a prototypical scenario

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Speaker 1: where you have a business that gets acquired and I'm

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Speaker 1: the founder. I've been working on this business for a

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Speaker 1: long time, and after the acquisition, the company that acquired

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Speaker 1: us strips away all our resources, so then I don't

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Speaker 1: hit my earnout and that's part of the acquisition price.

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Speaker 1: And now I file a lawsuit thinking that tomorrow I'm

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Speaker 1: going to get my ten million dollar earn out. But

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Speaker 1: in the meantime, not only have I not been paid

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Speaker 1: my earnout, but I also don't have money to pay

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Speaker 1: my lawyer, and so I might screep together some change,

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Speaker 1: get the complaint filed, the case is going well, you

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Speaker 1: survive some initial motions, but trial is still two years away.

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Speaker 1: And so that's really where a litigation funder could come

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Speaker 1: in and say, okay, leave the legal fees to us.

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Speaker 1: Not only will we pay for it, we'll keep your

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Speaker 1: lawyer on a budget, we'll make sure the case stays

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Speaker 1: on track, we'll offer our analysis of it compared to

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Speaker 1: the thousands of other cases we've evaluated, and we'll make

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Speaker 1: sure that we're your partner until the end.

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Speaker 2: What does the founder have to give up in exchange

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Speaker 2: for all that financial support? What is legalists share of

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Speaker 2: the outcome.

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Speaker 1: So the way that litigation finance works is that it

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Speaker 1: is non recourse, which means that if we invest into

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Speaker 1: litigation and it loses, then we don't get repaid.

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Speaker 2: All the risk is on you, exactly.

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Speaker 1: But if the litigation wins, then we share in the upside.

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Speaker 1: So we normally aim to take around thirty or forty

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Speaker 1: percent of the case, depending on how long it goes for.

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Speaker 2: So it's almost as if it's a lawyer charging a

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Speaker 2: contingency fee. Exactly, Hey, you don't have to pay me

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Speaker 2: any legal fees for this car accident, but if we win,

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Speaker 2: I take a third of the outcome.

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Speaker 1: Exactly exactly, And there are types of cases that lawyers

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Speaker 1: take on contingency. Frequently contingency lawyers are the original litigation funders,

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Speaker 1: but in order to put together a diversified portfolio, they

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Speaker 1: only have so much time, and so they usually do

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Speaker 1: things like personal injury, employment, class action, things that are

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Speaker 1: predictable in which where they have a lot of control

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Speaker 1: and cases settle quickly an earnout case or a commercial

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Speaker 1: case or a breach of contract case. Those costs hundreds

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Speaker 1: of thousands, if not millions of dollars, and lawyers don't

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Speaker 1: really want to put in all that time for free.

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Speaker 2: So you're y combinator over the summer, when do you decide, Hey,

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Speaker 2: this is a real business and I think I should

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Speaker 2: drop out of Harvard to do this.

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Speaker 1: Yeah. So, after we decided to switch to doing litigation funding,

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Speaker 1: we went to John Levey, who's the general counsel at YC,

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Speaker 1: and we were like, Okay, what do you know about

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Speaker 1: litigation funding? And he said, the only reason I know

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Speaker 1: about it is because I have friends who work in

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Speaker 1: insurance and insurance is the mirror image of litigation funding,

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Speaker 1: except for the defense side. They keep the lawyers on track,

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Speaker 1: they pay the defense costs, and they really don't like

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Speaker 1: that litigation funding now exists for the plaintiffs.

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Speaker 2: Right because they have a giant financial advantage being part

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Speaker 2: of a exactly big perpetual insurance company versus lawyers come and.

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Speaker 1: Go exactly So that was pretty much all we needed

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Speaker 1: to hear to actually make the switch. But then once

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Speaker 1: we made the switch, it was a lot more challenging

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Speaker 1: than we initially expected to actually raise a fund. There's

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Speaker 1: that John F. Kennedy quote where he says, you know,

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Speaker 1: we go to the moon. We choose to go to

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Speaker 1: the moon not because it is easy, but because it

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Speaker 1: is hard. I think a lot of startup founders are

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Speaker 1: actually the opposite, where it's like, we choose to go

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Speaker 1: to the moon not because it's easy, but because we

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Speaker 1: think it's going to be easy. I think if we

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Speaker 1: had known how difficult they would be for two twenty

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Speaker 1: year olds to raise a fund to invest in litigation,

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Speaker 1: it was just such a crazy idea at the time

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Speaker 1: that we would have been like, yeah, no, thank you,

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Speaker 1: we'll do something else.

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Speaker 2: So when you launched, there aren't a whole lot of

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Speaker 2: dedicated litigation finance funds. But you've become successful, are you

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Speaker 2: attracting competition or other people saying, Hey, we didn't realize

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Speaker 2: this was so doable. What's it look like out there?

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Speaker 1: So at the time that we launched, there were already

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Speaker 1: public companies that were doing litigation finance. One of our

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Speaker 1: LPs likes to say he likes to say that he

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Speaker 1: invests in managers where it's so time consuming and difficult

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Speaker 1: to do what they've done that no one in their

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Speaker 1: right mind would do it, And if they could go

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Speaker 1: back in time and redo it, even the founders wouldn't

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Speaker 1: do it over again. And I kind of think that

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Speaker 1: our business is a lot like that. If you were

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Speaker 1: to go into litigation finance at the outset, you would

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Speaker 1: not want to raise a really small litigation finance fund,

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Speaker 1: hire an engineering team, build an algorithm, scrape millions of

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Speaker 1: court records, do hundreds of investments in a given fund.

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Speaker 1: You would do what all the other litigation funders do,

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Speaker 1: which is invest in ten big cases with law firms

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Speaker 1: that you're familiar with.

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Speaker 2: Huh, really interesting, So you drop out of Harvard is

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Speaker 2: that twenty seventeen.

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Speaker 1: We drop out of Harvard in twenty sixteen, and it

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Speaker 1: takes us a full year to raise our first ten

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Speaker 1: million dollar fund in twenty seventeen.

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Speaker 2: Wow, So stay with dropping out of college. First of all,

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Speaker 2: what did your parents say? They must have been bereft.

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Speaker 1: My parents are immigrants, and so they feel like playing

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Speaker 1: it safe is always the way to go. But while

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Speaker 1: I was at Harvard, it quickly became apparent to me

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Speaker 1: that nothing you do plays it safe. Like you can

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Speaker 1: either be in lockstep with everyone else and do the

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Speaker 1: whole recruiting for a consulting firm and then working at

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Speaker 1: a consulting firm and then going to business school and

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Speaker 1: then you know, ascending the ladder and not take any chances,

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Speaker 1: or you can choose to do something else. And for

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Speaker 1: a long time I didn't know what that something else

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Speaker 1: would be. And when it presented itself to me, it

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Speaker 1: became very obvious that this is the direction the universe

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Speaker 1: was calling for me to go in.

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Speaker 2: Huh. So you raised ten million in your first year?

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Speaker 2: Ten million? Is that right?

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Speaker 1: That's right?

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Speaker 2: The first year? And then you are involved with the

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Speaker 2: Field Fellowship. Peter Thield's award to young people who he's

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Speaker 2: looking to, Hey, get out in the real world. You

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Speaker 2: don't need to go to school. Was how helpful was

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Speaker 2: Peter Teel's capital?

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Speaker 1: So the Teal Fellowship is a one hundred thousand dollars

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Speaker 1: grant that's given to people who drop out of school.

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Speaker 1: It's given to the individual rather than to the company.

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Speaker 1: But it did create a little bit of a problematic

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Speaker 1: situation for us early on because he was known for

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Speaker 1: his own litigation funding situation.

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Speaker 2: Well, the whole thing with what took place with Crocker

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Speaker 2: and Paul Cogan. There even was a book, right and

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Speaker 2: if that was actually quite fascinating.

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Speaker 1: But it's not actually litigation funding, that's right. That case

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Speaker 1: is not that a grudge, yes.

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Speaker 2: As a personal grudge, and it just goes to show

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Speaker 2: you even when only two people know a secret, it

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Speaker 2: still eventually comes out, which which is was my big

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Speaker 2: takeaway from that book. But back to the fellowship, did

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Speaker 2: it help you raise other assets that people say, oh,

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Speaker 2: Peter Teel is successful if he's putting money into EVA,

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Speaker 2: well he must see something there.

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Speaker 1: Not really, but we did get a lot of questions

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Speaker 1: about whether we were going to be suing media companies,

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Speaker 1: and the answer was always no, media companies are.

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Speaker 2: Not usually very That wasn't especially profitable, It just that

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Speaker 2: was that was you know, when you sue a small

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Speaker 2: website into oblivion, there's not a lot of cash to

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Speaker 2: pay back. That was just I'm going to spend what

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Speaker 2: it takes because I'm not happy with these people. You

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Speaker 2: guys are in business looking for an economic outcome, that's right,

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Speaker 2: not a personal outcome. So sounds like the first year

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Speaker 2: of raising capital for Legalist was very challenging. At any point,

249
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Speaker 2: were you thinking, hey, maybe I should go back to college,

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Speaker 2: maybe I should go to law school, and were you

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Speaker 2: Were you ever thinking about taking the bar or going

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Speaker 2: to law school.

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Speaker 1: So I was thinking of going to law school. But

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Speaker 1: what ended up happening was that in California there is

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Speaker 1: a Law Office study program where you can apprentice under

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Speaker 1: a lawyer and you have to study for a certain

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Speaker 1: number of hours per week. And Christian and I ended

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Speaker 1: up doing the Law Office apprenticeship program starting in twenty

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Speaker 1: eighteen with our general counsel at the time, Curtis.

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Speaker 2: And YC or Legalist GC.

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Speaker 1: LEGALISTGC, and that took us almost five years and then

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Speaker 1: We ended up taking the bar exam last year and

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Speaker 1: we both passed. Oh that's so now we actually are lawyers.

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Speaker 2: That's amazing that you went that route instead of going

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Speaker 2: to finishing college and going to law school. Tell us

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Speaker 2: a little bit about your partner, Christian hay Am I

267
00:14:44,840 --> 00:14:45,360
Speaker 2: pronouncing that.

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Speaker 1: Right now, Christian hag Haigu.

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Speaker 2: So he's your co founder. He's the person who was

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Speaker 2: initially scraping all the data off of the Massachusetts court

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Speaker 2: system websites. He sounds more like a computer science che

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Speaker 2: then a legal geek. What was his background and tell

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Speaker 2: us a little bit about how you guys met.

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Speaker 1: So Christian was studying economics and computer science and I

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Speaker 1: actually think he's incredibly operationally minded and just one of

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Speaker 1: the smartest people I've ever met. And the crazy thing

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Speaker 1: is that we've known each other for over ten years

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Speaker 1: at this point, and it's definitely one of the most

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Speaker 1: important relationships in my life. And when there's a fire

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Speaker 1: at the company, when the two of us leap into

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Speaker 1: action to solve it, there's really nothing like it. It's

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Speaker 1: like when you have someone that you've worked with for

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Speaker 1: so long and you basically know what they're going to say.

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Speaker 1: Or think before they actually say it. And over the years,

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Speaker 1: a lot of people that I've talked to disparage these

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Speaker 1: fifty to fifty partnerships because I think they think it's

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Speaker 1: riskier if you can't come to an agreement. And what

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Speaker 1: I actually think is that anything that's so worth doing

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Speaker 1: has a lot of inherent risk, and so if you

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Speaker 1: make a partnership work, it can actually work much better

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Speaker 1: than just having one person be in charge. So I'll

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Speaker 1: tell a story about why I think it's so difficult

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Speaker 1: to do what we do, or to even just start

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Speaker 1: a business so young alone. So I mean, for the record,

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Speaker 1: today we have over four hundred investments and seventy five

296
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Speaker 1: percent success rate, hundreds of realizations. But back in the

297
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Speaker 1: day when we had our very first case lose, it

298
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Speaker 1: was only one hundred and fifty thousand dollars investment, but

299
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Speaker 1: it was our very first loss, and it meant a

300
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Speaker 1: lot to us because it threw into question our entire

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Speaker 1: business model.

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Speaker 2: Was that your first investment, or was that your first

303
00:16:43,160 --> 00:16:46,400
Speaker 2: loss then you had subsequent you had previous winners to that.

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Speaker 1: It was one of the early cases and it was

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00:16:49,160 --> 00:16:53,640
Speaker 1: our first loss. So I just remember feeling like the

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00:16:53,760 --> 00:16:57,080
Speaker 1: entire world was falling, and we were also so young

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Speaker 1: that we hadn't been through a lot of bad things

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Speaker 1: happen in our life. And so Christian and I we

309
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Speaker 1: snuck into the back of a Costco because we didn't

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Speaker 1: have a Costco membership, and then we bought those one

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Speaker 1: dollar fifty hot dogs that they sell at Costco, and

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Speaker 1: then we ate it for dinner more roastly, and we

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Speaker 1: were like, this is the dinner we deserve. And I

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Speaker 1: can't imagine what I would have done if I had

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Speaker 1: been doing this alone. So that's why I think a

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Speaker 1: lot of people warn't against partnerships because of the two

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Speaker 1: sigma problem where you can't get along with your partner,

318
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Speaker 1: then the whole firm collapses. But to us, I think

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Speaker 1: it's one of our major superpowers.

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Speaker 2: Huh. Really interesting. So the initial strategy of litigation finance

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Speaker 2: comes from the general council at Y Combinator. Why did

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Speaker 2: do you think it took so long to convince you

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Speaker 2: that that was the way to monetize the tech that

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Speaker 2: you guys had developed scraping state judicial records.

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Speaker 1: Litigation finance is a very obscure asset class. It's really

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Speaker 1: not the first thing that a college kid would think

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Speaker 1: of as a business to run. And I also think

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Speaker 1: that one of the features of being young is that

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00:18:08,720 --> 00:18:12,080
Speaker 1: you can't recognize or understand good advice, even when it

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00:18:12,119 --> 00:18:15,320
Speaker 1: comes your way. I remember there was one other hedge

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Speaker 1: fund that did credit on these p top lending platforms

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Speaker 1: that was a few years ahead of us, and back

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00:18:22,320 --> 00:18:24,080
Speaker 1: when we were trying to raise our first fund, they

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00:18:24,080 --> 00:18:27,720
Speaker 1: had already raised a few hundred million. So I went

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00:18:27,760 --> 00:18:30,840
Speaker 1: to their office and I was like, give me your advice.

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Speaker 1: How did you do it? And the two tidbits that

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00:18:34,240 --> 00:18:37,640
Speaker 1: I remember from that conversation where he was like, I've

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00:18:37,640 --> 00:18:41,760
Speaker 1: got this really nice, expensive pair of shoes, they're like

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00:18:41,800 --> 00:18:45,480
Speaker 1: seven hundred dollars, and I also have these business cards

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00:18:45,680 --> 00:18:49,040
Speaker 1: that are very professional and they have just a lot

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Speaker 1: of heft and texture. And it took a really long

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00:18:53,000 --> 00:18:56,080
Speaker 1: time for the moral of that story to actually become

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Speaker 1: apparent to me, because I was perplexed by this information

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Speaker 1: for just such a long time, and it was only

345
00:19:02,280 --> 00:19:05,119
Speaker 1: years later that I was like, Oh, what he's really

346
00:19:05,160 --> 00:19:08,240
Speaker 1: saying is when you're young, you should try to look

347
00:19:08,280 --> 00:19:13,520
Speaker 1: professional and institutional and reassure investors, especially LP investors, that

348
00:19:13,560 --> 00:19:15,679
Speaker 1: you're not going to lose their money. And he was

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00:19:15,760 --> 00:19:17,800
Speaker 1: using those details to make a point, but I was

350
00:19:17,880 --> 00:19:21,159
Speaker 1: just too naive to understand what he was actually saying.

351
00:19:21,400 --> 00:19:22,959
Speaker 1: So I think a lot of advice is like that.

352
00:19:23,000 --> 00:19:24,960
Speaker 1: If it comes to you at the wrong time, it's

353
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Speaker 1: as good as if you didn't hear it at all.

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Speaker 2: It's very hard to take advice when you're young, because

355
00:19:30,080 --> 00:19:32,840
Speaker 2: you don't have a frame of reference, right, You don't

356
00:19:32,880 --> 00:19:36,880
Speaker 2: have the breath of hear the range of possibilities right.

357
00:19:37,080 --> 00:19:40,720
Speaker 2: And that's why this advice is really useful for someone

358
00:19:40,760 --> 00:19:45,720
Speaker 2: who's been through that. Really very very interesting. Now you're

359
00:19:45,760 --> 00:19:49,640
Speaker 2: almost the firm is almost ten years old. What sort

360
00:19:49,640 --> 00:19:52,560
Speaker 2: of advice are you getting now that you might be

361
00:19:52,560 --> 00:19:56,840
Speaker 2: paying more attention to that in twenty sixteen, twenty seventeen

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00:19:57,480 --> 00:20:00,000
Speaker 2: just went right by without a whole lot of notice.

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00:20:01,000 --> 00:20:06,800
Speaker 1: I remember one of our advisors in LPs, who's a billionaire,

364
00:20:06,880 --> 00:20:10,119
Speaker 1: came by our office and I was like, what's the

365
00:20:10,160 --> 00:20:12,600
Speaker 1: secret to your success? And this is when I think

366
00:20:12,600 --> 00:20:15,119
Speaker 1: I must have been like twenty two or so, and

367
00:20:15,160 --> 00:20:18,000
Speaker 1: he was like, hire good people and retain them. And

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00:20:18,040 --> 00:20:21,800
Speaker 1: I was like, well, obviously, what else? And then the

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00:20:22,400 --> 00:20:25,560
Speaker 1: farther I get into the business, the more I'm like, oh, yeah,

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00:20:25,560 --> 00:20:28,480
Speaker 1: that is the main thing. It's just that when you're

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00:20:28,520 --> 00:20:31,680
Speaker 1: at that stage, it's not apparent to you exactly how

372
00:20:31,680 --> 00:20:32,280
Speaker 1: to apply it.

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Speaker 2: And that's really interesting. One of the things you don't

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00:20:35,080 --> 00:20:38,200
Speaker 2: realize when you are making your first I don't know

375
00:20:38,320 --> 00:20:42,000
Speaker 2: ten hires, first dozen HighRes that five or ten years

376
00:20:42,040 --> 00:20:45,640
Speaker 2: down the road, that group of people you're hiring are

377
00:20:45,720 --> 00:20:48,920
Speaker 2: going to be the ones doing the subsequent hiring yeah road,

378
00:20:49,320 --> 00:20:52,960
Speaker 2: And you just can't anticipate that until you've lived through it,

379
00:20:53,000 --> 00:20:55,919
Speaker 2: and then it's like, wow, those were really important hires

380
00:20:55,960 --> 00:20:58,720
Speaker 2: that first you know five or ten people. It makes

381
00:20:58,760 --> 00:21:01,719
Speaker 2: such it sets the time for everything going forward, and

382
00:21:01,760 --> 00:21:04,119
Speaker 2: there's no way to understand that until you've lived it.

383
00:21:04,320 --> 00:21:07,160
Speaker 2: Maybe that's where the advice aspect comes in.

384
00:21:07,560 --> 00:21:12,000
Speaker 1: I also think that the cohesion of an organization is

385
00:21:12,040 --> 00:21:17,760
Speaker 1: so much more important than how talented the individual parts are.

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00:21:18,320 --> 00:21:21,840
Speaker 1: So there's this children's book called Enders Game, which I've

387
00:21:21,840 --> 00:21:23,159
Speaker 1: always loved. You reread it.

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00:21:23,320 --> 00:21:25,520
Speaker 2: I don't know if I would call that a children's book.

389
00:21:25,920 --> 00:21:30,120
Speaker 2: I mean it's a sci fi book scott orson Cards.

390
00:21:30,000 --> 00:21:34,760
Speaker 1: Or scott Card. Yeah, but in Enders Game you'll notice

391
00:21:34,800 --> 00:21:38,320
Speaker 1: that at the very end, they don't bring in the

392
00:21:38,359 --> 00:21:43,000
Speaker 1: top kids from every class they alert. Yeah, and when

393
00:21:43,000 --> 00:21:45,760
Speaker 1: they're actually battling the aliens for the final battle on

394
00:21:45,840 --> 00:21:47,960
Speaker 1: behalf of all of humanity. I'm outing myself as a

395
00:21:48,000 --> 00:21:51,480
Speaker 1: huge nerd here, but they bring in Ender's closest friends.

396
00:21:51,840 --> 00:21:52,439
Speaker 1: And these are.

397
00:21:52,280 --> 00:21:56,160
Speaker 2: People that he respects, not just one person, because all

398
00:21:56,240 --> 00:22:02,320
Speaker 2: these any challenge against high are high odds. It's never

399
00:22:02,960 --> 00:22:06,000
Speaker 2: just Michael Jordan. It's got to be everybody around him,

400
00:22:06,160 --> 00:22:08,880
Speaker 2: right right, And if you look at I don't want

401
00:22:08,880 --> 00:22:12,880
Speaker 2: to go into sports metaphors because occasionally Michael Jordan can

402
00:22:12,920 --> 00:22:15,560
Speaker 2: carry a team, but even the Bulls didn't start winning

403
00:22:15,640 --> 00:22:17,879
Speaker 2: until he had good players around him, and it made

404
00:22:17,920 --> 00:22:18,600
Speaker 2: a big difference.

405
00:22:19,080 --> 00:22:24,040
Speaker 1: Yeah, And I always wondered why huge bureaucracies could sometimes

406
00:22:24,119 --> 00:22:27,600
Speaker 1: lose to startups, and it's because there's so much internal

407
00:22:27,840 --> 00:22:31,199
Speaker 1: energy that's spent fighting each other, and the lack of

408
00:22:31,240 --> 00:22:34,240
Speaker 1: cohesion means that you can't all row the boat in

409
00:22:34,280 --> 00:22:37,360
Speaker 1: the same directions. There's actually energy working against each other.

410
00:22:38,000 --> 00:22:40,920
Speaker 1: And that's one of the reasons why many of our

411
00:22:40,920 --> 00:22:45,520
Speaker 1: employees have been with the firm for five plus years

412
00:22:45,960 --> 00:22:49,080
Speaker 1: and why that kind of trust and loyalty and culture

413
00:22:49,520 --> 00:22:52,639
Speaker 1: is I think the root of what enables everything we

414
00:22:52,720 --> 00:22:53,200
Speaker 1: do today.

415
00:22:53,600 --> 00:22:57,520
Speaker 2: Let's talk a little bit about the process of litigation

416
00:22:57,880 --> 00:23:02,639
Speaker 2: financing and some of your other strategies. The flagship strategy

417
00:23:02,720 --> 00:23:07,439
Speaker 2: obviously litigation financing. You mentioned you've done about four hundred

418
00:23:07,640 --> 00:23:08,600
Speaker 2: financing so far.

419
00:23:08,680 --> 00:23:10,560
Speaker 1: Is that about right? That's right. We've done over four

420
00:23:10,600 --> 00:23:11,520
Speaker 1: hundred deals.

421
00:23:11,240 --> 00:23:14,040
Speaker 2: And how many of these have reached their.

422
00:23:13,920 --> 00:23:16,520
Speaker 1: Conclusion over one hundred and thirty.

423
00:23:16,640 --> 00:23:18,439
Speaker 2: So you're about a third of the way through the

424
00:23:18,480 --> 00:23:21,600
Speaker 2: initial the first let's call it five years or so,

425
00:23:21,720 --> 00:23:23,119
Speaker 2: seven years of financing.

426
00:23:23,480 --> 00:23:26,480
Speaker 1: It's been a long time, I mean, so we raised

427
00:23:26,480 --> 00:23:29,359
Speaker 1: our first fund in twenty seventeen, second fund in twenty nineteen,

428
00:23:29,520 --> 00:23:33,439
Speaker 1: third fund in twenty twenty one. I think the pace

429
00:23:33,600 --> 00:23:36,880
Speaker 1: of the number of deals we do is definitely accelerating,

430
00:23:36,960 --> 00:23:39,040
Speaker 1: considering the fact that we only had ten million for

431
00:23:39,080 --> 00:23:43,440
Speaker 1: the first two years. But we've learned a lot along

432
00:23:43,440 --> 00:23:43,920
Speaker 1: the way.

433
00:23:44,359 --> 00:23:47,320
Speaker 2: And in twenty twenty two you raised four hundred million dollars.

434
00:23:47,359 --> 00:23:50,760
Speaker 2: That's a pretty hefty number for what was then, I

435
00:23:50,840 --> 00:23:53,000
Speaker 2: guess a five year old fun putting together a good

436
00:23:53,080 --> 00:23:57,400
Speaker 2: track record. Let's talk a little bit about the sort

437
00:23:57,400 --> 00:24:01,160
Speaker 2: of returns you target and how long the should take.

438
00:24:01,760 --> 00:24:05,359
Speaker 2: So you have four hundred investments done since twenty seventeen,

439
00:24:06,480 --> 00:24:09,840
Speaker 2: about a third of them have reached fruition. What's the

440
00:24:09,880 --> 00:24:13,080
Speaker 2: win loss rate? You mentioned seventy five percent before.

441
00:24:12,840 --> 00:24:16,399
Speaker 1: That's right, So we went about seventy five percent of

442
00:24:16,480 --> 00:24:19,679
Speaker 1: the deals that we do when being calculated as it

443
00:24:19,760 --> 00:24:22,920
Speaker 1: makes above the amount that we put in and lost

444
00:24:22,960 --> 00:24:24,920
Speaker 1: being anything below principle.

445
00:24:24,600 --> 00:24:27,080
Speaker 2: So you could actually win the case but not be

446
00:24:27,240 --> 00:24:31,160
Speaker 2: financially successful because there returns are less than the initial investment.

447
00:24:31,440 --> 00:24:33,760
Speaker 1: That was the big thing that we learned in the

448
00:24:33,840 --> 00:24:36,040
Speaker 1: early years. So in the early years, we only had

449
00:24:36,080 --> 00:24:39,480
Speaker 1: ten million of assets, but we had billions of dollars

450
00:24:39,520 --> 00:24:41,760
Speaker 1: of deal flow. And so what we would do is

451
00:24:41,800 --> 00:24:45,080
Speaker 1: we would work with other litigation funders multi strat hedge

452
00:24:45,119 --> 00:24:48,320
Speaker 1: funds that did litigation funding, and we would refer cases

453
00:24:48,359 --> 00:24:51,879
Speaker 1: to them and watch how they did their work. And

454
00:24:51,960 --> 00:24:56,120
Speaker 1: what we noticed was that litigation is essentially like an

455
00:24:56,280 --> 00:24:59,160
Speaker 1: envelope with a check in it. You do not know

456
00:24:59,560 --> 00:25:01,320
Speaker 1: how much is written on that check.

457
00:25:01,400 --> 00:25:02,600
Speaker 2: Oh it's a sealed envelope.

458
00:25:02,600 --> 00:25:07,439
Speaker 1: It can seal develope, right, And everyone has their best

459
00:25:07,560 --> 00:25:10,160
Speaker 1: estimate of how much is in that check. But theoretically,

460
00:25:10,400 --> 00:25:13,320
Speaker 1: if you were to buy the envelope for ten dollars

461
00:25:13,760 --> 00:25:16,359
Speaker 1: or even ten thousand dollars, you would always make money.

462
00:25:16,600 --> 00:25:18,800
Speaker 1: A defendant is always willing to settle for at least

463
00:25:18,840 --> 00:25:21,080
Speaker 1: ten thousand dollars just to avoid paying their lawyers.

464
00:25:21,160 --> 00:25:23,280
Speaker 2: Make it go away, absolutely exactly.

465
00:25:23,600 --> 00:25:27,320
Speaker 1: That's called a nuisance value settlement. And so theoretically, the

466
00:25:27,440 --> 00:25:30,159
Speaker 1: less money you can invest in each claim, the higher

467
00:25:30,200 --> 00:25:32,840
Speaker 1: the likelihood of success. And if you were to invest

468
00:25:32,960 --> 00:25:35,919
Speaker 1: one dollar, you would win every single lidiation.

469
00:25:35,720 --> 00:25:37,720
Speaker 2: Because you would always take the ten thousand dollars check

470
00:25:37,800 --> 00:25:41,200
Speaker 2: to go away. That's a great ROI. In reality, you

471
00:25:41,240 --> 00:25:43,880
Speaker 2: have a plaintiff that doesn't want to settle for right

472
00:25:43,920 --> 00:25:48,040
Speaker 2: brand they feel they're wrong. Once it gets you know,

473
00:25:48,080 --> 00:25:52,479
Speaker 2: people forget. Ninety something percent of cases settle before trial.

474
00:25:52,640 --> 00:25:55,400
Speaker 2: So one question I have to ask you is, when

475
00:25:55,480 --> 00:26:01,359
Speaker 2: you're doing litigation financing, of the cases that are resolved,

476
00:26:01,440 --> 00:26:04,320
Speaker 2: how many of them actually go to trial and how

477
00:26:04,320 --> 00:26:07,080
Speaker 2: many of them are resolved way before trial?

478
00:26:07,640 --> 00:26:12,399
Speaker 1: The majority of them are settled, and litigation finance, I

479
00:26:12,480 --> 00:26:17,280
Speaker 1: have to admit, does introduce a hurdle beyond which the

480
00:26:17,320 --> 00:26:21,480
Speaker 1: plaintiff has to hit in order to settle for a

481
00:26:21,520 --> 00:26:24,159
Speaker 1: reasonable amount and make a reasonable amount of money. So

482
00:26:24,280 --> 00:26:26,800
Speaker 1: that's the reason why in litigation finance you don't see

483
00:26:26,800 --> 00:26:30,119
Speaker 1: settlement rates that are as high as you would normally see.

484
00:26:30,400 --> 00:26:33,560
Speaker 1: The plus side of this is that normally a lot

485
00:26:33,600 --> 00:26:35,600
Speaker 1: of plaintiffs run out of money and then they settle

486
00:26:35,600 --> 00:26:37,920
Speaker 1: the case for pennies on the dollar, and so litigation

487
00:26:38,000 --> 00:26:40,320
Speaker 1: finance allows them to hold out for what they're owed.

488
00:26:40,760 --> 00:26:42,760
Speaker 2: I would think that it's a self selecting group in

489
00:26:42,840 --> 00:26:46,800
Speaker 2: two ways. One is people who know in advance I'm

490
00:26:46,800 --> 00:26:49,480
Speaker 2: giving up some of my upside, but I want to

491
00:26:49,520 --> 00:26:54,360
Speaker 2: go the distance. And two, because they're funded, they don't

492
00:26:54,440 --> 00:26:57,520
Speaker 2: have to take a low bull settlement. I would imagine

493
00:26:57,560 --> 00:27:01,040
Speaker 2: the defense side, Oh, they have a deep pot supporting them,

494
00:27:01,480 --> 00:27:03,840
Speaker 2: We're going to have to be prepared to go to court.

495
00:27:04,200 --> 00:27:08,639
Speaker 2: It changes the dynamics of the subsequent settlement discussions. I

496
00:27:08,640 --> 00:27:12,000
Speaker 2: would imagine it makes the defendant a whole lot more

497
00:27:12,640 --> 00:27:16,159
Speaker 2: serious about the case. Then we could just wait this

498
00:27:16,240 --> 00:27:18,760
Speaker 2: guy out and eventually they'll run out of.

499
00:27:18,720 --> 00:27:23,560
Speaker 1: Cash exactly exactly. Now. The secret about the defense side

500
00:27:23,680 --> 00:27:27,359
Speaker 1: is that it's often in their best interest to draw

501
00:27:27,520 --> 00:27:30,680
Speaker 1: out the litigation process, One because the plaintiff might run

502
00:27:30,680 --> 00:27:35,280
Speaker 1: out of money, and two just because if I'm owed

503
00:27:35,400 --> 00:27:38,840
Speaker 1: ten million dollars in an earnout, it benefits the defendant

504
00:27:38,880 --> 00:27:41,359
Speaker 1: to pay that to me in five years rather than today,

505
00:27:41,400 --> 00:27:44,520
Speaker 1: even if they settle for the full amount. So that's

506
00:27:44,560 --> 00:27:49,120
Speaker 1: why a lot of defendants, especially big companies, will weaponize

507
00:27:49,119 --> 00:27:51,680
Speaker 1: the fact that they have deep pockets, can pay for lawyers,

508
00:27:51,760 --> 00:27:53,960
Speaker 1: can drag things out, and you know what's the plaintiff

509
00:27:54,000 --> 00:27:56,480
Speaker 1: going to do? Sue them in court and take five

510
00:27:56,560 --> 00:27:59,400
Speaker 1: years to do so. And so that's why you might

511
00:27:59,440 --> 00:28:03,520
Speaker 1: see cases where both sides recognize the plaintiff is at

512
00:28:03,560 --> 00:28:06,639
Speaker 1: least entitled to something, but where the defendant just hasn't

513
00:28:06,680 --> 00:28:09,400
Speaker 1: settled because it's in their economic best interest to drag

514
00:28:09,440 --> 00:28:09,760
Speaker 1: it out.

515
00:28:09,960 --> 00:28:15,160
Speaker 2: Huh interesting. So, given three quarters seventy five percent success rate,

516
00:28:16,160 --> 00:28:18,520
Speaker 2: what sort of returns are you targeting? I know we

517
00:28:18,520 --> 00:28:22,439
Speaker 2: can't talk about actual performance, but when you're looking at

518
00:28:22,480 --> 00:28:26,680
Speaker 2: an individual case, one would have to think the average

519
00:28:26,680 --> 00:28:29,960
Speaker 2: of the cases are looking for x percent a year?

520
00:28:30,160 --> 00:28:33,160
Speaker 2: Is it fifteen percent? Is it twenty percent? The winners

521
00:28:33,200 --> 00:28:36,160
Speaker 2: have to offset the losers, So I got to think

522
00:28:36,200 --> 00:28:38,880
Speaker 2: you're looking for way more than ten percent.

523
00:28:38,680 --> 00:28:43,000
Speaker 1: Right, that's right. So we usually charge a significant multiple

524
00:28:43,520 --> 00:28:47,880
Speaker 1: on our dollars put out and across the fund we

525
00:28:47,960 --> 00:28:50,680
Speaker 1: target a twenty to twenty five percent net, So we're

526
00:28:50,720 --> 00:28:53,680
Speaker 1: trying to be comparable to private equity, but in half

527
00:28:53,720 --> 00:28:55,840
Speaker 1: the duration and uncorrelated of course.

528
00:28:56,600 --> 00:29:01,160
Speaker 2: So litigation finances the flagship strategy. What other strategies do

529
00:29:01,200 --> 00:29:01,760
Speaker 2: you employ?

530
00:29:02,680 --> 00:29:05,960
Speaker 1: So litigation finance is by far our largest strategy, But

531
00:29:06,000 --> 00:29:10,560
Speaker 1: we also have a couple hundred million in a type

532
00:29:10,560 --> 00:29:15,080
Speaker 1: of distress lending in bankruptcy called dip lending. And we

533
00:29:15,120 --> 00:29:18,040
Speaker 1: also have a couple hundred million in a type of

534
00:29:18,480 --> 00:29:23,000
Speaker 1: alternative credit called government receivables. So government receivables is where

535
00:29:23,320 --> 00:29:25,680
Speaker 1: you have a ninety to one hundred and twenty day

536
00:29:25,800 --> 00:29:29,240
Speaker 1: receivable from a federal or state government entity, either because

537
00:29:29,280 --> 00:29:31,920
Speaker 1: of a grant or a contract that you performed on

538
00:29:32,040 --> 00:29:34,520
Speaker 1: or a credit of some sort, and we advance against

539
00:29:34,560 --> 00:29:36,720
Speaker 1: that and then get paid directly by the government.

540
00:29:36,840 --> 00:29:40,400
Speaker 2: I just had a conversation with a friend who does

541
00:29:40,440 --> 00:29:43,800
Speaker 2: that sort of work for state and county governments, and

542
00:29:44,920 --> 00:29:47,600
Speaker 2: the problem they run into is when they're too successful,

543
00:29:47,960 --> 00:29:53,600
Speaker 2: when they have all these accounts receivable to them, it's like, Hey,

544
00:29:53,640 --> 00:29:55,680
Speaker 2: we have too much business. How do we fund this?

545
00:29:56,240 --> 00:29:58,880
Speaker 2: And it seems like it's pretty guaranteed. I didn't realize

546
00:29:58,920 --> 00:30:02,280
Speaker 2: that sort of old credit was something you do. How

547
00:30:02,480 --> 00:30:06,240
Speaker 2: large of a receivable are you looking at? I'm assuming

548
00:30:06,240 --> 00:30:08,400
Speaker 2: you're not doing this for five and ten thousand dollars

549
00:30:08,440 --> 00:30:11,520
Speaker 2: at a pop. Right, it's probably millions of dollars, if

550
00:30:11,560 --> 00:30:11,960
Speaker 2: not more.

551
00:30:12,520 --> 00:30:15,840
Speaker 1: Right, So, the individual receivables can be as low as

552
00:30:16,080 --> 00:30:19,200
Speaker 1: ten twenty thousand, but we usually set them up as

553
00:30:19,640 --> 00:30:23,680
Speaker 1: credit facilities with people who generate lots of these receivables,

554
00:30:23,760 --> 00:30:27,040
Speaker 1: and the facilities might be a couple million. And the

555
00:30:27,080 --> 00:30:30,120
Speaker 1: reason why we're able to find these businesses is because,

556
00:30:30,400 --> 00:30:33,400
Speaker 1: and you'll notice, everything we do is related to either

557
00:30:33,520 --> 00:30:36,080
Speaker 1: the legal system, the judicial system, or the government in

558
00:30:36,120 --> 00:30:39,520
Speaker 1: some way. Because what our technology does best, and we

559
00:30:39,560 --> 00:30:43,000
Speaker 1: call our technology the truffle sniffer, as in like a

560
00:30:43,040 --> 00:30:46,280
Speaker 1: pig that goes into the forest and then finds valuable truffles,

561
00:30:46,840 --> 00:30:50,760
Speaker 1: is we crawl through these comprehensive government databases and pull

562
00:30:50,800 --> 00:30:54,680
Speaker 1: out the information that is relevant for investment purposes and

563
00:30:54,800 --> 00:30:58,160
Speaker 1: go after those deals specifically. So in litigation, we're looking

564
00:30:58,160 --> 00:31:01,680
Speaker 1: for cases that win in government receivables. We're looking for

565
00:31:01,760 --> 00:31:04,560
Speaker 1: businesses that are owed receivables and are likely to be

566
00:31:04,600 --> 00:31:08,440
Speaker 1: in financial need of receivable financing. So Boeing, for instance,

567
00:31:08,440 --> 00:31:12,640
Speaker 1: would be excluded even though they generate huge amount of receivables.

568
00:31:12,720 --> 00:31:14,760
Speaker 1: And I would love to fund Boeing, but Boeing would

569
00:31:14,800 --> 00:31:16,760
Speaker 1: never want funding from us. So it is what it is.

570
00:31:17,720 --> 00:31:20,720
Speaker 2: That's really interesting. And you mentioned dip or debtor in

571
00:31:20,800 --> 00:31:25,240
Speaker 2: possession financing. So in a bankruptcy, the debtor takes control

572
00:31:25,280 --> 00:31:29,320
Speaker 2: of the entity and suddenly they're operating on behalf of

573
00:31:29,440 --> 00:31:32,680
Speaker 2: all the other creditors and that requires a line of

574
00:31:32,720 --> 00:31:33,480
Speaker 2: capital as well.

575
00:31:34,120 --> 00:31:39,560
Speaker 1: So most large bankruptcies are called pre packaged bankruptcy, so

576
00:31:39,600 --> 00:31:42,560
Speaker 1: there's already a dip lender in place. What we specialize

577
00:31:42,560 --> 00:31:46,920
Speaker 1: in is looking for these sub scale dip opportunities where

578
00:31:47,560 --> 00:31:50,440
Speaker 1: there is no prepetition lender that's willing to put up

579
00:31:50,480 --> 00:31:52,800
Speaker 1: the dip financing and so you can come in and

580
00:31:52,800 --> 00:31:56,920
Speaker 1: be a priming lean on all the assets of the bankruptcy.

581
00:31:57,240 --> 00:32:01,360
Speaker 2: And we briefly discussed competitors, but but it sounds like

582
00:32:01,680 --> 00:32:06,240
Speaker 2: it's deep pocketed high net worth individuals and some multi

583
00:32:06,360 --> 00:32:09,720
Speaker 2: strat funds that sort of do this on the side.

584
00:32:09,840 --> 00:32:15,160
Speaker 2: Is anybody else focusing on this sort of strategy directly

585
00:32:15,400 --> 00:32:17,880
Speaker 2: or for now? Do you pretty much own the space?

586
00:32:18,800 --> 00:32:22,200
Speaker 1: So we did not invent any of the asset classes

587
00:32:22,520 --> 00:32:25,480
Speaker 1: that we are in. However, we approach what we do

588
00:32:25,560 --> 00:32:27,680
Speaker 1: in a very unusual way, and a lot of our

589
00:32:27,800 --> 00:32:30,920
Speaker 1: LPs see that. So the reason that we even came

590
00:32:31,000 --> 00:32:34,520
Speaker 1: up with a government receivable strategy, which is a liquid

591
00:32:34,560 --> 00:32:37,000
Speaker 1: hedge fund. It's got a much shorter duration than we're

592
00:32:37,040 --> 00:32:39,360
Speaker 1: used to, it's a different type of database, is because

593
00:32:39,400 --> 00:32:44,040
Speaker 1: one of our LPs, a university endowment, approached us and said, hey, look,

594
00:32:44,080 --> 00:32:48,080
Speaker 1: I've got this other manager. They do government receivables financing.

595
00:32:48,720 --> 00:32:51,080
Speaker 1: I freaking love this asset class and I want more

596
00:32:51,120 --> 00:32:53,960
Speaker 1: of it. But they're not able to source more because

597
00:32:53,960 --> 00:32:55,960
Speaker 1: they're using their relationships to source.

598
00:32:56,120 --> 00:32:58,440
Speaker 2: You're scraping it right off the sites. That gives you

599
00:32:58,480 --> 00:32:59,320
Speaker 2: a ugee.

600
00:32:59,560 --> 00:33:01,880
Speaker 1: Yeah, we don't need to go to people we know

601
00:33:02,320 --> 00:33:05,480
Speaker 1: and say hey, is there any chance you want financing?

602
00:33:05,560 --> 00:33:10,440
Speaker 1: We can actually go into the government contract websites and say, okay,

603
00:33:10,520 --> 00:33:13,640
Speaker 1: who here looks like they would need government receivables financing.

604
00:33:13,800 --> 00:33:18,760
Speaker 2: So everything you've described so far is both technologically driven

605
00:33:19,480 --> 00:33:23,120
Speaker 2: and outside of what we think of as traditional finance

606
00:33:23,200 --> 00:33:27,560
Speaker 2: or even old finance. I don't want to use the

607
00:33:27,600 --> 00:33:31,480
Speaker 2: phrase niche, but I got to ask how far can

608
00:33:31,560 --> 00:33:33,480
Speaker 2: this scale up? Like this is not going to be

609
00:33:33,520 --> 00:33:36,440
Speaker 2: a trillion dollar business ever, Right, even if you attract

610
00:33:36,600 --> 00:33:41,200
Speaker 2: thousands of competitors, you're coming up on a billion dollars.

611
00:33:41,320 --> 00:33:44,360
Speaker 2: Is there room in the space for ten billion or

612
00:33:44,360 --> 00:33:48,120
Speaker 2: twenty billion or is there just not enough juice to

613
00:33:48,200 --> 00:33:49,560
Speaker 2: make it worth a squeeze there?

614
00:33:50,400 --> 00:33:54,880
Speaker 1: So each one of our strategies individually is capacity constrained.

615
00:33:55,080 --> 00:33:56,800
Speaker 1: And you can see this by the fact that the

616
00:33:56,920 --> 00:33:59,800
Speaker 1: industries that they are in are not that large. So

617
00:34:00,680 --> 00:34:03,920
Speaker 1: the largest government receivables funder has two billion of assets

618
00:34:04,000 --> 00:34:07,600
Speaker 1: under management, the largest litigation funder has a couple billion

619
00:34:07,600 --> 00:34:10,359
Speaker 1: of assets under management. They are kind of what they are.

620
00:34:10,560 --> 00:34:15,839
Speaker 1: But we see our firm as a tech driven alternative

621
00:34:15,880 --> 00:34:18,799
Speaker 1: credit firm, and the types of alternative credit there are

622
00:34:18,840 --> 00:34:20,320
Speaker 1: out there is huge.

623
00:34:20,520 --> 00:34:24,280
Speaker 2: Right, that's a trillion dollar industry, clearly, But you've found

624
00:34:24,280 --> 00:34:29,520
Speaker 2: an area that is the fishinghole you you're operating in

625
00:34:29,600 --> 00:34:34,720
Speaker 2: as relatively small as compared to let's call it middle

626
00:34:34,840 --> 00:34:39,640
Speaker 2: market funding of existing companies. So the other thing I

627
00:34:39,680 --> 00:34:43,760
Speaker 2: find so fascinating. So you've diversified across three different lines,

628
00:34:44,160 --> 00:34:48,759
Speaker 2: so it's debtorin possession of financing accounts receivable, and then

629
00:34:48,920 --> 00:34:54,360
Speaker 2: litigation finance. But all of this sounds completely uncorrelated to

630
00:34:54,400 --> 00:34:58,439
Speaker 2: the economy, to the stock market, to interest rates. What's

631
00:34:58,520 --> 00:35:03,799
Speaker 2: the relationship of the fund success rate versus all the

632
00:35:03,840 --> 00:35:07,319
Speaker 2: other things we look at as either correlated or uncorrelated.

633
00:35:07,760 --> 00:35:11,360
Speaker 1: So that is the niche that we occupy for our LPs.

634
00:35:12,280 --> 00:35:14,840
Speaker 1: They have a lot of things that are market correlated,

635
00:35:15,280 --> 00:35:19,359
Speaker 1: and depending on their liquidity and return profile that they're

636
00:35:19,400 --> 00:35:22,960
Speaker 1: looking for, they might invest in lidiation finance, which is

637
00:35:23,080 --> 00:35:25,959
Speaker 1: longer duration, it's a kind of a five to seven

638
00:35:26,000 --> 00:35:28,719
Speaker 1: year draw down fund. Or if they're really looking for

639
00:35:28,800 --> 00:35:31,760
Speaker 1: liquidity but are willing to do a lower return profile,

640
00:35:32,040 --> 00:35:34,879
Speaker 1: they might look for something like government receivables, which has

641
00:35:35,000 --> 00:35:37,399
Speaker 1: quarterly redemptions but is more of a ten to twelve

642
00:35:37,440 --> 00:35:39,960
Speaker 1: percent net And then DIP is somewhere in the middle.

643
00:35:40,320 --> 00:35:43,359
Speaker 1: So across all of our strategies, I think the non

644
00:35:43,440 --> 00:35:47,640
Speaker 1: correlated component is a super important part of both how

645
00:35:47,680 --> 00:35:50,160
Speaker 1: we market and the value that we provide for our investors.

646
00:35:50,440 --> 00:35:54,080
Speaker 2: Huh. So some people want liquidity, they're going to do

647
00:35:54,120 --> 00:35:58,479
Speaker 2: accounts receivable. If a big endowment or foundation is less

648
00:35:58,480 --> 00:36:03,680
Speaker 2: concerned about regular demands on capital or future liabilities. If

649
00:36:03,719 --> 00:36:06,839
Speaker 2: you're doing the flagship litigation finance, expect to be locked

650
00:36:06,920 --> 00:36:09,120
Speaker 2: up seven years, fair statement.

651
00:36:08,760 --> 00:36:10,799
Speaker 1: Five to seven years, five to seven years.

652
00:36:10,840 --> 00:36:14,399
Speaker 2: Really interesting. I got to ask about the name. Where

653
00:36:14,400 --> 00:36:17,000
Speaker 2: did the name legalists come from?

654
00:36:17,080 --> 00:36:20,360
Speaker 1: I think that it was related to our very very

655
00:36:20,400 --> 00:36:25,319
Speaker 1: original business idea, which was a list of attorneys and

656
00:36:25,400 --> 00:36:26,440
Speaker 1: a list of cases.

657
00:36:26,760 --> 00:36:30,160
Speaker 2: Legal list. That's right, So back and White combinator, when

658
00:36:30,160 --> 00:36:32,400
Speaker 2: you're just scraping this and saying, we don't know what

659
00:36:32,400 --> 00:36:34,000
Speaker 2: the hell we're going to do with this, but here's

660
00:36:34,040 --> 00:36:34,520
Speaker 2: a list.

661
00:36:34,320 --> 00:36:36,160
Speaker 1: Of attorneys in cases exactly.

662
00:36:36,280 --> 00:36:39,200
Speaker 2: Huh. But you just kept it for for nostalgia sake.

663
00:36:39,280 --> 00:36:42,520
Speaker 1: I do. I do identify as a legalist. I'm very

664
00:36:42,520 --> 00:36:43,520
Speaker 1: big on rule of law.

665
00:36:43,960 --> 00:36:48,360
Speaker 2: Yeah, some people less so right to say that. So

666
00:36:48,440 --> 00:36:50,879
Speaker 2: let's talk a little bit about the asset growth, which

667
00:36:50,920 --> 00:36:54,480
Speaker 2: has been pretty amazing. You start with ten million and

668
00:36:54,560 --> 00:36:59,640
Speaker 2: twenty seventeen. By twenty twenty one, that's under half a

669
00:36:59,680 --> 00:37:04,240
Speaker 2: billion in now you're knocking at a billion. That's pretty

670
00:37:04,360 --> 00:37:09,000
Speaker 2: rapid growth for a startup. Most startup al credit funds

671
00:37:09,600 --> 00:37:12,440
Speaker 2: or alt edge funds don't scale up to a billion

672
00:37:12,480 --> 00:37:13,360
Speaker 2: dollars that quickly.

673
00:37:15,280 --> 00:37:18,279
Speaker 1: I think that's right. I think we happen to be

674
00:37:18,320 --> 00:37:21,640
Speaker 1: at a very good moment in time where a lot

675
00:37:21,680 --> 00:37:25,520
Speaker 1: of our investors are people who were already familiar with

676
00:37:25,560 --> 00:37:28,960
Speaker 1: litigation finance but happened to not like how it was

677
00:37:29,040 --> 00:37:32,840
Speaker 1: being done before. So the big problem with litigation finance

678
00:37:32,880 --> 00:37:36,840
Speaker 1: traditionally as an industry is that each litigation itself carries

679
00:37:36,960 --> 00:37:39,920
Speaker 1: a ton of idiosyncratic risk. You could have the best

680
00:37:39,920 --> 00:37:42,040
Speaker 1: case in the world and get in front of a

681
00:37:42,120 --> 00:37:44,520
Speaker 1: judge and the judge is feeling kind of crotchety that day,

682
00:37:44,880 --> 00:37:46,839
Speaker 1: and so then he dismisses it, and then you're done.

683
00:37:47,760 --> 00:37:51,799
Speaker 1: And what our strategy does is our strategy takes the

684
00:37:51,800 --> 00:37:56,720
Speaker 1: idiosyncratic risk out of each individual investment out by pulling

685
00:37:56,760 --> 00:37:58,840
Speaker 1: it with hundreds of other investments. And there were no

686
00:37:58,920 --> 00:38:02,759
Speaker 1: other litigation funders. There are no other litigation funders that

687
00:38:02,800 --> 00:38:03,719
Speaker 1: do it the way that we do.

688
00:38:03,880 --> 00:38:08,640
Speaker 2: Huh really interesting, Well, you're out if the judge dismisses it,

689
00:38:08,719 --> 00:38:11,239
Speaker 2: unless there's an appeal. Do you guys fund appeals?

690
00:38:11,680 --> 00:38:13,920
Speaker 1: We don't fund appeals for cases that have lost.

691
00:38:15,600 --> 00:38:18,640
Speaker 2: We have well would you fund? Would you fund an

692
00:38:18,640 --> 00:38:22,480
Speaker 2: appeal for cases that one? Not because you're challenging the outcome,

693
00:38:22,520 --> 00:38:26,080
Speaker 2: but you're challenging the dollar amount the award, not the verdict.

694
00:38:27,239 --> 00:38:32,359
Speaker 1: So the qualifier for the Truffle Sniffer is based on

695
00:38:32,400 --> 00:38:36,080
Speaker 1: a set of variables that include static variables, so these

696
00:38:36,080 --> 00:38:39,760
Speaker 1: are things that would eliminate a case categorically or qualify

697
00:38:39,760 --> 00:38:43,920
Speaker 1: a case categorically. And then there are also time series variables.

698
00:38:44,000 --> 00:38:46,600
Speaker 1: So the time series variables are related to things that

699
00:38:46,680 --> 00:38:49,600
Speaker 1: happen in the case. And this is not at all

700
00:38:49,719 --> 00:38:52,360
Speaker 1: obvious to detect, and this is what our machine learning

701
00:38:52,440 --> 00:38:55,239
Speaker 1: is trained on. But we're looking for signs that a

702
00:38:55,280 --> 00:38:58,600
Speaker 1: case is going really well. For certain types of cases,

703
00:38:59,360 --> 00:39:02,240
Speaker 1: getting a pro may injunction might be a really big deal.

704
00:39:02,640 --> 00:39:05,920
Speaker 1: For other types of cases, like patent cases. For instance,

705
00:39:06,400 --> 00:39:10,520
Speaker 1: fifty percent of patent judgments are overturned on appeal even

706
00:39:10,560 --> 00:39:13,359
Speaker 1: if they win. Wow. So for that reason, we don't

707
00:39:13,400 --> 00:39:16,600
Speaker 1: do any patent cases because there is really no stage

708
00:39:16,680 --> 00:39:18,279
Speaker 1: at which we could fund it where it has been

709
00:39:18,320 --> 00:39:22,160
Speaker 1: de risked, and we're really looking for preliminary motion hurdles

710
00:39:22,200 --> 00:39:24,080
Speaker 1: that de risk a case. Huh.

711
00:39:24,120 --> 00:39:28,799
Speaker 2: So the future is inherently unpredictable, but by controlling a

712
00:39:28,800 --> 00:39:32,560
Speaker 2: handful of variables, you can narrow the range of potential

713
00:39:32,600 --> 00:39:35,120
Speaker 2: outcomes to something manageable exactly.

714
00:39:35,440 --> 00:39:38,520
Speaker 1: And what then our underwriters do. And there is still

715
00:39:38,560 --> 00:39:43,160
Speaker 1: a big human lawyer underwriting component for the simple reason

716
00:39:43,200 --> 00:39:45,160
Speaker 1: that you know, if you look at a case, there

717
00:39:45,160 --> 00:39:48,399
Speaker 1: are three elements to underwriting it. There's will it win?

718
00:39:49,160 --> 00:39:51,160
Speaker 1: How much will it win? And if they do win,

719
00:39:51,200 --> 00:39:53,839
Speaker 1: can the defendant even pay it? And the latter two

720
00:39:54,000 --> 00:39:56,719
Speaker 1: are really what we still need a lawyer to check for.

721
00:39:57,800 --> 00:39:59,799
Speaker 1: So a lot of what the lawyers check for is

722
00:40:01,160 --> 00:40:05,040
Speaker 1: does it actually make sense for this guy to get

723
00:40:05,040 --> 00:40:08,960
Speaker 1: this amount of money? And we call this the no policy.

724
00:40:08,600 --> 00:40:10,960
Speaker 2: Good policy in just about every endeavor.

725
00:40:11,280 --> 00:40:14,960
Speaker 1: Yeah, but what we found is that people put out

726
00:40:15,160 --> 00:40:17,799
Speaker 1: energy into the world and then it is reflected back

727
00:40:17,800 --> 00:40:20,759
Speaker 1: to them. And so when we've had situations where we've

728
00:40:20,800 --> 00:40:23,680
Speaker 1: just we're just like, did you really hate that guy?

729
00:40:23,760 --> 00:40:26,759
Speaker 1: I really hated that guy and he's got such a

730
00:40:26,920 --> 00:40:30,880
Speaker 1: technically good case on paper, And we've had a handful

731
00:40:30,920 --> 00:40:33,759
Speaker 1: of losses that have had this BAC pattern, But once

732
00:40:33,800 --> 00:40:37,360
Speaker 1: they get to trial, the judge is like, oh, I

733
00:40:37,400 --> 00:40:40,399
Speaker 1: can see why you terminated that contract, right, I can

734
00:40:40,440 --> 00:40:42,400
Speaker 1: see why you didn't want to work with him, right,

735
00:40:42,480 --> 00:40:45,320
Speaker 1: And then they inevitably lose, and the jury will drape

736
00:40:45,360 --> 00:40:48,200
Speaker 1: the law over whichever party they feel like is more deserving,

737
00:40:48,440 --> 00:40:50,480
Speaker 1: because we all have a sense of inherent right and

738
00:40:50,520 --> 00:40:53,800
Speaker 1: wrong in our hearts and we want to act according

739
00:40:53,840 --> 00:40:54,040
Speaker 1: to that.

740
00:40:54,920 --> 00:40:59,520
Speaker 2: It's always funny when you when you come to the realization, hey,

741
00:40:59,560 --> 00:41:02,160
Speaker 2: this ape million people in the world. Even if one

742
00:41:02,200 --> 00:41:05,400
Speaker 2: percent of them are let's use the word jerks instead

743
00:41:05,400 --> 00:41:12,399
Speaker 2: of the a word. That's still you know, a ton

744
00:41:12,440 --> 00:41:15,439
Speaker 2: of people. That's still if there's eight billion people, well,

745
00:41:15,920 --> 00:41:18,960
Speaker 2: guess what, it's eighty million jerks out there. I don't

746
00:41:19,000 --> 00:41:22,320
Speaker 2: need to deal with them. So anyway, I totally get

747
00:41:22,400 --> 00:41:25,839
Speaker 2: that rule of thumb and it works well. But since

748
00:41:25,880 --> 00:41:32,720
Speaker 2: we're talking about this sort of squishy individual personal things

749
00:41:33,360 --> 00:41:37,640
Speaker 2: you mentioned many of the multistread funds that do these

750
00:41:37,680 --> 00:41:41,200
Speaker 2: sort of deals, they have a network of people. It's

751
00:41:41,280 --> 00:41:44,800
Speaker 2: sort of who knows who and how they come across

752
00:41:44,880 --> 00:41:48,080
Speaker 2: these cases, and one person refers it to another person,

753
00:41:48,080 --> 00:41:51,879
Speaker 2: and that lawyer refers it to a third person. Your

754
00:41:52,120 --> 00:41:56,160
Speaker 2: approach to originating these things are completely different. You're pulling

755
00:41:56,160 --> 00:41:58,359
Speaker 2: the data off of I'm now going to assume it's

756
00:41:58,480 --> 00:42:00,919
Speaker 2: just about every state in the country that's right off

757
00:42:00,960 --> 00:42:04,680
Speaker 2: of the judicial websites of the states, and then you're

758
00:42:04,760 --> 00:42:08,200
Speaker 2: running your analytics on it to say, hey, let's see

759
00:42:08,280 --> 00:42:11,120
Speaker 2: if we can find a case that's worthy, and at

760
00:42:11,120 --> 00:42:14,279
Speaker 2: that point take us through the process of reaching out

761
00:42:14,280 --> 00:42:17,640
Speaker 2: to that planiff. How does that conversation go, Hey, we

762
00:42:17,680 --> 00:42:20,360
Speaker 2: saw your case. We're wondering if you need assistance on

763
00:42:21,000 --> 00:42:21,839
Speaker 2: financing it.

764
00:42:22,440 --> 00:42:25,319
Speaker 1: So, even though we fund the plaintiffs, the attorneys are

765
00:42:25,400 --> 00:42:29,640
Speaker 1: usually our primary points of contact because attorneys are repeat players,

766
00:42:29,800 --> 00:42:31,759
Speaker 1: and so at this point, you know, our team has

767
00:42:31,840 --> 00:42:37,000
Speaker 1: five thousand calls with attorneys every single year, and at

768
00:42:37,000 --> 00:42:39,680
Speaker 1: this point we've spoken to tens of thousands of attorneys

769
00:42:39,719 --> 00:42:42,200
Speaker 1: pretty much everyone that does the type of case that

770
00:42:42,239 --> 00:42:45,000
Speaker 1: we'd like to do. When we first started out, it

771
00:42:45,040 --> 00:42:48,520
Speaker 1: was all cold outreach, but these days it's a lot more. Hey,

772
00:42:48,600 --> 00:42:51,360
Speaker 1: I saw that your X case just survived motion for

773
00:42:51,400 --> 00:42:55,759
Speaker 1: summary judgment? Congratulations, Do you want to reconnect in a

774
00:42:55,800 --> 00:42:58,200
Speaker 1: couple weeks, even though I know we just talked, you know,

775
00:42:58,280 --> 00:43:00,239
Speaker 1: six months ago. So it's a lot more of these

776
00:43:00,280 --> 00:43:04,320
Speaker 1: warm connections. And it's not that we are not bullish

777
00:43:04,360 --> 00:43:07,520
Speaker 1: on relationships. It's that I think that when you have

778
00:43:09,719 --> 00:43:15,320
Speaker 1: a solely relationship driven origination approach, you're really limiting the

779
00:43:15,560 --> 00:43:16,520
Speaker 1: number of deals that you can.

780
00:43:16,640 --> 00:43:19,520
Speaker 2: You're relying too much on serendipity as opposed to something

781
00:43:19,600 --> 00:43:24,840
Speaker 2: that is not only quantitative, but structured and rules driven.

782
00:43:25,600 --> 00:43:28,400
Speaker 2: It gives you a more consistent thing. So you mentioned

783
00:43:28,400 --> 00:43:31,680
Speaker 2: no patent cases. What are the sort of commercial cases

784
00:43:31,719 --> 00:43:34,120
Speaker 2: that you very much like, what catches your eye?

785
00:43:34,480 --> 00:43:37,360
Speaker 1: So two thirds of our cases are breach of contract

786
00:43:37,400 --> 00:43:39,840
Speaker 1: and business towards. Do you know what business to Of course.

787
00:43:41,160 --> 00:43:44,080
Speaker 2: I didn't do your out. I went to law school,

788
00:43:44,080 --> 00:43:48,880
Speaker 2: so I kinda yeah, I know what business torts are.

789
00:43:49,520 --> 00:43:52,359
Speaker 2: That's why, which is part of the reason why I'm

790
00:43:52,400 --> 00:43:56,239
Speaker 2: in finance, because I found that stuff kind of not

791
00:43:56,440 --> 00:43:58,239
Speaker 2: nearly as interesting as finances.

792
00:43:58,960 --> 00:44:02,000
Speaker 1: It does make me a lot more aware of all

793
00:44:02,120 --> 00:44:04,520
Speaker 1: the things that could go wrong when you do business

794
00:44:04,560 --> 00:44:08,520
Speaker 1: with people. It's like, no matter what industry it is.

795
00:44:08,640 --> 00:44:14,960
Speaker 1: We've had several cases with indoor trampoline companies, right. I

796
00:44:15,320 --> 00:44:19,040
Speaker 1: was really shocked when the second indoor trampoline company dispute

797
00:44:19,120 --> 00:44:21,440
Speaker 1: came my way. I was like, how many indoor trampoline

798
00:44:21,480 --> 00:44:23,840
Speaker 1: companies are there anyway, meaning like.

799
00:44:23,840 --> 00:44:26,640
Speaker 2: Where kids go to play or companies at manufacture them

800
00:44:26,680 --> 00:44:29,000
Speaker 2: and sell them, because the ones where kids go to play,

801
00:44:29,440 --> 00:44:32,960
Speaker 2: even if you're like padding everything, it still looks like

802
00:44:33,040 --> 00:44:34,160
Speaker 2: a litigation nightmare.

803
00:44:35,400 --> 00:44:39,759
Speaker 1: These are contract disputes between franchisees, franchise ors, distributors, things

804
00:44:39,800 --> 00:44:43,080
Speaker 1: like that. But no matter what type of company it is,

805
00:44:43,719 --> 00:44:48,320
Speaker 1: whether it's a trucking company, a software company, an entertainment company,

806
00:44:48,719 --> 00:44:50,680
Speaker 1: there are only so many types of disputes. It's like

807
00:44:50,760 --> 00:44:53,799
Speaker 1: you don't honor your contract right. You steal someone's money,

808
00:44:54,200 --> 00:44:56,960
Speaker 1: you steal their employees, you steal their trade secrets, you

809
00:44:58,719 --> 00:45:00,960
Speaker 1: take the business opportunity you were meant to do together

810
00:45:01,040 --> 00:45:03,560
Speaker 1: and then do it yourself. And it makes you realize

811
00:45:03,600 --> 00:45:07,640
Speaker 1: that humans act extremely consistently no matter what industry they're in.

812
00:45:07,760 --> 00:45:08,120
Speaker 1: That's right.

813
00:45:08,200 --> 00:45:13,560
Speaker 2: The interesting thing you raised about franchises, I've noticed, and

814
00:45:13,640 --> 00:45:16,520
Speaker 2: it kind of waxes and wings over time, but there

815
00:45:16,600 --> 00:45:22,240
Speaker 2: is a regular series of litigation between franchisees and Burger

816
00:45:22,360 --> 00:45:27,080
Speaker 2: King or McDonald's or whoever the franchiser is. Have you

817
00:45:27,200 --> 00:45:29,560
Speaker 2: looked at those sorts of cases that seems to be

818
00:45:29,760 --> 00:45:31,920
Speaker 2: something that pops up pretty regularly.

819
00:45:33,280 --> 00:45:37,200
Speaker 1: It's not common for us to fund franchise e franchise

820
00:45:37,360 --> 00:45:40,960
Speaker 1: or cases. This is not really detailed because the franchise

821
00:45:41,960 --> 00:45:45,160
Speaker 1: franchise or agreements are written in a pretty air tight way. Yeah.

822
00:45:45,239 --> 00:45:48,759
Speaker 2: No, that McDonald's is as slick and tight as you

823
00:45:48,800 --> 00:45:53,000
Speaker 2: can possibly get. And how much upside is there? What

824
00:45:53,120 --> 00:45:55,239
Speaker 2: made me think of this is I just saw a

825
00:45:55,320 --> 00:45:59,320
Speaker 2: bunch of franchisees or up in arms over the possible

826
00:45:59,400 --> 00:46:02,960
Speaker 2: reintroduction of the five dollars value meal, which McDonald's wants

827
00:46:03,000 --> 00:46:06,800
Speaker 2: to do, and somebody claimed it's violation of their franchise agreement.

828
00:46:06,840 --> 00:46:10,400
Speaker 2: I'm I gotta think McDonald's is savvier than that, Like,

829
00:46:10,520 --> 00:46:12,799
Speaker 2: if they want to introduce the fi dollar value meal,

830
00:46:14,360 --> 00:46:16,160
Speaker 2: you're gonna you're gonna have to eat it. You know,

831
00:46:16,280 --> 00:46:18,799
Speaker 2: it's it's even if it's a if it's a break

832
00:46:18,840 --> 00:46:21,080
Speaker 2: even or a loss. They're doing it to bring bodies

833
00:46:21,800 --> 00:46:25,480
Speaker 2: into the store, and I have to imagine it's covered

834
00:46:25,520 --> 00:46:26,600
Speaker 2: in the franchise agreement.

835
00:46:26,760 --> 00:46:31,680
Speaker 1: Another commonly misunderstood litigation is the McDonald's coffee litigation. Did

836
00:46:31,719 --> 00:46:32,640
Speaker 1: you hear about that? Oh?

837
00:46:32,719 --> 00:46:38,920
Speaker 2: God, that's an infamous one which anti anti lawyer people

838
00:46:39,560 --> 00:46:41,920
Speaker 2: talk about all the time, but when you read the

839
00:46:41,960 --> 00:46:45,120
Speaker 2: facts of the case, this woman was badly scolded. The

840
00:46:45,239 --> 00:46:49,480
Speaker 2: coffee was thirty degrees hotter than the typical takeout coffee.

841
00:46:49,640 --> 00:46:52,279
Speaker 2: They screwed up. They have the top on. I mean,

842
00:46:52,520 --> 00:46:56,160
Speaker 2: there's talk about the wronghill to die on. If you're

843
00:46:56,200 --> 00:46:59,959
Speaker 2: against litigation as a way to solve some societal problem,

844
00:47:00,760 --> 00:47:02,360
Speaker 2: that's not the case you want to use.

845
00:47:02,880 --> 00:47:06,800
Speaker 1: Right, right. I think that litigation is frequently misunderstood in

846
00:47:06,880 --> 00:47:10,600
Speaker 1: that way. Most people do not want to be in litigation.

847
00:47:10,880 --> 00:47:12,640
Speaker 1: It's not a fun place to be in, which is

848
00:47:12,680 --> 00:47:14,480
Speaker 1: where you see, which is why you see so few

849
00:47:14,600 --> 00:47:18,920
Speaker 1: lawyers act as plaintiffs themselves in litigation because it's just

850
00:47:19,040 --> 00:47:22,319
Speaker 1: not very fun. It kind of eats you from the inside, emotional.

851
00:47:22,040 --> 00:47:26,239
Speaker 2: Straining, it's emotionally difficult. And you know, I always see

852
00:47:26,280 --> 00:47:28,920
Speaker 2: people threatening litigation, and it's like, hey, if you want

853
00:47:28,960 --> 00:47:32,080
Speaker 2: to sue, sue, don't wave a gun around, use it.

854
00:47:32,280 --> 00:47:35,000
Speaker 2: Don't threaten to use it, right, And that's what litigation

855
00:47:35,120 --> 00:47:38,680
Speaker 2: seems to be. Anyone who threatens litigation usually isn't serious,

856
00:47:39,040 --> 00:47:40,840
Speaker 2: right me. Know, when you fired an attorney and you

857
00:47:40,960 --> 00:47:44,200
Speaker 2: filed the summary, you know emotion and complaint, and then

858
00:47:44,239 --> 00:47:46,400
Speaker 2: we can have a conversation about how serious you are.

859
00:47:46,800 --> 00:47:49,920
Speaker 1: Right, The reason that litigation happens is because of a

860
00:47:50,080 --> 00:47:53,840
Speaker 1: gap in expectations between the plaintiff and the defendant. So

861
00:47:53,920 --> 00:47:56,279
Speaker 1: the closer the gap is, the more likely it is

862
00:47:56,400 --> 00:47:59,880
Speaker 1: to settle quickly. And then the wider the gap is,

863
00:48:00,560 --> 00:48:03,480
Speaker 1: whether one side is unreasonable or the other, the more

864
00:48:03,640 --> 00:48:05,680
Speaker 1: likely it is to drag on and actually go to trial.

865
00:48:06,239 --> 00:48:08,600
Speaker 1: And we see this even with going back to the

866
00:48:08,640 --> 00:48:12,280
Speaker 1: earnout example, even with a pretty clear cut eurnout example,

867
00:48:12,480 --> 00:48:14,920
Speaker 1: because it might have stages to it, so you might

868
00:48:15,000 --> 00:48:17,560
Speaker 1: get one million if you hit this milestone, two million

869
00:48:17,600 --> 00:48:20,680
Speaker 1: if you hit this milestone, And even if everyone agrees

870
00:48:20,719 --> 00:48:24,320
Speaker 1: that somewhere between five and ten million, they'll still litigate

871
00:48:24,440 --> 00:48:26,839
Speaker 1: over whether it's five or whether it's meant to be ten.

872
00:48:27,440 --> 00:48:30,680
Speaker 2: The assumption is everybody is operating in good faith, and

873
00:48:30,840 --> 00:48:35,640
Speaker 2: once that good faith disappears, then whatever the opposing party

874
00:48:35,719 --> 00:48:38,560
Speaker 2: is doing is read in a negative light and it

875
00:48:38,840 --> 00:48:43,080
Speaker 2: just gets further and further apart. Yea not a big surprise. So,

876
00:48:43,840 --> 00:48:48,360
Speaker 2: given how tech oriented you are, how much time and

877
00:48:48,440 --> 00:48:51,920
Speaker 2: effort do you spend building out the tech continuing to

878
00:48:52,080 --> 00:48:57,600
Speaker 2: expand it, making it just beefier than it was. How

879
00:48:57,680 --> 00:49:02,319
Speaker 2: much innovation can there be in terms of scraping state

880
00:49:02,440 --> 00:49:05,560
Speaker 2: judicial or federal judicial websites.

881
00:49:06,520 --> 00:49:09,160
Speaker 1: So there are two ways in which we can improve

882
00:49:09,239 --> 00:49:13,200
Speaker 1: the technology. One is adding more data sources for instance,

883
00:49:13,880 --> 00:49:16,880
Speaker 1: you know, adding our government receivable strategy. It was so

884
00:49:17,000 --> 00:49:19,600
Speaker 1: many new government websites that had to be scraped. And

885
00:49:19,640 --> 00:49:22,960
Speaker 1: then the second way is improving our existing process. And

886
00:49:23,440 --> 00:49:25,320
Speaker 1: I don't know if you've heard about the advent of

887
00:49:25,440 --> 00:49:28,719
Speaker 1: generative AI, but it has been kind of a game

888
00:49:28,840 --> 00:49:32,279
Speaker 1: changer for us and for a lot of legal tech

889
00:49:32,320 --> 00:49:36,200
Speaker 1: companies because now we're not just able to analyze the

890
00:49:37,880 --> 00:49:41,800
Speaker 1: the docket, but we're actually able to analyze the rulings

891
00:49:41,880 --> 00:49:45,000
Speaker 1: themselves and figure out what we like about them before

892
00:49:45,040 --> 00:49:45,759
Speaker 1: we reach out too.

893
00:49:45,800 --> 00:49:48,799
Speaker 2: So you're looking at rulings, are you looking at motion

894
00:49:48,960 --> 00:49:53,400
Speaker 2: papers also to see the strength of either either side's argument?

895
00:49:53,880 --> 00:49:55,279
Speaker 2: Is that something else you're looking at?

896
00:49:55,800 --> 00:49:59,080
Speaker 1: We usually analyze the orders themselves, so when an order

897
00:49:59,239 --> 00:50:02,520
Speaker 1: comes down, we can see exactly how many counts were

898
00:50:02,600 --> 00:50:06,919
Speaker 1: denied and how many counts were accepted, and that will

899
00:50:06,960 --> 00:50:09,359
Speaker 1: influence whether we reach out and when we reach out

900
00:50:09,400 --> 00:50:10,239
Speaker 1: and what we say when we.

901
00:50:10,280 --> 00:50:14,279
Speaker 2: Do reach out really interesting. So we're talking about scraping

902
00:50:15,920 --> 00:50:20,719
Speaker 2: data off of websites. In the world of economics, I

903
00:50:20,840 --> 00:50:23,759
Speaker 2: could go to FRED, or I could go to BLS

904
00:50:24,600 --> 00:50:28,200
Speaker 2: or BEEA, and I could just download an Excel spreadsheet

905
00:50:28,320 --> 00:50:33,120
Speaker 2: of all the historical data. Do the states not make

906
00:50:33,320 --> 00:50:36,000
Speaker 2: that sort of data available for anybody who wants it?

907
00:50:36,480 --> 00:50:39,320
Speaker 2: Does it require this complex scraping process.

908
00:50:39,760 --> 00:50:44,160
Speaker 1: So everything that the government does has to be publicly accessible,

909
00:50:44,560 --> 00:50:46,880
Speaker 1: but it doesn't mean that it has to be easy

910
00:50:46,960 --> 00:50:50,520
Speaker 1: to access, which is a completely different standard. And so

911
00:50:50,640 --> 00:50:53,880
Speaker 1: many of these state court websites are extremely difficult to access.

912
00:50:54,640 --> 00:51:00,080
Speaker 1: They are updated every day with new filings, But it

913
00:51:00,120 --> 00:51:02,240
Speaker 1: doesn't mean that you can just go in and download

914
00:51:02,280 --> 00:51:04,480
Speaker 1: a CSV. I mean, if we could, that would make

915
00:51:04,520 --> 00:51:05,279
Speaker 1: our lives so much.

916
00:51:05,200 --> 00:51:07,440
Speaker 2: Easier, although it make it easier for people to come

917
00:51:07,480 --> 00:51:08,239
Speaker 2: in and compete with you.

918
00:51:08,400 --> 00:51:09,080
Speaker 1: That's also true.

919
00:51:10,239 --> 00:51:12,600
Speaker 2: Do you ever get pushed back from states? Hey, why

920
00:51:12,640 --> 00:51:15,120
Speaker 2: are you spending so much time on our servers? We've

921
00:51:15,239 --> 00:51:18,120
Speaker 2: noticed that eighty percent of our traffic was you last week.

922
00:51:18,239 --> 00:51:22,920
Speaker 2: What sort of pushback do you get from individual state websites?

923
00:51:23,360 --> 00:51:25,960
Speaker 1: So that was the problem that Christian ran into at

924
00:51:26,000 --> 00:51:29,080
Speaker 1: Harvard back in the day, and it was because we

925
00:51:29,160 --> 00:51:31,840
Speaker 1: were newbies at it. And when you actually do it

926
00:51:31,920 --> 00:51:34,200
Speaker 1: for a long time, you learn to moderate your traffic

927
00:51:34,360 --> 00:51:36,160
Speaker 1: and only go to the pages that you need to

928
00:51:36,200 --> 00:51:36,400
Speaker 1: go to.

929
00:51:36,640 --> 00:51:38,560
Speaker 2: Right, I'm assuming you could do that at night. You

930
00:51:38,640 --> 00:51:42,080
Speaker 2: could do it when it's less less trafficked. You could

931
00:51:42,120 --> 00:51:44,520
Speaker 2: show up in a way that isn't taxing to them.

932
00:51:44,840 --> 00:51:48,319
Speaker 1: We're trying to build a sustainable business here, not take

933
00:51:48,400 --> 00:51:49,799
Speaker 1: down a state server.

934
00:51:50,160 --> 00:51:53,640
Speaker 2: Right, easy enough. So out of all of these cases

935
00:51:53,719 --> 00:51:57,279
Speaker 2: that you've done over the years, and now you're on

936
00:51:57,400 --> 00:51:58,719
Speaker 2: your fourth fund, is that right?

937
00:51:58,840 --> 00:52:01,719
Speaker 1: Fourth? Fie? Right? We're launching our fourth fund later this year.

938
00:52:02,680 --> 00:52:07,520
Speaker 2: So what's the biggest takeaway from the process that you've learned? Like,

939
00:52:07,719 --> 00:52:11,160
Speaker 2: having done this for nearly a decade, how are you

940
00:52:11,320 --> 00:52:15,200
Speaker 2: looking at this practice of alt credit? What's the big

941
00:52:15,400 --> 00:52:20,720
Speaker 2: lesson you've learned in building the fund since twenty seventeen.

942
00:52:22,239 --> 00:52:28,240
Speaker 1: So I think that people over complicate finance. I've learned

943
00:52:28,280 --> 00:52:31,480
Speaker 1: that if I can't understand someone after having it explained

944
00:52:31,520 --> 00:52:34,880
Speaker 1: to me once or twice, then it probably doesn't make

945
00:52:34,960 --> 00:52:38,640
Speaker 1: sense and they're just pretending to understand it. I think

946
00:52:38,880 --> 00:52:42,520
Speaker 1: the underlying fact of credit or finance or any kind

947
00:52:42,560 --> 00:52:45,560
Speaker 1: of investing is I give you a certain amount of money,

948
00:52:46,120 --> 00:52:49,680
Speaker 1: and you give it back to me if X, y Z,

949
00:52:50,200 --> 00:52:53,200
Speaker 1: and you have to understand under what circumstances you get

950
00:52:53,239 --> 00:52:55,120
Speaker 1: it back and how you get it back, And you

951
00:52:55,200 --> 00:52:57,839
Speaker 1: have to understand under what circumstances you disperse and how

952
00:52:57,920 --> 00:53:01,040
Speaker 1: you disperse, and then you try to minim the gap

953
00:53:01,120 --> 00:53:03,920
Speaker 1: in time and maximize the difference between what you put

954
00:53:03,960 --> 00:53:07,000
Speaker 1: out and what you get back. It's really not that complicated,

955
00:53:07,120 --> 00:53:10,680
Speaker 1: but I think that modern finance has had so many

956
00:53:10,760 --> 00:53:14,279
Speaker 1: smart people try and overcomplicate it that they've obscured that

957
00:53:14,440 --> 00:53:15,279
Speaker 1: very simple fact.

958
00:53:15,840 --> 00:53:19,080
Speaker 2: So I'm going to give you a little pushback on that.

959
00:53:19,680 --> 00:53:23,239
Speaker 2: I think complexity is a feature, not a bug, and

960
00:53:23,440 --> 00:53:28,480
Speaker 2: it's done by people within a particular industry. That's what

961
00:53:28,680 --> 00:53:33,239
Speaker 2: jargon is because they're trying to prevent people from understanding.

962
00:53:33,960 --> 00:53:35,800
Speaker 2: And you're not going to pay for a consultant or

963
00:53:35,800 --> 00:53:38,920
Speaker 2: an expert if it's simple. But look how complex it is.

964
00:53:39,320 --> 00:53:41,000
Speaker 2: Write me a big check and I'll explain it to

965
00:53:41,520 --> 00:53:43,600
Speaker 2: or I'll explain it to whoever you want me to

966
00:53:43,640 --> 00:53:46,880
Speaker 2: explain it to. It seems I completely agree with you,

967
00:53:47,520 --> 00:53:50,600
Speaker 2: but a lot of what I see that's complex.

968
00:53:51,760 --> 00:53:52,520
Speaker 1: It's intentional.

969
00:53:52,760 --> 00:53:56,279
Speaker 2: You have to look at the insensive the incentive to

970
00:53:56,400 --> 00:54:00,200
Speaker 2: make things simple and understandable versus the incentive for them

971
00:54:00,239 --> 00:54:02,560
Speaker 2: to be complex, and the amount of fees that can

972
00:54:02,640 --> 00:54:03,400
Speaker 2: be charged on that.

973
00:54:04,280 --> 00:54:07,880
Speaker 1: My other pet theory about finance is that there are

974
00:54:08,760 --> 00:54:13,080
Speaker 1: many ways to make money, but most of them have

975
00:54:13,360 --> 00:54:17,360
Speaker 1: markets associated. And so anytime there's a market, the purpose

976
00:54:17,440 --> 00:54:19,760
Speaker 1: of a market is to compete out all the alpha

977
00:54:20,440 --> 00:54:24,120
Speaker 1: and so what people are saying is usually I'm smarter

978
00:54:24,280 --> 00:54:27,080
Speaker 1: than everyone else in the market, and that goes against

979
00:54:27,120 --> 00:54:30,440
Speaker 1: the fundamental efficient market hypothesis, right, And so where you

980
00:54:30,480 --> 00:54:33,000
Speaker 1: should try to be instead is the area where there

981
00:54:33,080 --> 00:54:35,040
Speaker 1: hasn't been a market formed yet. You should try to

982
00:54:35,080 --> 00:54:37,680
Speaker 1: be at the place where there isn't a sale and

983
00:54:37,760 --> 00:54:40,400
Speaker 1: then try to force them into a sale. Rather than

984
00:54:40,440 --> 00:54:42,479
Speaker 1: going to the auction house and assuming that you're buying

985
00:54:42,560 --> 00:54:44,000
Speaker 1: the art for the right price.

986
00:54:44,120 --> 00:54:47,719
Speaker 2: Right, when you're buying in a deep broad market, you

987
00:54:47,760 --> 00:54:51,480
Speaker 2: would assume that you're going to get something close to

988
00:54:51,600 --> 00:54:54,359
Speaker 2: fair value. It's not going to be If it's too

989
00:54:54,480 --> 00:54:57,319
Speaker 2: much over fair value, well people aren't going to buy it, right.

990
00:54:57,440 --> 00:54:59,680
Speaker 2: And if it's too much under fair value, it'll attract

991
00:54:59,760 --> 00:55:05,080
Speaker 2: enough competition that will eventually inefficiencies get arbitraged out of

992
00:55:05,120 --> 00:55:08,520
Speaker 2: the market. So let me throw you one curveball before

993
00:55:08,560 --> 00:55:11,920
Speaker 2: we get to our favorite questions. And I'm kind of

994
00:55:12,040 --> 00:55:16,560
Speaker 2: fascinated by this. So you publish essays kind of regularly

995
00:55:17,320 --> 00:55:21,440
Speaker 2: at Silicone Valet, and one of the questions I found.

996
00:55:21,640 --> 00:55:23,640
Speaker 2: One of the essays I found that was so interesting

997
00:55:23,800 --> 00:55:26,800
Speaker 2: is I woke up and I found that the Harvard

998
00:55:26,920 --> 00:55:31,919
Speaker 2: Registrars has finally shut down my at Harvard dot edu

999
00:55:32,640 --> 00:55:36,600
Speaker 2: email address. And even though you dropped out in twenty sixteen,

1000
00:55:36,680 --> 00:55:40,000
Speaker 2: you kept promising yourself, Hey, I'd be back on campus

1001
00:55:40,120 --> 00:55:44,200
Speaker 2: in the fall. Was that a little bittersweet losing your

1002
00:55:45,080 --> 00:55:49,440
Speaker 2: undergraduate email address? Because I know people at other schools

1003
00:55:49,520 --> 00:55:52,800
Speaker 2: like Wharton and Yale, they graduate, they keep that email

1004
00:55:52,800 --> 00:55:54,120
Speaker 2: address for their whole lives.

1005
00:55:55,080 --> 00:55:58,960
Speaker 1: So the interesting thing about my life has been that

1006
00:55:59,360 --> 00:56:02,560
Speaker 1: I kind of grew up with the company. So when

1007
00:56:02,560 --> 00:56:07,040
Speaker 1: I started the company, I was twenty and I was

1008
00:56:07,280 --> 00:56:10,520
Speaker 1: basically just out of my parents' house. And these days

1009
00:56:11,480 --> 00:56:14,040
Speaker 1: I have my own house and I have a one

1010
00:56:14,080 --> 00:56:18,880
Speaker 1: year old baby. And last fall I made Thanksgiving dinner

1011
00:56:19,000 --> 00:56:23,239
Speaker 1: for the first time and A lot of what I

1012
00:56:23,360 --> 00:56:26,560
Speaker 1: think about when I think about leaving Harvard is that

1013
00:56:27,800 --> 00:56:30,400
Speaker 1: it's really like gazing back at your own youth, and

1014
00:56:30,520 --> 00:56:33,200
Speaker 1: so you feel a lot of nostalgia for the person

1015
00:56:33,280 --> 00:56:35,239
Speaker 1: that you used to be and how different you are

1016
00:56:35,400 --> 00:56:39,160
Speaker 1: from them. And along the way, you know, I poured

1017
00:56:39,239 --> 00:56:41,759
Speaker 1: those years into the company and grew it to where

1018
00:56:41,800 --> 00:56:43,759
Speaker 1: it is today. So I think that's really what that

1019
00:56:44,320 --> 00:56:45,719
Speaker 1: essay is reflecting.

1020
00:56:45,880 --> 00:56:49,000
Speaker 2: All right, let's jump to our speed round, our favorite questions.

1021
00:56:49,080 --> 00:56:51,960
Speaker 2: We ask all our guests, starting with tell us what

1022
00:56:52,080 --> 00:56:54,160
Speaker 2: you're streaming these days? What are you watching or listening

1023
00:56:54,200 --> 00:56:56,239
Speaker 2: to that's keeping you entertained.

1024
00:56:57,160 --> 00:56:59,759
Speaker 1: So I'm a big fan of Morgan Housel's podcast, where

1025
00:57:00,000 --> 00:57:04,400
Speaker 1: talks about the psychology of money. It's very rare to

1026
00:57:04,480 --> 00:57:09,080
Speaker 1: find someone who's deeply philosophical but also interested in finance,

1027
00:57:09,280 --> 00:57:11,880
Speaker 1: and his podcast is the perfect intersection of that.

1028
00:57:12,320 --> 00:57:15,960
Speaker 2: Let's talk about your mentors who helped to shape your career.

1029
00:57:17,520 --> 00:57:22,080
Speaker 1: I'm going to have to say our old general counsel Curtis,

1030
00:57:22,280 --> 00:57:25,520
Speaker 1: who shaped everything that Christian and I know about litigation

1031
00:57:25,680 --> 00:57:27,960
Speaker 1: and also made us lawyers like it.

1032
00:57:28,800 --> 00:57:31,000
Speaker 2: Let's talk about books. What are some of your favorites

1033
00:57:31,000 --> 00:57:32,240
Speaker 2: and what are you reading right now?

1034
00:57:32,680 --> 00:57:35,600
Speaker 1: Oh? Okay, So there are two people who have worked

1035
00:57:35,640 --> 00:57:39,760
Speaker 1: in finance who have written actual literary works. One is

1036
00:57:40,000 --> 00:57:43,160
Speaker 1: Gary Sernowitz, who wrote The Counting House and I've got

1037
00:57:43,240 --> 00:57:46,520
Speaker 1: a copy for you today. And then the second is

1038
00:57:46,680 --> 00:57:49,640
Speaker 1: this guy name Amore Towels, who worked at an investment

1039
00:57:49,760 --> 00:57:53,800
Speaker 1: bank for twenty years and then switched completely to writing fiction.

1040
00:57:54,240 --> 00:57:55,920
Speaker 1: And so what I like about his stuff is that

1041
00:57:56,200 --> 00:58:00,240
Speaker 1: most literary authors have only ever been authors. And you're

1042
00:58:00,240 --> 00:58:03,280
Speaker 1: an author, you are coming from a place of passivity

1043
00:58:03,320 --> 00:58:05,720
Speaker 1: where you're not actually an actor in the world. You

1044
00:58:05,840 --> 00:58:08,320
Speaker 1: have no ability to change the world. You're just observing it.

1045
00:58:08,920 --> 00:58:12,400
Speaker 1: But because Amortowels has been in business for so long,

1046
00:58:12,880 --> 00:58:17,600
Speaker 1: he writes characters that are extremely proactive and optimistic and

1047
00:58:17,720 --> 00:58:20,200
Speaker 1: have such a good attitude that they're able to shape

1048
00:58:20,240 --> 00:58:22,520
Speaker 1: the world around them. So his most famous one is

1049
00:58:22,560 --> 00:58:23,920
Speaker 1: called a Gentleman in Moscow.

1050
00:58:24,240 --> 00:58:24,880
Speaker 2: Oh of course.

1051
00:58:25,040 --> 00:58:28,120
Speaker 1: Yeah. The main character is literally trapped in a hotel

1052
00:58:28,680 --> 00:58:32,360
Speaker 1: in revolutionary Russia, but he manages to create a life there,

1053
00:58:32,400 --> 00:58:35,080
Speaker 1: which shows that you can you can change your environment

1054
00:58:35,120 --> 00:58:36,320
Speaker 1: no matter what your environment is.

1055
00:58:36,480 --> 00:58:38,480
Speaker 2: You know, I used to think all of the Michael

1056
00:58:38,560 --> 00:58:42,160
Speaker 2: Lewis books that were so interesting were because he spent

1057
00:58:42,320 --> 00:58:46,240
Speaker 2: years in finances at Salomon Brothers. So Liar's Poker and

1058
00:58:46,320 --> 00:58:49,400
Speaker 2: The Big Short. Yeah, but then you start to see

1059
00:58:49,480 --> 00:58:55,720
Speaker 2: his other books like Moneyball or The blind Side or

1060
00:58:55,840 --> 00:59:00,360
Speaker 2: the Pandemic book Premonition, and he has no experience in

1061
00:59:00,400 --> 00:59:04,720
Speaker 2: those spaces. He's just like an incredibly talented writer. Yeah,

1062
00:59:05,960 --> 00:59:10,360
Speaker 2: but that's really an interesting set of observations. The guy

1063
00:59:10,400 --> 00:59:12,560
Speaker 2: who wrote Gentlemen in Moscow. What are some of the

1064
00:59:12,640 --> 00:59:15,000
Speaker 2: other books he's written.

1065
00:59:14,800 --> 00:59:19,240
Speaker 1: That you like. He has one that he just published

1066
00:59:19,400 --> 00:59:22,520
Speaker 1: called Table for Two. And then my favorite of his

1067
00:59:22,760 --> 00:59:25,760
Speaker 1: is a short story called You Have Arrived at Your Destination.

1068
00:59:26,360 --> 00:59:29,720
Speaker 1: And the short story is about this idea that if

1069
00:59:29,800 --> 00:59:31,760
Speaker 1: you were to be able to project the lives of

1070
00:59:31,840 --> 00:59:35,040
Speaker 1: your children, it would be in three acts like a play.

1071
00:59:35,600 --> 00:59:38,600
Speaker 1: So in the first act you have youthful optimism, where

1072
00:59:38,640 --> 00:59:40,640
Speaker 1: you have all these hopes and dreams and the world

1073
00:59:40,720 --> 00:59:43,040
Speaker 1: is opening itself up to you. But then you have

1074
00:59:43,120 --> 00:59:46,040
Speaker 1: the second act where you experience a setback. And he

1075
00:59:46,200 --> 00:59:49,160
Speaker 1: calls this second act setback coming to terms with their

1076
00:59:49,200 --> 00:59:52,640
Speaker 1: own limitations. And at this point a lot of people

1077
00:59:52,880 --> 00:59:55,880
Speaker 1: just retreat or they give up. But then if you're

1078
00:59:55,920 --> 00:59:58,000
Speaker 1: able to kind of accept who you are, you can

1079
00:59:58,080 --> 01:00:01,480
Speaker 1: move into the third phase, which is a place where

1080
01:00:01,480 --> 01:00:03,600
Speaker 1: you can be a better person and live a deeper

1081
01:00:03,680 --> 01:00:04,400
Speaker 1: and richer life.

1082
01:00:04,640 --> 01:00:08,000
Speaker 2: I can't argue with that. That sounds pretty accurate. Our

1083
01:00:08,120 --> 01:00:12,680
Speaker 2: final two questions, some of which I'm really curious to

1084
01:00:12,720 --> 01:00:15,920
Speaker 2: see your answers. So what sort of advice would you

1085
01:00:16,040 --> 01:00:19,960
Speaker 2: give I shouldn't even say, reaching recent college grad somebody

1086
01:00:20,040 --> 01:00:24,080
Speaker 2: in college who was interested in a career in all

1087
01:00:24,480 --> 01:00:28,200
Speaker 2: credit or hedge funds or finance, how would you advise them?

1088
01:00:29,280 --> 01:00:33,520
Speaker 1: So my own trajectory has been a little bit unusual,

1089
01:00:34,400 --> 01:00:37,720
Speaker 1: and I think that most people assume that finance is

1090
01:00:37,840 --> 01:00:42,080
Speaker 1: an apprenticeship business where you can only learn by studying

1091
01:00:42,160 --> 01:00:44,600
Speaker 1: with someone who has already done it. But I think

1092
01:00:44,680 --> 01:00:47,040
Speaker 1: that coming from that perspective means that you're always going

1093
01:00:47,120 --> 01:00:49,040
Speaker 1: to do it the way that people did it before,

1094
01:00:49,360 --> 01:00:52,960
Speaker 1: and we've always had this advantage from being able to

1095
01:00:53,040 --> 01:00:57,920
Speaker 1: examine everything from first principles. So I guess my advice

1096
01:00:57,960 --> 01:01:01,120
Speaker 1: would be that people should not be afraid to deviate

1097
01:01:01,280 --> 01:01:03,240
Speaker 1: from that traditional lockstep path.

1098
01:01:03,840 --> 01:01:06,200
Speaker 2: And our final question, what do you know about the

1099
01:01:06,240 --> 01:01:12,800
Speaker 2: world of litigation, finance, data scraping, investing, Waltz credit today

1100
01:01:13,320 --> 01:01:15,960
Speaker 2: you wish you knew back in twenty sixteen when you

1101
01:01:16,040 --> 01:01:18,680
Speaker 2: were first thinking about launching the business.

1102
01:01:19,400 --> 01:01:23,479
Speaker 1: Back then, I really didn't know anything. So being young

1103
01:01:23,720 --> 01:01:26,360
Speaker 1: is like having a flashlight that only shines on and

1104
01:01:26,440 --> 01:01:27,840
Speaker 1: step ahead of you and no further.

1105
01:01:29,000 --> 01:01:29,920
Speaker 2: That's very interesting.

1106
01:01:30,480 --> 01:01:32,760
Speaker 1: I don't think that there's anything that I've could have

1107
01:01:32,840 --> 01:01:35,600
Speaker 1: told myself that I would have had the context to understand.

1108
01:01:35,800 --> 01:01:39,960
Speaker 2: So it's really the journey, the process that you learn

1109
01:01:40,000 --> 01:01:42,920
Speaker 2: along the way. Even had you started with what you

1110
01:01:43,080 --> 01:01:45,080
Speaker 2: know today, it doesn't sound like you think it would

1111
01:01:45,080 --> 01:01:46,000
Speaker 2: have been in any use.

1112
01:01:46,400 --> 01:01:51,840
Speaker 1: Yeah, So land Samantha Chang has this quote where she says,

1113
01:01:52,640 --> 01:01:55,280
Speaker 1: if I could change anything about my life, I would

1114
01:01:55,320 --> 01:01:57,320
Speaker 1: not have been so unhappy when I was young.

1115
01:01:57,920 --> 01:02:01,200
Speaker 2: You're so focused on the future sometimes forget to enjoy

1116
01:02:01,280 --> 01:02:04,680
Speaker 2: the moment exactly, and that is very true for a

1117
01:02:04,720 --> 01:02:08,760
Speaker 2: lot of young people, especially in hyper competitive fields, no

1118
01:02:08,880 --> 01:02:12,000
Speaker 2: doubt about it. Well, Eva, this has been absolutely fascinating.

1119
01:02:12,040 --> 01:02:14,480
Speaker 2: We have been speaking with Eva Shang. She is the

1120
01:02:14,560 --> 01:02:18,960
Speaker 2: co founder, CEO, and general partner at Legalist. If you

1121
01:02:19,200 --> 01:02:21,800
Speaker 2: enjoy this conversation, well check out any of the past

1122
01:02:22,480 --> 01:02:26,560
Speaker 2: five hundred discussions we've had over the previous July will

1123
01:02:26,600 --> 01:02:30,320
Speaker 2: be ten years. You can find those at iTunes, Spotify, YouTube,

1124
01:02:30,440 --> 01:02:34,280
Speaker 2: wherever you find your favorite podcast. Be sure and check

1125
01:02:34,320 --> 01:02:38,400
Speaker 2: out my new podcast At the Money, short ten minute

1126
01:02:38,440 --> 01:02:44,080
Speaker 2: conversations with experts about topics that affect your cash, earning it,

1127
01:02:44,240 --> 01:02:48,160
Speaker 2: spending it, and most importantly, investing it. You can find

1128
01:02:48,160 --> 01:02:50,880
Speaker 2: those in the Masters and Business feed, or wherever you

1129
01:02:51,000 --> 01:02:54,640
Speaker 2: find your favorite podcasts. I would be remiss if I

1130
01:02:54,720 --> 01:02:56,760
Speaker 2: did not thank the Cracked team that helps us put

1131
01:02:56,800 --> 01:03:00,760
Speaker 2: these conversations together each week. Sage Bauman is my head

1132
01:03:00,920 --> 01:03:05,040
Speaker 2: of Podcasts at Bloomberg. Sarah Livesey is my audio engineer

1133
01:03:05,160 --> 01:03:08,880
Speaker 2: at Tiko of Albroun. My project manager, Anna Luke is

1134
01:03:08,960 --> 01:03:14,040
Speaker 2: my producer. Sean Russo my researcher. I'm Barry Brittoltz. You've

1135
01:03:14,080 --> 01:03:17,640
Speaker 2: been listening to Masters in Business on Bloomberg Radio.