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

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Speaker 2: This week on the podcast, yet another extra special guest.

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Speaker 2: Jason Wenk is founder and CEO of Altruists, a new

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Speaker 2: artificial intelligence driven custodian challenging a lot of the legacy

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Speaker 2: entities like Fidelity and Schwab that are stuck with all

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Speaker 2: of their old hardware and software. I thought the conversation

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Speaker 2: was fascinating, and I think you will also with no

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Speaker 2: further ado, my interview of Jason Wenck. Jason Wenks, Welcome

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Speaker 2: to Bloomberg.

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Speaker 3: My pleasure, such a great intro.

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Speaker 2: Full disclosure. My Firmer Holtzwalth Management uses Altruist, and both

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Speaker 2: myself and my firm are investors in the firm. So

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Speaker 2: I'm fascinated by the through line of your career. You

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Speaker 2: were constantly focusing on creating lower cost, tech enabled financial advice.

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Speaker 2: But I'm going to put a pin in that and

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Speaker 2: come back. I got to start with your background. You

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Speaker 2: study computer science at Grand Valley State University. What was

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Speaker 2: the original career plan. Was it technology and computers or finance?

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Speaker 3: Yeah?

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Speaker 1: Yeah, no, So I'd never taken a finance class. I

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Speaker 1: never met anybody who had money, my family never owned

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Speaker 1: any stocks or mutual funds. I didn't know what an

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Speaker 1: IRA was, or even a four to one K for

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Speaker 1: that matter. But I grew up in the eighties and nineties,

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Speaker 1: so I remember getting our first personal computer.

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Speaker 3: In the mid nineties.

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Speaker 1: You know, Internet started to pick up a little bit

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Speaker 1: of speed in the late nineties, and that was my dream,

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Speaker 1: was to go to Silicon Valley work at a dot com.

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Speaker 1: You know, you probably recall the market peaked out around

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Speaker 1: nineteen ninety nine and then you know, a pretty major

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Speaker 1: crash ensued. So you know, very accidentally did an internship

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Speaker 1: at Morgan Stanley at nineteen years old as a bit

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Speaker 1: of an odd duck in that I took a lot

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Speaker 1: of college classes when I was in high school, so

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Speaker 1: I was already taking doing internships, you know, my first

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Speaker 1: year of university. And yeah, it was presented an opportunity

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Speaker 1: to move here to New York and to join Morgan Stanley,

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Speaker 1: and that was really my crash course in finance.

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Speaker 2: And you were nineteen or twenty.

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Speaker 1: Nineteen as an intern and officially joined at age twenty

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Speaker 1: a half.

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Speaker 2: So what drew you to financial services instead of technology

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Speaker 2: was simply, you know, the dot com implosion, and there

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Speaker 2: was no jobs we had in technology.

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Speaker 3: Yeah, I was still I was still working in technology.

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Speaker 1: So my role, you know, the internship was like productivity software,

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Speaker 1: but again just happened before for a big investment bank.

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Speaker 1: And then I spent about two years building different types

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Speaker 1: of technology, like within the Morgan Stanley ecosystem. By the

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Speaker 1: time I joined, they were Morgan Stanley Dean Witter, so

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Speaker 1: they had this kind of big retail wealth business. They

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Speaker 1: also had like prop trading in a number of other

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Speaker 1: divisions too, So I didn't really get too involved into

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Speaker 1: personal wealth until kind of the latter maybe the last

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Speaker 1: six months I was there.

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Speaker 3: I was put on a project.

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Speaker 1: We're doing a lot of work with morning Star, which

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Speaker 1: back then they were still sending out cd ROMs to

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Speaker 1: branches around the country, and so you know, if you

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Speaker 1: had a big branch, that'd be hard who had the

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Speaker 1: cd romy. So we were just building networked versions of

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Speaker 1: essentially the morning Star database. But I remember around that time,

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Speaker 1: you know, I was I was doing some like pre

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Speaker 1: built prompts inside of these like research platforms. And you know,

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Speaker 1: again my u the way my mind worked, which was

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Speaker 1: more around math, physics, computer science. I looked at these prompts,

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Speaker 1: and I thought these are terrible prompts. In other words,

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Speaker 1: like the prompt would be, let's build a screen so

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Speaker 1: that financial advisors can.

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Speaker 3: Easily build a portfolio.

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Speaker 1: And the screen will be something like find funds that

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Speaker 1: have been around for five years with turnover under one

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Speaker 1: hundred percent with the same manager for you know, for

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Speaker 1: the five years or longer. That's in the top qure

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Speaker 1: tile of their peer group. And it was when you, like,

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Speaker 1: on the surface, you go, well, yeah, it seems like

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Speaker 1: pretty reasonable and fair. But that's as like that is

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Speaker 1: no prediction of the future result. Like I mean, there's

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Speaker 1: like that is a terrible predictor of future outcomes.

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Speaker 3: But it was sort of built as as it was

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Speaker 3: a good per.

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Speaker 2: Well, you have the data past performances right there. We

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Speaker 2: exactly something with it. I give Morning Star credit. They

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Speaker 2: had an internal survey that more or less said, hey,

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Speaker 2: don't worry about the stars. The data shows if you

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Speaker 2: just buy the least expensive fund, that's the one most

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Speaker 2: likely to give you the highest level of performance. And

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Speaker 2: to their credit, they published that. I want to say

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Speaker 2: that was like twenty eleven. Yeah as well, really fascinating.

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Speaker 2: So you never really worked rotated through the departments where

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Speaker 2: you're smiling and dialing. Did you ever work as a broker?

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Speaker 3: So I got license.

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Speaker 1: I took the series seven, series eight, series, twenty four

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Speaker 1: series sort of like all the classic life.

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Speaker 2: Twenty four you want to be super.

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Speaker 1: Yeah, yeah, I'm not sure why. I also like a

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Speaker 1: registered options principle.

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Speaker 3: I did that.

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Speaker 1: I have no idea manage futures. Like again, not sure

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Speaker 1: why I did that, but yeah, I did all of this,

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Speaker 1: the the did all of the research to understand the space,

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Speaker 1: and I did go through the broker training program sort

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Speaker 1: of twenty twenty one. And part of it was because

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Speaker 1: I wanted to move back to the Midwest twenty one

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Speaker 1: actually two thousand and one.

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Speaker 3: Yeah, yeah, little datch mistake there.

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Speaker 1: Yeah, And you know, I think I had this like

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Speaker 1: romantic notion of like going back home and you know,

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Speaker 1: helping people that I knew. The real is nobody knew

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Speaker 1: any money, you know, so like that wasn't really going

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Speaker 1: to work anyway. And really before I even got started,

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Speaker 1: I made the decision to leave and go start another business.

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Speaker 1: I'm kind of in the space, but adjacent didn't do

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Speaker 1: direct work with clients.

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Speaker 2: So let's talk about that What was the first thing

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Speaker 2: that you noticed in financial advice that led you to say, hey,

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Speaker 2: this is broken, and I think I could use technology

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Speaker 2: to build something better. Yeah.

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Speaker 3: I mean so two things in particular.

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Speaker 1: I mean, one was the around that time there was

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Speaker 1: a transition from commission bake based you know, sort of

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Speaker 1: sales brokers, if you will, and there was a transition

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Speaker 1: to more fee oriented financial planners. And for me that

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Speaker 1: really resonated. So I think this notion of hey, can

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Speaker 1: you give people more comprehensive planning advice and.

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Speaker 2: Be a fiduciary?

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Speaker 3: Yeah.

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Speaker 1: And also I mean I look, I looked realistically at

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Speaker 1: the way asset management worked, and I thought that, you know,

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Speaker 1: I've very much agreed with the morning Star study that

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Speaker 1: you know, they published, He said some ten years later.

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Speaker 1: You know a lot of this, Uh you know, I'd say,

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Speaker 1: goes all the way back to Jack Bogel's work. But

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Speaker 1: I just, you know, looking at you a couple of

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Speaker 1: years worth of research around asset management, I didn't see

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Speaker 1: a discernible benefit to stock.

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Speaker 3: Picking or market timing.

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Speaker 1: You know, again, high high cost, high turnover, high taxes

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Speaker 1: like these all eroded wealth. So part of you, well,

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Speaker 1: is there a way that you can just get more

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Speaker 1: people access to empirically sort of evidence based investing. Maybe

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Speaker 1: that's will help people do better. The other part was accessibility. Again,

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Speaker 1: I grew up like in a farming town. Really there

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Speaker 1: were no brokers, there were no bank advisors, there were

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Speaker 1: no Edward Jones offices, like, there was really no access

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Speaker 1: to advice. And I could see the direction the Internet

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Speaker 1: was taking as to really flattening the world, like everybody

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Speaker 1: should be able to find advice and help, you know,

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Speaker 1: through through the internet. So really the first business was

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Speaker 1: from accessibility perspective is going to be internet based. It

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Speaker 1: was a subscription service and it was designed for people

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Speaker 1: with four to one k's because when I looked at

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Speaker 1: the people, I knew that was about the closest thing

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Speaker 1: they had to Wall Street to a broke Wridge account

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Speaker 1: was their defined kind tribution plan. So the idea was,

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Speaker 1: let's make it easy for people that have a four

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Speaker 1: one K plan to get the absolute best results they

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Speaker 1: can from their four one K and and I spent

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Speaker 1: about almost three years building that business.

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Speaker 2: It's like not environment Wealth Advisors, this this.

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Speaker 1: Is the one that doesn't exist on my LinkedIn profiles.

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Speaker 2: You know, this is before that.

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Speaker 1: Oh yeah, yeah, yeah, is I spent you know, from

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Speaker 1: twenty twenty one until twenty twenty four, effectively building a

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Speaker 1: four to one K subscription business.

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Speaker 2: Two thousand and one to two two thousand and one.

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Speaker 1: Gosh, you' shows how old I am, very my vision

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Speaker 1: only my decades and just trends in one yeah. Yeah, yeah,

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Speaker 1: so two thousand and one until two thousand and four,

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Speaker 1: and yeah, it was honestly, like when I look back

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Speaker 1: at it, it.

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Speaker 3: Was just kind of like maybe a little bit too early.

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Speaker 1: This was like pre robo Advisor, pre blogging, like pre

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Speaker 1: a lot of things that you know, just got more

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Speaker 1: people connected, but.

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Speaker 2: Those just start. Yeah, we went from GeoCities.

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Speaker 3: Yeah, you're a real trailblazer in that.

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Speaker 2: Yeah, it was a compulsion.

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Speaker 1: I had no choice, so I look the the pay

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Speaker 1: per click advertising was just coming out. So you had

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Speaker 1: things like overture, which is like kind of pre Yahoo,

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Speaker 1: pre Google, but you could buy the keyword for something

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Speaker 1: like a phrase like how to manage my four one

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Speaker 1: K for a penny, right, and you could be the

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Speaker 1: top ranked you know, search people then land on my website,

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Speaker 1: which is called smarter than Wall Street back then, and yeah,

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Speaker 1: and it would allow you to say, I work at

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Speaker 1: General Motors, answer a few questions, and it would say,

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Speaker 1: here's how to allocate your four one k. They'd get

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Speaker 1: an email once a month if there was anything they

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Speaker 1: should do differently. Of course, the email never said that

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Speaker 1: I should ever do anthing differently. And after about a year,

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Speaker 1: you know, I started I built a pretty good size

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Speaker 1: subscription business. But I started to have some churn because

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Speaker 1: people are like, why am I paying you every month

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Speaker 1: to just send an email that says the same thing

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Speaker 1: as the email the month before. And eventually I started

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Speaker 1: asking people what would be more valuable, sort of like

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Speaker 1: a churn survey, if you will, and people would say, look,

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Speaker 1: if you would just do this for me, I'd pay

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Speaker 1: you a lot more than twenty bucks a month. Like

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Speaker 1: that was really the genesis to retirement wealth, you know,

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Speaker 1: And that's even why it was called retirement wealth, because

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Speaker 1: a lot of these four and K folks were retirement folks.

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Speaker 2: And that scaled up pretty rapidly. That when was that

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Speaker 2: the four billion dollar advisory shop or that? Where did

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Speaker 2: that go?

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Speaker 1: And so I ended up going to about one point

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Speaker 1: one or one point two billion in assets.

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Speaker 3: Yeah, groovily fast.

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Speaker 1: I started it in November December of two thousand and four,

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Speaker 1: was when I got my registration. Ran that for about

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Speaker 1: six years.

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Speaker 2: Roughly a billion in AUM is not in substantial. It

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Speaker 2: put you into.

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Speaker 3: A category, especially back then.

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Speaker 2: Yeah, no, the inflation adjusted, we're probably talking about three

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Speaker 2: billion today. But that's real revenue, that's real clients. What

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Speaker 2: made you say, all right, I've kind of done this,

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Speaker 2: now let's look at formula folios.

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Speaker 1: Yes, so I was always I was always driven probably

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Speaker 1: more by impact than by like the size of assets

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Speaker 1: or a revenue.

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Speaker 3: You know, that company was bootstrapped.

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Speaker 1: I built every single thing myself, wrote all of the code.

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Speaker 3: You know.

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Speaker 1: It was although the name was Retirement Wealth, it was

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Speaker 1: a fairly tech forward platform. I built my own proposal

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Speaker 1: systems to help, you know, really analyze the portfolio and

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Speaker 1: then propose a new solution.

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Speaker 3: H digitize, a.

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Speaker 1: Lot of onboarding to really automate getting new clients on boarded.

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Speaker 3: And it was mostly virtual.

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Speaker 1: So it was also before it's time in the sense

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Speaker 1: that it was built mostly from blogging, you know, back

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Speaker 1: in like the two thousand and six to ten era.

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Speaker 1: So you know, it was a lot of things that

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Speaker 1: was doing well before it's time. And what ended up

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Speaker 1: happening really the catalyst to moving into the next business

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Speaker 1: was I was invited to speak at TDM Error Trades

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Speaker 1: National Conference.

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Speaker 3: They were my custodian at the time. I loved, loved

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Speaker 3: the people there.

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Speaker 1: They saw the unusual growth and also that I was

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Speaker 1: still in my twenties and and they thought, hey, we'd

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Speaker 1: love to have you come speak and share a bit

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Speaker 1: how you're doing what you're doing. So I went to

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Speaker 1: San Diego, Uh, you know, I gave a session where

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Speaker 1: I just said, hey, here's how I'm get you know,

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Speaker 1: getting new clients. I'm writing these blog posts. Here's the

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Speaker 1: framework how I do it. Here's how I take these

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Speaker 1: people then through you know, from a you know stranger

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Speaker 1: from the internet, you know, into a defined financial planning

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Speaker 1: process and then a defined you know portfolio. And it

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Speaker 1: was so you know, structured that I could then train

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Speaker 1: other advisors, and so I hired a few other advisors.

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Speaker 1: They came out they could then run the process, and

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Speaker 1: so that was the content and at that time a

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Speaker 1: bunch of other advisors and I'd say hundreds of other

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Speaker 1: advisors started to reach out inbound, Hey how can I

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Speaker 1: get access to your system, they would kind.

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Speaker 3: Of call it.

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Speaker 1: And the reality was, like, I didn't want to hire

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Speaker 1: fifty financial planners. I I've always been a bit reclusive,

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Speaker 1: so I didn't, you know, I didn't want to.

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Speaker 2: You don't want to manage fifty Yeah, but selling them

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Speaker 2: the software, yeahs a fair relationship.

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Speaker 3: That seemed a lot better, right.

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Speaker 1: So yeah, so just the idea of responded, Hey, maybe

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Speaker 1: it makes more sense to license the software, make it

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Speaker 1: easier for people to run their own business, but leveraging

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Speaker 1: a lot of our technology.

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Speaker 2: And that was the was that formula folios?

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Speaker 3: Correct? Yeah?

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Speaker 2: All right? And how big did that scale up to?

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Speaker 1: Someone went zero to four billion in five years and

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Speaker 1: today it's I think fourteen billion or something like that.

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Speaker 2: So I know that you were a programmer in college.

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Speaker 2: You describe yourself as a developer and a math geek.

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Speaker 2: You very much have a little bit of a hacker mentality.

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Speaker 2: How did that technical I don't want to use the

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Speaker 2: word self identity, but just your self perception. How did

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Speaker 2: that affect your view of here are the services that

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Speaker 2: make sense for investors, for advisors, for this whole ecosystem

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Speaker 2: that has been especially in the two thousands, mostly ignored

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Speaker 2: by Wall Street, Like it took twenty five years before

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Speaker 2: the fiduciary side to pass the commission based brokeward side.

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Speaker 2: So how did the technology background affect just your perception

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Speaker 2: of that market?

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Speaker 1: Sure, I mean, look, I think I've always been a

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Speaker 1: little bit idyllic. You know, you name your company altruist,

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Speaker 1: you probably have probly have some like generally, yeah, I

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Speaker 1: don like tendencies, but you know, I think you know,

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Speaker 1: I think people know me well they would say I'm

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Speaker 1: I'm a bit of a macro thinker, but I don't

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Speaker 1: like working in the day to day weeds of most things.

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Speaker 1: So for me, I've always thought in decades, and it

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Speaker 1: wasn't hard to look at the market in the early

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Speaker 1: two thousands and say, well, this is the future, even

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Speaker 1: though to your point, like the RIA fiduciary channel, back

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Speaker 1: in two thousand and four when I started my first firm,

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Speaker 1: I mean, it was maybe six to eight hundred billion

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Speaker 1: in assets. You know today it's probably ten trillion, So

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Speaker 1: today it seems very obvious, but back then it was

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Speaker 1: a real relatively small part of the market. It was

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Speaker 1: was not obvious maybe to everybody. But I look at

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Speaker 1: like the demographics of the country and just there'll be

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Speaker 1: such a huge number of people who are going to

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Speaker 1: need good quality advice and planning, and that just again,

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Speaker 1: if you if you think in first principles, which is

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Speaker 1: a very common technology metaphor, and you you have no

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Speaker 1: bias of like the way things had been done historically,

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Speaker 1: just say well, what is the right way to do things?

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Speaker 1: That just seemed like the obvious and only an objective

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Speaker 1: you know, future for this industry, and I wanted to be,

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Speaker 1: you know, on the forefront of that. So yeah, so

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Speaker 1: now you know, some twenty plus years later, you know,

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Speaker 1: the market is you know, very obvious to a lot

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Speaker 1: of people. They want to build in the space, and

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Speaker 1: it's the place that seems to be growing the fastest.

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Speaker 1: That was crystal clear to me twenty years ago. I

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Speaker 1: think a lot of it comes from just again in

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Speaker 1: that more first principled you know, sort of Silken Valley

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Speaker 1: way of seeing the world.

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Speaker 2: Coming up, we continue our conversation with Jason Wenk, founder

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Speaker 2: and CEO of Altruist, discussing how we built the firm

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Speaker 2: to compete with the big guys. I'm Barry Ridults. You're

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Speaker 2: listening to masters in business on Bloomberg Radio. I'm Barry

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Speaker 2: rid Haults. You're listening to Masters in Business on Bloomberg Radio.

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Speaker 2: My guest this week is Jason Wenk, founder and CEO

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Speaker 2: of The New Custodian Altruist. So Altruist describes itself as

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Speaker 2: a modern custodian emphasis on modern for independent financial advisors.

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Speaker 2: What does that mean in the real world? And this

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Speaker 2: has always been such like a boring, you know, plumbing

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Speaker 2: type of industry. What was broken that required your attention?

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Speaker 1: Yeah, well, I guess you know, the the the opposite

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Speaker 1: of modern is not modern.

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Speaker 3: And you know, so that the whole rest of the

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Speaker 3: industry is pretty old.

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Speaker 1: If you think about most of the infrastructure that's used

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Speaker 1: by financial professionals, the majority of its fifty to seventy

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Speaker 1: years old.

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Speaker 2: That's amazing.

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Speaker 1: And it operates on mainframes, not you know, cloud native platforms.

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Speaker 1: So I think like the starting point is and with

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Speaker 1: no disrepect, these were innovative companies fifty years ago.

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Speaker 3: You know, they're just not that innovative today. So as

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Speaker 3: far as I get.

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Speaker 2: You're saying the electric type right or heage anymore.

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Speaker 3: I mean they're still fun to use, you know.

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Speaker 2: The click and they make a nice noise.

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Speaker 1: Yeah, it's like it feels very uh, you know, it

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Speaker 1: reminds me of like my grandparents' house in the nineties

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Speaker 1: or something.

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Speaker 3: You know.

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Speaker 1: So look the I think getting to the problem statements.

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Speaker 1: Having been in the space a long time, for the

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Speaker 1: longest time, I would look at the industry and go,

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Speaker 1: that just doesn't make any sense. You know, why do

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Speaker 1: we why do we do it this way? Right, So

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Speaker 1: you've always done it that way, Yeah, exactly right, It

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Speaker 1: doesn't mean it's the right way. And so some examples

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Speaker 1: of that, I think it's a bit crazy that if

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Speaker 1: you use if you're a financial advisory, wealth manager, and

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Speaker 1: I think if someone's listening to this and they're not

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Speaker 1: one of those who they'll think this is literally crazy.

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Speaker 3: This is what works.

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Speaker 1: But so first you have to have a custodian right

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Speaker 1: and this is a place where you'll open accounts for

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Speaker 1: your clients. They'll safeguard your client assets to all your

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Speaker 1: record keep being process frustrateds.

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Speaker 2: Third party who is not managing the money, and that

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Speaker 2: creates a built in checks and.

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Speaker 1: Balance somewhat I mean, or it could be a built

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Speaker 1: in limitation keeping that advisor from doing high quality work, right,

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Speaker 1: which is I think what I sort of discover is

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Speaker 1: I kind of peel back the layers of the onion.

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Speaker 1: But so these custodians, one would think a very simple

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Speaker 1: thing they should be able to do is, let's say

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Speaker 1: you have three accounts with your financial planner. You've got

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Speaker 1: an IRA, maybe a roth IRA, a joint account with

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Speaker 1: your partner, and you want to know how am I

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Speaker 1: doing over the past twelve months.

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Speaker 3: You'd think you could.

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Speaker 1: Just log on to schwab And or Fidelity or Pershing

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Speaker 1: or whatever and just click a button or something and

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Speaker 1: it would tell you that. But the reality is that

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Speaker 1: you cannot get that information from your custodian. The custodian

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Speaker 1: will only be able to tell you what you have today.

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Speaker 1: It will give you access to your statements. The statements

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Speaker 1: are not bundled at the household level. And what the

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Speaker 1: custodian will tell you is that if you want that

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Speaker 1: type of information, you need to buy a third party

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Speaker 1: portfolio accounting software. We'll send them a daily file of

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Speaker 1: all of your positions and transactions. That third party will

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Speaker 1: reconcile all of that data and it will then allow.

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Speaker 3: You to run reports for your clients.

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Speaker 1: And you're gonna have to pay, you know, depending the

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Speaker 1: size of your firm, anywhere from tens of thousands to millions

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Speaker 1: of dollars for this third party software. And like this

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Speaker 1: just fundamentally makes no sense at all. The custodian has

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Speaker 1: all of the data, it should easily be able to

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Speaker 1: reconcile that and run reports for advisors, but they can't

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Speaker 1: and they won't, and you could go down this long

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Speaker 1: list of things that they should be able to do again,

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Speaker 1: just like the logic would tell you. For example, if

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Speaker 1: you want to bill a fee to your client, client

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Speaker 1: signs of fee agreement says I'm willing to pay my

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Speaker 1: advisor one percent hypothetically, and I'm willing to pay them

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Speaker 1: that every quarter, you know, by calculating the average daily

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Speaker 1: balance and build me in arrears something simple. Custodian will say,

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Speaker 1: that's cool. What you need to do is we'll send

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Speaker 1: you the data to a third party. They can reconcile

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Speaker 1: the data. You can then run a billing schema. It'll

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Speaker 1: create a CSV file. You can then upload that to

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Speaker 1: our system. Will then debit those fees from the accounts.

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Speaker 1: But this whole process can take days and by the

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Speaker 1: time you go to debit those fees. Sometimes a client

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Speaker 1: will have had a distribution in their account or a

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Speaker 1: trade or something, and the fees get busted. It creates

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Speaker 1: an account that it's overdrawn, and like just fundamentally, again,

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Speaker 1: there's hundreds of these things, and you go, this makes

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Speaker 1: no sense, Like why is this the way things operate?

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Speaker 1: This is largely the genesis to why would you build

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Speaker 1: the brand new custodian from scratch? And if you are

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Speaker 1: going to build it in a modern way, you would

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Speaker 1: probably make sure all of these things are just built

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Speaker 1: in automatically.

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Speaker 2: So that raise is really a fascinating observation. Altruists first

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Speaker 2: came to market twenty twenty, was it twenty?

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Speaker 1: We wrote the first lines of code in January of

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Speaker 1: twenty nineteen, and I think we went into beta in

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Speaker 1: early twenty twenty and then launched the product right now

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Speaker 1: the pandemic and twenty twenty tweve.

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Speaker 2: So I remember when the firm first launched, and I

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Speaker 2: remember hearing about it and the initial reaction was, I

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Speaker 2: don't want to say crickets, but kind of low key, yeah,

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Speaker 2: someone's going to disrupt these ten we got ten trillion dollars,

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Speaker 2: we know what we're doing custody wise, and what started

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Speaker 2: out is sort of a shrug. It didn't take very

442
00:21:29,400 --> 00:21:32,320
Speaker 2: long before there was a little bit of a freak out, like,

443
00:21:32,440 --> 00:21:35,680
Speaker 2: wait a second, what's going on here? They're actually winning clients?

444
00:21:36,520 --> 00:21:41,600
Speaker 2: How is this a thing from your preceipt within building

445
00:21:41,600 --> 00:21:45,719
Speaker 2: the company? How did you see the rest of the

446
00:21:45,760 --> 00:21:52,159
Speaker 2: custodian market react to Altruis launch and so just rolling

447
00:21:52,160 --> 00:21:55,919
Speaker 2: out one new capability after another.

448
00:21:57,000 --> 00:21:59,640
Speaker 1: So there's I wish I could remember where to properly

449
00:22:00,280 --> 00:22:04,119
Speaker 1: attribute this to. But there's a great saying that is

450
00:22:04,160 --> 00:22:06,639
Speaker 1: that first they ignore you, then they laugh at you,

451
00:22:06,680 --> 00:22:10,639
Speaker 1: then then you win. So it's not surprising that somebody

452
00:22:10,640 --> 00:22:12,680
Speaker 1: has a big bowld declaration they're going to change in

453
00:22:12,720 --> 00:22:18,440
Speaker 1: industry and make it better if you're you know, effectively

454
00:22:18,480 --> 00:22:21,760
Speaker 1: like a duopoly or oligopoly, as our industry was. You know,

455
00:22:21,760 --> 00:22:24,120
Speaker 1: almost all the assets were held by at the time

456
00:22:24,200 --> 00:22:27,680
Speaker 1: three custodians. Back then it was Schwab Fidelity and ted

457
00:22:27,760 --> 00:22:30,480
Speaker 1: Am Error Trade. Td amer Trade shortly after we launched,

458
00:22:30,560 --> 00:22:35,320
Speaker 1: was acquired by by Schwab, really making the the the powerdynamic,

459
00:22:35,400 --> 00:22:38,439
Speaker 1: like two companies that have eighty plus percent market share,

460
00:22:39,240 --> 00:22:44,200
Speaker 1: So you know, respectfully, I think, yeah, like there's going

461
00:22:44,200 --> 00:22:46,320
Speaker 1: to be a natural rent seeking, you know sort of

462
00:22:46,359 --> 00:22:49,320
Speaker 1: mentality from those people who are the dominant players. Why

463
00:22:49,400 --> 00:22:51,480
Speaker 1: would they ever want there to be any change, you know,

464
00:22:51,480 --> 00:22:54,479
Speaker 1: why would they want to change their cost structure, Why

465
00:22:54,520 --> 00:22:56,880
Speaker 1: would they want to modernize their systems? Like things were

466
00:22:56,920 --> 00:23:00,000
Speaker 1: great you know for those companies, so not so prose

467
00:23:00,240 --> 00:23:03,920
Speaker 1: that some folks may have been dismissive, but advisors never were.

468
00:23:03,960 --> 00:23:06,919
Speaker 1: Like when we first started putting prototypes out into the

469
00:23:06,920 --> 00:23:11,679
Speaker 1: public and you sharing our vision, we had thousands of

470
00:23:11,720 --> 00:23:15,679
Speaker 1: advisors that signed up for our waitlist, hundreds that decided

471
00:23:15,720 --> 00:23:18,160
Speaker 1: to become design partners, like very early kind of design

472
00:23:18,200 --> 00:23:22,159
Speaker 1: partners help us build you know, the platform, and you know,

473
00:23:22,160 --> 00:23:26,360
Speaker 1: we have this sort of very loyal base of users

474
00:23:26,359 --> 00:23:27,120
Speaker 1: that are very.

475
00:23:26,960 --> 00:23:29,000
Speaker 3: Loud about, you know, how happy they are with the product.

476
00:23:29,040 --> 00:23:32,000
Speaker 1: And we've we've done this by co creating it with

477
00:23:32,320 --> 00:23:36,200
Speaker 1: the advisors. So you know, it's not lost on me

478
00:23:36,440 --> 00:23:39,960
Speaker 1: that there are literally thousands of features that you have

479
00:23:40,000 --> 00:23:42,680
Speaker 1: to build to support you know, the wealth management industry.

480
00:23:43,600 --> 00:23:46,320
Speaker 1: We can't possibly know all thousand internally, so you need

481
00:23:46,359 --> 00:23:47,879
Speaker 1: to have some awesome partners that can help, you know,

482
00:23:47,880 --> 00:23:49,879
Speaker 1: try to light on, like what are the most important things?

483
00:23:49,920 --> 00:23:55,040
Speaker 1: So yeah, in the end, I think we have more

484
00:23:55,040 --> 00:23:57,440
Speaker 1: than caught their attention. I think now you know, there's

485
00:23:57,920 --> 00:24:00,760
Speaker 1: a fairly deep rooted fear actually from a lot of bigger.

486
00:24:01,119 --> 00:24:03,200
Speaker 2: So you have the three big incumbents, it's a little

487
00:24:03,240 --> 00:24:05,919
Speaker 2: bit of an oligopoly of Schwab which is now Schwap

488
00:24:05,960 --> 00:24:12,960
Speaker 2: TD combined Fidelity Pershing Bank in New York. Everybody kind

489
00:24:13,000 --> 00:24:14,600
Speaker 2: of looked at them and said, there's no way we're

490
00:24:14,640 --> 00:24:19,400
Speaker 2: going up against those behemoths. You're one of the first

491
00:24:19,720 --> 00:24:23,840
Speaker 2: companies to say we're going to take on the custodians

492
00:24:23,920 --> 00:24:26,760
Speaker 2: because their legacy platforms just can't do the things that

493
00:24:26,800 --> 00:24:32,280
Speaker 2: we can do at scale. How do you think about

494
00:24:32,400 --> 00:24:37,040
Speaker 2: the challenges of going up against what is Fidelity eighteen

495
00:24:37,160 --> 00:24:41,720
Speaker 2: trillion and Schwab is twelve trillion? Like these are monster

496
00:24:42,080 --> 00:24:45,200
Speaker 2: bank of New York. Pershing is the oldest bank, it's

497
00:24:45,240 --> 00:24:49,720
Speaker 2: Hamilton's Bank literally, Like these are not Oh, I think

498
00:24:49,800 --> 00:24:52,760
Speaker 2: I could disrupt Nokia with a better product. These are

499
00:24:52,960 --> 00:25:01,080
Speaker 2: just the most entrenched, well thought of partners for advisors.

500
00:25:02,280 --> 00:25:05,080
Speaker 2: What gave you the confidence to say we could beat

501
00:25:05,119 --> 00:25:06,000
Speaker 2: them at their own game?

502
00:25:06,800 --> 00:25:07,840
Speaker 3: Yeah, I think.

503
00:25:10,119 --> 00:25:13,520
Speaker 1: So. A big part of the confidence came from that

504
00:25:13,640 --> 00:25:14,840
Speaker 1: early advisor reaction.

505
00:25:15,000 --> 00:25:18,720
Speaker 3: But you know the truth is that these.

506
00:25:18,320 --> 00:25:21,199
Speaker 1: Companies don't have high nps like these aren't like loved

507
00:25:21,200 --> 00:25:23,479
Speaker 1: by the net promoter set promoter.

508
00:25:23,640 --> 00:25:26,280
Speaker 2: Okay, yeah, we do one of the surveys every year.

509
00:25:27,480 --> 00:25:31,320
Speaker 2: I know, that's become super popular everywhere the past twenty years.

510
00:25:31,320 --> 00:25:33,720
Speaker 1: You're gonna have to look very far and wide or

511
00:25:33,720 --> 00:25:37,639
Speaker 1: have too many conversations to hear wealth managers gripe about

512
00:25:37,640 --> 00:25:39,800
Speaker 1: their custodians. I mean again, I was running one of

513
00:25:39,840 --> 00:25:42,720
Speaker 1: the largest I think when I stepped down from former flows.

514
00:25:42,720 --> 00:25:44,800
Speaker 1: At the time, it was the fastest growing RA in

515
00:25:44,840 --> 00:25:46,240
Speaker 1: the history of the entire industry.

516
00:25:46,600 --> 00:25:47,560
Speaker 3: You know, we were growing.

517
00:25:47,280 --> 00:25:51,200
Speaker 1: At sixteen thousand percent. You know, had a three year

518
00:25:51,440 --> 00:25:54,520
Speaker 1: growth rate. So it was a true rocket ship, you

519
00:25:54,560 --> 00:25:55,879
Speaker 1: know in this in sense of like you know, the

520
00:25:56,000 --> 00:26:00,960
Speaker 1: RA space. And I felt tremendous pain. My biggest pain

521
00:26:01,040 --> 00:26:04,040
Speaker 1: point was my custodian onboarding new clients.

522
00:26:04,040 --> 00:26:04,240
Speaker 3: Skin.

523
00:26:04,320 --> 00:26:07,119
Speaker 1: They were making you download forms from a form library,

524
00:26:07,760 --> 00:26:11,240
Speaker 1: populate the forms by hand, send them out via DocuSign

525
00:26:11,359 --> 00:26:15,200
Speaker 1: at best, sometimes requiring wedding signatures or medallion stamp signature

526
00:26:15,200 --> 00:26:18,960
Speaker 1: guarantees like it was literally like going backwards in time

527
00:26:19,040 --> 00:26:22,159
Speaker 1: twenty years. Meanwhile, you had companies like Robinhood that you

528
00:26:22,160 --> 00:26:25,600
Speaker 1: could download an app on your phone at eighteen years old,

529
00:26:25,880 --> 00:26:27,879
Speaker 1: have your count open in thirty seconds, fund it with

530
00:26:27,960 --> 00:26:30,439
Speaker 1: one hundred dollars and buy fractional shares of Berkshire Hathaway

531
00:26:30,480 --> 00:26:33,959
Speaker 1: stock commission free. I mean, it was so obvious to

532
00:26:34,000 --> 00:26:36,760
Speaker 1: me that the old way that Custodian has been operating,

533
00:26:36,800 --> 00:26:40,440
Speaker 1: they were still charging commissions using paper. This was definitely

534
00:26:40,440 --> 00:26:42,439
Speaker 1: not the right way to do things. And if you

535
00:26:42,600 --> 00:26:45,760
Speaker 1: started looking at the impact to clients, So what is

536
00:26:45,800 --> 00:26:48,439
Speaker 1: the impact of forcing people to use whole shares, Like,

537
00:26:48,480 --> 00:26:50,640
Speaker 1: why would the big custodians force you to use whole

538
00:26:50,680 --> 00:26:53,920
Speaker 1: shares versus fractional shares? Fractional share trading had been around

539
00:26:54,000 --> 00:26:56,919
Speaker 1: for over twenty years. Well, just math, it's not that

540
00:26:57,040 --> 00:27:00,639
Speaker 1: difficult to correct. And this is even like or you know,

541
00:27:00,920 --> 00:27:02,160
Speaker 1: Gemetric right.

542
00:27:02,320 --> 00:27:05,280
Speaker 2: About exponential algos or anything like that.

543
00:27:05,200 --> 00:27:07,320
Speaker 1: Precisely, but you know, a lot of it is you

544
00:27:07,400 --> 00:27:09,280
Speaker 1: just start kind of going okay, like you know, maybe

545
00:27:09,280 --> 00:27:11,160
Speaker 1: this is a good tinfoil hat you know, theory here,

546
00:27:11,160 --> 00:27:14,359
Speaker 1: But I'd say, what would the benefit to them be

547
00:27:15,280 --> 00:27:18,560
Speaker 1: by not enabling fractional shares, maybe that means more cash

548
00:27:18,600 --> 00:27:21,199
Speaker 1: will be in client accounts. Maybe they make half of

549
00:27:21,240 --> 00:27:23,680
Speaker 1: their revenue from the cash spread, right, the net interest

550
00:27:23,720 --> 00:27:26,840
Speaker 1: income on cash that sits idle in client accounts. Maybe

551
00:27:26,880 --> 00:27:30,199
Speaker 1: the it also forces you, if you do want to

552
00:27:30,280 --> 00:27:32,840
Speaker 1: use fractional shares, the only vehicle you can use that

553
00:27:32,960 --> 00:27:35,119
Speaker 1: trades and fractional shares. You know, there's a you can

554
00:27:35,160 --> 00:27:38,280
Speaker 1: do notional dollar base buying our mutual funds, and these

555
00:27:38,359 --> 00:27:42,520
Speaker 1: mutual funds pay tremendous fees for distribution through these brokerage platforms.

556
00:27:44,119 --> 00:27:49,160
Speaker 1: What if they are not allowing fractional shares because they

557
00:27:49,400 --> 00:27:54,080
Speaker 1: really don't want to disintermediate packaged products in general, Right,

558
00:27:54,119 --> 00:27:57,159
Speaker 1: so make things like direct securities more accessible to more people.

559
00:27:57,440 --> 00:27:58,919
Speaker 1: I mean, I just went down this rabbit hole. But

560
00:27:58,960 --> 00:28:01,879
Speaker 1: the end result is it costs investors a ton of money.

561
00:28:02,520 --> 00:28:05,520
Speaker 1: You end up limiting the amount of tax benefits, you

562
00:28:05,600 --> 00:28:08,280
Speaker 1: end up increasing the average client account side. So if

563
00:28:08,320 --> 00:28:11,800
Speaker 1: you really want to have great efficacy kind of investment outcomes,

564
00:28:12,080 --> 00:28:14,520
Speaker 1: you'd have to have tens of millions of dollars. And

565
00:28:14,640 --> 00:28:17,760
Speaker 1: if you had fractional shares as just one example, all

566
00:28:17,760 --> 00:28:20,560
Speaker 1: of a sudden, you know, a ton of that entrenched

567
00:28:20,640 --> 00:28:24,000
Speaker 1: you know kind of history goes away completely. Everybody can

568
00:28:24,040 --> 00:28:27,080
Speaker 1: get access to the same type of investment strategies individually.

569
00:28:27,200 --> 00:28:31,320
Speaker 1: You know, managed accounts, you know lot level tax trading,

570
00:28:31,400 --> 00:28:33,840
Speaker 1: so you can get the best possible after tax outcomes.

571
00:28:34,160 --> 00:28:36,480
Speaker 1: You can compress cash down to the lowest amounts, you're

572
00:28:36,520 --> 00:28:40,600
Speaker 1: reducing cash drag. This increases outcomes. So you know, I

573
00:28:40,600 --> 00:28:43,320
Speaker 1: think in the end, if you if you put yourself

574
00:28:43,360 --> 00:28:46,560
Speaker 1: on the right side of the client and you have

575
00:28:47,200 --> 00:28:49,720
Speaker 1: time on your side, like you will absolutely win. I

576
00:28:49,760 --> 00:28:51,640
Speaker 1: think one of the best examples of that in our

577
00:28:51,680 --> 00:28:54,760
Speaker 1: industry is Vanguard. Like what they did, they were laughed

578
00:28:54,800 --> 00:28:58,560
Speaker 1: at and long time, you know, and they didn't even

579
00:28:58,640 --> 00:29:02,360
Speaker 1: really reach massive scale for twenty five thirty years into

580
00:29:02,360 --> 00:29:04,600
Speaker 1: their journey. But I think again, if you just put

581
00:29:04,640 --> 00:29:07,440
Speaker 1: yourself on the right side of the client the end, client, hey,

582
00:29:07,440 --> 00:29:10,640
Speaker 1: we're going to do things that objectively and obviously produce

583
00:29:10,760 --> 00:29:14,480
Speaker 1: better outcomes on an after fee, after tax, after cash

584
00:29:14,520 --> 00:29:17,920
Speaker 1: trag basis. We're going to provide delightful experiences with the

585
00:29:17,960 --> 00:29:22,480
Speaker 1: true partnership with our advisor clients. These things will work.

586
00:29:23,080 --> 00:29:25,440
Speaker 1: And again I think you have to have a certain

587
00:29:25,440 --> 00:29:28,280
Speaker 1: amount of craziness. One of our early investors you might

588
00:29:28,280 --> 00:29:32,840
Speaker 1: know Omani Carson, formerly known as Ron Carson. Samani is

589
00:29:32,880 --> 00:29:36,520
Speaker 1: his new new names retirement name, and I love him dearly.

590
00:29:36,760 --> 00:29:39,520
Speaker 1: But I remember I met him very early in building Altruists,

591
00:29:39,520 --> 00:29:42,560
Speaker 1: and we met for coffee in Venice, California, where the

592
00:29:42,560 --> 00:29:47,000
Speaker 1: company was started, and Omani, uh, you know, looks at

593
00:29:47,040 --> 00:29:49,760
Speaker 1: me after I explain the company and he's like, that's

594
00:29:49,840 --> 00:29:51,280
Speaker 1: the and you know, pardon my friends.

595
00:29:51,280 --> 00:29:52,440
Speaker 3: Everybody's like, you know.

596
00:29:52,440 --> 00:29:56,040
Speaker 1: This is the craziest efen idea I've ever heard. I'm in, like,

597
00:29:56,080 --> 00:29:57,360
Speaker 1: how do I give you part of it? I think

598
00:29:57,360 --> 00:29:59,360
Speaker 1: there's a certain number of people who just like, we've

599
00:29:59,400 --> 00:30:02,360
Speaker 1: been doing this a lot long time. You eventually become

600
00:30:02,440 --> 00:30:05,080
Speaker 1: numb to the status quo. The status quo was totally

601
00:30:05,480 --> 00:30:06,720
Speaker 1: it was not good for anybody.

602
00:30:07,600 --> 00:30:10,600
Speaker 2: And so except for the custodians, yeah, there was one.

603
00:30:10,440 --> 00:30:13,120
Speaker 1: Party that really was happy with the status quo, right,

604
00:30:13,760 --> 00:30:15,120
Speaker 1: and so I think as soon as we shed a

605
00:30:15,120 --> 00:30:17,160
Speaker 1: little bit of light, now there's a ton of challenges

606
00:30:17,200 --> 00:30:17,880
Speaker 1: you have to overcome.

607
00:30:17,920 --> 00:30:19,520
Speaker 3: But again, there's no doubt in my mind this is

608
00:30:19,520 --> 00:30:19,880
Speaker 3: going to work.

609
00:30:19,880 --> 00:30:22,320
Speaker 2: When I started, you mentioned Robin hon and zero commission,

610
00:30:22,360 --> 00:30:25,480
Speaker 2: which I want to say was twenty fourteen or twenty fifteen.

611
00:30:26,000 --> 00:30:29,480
Speaker 2: Then Schwab rolled out, you know, commission free trading in

612
00:30:29,560 --> 00:30:34,800
Speaker 2: twenty nineteen. What did that shift in cost structure due

613
00:30:34,840 --> 00:30:41,280
Speaker 2: to the relationship between investors and custodians, advisors and custodians.

614
00:30:41,680 --> 00:30:46,120
Speaker 2: Did that change the way everybody looked at this or

615
00:30:46,960 --> 00:30:49,080
Speaker 2: was this just okay, I guess this is an even

616
00:30:49,160 --> 00:30:50,600
Speaker 2: lower margin business.

617
00:30:51,080 --> 00:30:53,120
Speaker 3: Yeah, so I think that's a I think it's a

618
00:30:53,200 --> 00:30:54,120
Speaker 3: huge misconception.

619
00:30:54,240 --> 00:30:58,040
Speaker 1: Yeah. So what's interesting is that I wrote this piece

620
00:30:58,200 --> 00:31:01,160
Speaker 1: in twenty eighteen, and and you know, we had one

621
00:31:01,160 --> 00:31:04,360
Speaker 1: of our designers kind of draw infographic kind of behind it,

622
00:31:04,440 --> 00:31:06,280
Speaker 1: and it was the classic sort of tip of the

623
00:31:06,320 --> 00:31:09,120
Speaker 1: iceberg where we showed the you know, what you see

624
00:31:09,160 --> 00:31:11,680
Speaker 1: above the water line and then what exists below the

625
00:31:11,720 --> 00:31:12,440
Speaker 1: water line.

626
00:31:12,560 --> 00:31:14,960
Speaker 2: I just did one of those two weeks ago.

627
00:31:14,760 --> 00:31:18,080
Speaker 3: And great metaphor. You know, it really is so.

628
00:31:18,240 --> 00:31:21,160
Speaker 2: Perfect to like, hey, here's what you're focusing on, but

629
00:31:21,200 --> 00:31:23,800
Speaker 2: you got to look at the things that matter even more.

630
00:31:23,800 --> 00:31:28,880
Speaker 1: So, we did this for custodians, right, and the thing

631
00:31:28,960 --> 00:31:31,960
Speaker 1: people saw was the commission. So there was this belief

632
00:31:32,000 --> 00:31:35,560
Speaker 1: and advisors even didn't know, you know the facts. They

633
00:31:35,560 --> 00:31:37,880
Speaker 1: would go to clients and say, hey, when you work

634
00:31:37,920 --> 00:31:41,080
Speaker 1: with us in our independent, third party custodian, here's how

635
00:31:41,080 --> 00:31:43,320
Speaker 1: they get paid. They get paid seven dollars if you

636
00:31:43,360 --> 00:31:45,360
Speaker 1: do a trade. It's a pretty cheap water price. You know,

637
00:31:45,440 --> 00:31:49,200
Speaker 1: it's for waterflow, correct. I mean the big money is

638
00:31:49,280 --> 00:31:50,440
Speaker 1: the commission is just to.

639
00:31:50,360 --> 00:31:51,680
Speaker 2: Break even one hundred percent.

640
00:31:51,800 --> 00:31:54,120
Speaker 1: Right If if you look at the big public companies

641
00:31:54,120 --> 00:31:56,280
Speaker 1: that were in the space, they were making maybe five

642
00:31:56,360 --> 00:32:00,080
Speaker 1: to ten percent of the revenue is from from transactions,

643
00:32:00,560 --> 00:32:03,520
Speaker 1: and commissions were maybe half of the transaction revenue.

644
00:32:03,560 --> 00:32:05,560
Speaker 2: Right. The trends, well, we get to the float, which

645
00:32:05,600 --> 00:32:06,360
Speaker 2: everything I love.

646
00:32:06,760 --> 00:32:09,880
Speaker 1: So there's there's a ton of like un things that

647
00:32:09,880 --> 00:32:11,120
Speaker 1: it's a historically.

648
00:32:10,720 --> 00:32:13,040
Speaker 3: Been ignored or unknown.

649
00:32:13,640 --> 00:32:17,080
Speaker 1: The biggest revelation when everybody went commission free was people

650
00:32:17,080 --> 00:32:19,520
Speaker 1: start asking question, well, how the heck do you make money? Like,

651
00:32:19,560 --> 00:32:22,640
Speaker 1: how does this business actually work if you're giving away

652
00:32:22,680 --> 00:32:26,480
Speaker 1: everything for free. Only then did people start to go, oh,

653
00:32:26,480 --> 00:32:28,680
Speaker 1: wait a minute, like that wasn't even how you made money.

654
00:32:28,800 --> 00:32:32,479
Speaker 1: That was literally like just a complete smoke in mirror's

655
00:32:32,520 --> 00:32:34,720
Speaker 1: way to fool me into believing you only made seven

656
00:32:34,760 --> 00:32:37,400
Speaker 1: dollars a trade, when the reality was all of the

657
00:32:37,440 --> 00:32:40,240
Speaker 1: real money was made by paying me zero point zero

658
00:32:40,280 --> 00:32:43,320
Speaker 1: one percent interest on my idle cash, making me trade

659
00:32:43,320 --> 00:32:45,680
Speaker 1: whole shares, which makes me have more cash my account

660
00:32:45,680 --> 00:32:48,480
Speaker 1: than I really should, making me buy these different funds

661
00:32:48,520 --> 00:32:50,840
Speaker 1: that all have bunch of conflicts of interest through all

662
00:32:50,840 --> 00:32:54,280
Speaker 1: of their various you know forms of twelve B one

663
00:32:54,440 --> 00:32:58,280
Speaker 1: and fifteen C three revenue sharing agreements. I mean, like

664
00:32:58,480 --> 00:33:01,200
Speaker 1: just like very esoteric stuff, but very few people ever

665
00:33:01,240 --> 00:33:04,719
Speaker 1: talked about and to your point on float and liquidity

666
00:33:04,760 --> 00:33:07,800
Speaker 1: through pefoff payment for order flow. I mean, it just

667
00:33:07,920 --> 00:33:11,240
Speaker 1: it really opened everyone's eyes into the fact that the

668
00:33:11,280 --> 00:33:15,000
Speaker 1: clearing and custody business turns out it wasn't a high scale,

669
00:33:15,040 --> 00:33:18,200
Speaker 1: low margin business at all. In fact, it was a

670
00:33:18,320 --> 00:33:22,880
Speaker 1: very high you know margin business, and that was just

671
00:33:22,960 --> 00:33:26,320
Speaker 1: one kind of irrelevant piece that you know, confused people

672
00:33:26,360 --> 00:33:29,000
Speaker 1: into believing that was the full full price admission.

673
00:33:29,280 --> 00:33:32,800
Speaker 2: I recall a couple of years ago, it was after

674
00:33:33,000 --> 00:33:38,480
Speaker 2: Schwab went free commission zero commission free trading. I don't

675
00:33:38,520 --> 00:33:43,080
Speaker 2: remember if it was TD or Schwab, that one of

676
00:33:43,080 --> 00:33:48,040
Speaker 2: the public companies in a poorly earnings fifty seven percent

677
00:33:48,320 --> 00:33:54,400
Speaker 2: of their gross came from the float came from what

678
00:33:54,440 --> 00:33:57,280
Speaker 2: they got paid. The difference between what they were paying

679
00:33:58,800 --> 00:34:03,640
Speaker 2: investors go whatever and the actual rate that they could

680
00:34:03,640 --> 00:34:07,720
Speaker 2: generate internally. How does how does altruist deal with that?

681
00:34:08,680 --> 00:34:11,880
Speaker 1: So I think the key is doing whatever you're doing transparently,

682
00:34:12,200 --> 00:34:14,920
Speaker 1: uh and whenever you can, giving as much of the

683
00:34:15,320 --> 00:34:16,600
Speaker 1: economics to the client.

684
00:34:16,760 --> 00:34:18,640
Speaker 3: So I'm a big.

685
00:34:18,320 --> 00:34:21,960
Speaker 1: Believer in uh, you know the flywheel kind of made

686
00:34:22,000 --> 00:34:24,760
Speaker 1: popular by Good to Great, one of my favorite books.

687
00:34:25,760 --> 00:34:28,680
Speaker 1: And you know, our flywheel is that the first spoke

688
00:34:28,920 --> 00:34:33,320
Speaker 1: is uh, invest in innovation that drives better outcomes for advisors.

689
00:34:33,440 --> 00:34:36,200
Speaker 1: The second is invest invation that drives better outcomes for

690
00:34:36,360 --> 00:34:39,000
Speaker 1: end consumers, the end client. If we do those two things,

691
00:34:39,000 --> 00:34:42,080
Speaker 1: it will drive the highest satisfaction amongst our user base.

692
00:34:42,520 --> 00:34:45,319
Speaker 1: This will increase amount of acets on our platform, which

693
00:34:45,320 --> 00:34:47,640
Speaker 1: gives us a scale to invest more in innovation, right, so,

694
00:34:47,719 --> 00:34:50,320
Speaker 1: which drives better outcomes for advisors, better outcomes for clients.

695
00:34:51,680 --> 00:34:55,359
Speaker 1: You if you're going to do that, there's uh there.

696
00:34:55,400 --> 00:34:58,319
Speaker 1: You have to earn revenue like of course, but in

697
00:34:58,360 --> 00:35:02,000
Speaker 1: our case, we built a very integrated wealth platforms. So yes,

698
00:35:02,040 --> 00:35:04,480
Speaker 1: we have custody and clearing revenue. We make money on

699
00:35:04,640 --> 00:35:08,040
Speaker 1: net interest income the float, if you will. We make

700
00:35:08,120 --> 00:35:11,279
Speaker 1: some revenue on payment for order flow, but we built

701
00:35:11,280 --> 00:35:14,480
Speaker 1: what's called the wheel order routing system. It's one hundred

702
00:35:14,480 --> 00:35:17,440
Speaker 1: percent optimized to drive the best possible execution for every

703
00:35:17,480 --> 00:35:18,560
Speaker 1: single client transaction.

704
00:35:19,080 --> 00:35:20,480
Speaker 3: If we happen to get a.

705
00:35:20,320 --> 00:35:24,400
Speaker 1: Better execution through US at Adel or Jane Street, whomever,

706
00:35:25,480 --> 00:35:28,000
Speaker 1: we might make a tiny amount, like literally measured in

707
00:35:28,080 --> 00:35:30,959
Speaker 1: fractions of bases, points and mills. It's the lowest amount

708
00:35:30,960 --> 00:35:33,120
Speaker 1: of revenue we earn, but like there is something there.

709
00:35:35,280 --> 00:35:37,680
Speaker 1: We do earn money again on float, but we offer

710
00:35:37,760 --> 00:35:39,800
Speaker 1: fractional shares, so we have the lowest cash holdings of

711
00:35:39,800 --> 00:35:43,440
Speaker 1: the entire industry. People can hold virtually nothing. We also

712
00:35:43,520 --> 00:35:46,200
Speaker 1: have some earnings from things like mutual funds, but we

713
00:35:46,239 --> 00:35:47,960
Speaker 1: have the lowest amount of mutual funds in the entire

714
00:35:47,960 --> 00:35:51,600
Speaker 1: industry because we offer fractional shares, so people can buy ETFs,

715
00:35:51,640 --> 00:35:54,839
Speaker 1: they can buy individual securities. So we have very very

716
00:35:54,880 --> 00:35:57,799
Speaker 1: little in way of rev share through fun companies, but

717
00:35:58,239 --> 00:36:01,000
Speaker 1: there's definitely money that is made that clearing layer. Where

718
00:36:01,000 --> 00:36:03,719
Speaker 1: we've really innovated is that we also do all of

719
00:36:03,719 --> 00:36:06,200
Speaker 1: the software layer, you know, for advisors. We offer an

720
00:36:06,200 --> 00:36:09,760
Speaker 1: asset management layer for advisors, so each kind of component

721
00:36:09,760 --> 00:36:12,400
Speaker 1: of the ULTRAS business is generally going to be sixty

722
00:36:12,440 --> 00:36:15,640
Speaker 1: to eighty percent cheaper than if these things were bought individually.

723
00:36:16,040 --> 00:36:17,800
Speaker 1: So you may recall, you know, when I shared the

724
00:36:17,800 --> 00:36:19,319
Speaker 1: story about how you go to a custodian and say,

725
00:36:19,360 --> 00:36:20,479
Speaker 1: why can't you do my fee billing?

726
00:36:20,560 --> 00:36:23,080
Speaker 3: That makes no sense if to buy a third party software.

727
00:36:23,800 --> 00:36:26,360
Speaker 1: We built all of these things natively, and most of

728
00:36:26,400 --> 00:36:28,880
Speaker 1: them are either free or very low cost because we

729
00:36:28,920 --> 00:36:31,040
Speaker 1: have this sort of benefit, if you will, of stacking

730
00:36:31,040 --> 00:36:34,480
Speaker 1: the various forms of services that advisors and their clients.

731
00:36:34,200 --> 00:36:36,520
Speaker 2: Need on a modern platform.

732
00:36:36,680 --> 00:36:39,319
Speaker 1: Correct, and we do it with i'd say fair the

733
00:36:39,320 --> 00:36:43,640
Speaker 1: insane amounts of automation, so you know, the the kind

734
00:36:43,680 --> 00:36:47,319
Speaker 1: of knock I made on using PDFs, like, there's no

735
00:36:47,400 --> 00:36:49,600
Speaker 1: PDFs necessary at ULTRAS, so.

736
00:36:49,520 --> 00:36:51,880
Speaker 2: You're not you're not exporting csvs and then having to

737
00:36:51,920 --> 00:36:55,759
Speaker 2: upload it to cloud to get a literally ridiculous or.

738
00:36:56,000 --> 00:36:57,279
Speaker 3: A year a hundred percent.

739
00:36:57,400 --> 00:37:01,000
Speaker 1: Yeah, you can open an entire families accounts, do all

740
00:37:01,000 --> 00:37:03,080
Speaker 1: of their account transfers, link all their bank accounts, and

741
00:37:03,120 --> 00:37:05,520
Speaker 1: do the whole thing in under two minutes. The accounts

742
00:37:05,560 --> 00:37:09,200
Speaker 1: are being real time validated, the transfers are being real

743
00:37:09,239 --> 00:37:12,439
Speaker 1: time validated. Ninety eight plus percent of these workflows there's

744
00:37:12,480 --> 00:37:15,160
Speaker 1: no human being ever involved in them. So every time

745
00:37:15,160 --> 00:37:17,799
Speaker 1: we build a new innovation or automation, we're able to

746
00:37:17,840 --> 00:37:20,319
Speaker 1: operate with a much higher amount of operating leverage than

747
00:37:20,320 --> 00:37:22,880
Speaker 1: anyone else in the industry. This allows us to invest

748
00:37:22,920 --> 00:37:26,879
Speaker 1: back into more innovation, which allows us to offer more

749
00:37:26,920 --> 00:37:30,240
Speaker 1: services at lower price points. So look, we earn revenue

750
00:37:30,280 --> 00:37:33,200
Speaker 1: just like everyone else does. I think one interesting tidbit

751
00:37:33,239 --> 00:37:34,919
Speaker 1: we don't talk a lot about, but is the fact

752
00:37:34,920 --> 00:37:38,400
Speaker 1: that on the aggregate, ultrast earns more revenue than I

753
00:37:38,480 --> 00:37:41,920
Speaker 1: believe any other ri custodian on a per dollar basis

754
00:37:42,000 --> 00:37:44,680
Speaker 1: means per dollar in our platform, we earn more revenue

755
00:37:44,719 --> 00:37:47,879
Speaker 1: than the big players, and it's not because we charge more.

756
00:37:47,920 --> 00:37:49,680
Speaker 1: In fact, we have the lowest fee schedule in the

757
00:37:49,840 --> 00:37:53,319
Speaker 1: entire industry. But it's because we do more for those

758
00:37:53,360 --> 00:37:57,000
Speaker 1: advisors than just provide custody and clearing. We're offering software

759
00:37:57,040 --> 00:38:02,000
Speaker 1: and services, AI products, asset manage services, automations around things

760
00:38:02,040 --> 00:38:05,439
Speaker 1: like tax management and tax loss harvesting. So because people

761
00:38:05,560 --> 00:38:08,360
Speaker 1: use more surface area, we end up having in more

762
00:38:08,400 --> 00:38:11,480
Speaker 1: and more diverse revenue as a business, and we have

763
00:38:11,680 --> 00:38:14,480
Speaker 1: much better operating leverage because we have so much automation

764
00:38:15,040 --> 00:38:16,720
Speaker 1: that we don't have to hire a lot of people

765
00:38:16,800 --> 00:38:19,960
Speaker 1: to actually offer this at scale. So these are a

766
00:38:20,000 --> 00:38:22,200
Speaker 1: lot of the benefits to modern Right, you do it

767
00:38:22,560 --> 00:38:24,560
Speaker 1: this way in this day and age, you're not going

768
00:38:24,560 --> 00:38:25,640
Speaker 1: to build the same way you would.

769
00:38:25,480 --> 00:38:26,480
Speaker 3: If you did it fifty years ago.

770
00:38:26,520 --> 00:38:30,520
Speaker 2: You're earning more revenue as the custodian per dollar on

771
00:38:30,560 --> 00:38:34,359
Speaker 2: the platform, yet at the same time the advisor is

772
00:38:34,440 --> 00:38:38,080
Speaker 2: paying less costs per dollar on the platform. Of course,

773
00:38:38,160 --> 00:38:42,240
Speaker 2: they're not working with five or ten third party add ons.

774
00:38:42,360 --> 00:38:45,000
Speaker 2: It's just one turnkey solution, correct.

775
00:38:45,080 --> 00:38:50,439
Speaker 1: Yeah, it's material and consumers. You know, consumers if using

776
00:38:50,440 --> 00:38:53,080
Speaker 1: the platform correctly, are getting better results as well, so

777
00:38:53,239 --> 00:38:55,799
Speaker 1: because they don't have things like cash drag, because they

778
00:38:55,840 --> 00:38:59,239
Speaker 1: can be more fully invested, because they can reduce the

779
00:38:59,320 --> 00:39:02,360
Speaker 1: need for third party investment products. They can hold securities

780
00:39:02,360 --> 00:39:06,719
Speaker 1: directly on the platform, reducing expense ratios. Because we have

781
00:39:06,800 --> 00:39:09,960
Speaker 1: automation around tax management, they can drive down the tax

782
00:39:10,000 --> 00:39:13,400
Speaker 1: consequences of investing materially. So again it's one of these

783
00:39:13,440 --> 00:39:15,440
Speaker 1: things where it almost sounds too good to be true, right,

784
00:39:15,480 --> 00:39:18,520
Speaker 1: But like, yes, advisors should be able to run more efficient,

785
00:39:18,600 --> 00:39:23,080
Speaker 1: better businesses. We can have a great business and consumers

786
00:39:23,120 --> 00:39:26,160
Speaker 1: can win too. Like that is very much a real possibility.

787
00:39:26,200 --> 00:39:29,000
Speaker 1: There doesn't have to be a loser. It's a winning system.

788
00:39:29,360 --> 00:39:34,280
Speaker 2: Let's talk about AI and automation and your platform, Hazel.

789
00:39:34,600 --> 00:39:37,920
Speaker 2: I know my team loves it. Everybody is super super

790
00:39:38,440 --> 00:39:43,279
Speaker 2: positive about it. Is Hazel a standalone AI bed? Is

791
00:39:43,280 --> 00:39:46,320
Speaker 2: it part of the long term vision? Is it planning

792
00:39:46,360 --> 00:39:50,759
Speaker 2: and custodi, custody, ship and other services as one seamless

793
00:39:50,800 --> 00:39:55,520
Speaker 2: workflow on a single platform. Tell us all about Hazel.

794
00:39:56,040 --> 00:39:59,719
Speaker 1: Yeah, so the basic thought, so first to answer your question,

795
00:40:00,320 --> 00:40:04,640
Speaker 1: it's very tightly integrated with Altrus, but it's available totally separate,

796
00:40:04,719 --> 00:40:07,080
Speaker 1: so really any wealth manager can use it. We have

797
00:40:07,120 --> 00:40:11,320
Speaker 1: people using it all over the world in many different industries.

798
00:40:11,360 --> 00:40:14,440
Speaker 1: So we have large CPA firms that are using Hazel,

799
00:40:14,520 --> 00:40:19,120
Speaker 1: and obviously large financial advisory firms. So part of the

800
00:40:19,160 --> 00:40:23,200
Speaker 1: thinking here is that the altruist business will eventually be

801
00:40:23,719 --> 00:40:27,440
Speaker 1: a very large scaled business with trillions of dollars in assets,

802
00:40:27,480 --> 00:40:30,279
Speaker 1: but the total size of our industry is going to

803
00:40:30,320 --> 00:40:33,880
Speaker 1: be tenfold that, right, so we don't want to limit

804
00:40:34,160 --> 00:40:37,319
Speaker 1: the power of AI to just the whatever percentage of

805
00:40:37,360 --> 00:40:40,120
Speaker 1: market share that Altruis has. We want everybody to benefit

806
00:40:40,120 --> 00:40:44,040
Speaker 1: from these innovations. And so the things that are really

807
00:40:44,080 --> 00:40:46,680
Speaker 1: cool with Hazel is that again it can be used

808
00:40:46,680 --> 00:40:49,720
Speaker 1: by any financial advisor or really a lot of different

809
00:40:49,719 --> 00:40:51,080
Speaker 1: segments of financial services.

810
00:40:51,960 --> 00:40:53,040
Speaker 3: It's been a ton of fun to.

811
00:40:53,000 --> 00:40:55,920
Speaker 1: Build, and a lot of what we're doing is just

812
00:40:56,000 --> 00:41:00,960
Speaker 1: taking the hardest, most like laborious, non glamor but you know,

813
00:41:01,360 --> 00:41:05,640
Speaker 1: important work that used to really be hard to get

814
00:41:05,640 --> 00:41:08,640
Speaker 1: if you didn't have tens of millions of dollars, and

815
00:41:08,640 --> 00:41:10,600
Speaker 1: we're just bringing the unit costs down to like three

816
00:41:10,600 --> 00:41:13,880
Speaker 1: to five dollars, so you can do like incredibly complex

817
00:41:13,960 --> 00:41:16,560
Speaker 1: tax planning and do it for again effectively like a

818
00:41:16,600 --> 00:41:17,960
Speaker 1: dollar to five dollars.

819
00:41:19,160 --> 00:41:21,359
Speaker 3: This makes it accessible to everybody and AI.

820
00:41:21,560 --> 00:41:23,719
Speaker 1: You know, people have their fears about you know, what

821
00:41:23,800 --> 00:41:26,200
Speaker 1: could go wrong, but we like to think this is

822
00:41:26,239 --> 00:41:27,399
Speaker 1: a lot of the wook can go right.

823
00:41:27,760 --> 00:41:31,960
Speaker 2: Coming up, we continue our conversation with Jason Wenk, founder

824
00:41:32,000 --> 00:41:35,920
Speaker 2: and CEO of Altruist, discussing how we built the firm

825
00:41:36,040 --> 00:41:40,000
Speaker 2: to compete with the big guys. I'm Barry Ridults. You're

826
00:41:40,040 --> 00:41:44,560
Speaker 2: listening to Masters in Business on Bloomberg Radio. I'm Barry Ridults.

827
00:41:44,680 --> 00:41:48,080
Speaker 2: You're listening to Masters in Business on Bloomberg Radio. My

828
00:41:48,200 --> 00:41:52,239
Speaker 2: guest this week is Jason Wenk, founder and CEO of

829
00:41:52,320 --> 00:41:57,759
Speaker 2: the New Custodian Altruist. I've seen some crazy numbers as

830
00:41:57,760 --> 00:42:01,960
Speaker 2: to what advisors manage. I don't want to talk about

831
00:42:02,040 --> 00:42:04,360
Speaker 2: mutual funds. I want to talk about straight up rias.

832
00:42:04,640 --> 00:42:09,720
Speaker 2: Who are your prime clients as a custodian, Ten twelve,

833
00:42:10,160 --> 00:42:15,480
Speaker 2: twenty trillion dollars just crazy numbers out there. What is

834
00:42:15,520 --> 00:42:19,560
Speaker 2: the total addressable market there? And how much do you know?

835
00:42:19,719 --> 00:42:23,520
Speaker 2: The does the oligopoly the big three have of that

836
00:42:23,640 --> 00:42:24,400
Speaker 2: total market?

837
00:42:25,600 --> 00:42:30,080
Speaker 1: So the approximate number is ten trillion today, it's about

838
00:42:30,080 --> 00:42:33,440
Speaker 1: thirty five thousand firms. These firms are roughly half our

839
00:42:33,719 --> 00:42:36,160
Speaker 1: SEC registered investment advisors is meaning.

840
00:42:36,000 --> 00:42:37,960
Speaker 2: More than one hundred million or more than a hundred million.

841
00:42:38,080 --> 00:42:40,200
Speaker 1: And then the other half are state registered firms that

842
00:42:40,280 --> 00:42:43,000
Speaker 1: are a sub one hundred million. Some of those are

843
00:42:43,160 --> 00:42:44,920
Speaker 1: just new entrants, like there are just firms that are

844
00:42:45,000 --> 00:42:48,279
Speaker 1: first registration. They they'll probably mature into the SEC within

845
00:42:48,320 --> 00:42:50,400
Speaker 1: a year or two, and others just you know, they

846
00:42:50,440 --> 00:42:54,040
Speaker 1: operate small, independent, you know businesses serving a loyal but

847
00:42:54,120 --> 00:42:58,960
Speaker 1: small group of clients. The uh yeah, the the top

848
00:42:59,239 --> 00:43:02,399
Speaker 1: of the market, you know, I think it's Persian gets

849
00:43:02,440 --> 00:43:06,040
Speaker 1: oftentimes lumped into the big three. They don't have much

850
00:43:06,120 --> 00:43:09,640
Speaker 1: market share of the RIA segment. It gets it's a

851
00:43:09,800 --> 00:43:11,719
Speaker 1: bit muddy, but the reason is they support all of

852
00:43:11,760 --> 00:43:14,360
Speaker 1: the big broker dealers that usually they have a companion

853
00:43:14,800 --> 00:43:17,120
Speaker 1: corporate RIA and so that's kind of how they get

854
00:43:17,120 --> 00:43:20,719
Speaker 1: in here. But true standalone rias, I mean eighty five

855
00:43:20,760 --> 00:43:23,600
Speaker 1: percent of the assets are with just two companies, Schwab

856
00:43:23,680 --> 00:43:26,399
Speaker 1: being the largest they're north of fifty percent market share,

857
00:43:26,400 --> 00:43:29,799
Speaker 1: and then Fidelity being the second largest. So it's your

858
00:43:29,920 --> 00:43:33,200
Speaker 1: very classic you know disruption. Like if you were to

859
00:43:33,719 --> 00:43:35,720
Speaker 1: just kind of say, hey, what would be the recipe

860
00:43:35,760 --> 00:43:39,359
Speaker 1: for disruption, you'd say, big, fast growing market dominated by

861
00:43:39,640 --> 00:43:43,440
Speaker 1: old companies using old infrastructure with generally low NPS like

862
00:43:43,520 --> 00:43:44,840
Speaker 1: low customer satisfaction.

863
00:43:45,880 --> 00:43:47,880
Speaker 3: That is exactly the market that we are in today.

864
00:43:48,160 --> 00:43:52,200
Speaker 2: Huh. Really really fascinating. So given the fact that you

865
00:43:52,320 --> 00:43:56,840
Speaker 2: got to build a clean sheet custodian you're not built

866
00:43:56,920 --> 00:43:59,759
Speaker 2: on this legacy hardware that can't do all these things

867
00:44:00,040 --> 00:44:04,960
Speaker 2: asked and easy, what's the biggest take up from advisors?

868
00:44:05,000 --> 00:44:08,759
Speaker 2: Where are they still inefficient? Is it just paperwork and

869
00:44:08,800 --> 00:44:12,440
Speaker 2: portfolio management? Is it tax is it compliance? Is it

870
00:44:12,560 --> 00:44:16,680
Speaker 2: client service and disbursements? Like where are the biggest advantages

871
00:44:16,920 --> 00:44:19,279
Speaker 2: or is it just the whole thing?

872
00:44:19,680 --> 00:44:20,200
Speaker 3: Yeah?

873
00:44:20,280 --> 00:44:22,560
Speaker 1: I mean, so we break this down into like two elements.

874
00:44:22,560 --> 00:44:26,080
Speaker 1: So you know, with ultrast we have our core wealth business.

875
00:44:26,120 --> 00:44:28,640
Speaker 1: This is like the custody and lated software to custody

876
00:44:29,360 --> 00:44:32,360
Speaker 1: we started there. It's a super big, hairy build, like

877
00:44:32,440 --> 00:44:34,560
Speaker 1: it just takes a long time, you know, just hundreds

878
00:44:34,600 --> 00:44:38,080
Speaker 1: of thousands of engineering hours. You know, there's no shortcuts,

879
00:44:38,160 --> 00:44:39,960
Speaker 1: very expensive, time consuming.

880
00:44:40,440 --> 00:44:42,240
Speaker 2: But that was that a B. Hag reference?

881
00:44:42,239 --> 00:44:43,439
Speaker 3: Oh absolutely, Yeah.

882
00:44:43,600 --> 00:44:45,759
Speaker 1: I mean like this is like as big and hairy

883
00:44:45,800 --> 00:44:48,760
Speaker 1: as they get, right, and there's just again there's no shortcuts.

884
00:44:48,800 --> 00:44:52,800
Speaker 1: But that infrastructure is so critical because what it allows

885
00:44:52,840 --> 00:44:54,520
Speaker 1: you to do, if it's done the right way, is

886
00:44:54,520 --> 00:44:57,000
Speaker 1: it allows you to tackle all the other work. Right,

887
00:44:57,080 --> 00:45:00,839
Speaker 1: So I'll start with this work right, the part you

888
00:45:00,880 --> 00:45:03,440
Speaker 1: can open account super fast, you know, do all of

889
00:45:03,480 --> 00:45:06,800
Speaker 1: the automation around onboarding clients. This is great, but you

890
00:45:06,920 --> 00:45:09,880
Speaker 1: only onboard a client once, you know, ideally and so

891
00:45:10,000 --> 00:45:13,080
Speaker 1: if you serve a client for thirty years, the custody

892
00:45:13,120 --> 00:45:15,440
Speaker 1: part is really a pretty small part of the picture.

893
00:45:16,200 --> 00:45:18,719
Speaker 1: It was a huge, you know, kind of friction point

894
00:45:18,719 --> 00:45:21,360
Speaker 1: because it was oftentimes one of the first experiences that

895
00:45:21,400 --> 00:45:23,160
Speaker 1: a client would have with their advisor, and if it

896
00:45:23,200 --> 00:45:27,840
Speaker 1: was a bad experience, like yeah, it's usually not fast

897
00:45:28,000 --> 00:45:30,480
Speaker 1: like it's it's you don't have a lot of clarity

898
00:45:30,520 --> 00:45:32,960
Speaker 1: like hey, when is my transfer going to be done?

899
00:45:33,040 --> 00:45:34,960
Speaker 1: Like why did this thing get rejected? Why am I

900
00:45:35,000 --> 00:45:37,799
Speaker 1: redoing this paperwork? So we solved a lot of the

901
00:45:37,840 --> 00:45:42,719
Speaker 1: infrastructure now with our AI products Hazel or tackling like

902
00:45:42,760 --> 00:45:45,600
Speaker 1: the rest of the thirty years, right, So maybe there's

903
00:45:45,680 --> 00:45:49,120
Speaker 1: again a five percent or less of a client relationship

904
00:45:49,160 --> 00:45:52,120
Speaker 1: that's really connected the custodian. You know, you're onboarding the client,

905
00:45:52,160 --> 00:45:55,200
Speaker 1: you're setting up rules around trading and rebalancing and tax management.

906
00:45:55,960 --> 00:45:58,200
Speaker 1: But a lot of the work really is all of

907
00:45:58,239 --> 00:46:01,560
Speaker 1: the the one to one, hard to scale work. So

908
00:46:01,560 --> 00:46:04,400
Speaker 1: you meet a new client, they're a prospect at this point,

909
00:46:04,800 --> 00:46:07,400
Speaker 1: you need to you know, uncover a bunch of data

910
00:46:07,440 --> 00:46:10,120
Speaker 1: that they have. You need to then analyze that, build

911
00:46:10,160 --> 00:46:13,120
Speaker 1: a financial plan, create a proposal.

912
00:46:13,800 --> 00:46:14,719
Speaker 3: Once they agree to it.

913
00:46:14,800 --> 00:46:16,680
Speaker 1: Then you do that onboarding, and now you have to

914
00:46:16,719 --> 00:46:18,960
Speaker 1: serve that client for decades, and there's going to be

915
00:46:19,000 --> 00:46:21,799
Speaker 1: all of these life events that happen, all of these

916
00:46:21,840 --> 00:46:24,520
Speaker 1: emotions that kind of these folks will live through with you.

917
00:46:24,640 --> 00:46:28,200
Speaker 1: So it could be massive changes in macro conditions. It

918
00:46:28,239 --> 00:46:32,879
Speaker 1: could be you know, changes to their family, whether it's

919
00:46:33,280 --> 00:46:36,200
Speaker 1: you know, death, divorce, new children. I mean, there's so

920
00:46:36,280 --> 00:46:39,520
Speaker 1: many things that happen, and advisors have to be able

921
00:46:39,520 --> 00:46:42,560
Speaker 1: to react. Ideally, be proactive, but react to all these

922
00:46:42,560 --> 00:46:44,720
Speaker 1: things and make sure your money's aligned at all times.

923
00:46:45,360 --> 00:46:47,960
Speaker 1: And this is where AI is like incredibly powerful, where

924
00:46:48,000 --> 00:46:51,040
Speaker 1: you can take a ton of that work that used

925
00:46:51,080 --> 00:46:54,720
Speaker 1: to be heavily compromised and you compromise. Is interesting because

926
00:46:55,680 --> 00:46:57,600
Speaker 1: every advisor, whether they want to admit it or not,

927
00:46:58,600 --> 00:47:01,120
Speaker 1: historically has been making comprom for the clients. And so

928
00:47:01,200 --> 00:47:03,640
Speaker 1: kind of one of two directions, Like one compromise is

929
00:47:04,200 --> 00:47:06,240
Speaker 1: I want to save the world. I've got a hero complex.

930
00:47:06,320 --> 00:47:09,000
Speaker 1: I'm going to take every client under the sun. If

931
00:47:09,000 --> 00:47:12,440
Speaker 1: I do that, the compromises, I can't possibly give the

932
00:47:12,520 --> 00:47:14,879
Speaker 1: highest level of quality care and service to every client.

933
00:47:14,920 --> 00:47:17,080
Speaker 1: It's it's not possible. You can't earn enough money and

934
00:47:17,120 --> 00:47:20,000
Speaker 1: revenue from the lower end of your client client base.

935
00:47:20,560 --> 00:47:23,440
Speaker 1: The other compromise might be I am not willing to

936
00:47:23,440 --> 00:47:26,640
Speaker 1: compromise in the quality and service and attention, but as

937
00:47:26,640 --> 00:47:29,120
Speaker 1: a result, I can only serve fifty families, and so

938
00:47:29,200 --> 00:47:31,040
Speaker 1: my minimum is going to have to be ten million

939
00:47:31,080 --> 00:47:33,480
Speaker 1: dollars or something like that. Whereas the compromise is I

940
00:47:33,520 --> 00:47:36,640
Speaker 1: can't actually give my advice to as many people as

941
00:47:36,640 --> 00:47:40,480
Speaker 1: i'd like to. AI is this great equalizer where we

942
00:47:40,520 --> 00:47:43,719
Speaker 1: think about all the infrastructure we built on altruists, and

943
00:47:43,800 --> 00:47:46,600
Speaker 1: you then layer all of the agents that can do

944
00:47:46,640 --> 00:47:50,200
Speaker 1: things like gather data for you, build financial plans, build

945
00:47:50,239 --> 00:47:54,520
Speaker 1: tax plans, help you be incredibly responsive to client emails

946
00:47:54,520 --> 00:47:58,480
Speaker 1: and questions, to build a level of intelligence across your

947
00:47:58,520 --> 00:48:02,120
Speaker 1: client base that no human being could ever possibly attain.

948
00:48:02,560 --> 00:48:07,239
Speaker 1: So it's very easy to have, you know, incredibly precise

949
00:48:07,520 --> 00:48:11,440
Speaker 1: you know, uh and highly personalized uh you know, perspective

950
00:48:11,480 --> 00:48:13,200
Speaker 1: on every unique client that you serve.

951
00:48:13,600 --> 00:48:14,920
Speaker 3: So these are the things that we're building.

952
00:48:14,960 --> 00:48:16,799
Speaker 1: I mean, I think in the end, you know, the

953
00:48:16,880 --> 00:48:20,200
Speaker 1: clearing and custody business will end up becoming very edgentic,

954
00:48:20,239 --> 00:48:22,320
Speaker 1: Like these agents will be the ones who are probably

955
00:48:22,600 --> 00:48:25,239
Speaker 1: you know, logging on if you will, and they'll be

956
00:48:25,560 --> 00:48:28,640
Speaker 1: performing functions you know that today humans have to log into.

957
00:48:28,680 --> 00:48:29,799
Speaker 3: But it's a pretty exciting, uh.

958
00:48:29,719 --> 00:48:33,160
Speaker 2: You know, time of field really interesting. I recall a

959
00:48:33,200 --> 00:48:37,399
Speaker 2: couple of years ago. I don't want to put words

960
00:48:37,400 --> 00:48:40,799
Speaker 2: into anyone's mouth, but it was the CEO of either

961
00:48:40,880 --> 00:48:46,000
Speaker 2: Black Rock or Vanguard or somebody that size was asked

962
00:48:46,360 --> 00:48:49,000
Speaker 2: what keeps you up at night? And the answer was

963
00:48:49,680 --> 00:48:54,480
Speaker 2: cybersecurity and fraud? How do you make sure? And I

964
00:48:54,600 --> 00:48:56,799
Speaker 2: totally understand no one wants to wake up one day

965
00:48:57,200 --> 00:48:59,920
Speaker 2: and a billion dollars is missing. Uh, how do you

966
00:49:00,480 --> 00:49:06,279
Speaker 2: integrate that into altruist? How do you think about the

967
00:49:06,360 --> 00:49:09,719
Speaker 2: human element? You know, deep fakes and synthetic identity and

968
00:49:09,880 --> 00:49:15,200
Speaker 2: voice fraud and cloning and all that stuff. What can

969
00:49:15,320 --> 00:49:19,440
Speaker 2: the modern custodial platforms do that? Hey, some of the

970
00:49:19,480 --> 00:49:24,480
Speaker 2: big guys don't have the integration with technology to engage

971
00:49:24,520 --> 00:49:26,480
Speaker 2: in this arms race against the bad guys.

972
00:49:27,400 --> 00:49:29,719
Speaker 1: I mean, I think the biggest reason they'd have that

973
00:49:29,719 --> 00:49:33,560
Speaker 1: that that you know, paranoia, is that if you're working

974
00:49:33,600 --> 00:49:37,160
Speaker 1: on a you know, fifty year old tech stack and

975
00:49:37,200 --> 00:49:40,439
Speaker 1: we see this with like the latest anthropic model, these

976
00:49:40,640 --> 00:49:43,560
Speaker 1: kind of meethos you know connected models where you know,

977
00:49:43,600 --> 00:49:46,720
Speaker 1: they sit it on top of some you know, legacy

978
00:49:46,719 --> 00:49:50,600
Speaker 1: infrastructure and they'll find, you know, hundreds of critical vulnerabilities

979
00:49:50,600 --> 00:49:52,840
Speaker 1: that no human being could have ever identified because the

980
00:49:52,880 --> 00:49:56,360
Speaker 1: code base essentially one giant, monolithic code based So like

981
00:49:56,440 --> 00:49:59,400
Speaker 1: it's just like this huge albatross that these companies have

982
00:49:59,440 --> 00:50:03,600
Speaker 1: been dealing with for decades. And replatforming is really hard.

983
00:50:03,680 --> 00:50:05,680
Speaker 1: If you're already big in your scale and you've got

984
00:50:05,680 --> 00:50:08,960
Speaker 1: tens of trillions of dollars, it is nearly impossible to

985
00:50:09,040 --> 00:50:14,080
Speaker 1: replatform and go from you know, physical mainframe based technology

986
00:50:14,239 --> 00:50:18,200
Speaker 1: into a cloud based infrastructure using you know, smaller, more

987
00:50:18,239 --> 00:50:19,640
Speaker 1: manageable micro services.

988
00:50:20,120 --> 00:50:21,640
Speaker 3: So yeah, it's a huge risk.

989
00:50:21,680 --> 00:50:24,000
Speaker 1: If I was running a giant old bank or brokerage,

990
00:50:24,040 --> 00:50:27,799
Speaker 1: I would have the same probably primary paranoia. If you're

991
00:50:27,800 --> 00:50:32,000
Speaker 1: building today, you know, the best defense is oftentimes a

992
00:50:32,080 --> 00:50:35,520
Speaker 1: strong offense, So why not just build again in first principles,

993
00:50:35,640 --> 00:50:38,040
Speaker 1: a bunch of protocols to make it much harder for

994
00:50:38,080 --> 00:50:40,160
Speaker 1: bad actors to even get in the door. And this

995
00:50:40,200 --> 00:50:42,760
Speaker 1: is like overstating the obvious, but just having like modern

996
00:50:42,840 --> 00:50:49,320
Speaker 1: multi factor authentication and requirement of security keys even eliminating

997
00:50:49,560 --> 00:50:53,400
Speaker 1: some of the highest risk like, for example, like phone

998
00:50:53,480 --> 00:50:56,839
Speaker 1: calls are a lot easier to dupe, ironically than is

999
00:50:57,840 --> 00:51:02,080
Speaker 1: a properly built multi factor authentication program. So, you know,

1000
00:51:02,160 --> 00:51:06,000
Speaker 1: I think there's a lot that will change. We don't,

1001
00:51:06,120 --> 00:51:08,120
Speaker 1: you know, rest on like the fact that all we're

1002
00:51:08,120 --> 00:51:10,360
Speaker 1: a tech company, therefore we're impenetrable, Like, of course, we

1003
00:51:10,400 --> 00:51:12,120
Speaker 1: get it. You know, we have bad actors trying to

1004
00:51:12,120 --> 00:51:15,560
Speaker 1: come after our clients all the time. And I think

1005
00:51:15,600 --> 00:51:20,640
Speaker 1: that if you're not building especially AI that can help

1006
00:51:20,680 --> 00:51:24,360
Speaker 1: identify other AI and other bad actors, you're in a

1007
00:51:24,480 --> 00:51:25,600
Speaker 1: bit of a quandary.

1008
00:51:25,800 --> 00:51:26,920
Speaker 3: And it's really hard to do that.

1009
00:51:27,400 --> 00:51:30,480
Speaker 1: If your core platform again has tens of millions of

1010
00:51:30,520 --> 00:51:33,080
Speaker 1: lines of code written in languages that you know, honestly

1011
00:51:33,120 --> 00:51:36,319
Speaker 1: nobody uses and hasn't used for decades. That is a

1012
00:51:36,320 --> 00:51:38,040
Speaker 1: major problem with financial services.

1013
00:51:38,280 --> 00:51:41,280
Speaker 2: So you've raised the decent amount of venture capital money.

1014
00:51:42,160 --> 00:51:44,400
Speaker 2: I want to say, the twenty twenty five Series F

1015
00:51:44,680 --> 00:51:48,000
Speaker 2: gave you just under two billion dollar valuation. I think

1016
00:51:48,000 --> 00:51:49,759
Speaker 2: I'm in the Series F E.

1017
00:51:49,920 --> 00:51:51,040
Speaker 3: I don't remember correct.

1018
00:51:51,120 --> 00:51:56,719
Speaker 2: Last year discuss the need for capital to build out,

1019
00:51:56,800 --> 00:51:59,920
Speaker 2: and we're not talking about the hyperscalers that are spending

1020
00:52:00,400 --> 00:52:03,680
Speaker 2: you know, ungodly amounts of hundreds of billions dollars. This

1021
00:52:03,840 --> 00:52:06,200
Speaker 2: is just a nice little startup that's taking a couple

1022
00:52:06,239 --> 00:52:10,680
Speaker 2: of big entrenched companies and working off a clean sheet.

1023
00:52:11,280 --> 00:52:16,000
Speaker 2: What has the capital spend been like on the technology side.

1024
00:52:16,960 --> 00:52:19,720
Speaker 1: Yeah, so we've raised a little over six hundred million

1025
00:52:20,080 --> 00:52:24,160
Speaker 1: in capital over the last seven years. Yeah, I don't

1026
00:52:24,160 --> 00:52:26,799
Speaker 1: think we'll need any additional capital going forward. Like, we

1027
00:52:26,840 --> 00:52:29,080
Speaker 1: still have a lot of you know, cash on balance sheet.

1028
00:52:29,440 --> 00:52:32,640
Speaker 2: You're cash flow positive now, you're you're actually.

1029
00:52:32,400 --> 00:52:35,920
Speaker 1: Our broker dealer's been profitable for about three years profitable.

1030
00:52:36,000 --> 00:52:38,720
Speaker 2: I was even going profitably, just like at least holding

1031
00:52:38,719 --> 00:52:39,279
Speaker 2: your head about.

1032
00:52:40,120 --> 00:52:41,320
Speaker 3: Yeah, we'll look on our industry.

1033
00:52:41,640 --> 00:52:45,000
Speaker 1: Every broker dealer's financial records are public, so you know,

1034
00:52:45,120 --> 00:52:46,640
Speaker 1: you can go look up our balance sheet. It's not

1035
00:52:46,640 --> 00:52:49,480
Speaker 1: hard to find, you know. And then but we still

1036
00:52:49,560 --> 00:52:51,759
Speaker 1: we still use cash on balance sheet for R and

1037
00:52:51,840 --> 00:52:54,520
Speaker 1: D investments to keep building you know, more more tools.

1038
00:52:55,320 --> 00:52:57,640
Speaker 1: But you can imagine if we backed off from you know,

1039
00:52:57,680 --> 00:53:00,720
Speaker 1: our aggressive building of products and features. Yeah, it wouldn't

1040
00:53:00,719 --> 00:53:06,919
Speaker 1: be a hard business to run standalone for decades. But yeah,

1041
00:53:06,960 --> 00:53:10,760
Speaker 1: there's a serious cost to start a custodian so beyond

1042
00:53:10,880 --> 00:53:14,319
Speaker 1: the cost of building all of the technology, there's also

1043
00:53:14,440 --> 00:53:18,000
Speaker 1: the regulatory requirements and the capital requirements. So when you

1044
00:53:18,080 --> 00:53:21,600
Speaker 1: run brokerage business, every time you add a new client,

1045
00:53:21,640 --> 00:53:23,440
Speaker 1: a new dollars to your platform, you have to have

1046
00:53:23,520 --> 00:53:28,360
Speaker 1: reserve capital on your broker dealer. And so there's no shortcut.

1047
00:53:28,360 --> 00:53:30,560
Speaker 1: Like this is something where I tell people every now

1048
00:53:30,560 --> 00:53:32,759
Speaker 1: and again. The last be like, hey, you know what

1049
00:53:32,760 --> 00:53:34,399
Speaker 1: would it take for someone to compete? And I said,

1050
00:53:34,400 --> 00:53:36,800
Speaker 1: We'll take about five years and at least two hundred

1051
00:53:36,800 --> 00:53:38,840
Speaker 1: and fifty million dollars just to have a shot, just

1052
00:53:38,880 --> 00:53:40,839
Speaker 1: to have any shot in the dark of making it.

1053
00:53:41,080 --> 00:53:43,080
Speaker 1: That assumes, of course, you do it right and what

1054
00:53:43,120 --> 00:53:45,800
Speaker 1: you build is somehow substantially better than anything else in

1055
00:53:45,840 --> 00:53:48,600
Speaker 1: the market, and you can get enough clients to run

1056
00:53:48,600 --> 00:53:50,960
Speaker 1: it on. But just to give yourself a shot, it's

1057
00:53:51,000 --> 00:53:52,640
Speaker 1: like again non trivial.

1058
00:53:52,880 --> 00:53:54,840
Speaker 3: And just to pick up because you made it.

1059
00:53:54,880 --> 00:53:57,120
Speaker 1: Come about these these sort of hyper scalers building these

1060
00:53:57,160 --> 00:53:58,040
Speaker 1: foundation models.

1061
00:53:58,960 --> 00:54:01,400
Speaker 3: I'm not so.

1062
00:54:00,480 --> 00:54:03,520
Speaker 1: Sure that when we look back in twenty years and say, okay,

1063
00:54:03,560 --> 00:54:05,800
Speaker 1: well maybe thirty or four years, fift years, but some

1064
00:54:05,800 --> 00:54:07,560
Speaker 1: amount of time in the future, we look back at

1065
00:54:08,080 --> 00:54:10,720
Speaker 1: what were the most impactful companies that made the biggest

1066
00:54:10,719 --> 00:54:13,400
Speaker 1: difference on society. I'm not so sure those are the

1067
00:54:13,400 --> 00:54:14,560
Speaker 1: ones that we'll be talking about.

1068
00:54:14,680 --> 00:54:14,919
Speaker 2: Really.

1069
00:54:14,920 --> 00:54:16,880
Speaker 1: I think it'll be businesses like Altruists that we'll be

1070
00:54:16,920 --> 00:54:20,120
Speaker 1: talking about and going wow, Like they have managed to

1071
00:54:20,840 --> 00:54:25,400
Speaker 1: unlock trillions of dollars for consumers, and that is not

1072
00:54:25,520 --> 00:54:28,120
Speaker 1: something that any of us can be convinced as possible

1073
00:54:28,239 --> 00:54:30,800
Speaker 1: with foundation models. Yet at this point, all they are

1074
00:54:30,880 --> 00:54:34,480
Speaker 1: are money guzzling machines that have yet to figure out

1075
00:54:34,480 --> 00:54:36,920
Speaker 1: how to turn you know, sort of inference into profits.

1076
00:54:37,120 --> 00:54:39,560
Speaker 1: It's their costs or higher than what they're reselling their

1077
00:54:39,560 --> 00:54:42,759
Speaker 1: products and services for. I'm as big a fan and

1078
00:54:42,840 --> 00:54:46,560
Speaker 1: believer and user of AI products as anybody, But when

1079
00:54:46,560 --> 00:54:49,840
Speaker 1: we really start measuring impact, like what changes the world,

1080
00:54:50,640 --> 00:54:54,200
Speaker 1: you know, that's very possible, but there's nothing proven about it.

1081
00:54:54,600 --> 00:54:57,120
Speaker 1: What we're doing is very proven, Like you can very

1082
00:54:57,160 --> 00:55:00,960
Speaker 1: objectively say, if we give every single I don't know,

1083
00:55:01,040 --> 00:55:03,680
Speaker 1: one percent back in economic advantage and you scale that

1084
00:55:03,719 --> 00:55:06,960
Speaker 1: across trillions of dollars for decades, you can start measuring

1085
00:55:06,960 --> 00:55:10,759
Speaker 1: your impact in hundreds of billions of dollars. That's to

1086
00:55:10,840 --> 00:55:14,560
Speaker 1: me more than like a small startup like that's incredibly ambitious,

1087
00:55:14,760 --> 00:55:17,640
Speaker 1: but it's like incredibly good for humanity. I hope more

1088
00:55:17,640 --> 00:55:18,960
Speaker 1: people do this type of stuff.

1089
00:55:19,520 --> 00:55:24,440
Speaker 2: That's Eric Belchunis's column, which became a book, The Vanguard Effect.

1090
00:55:24,680 --> 00:55:26,960
Speaker 2: I want to say it was like twenty sixteen twenty eighteen,

1091
00:55:27,360 --> 00:55:30,840
Speaker 2: Vanguard has saved two trillion dollars in fees for clients.

1092
00:55:30,880 --> 00:55:35,120
Speaker 2: I mean, that's an insane, insane number. And you guys

1093
00:55:35,160 --> 00:55:37,960
Speaker 2: are are looking to push into the same space. I

1094
00:55:38,040 --> 00:55:40,080
Speaker 2: want to be respectful of your time. Before I jump

1095
00:55:40,120 --> 00:55:43,680
Speaker 2: to my favorite questions, I just have to ask one

1096
00:55:43,960 --> 00:55:49,280
Speaker 2: other question. You've built multiple businesses in the wealth management

1097
00:55:49,360 --> 00:55:54,160
Speaker 2: and fintech space. What's the reputable lesson that carries over

1098
00:55:54,200 --> 00:55:57,719
Speaker 2: from one to another? Or is each one a completely

1099
00:55:58,120 --> 00:55:58,880
Speaker 2: different animal?

1100
00:55:59,800 --> 00:56:01,280
Speaker 3: They are all pretty connected businesses.

1101
00:56:01,280 --> 00:56:03,600
Speaker 1: If someone looks at like the evolution arc of my career,

1102
00:56:03,600 --> 00:56:06,840
Speaker 1: it's sort of like each time I find a problem,

1103
00:56:07,600 --> 00:56:11,680
Speaker 1: uh you know again metaphorlity, Yeah, you gotta go okay,

1104
00:56:11,680 --> 00:56:13,480
Speaker 1: well that was an interesting problem, but this isn't even

1105
00:56:13,520 --> 00:56:17,319
Speaker 1: bigger problem. And this is even bigger problem. Yeah, I'm

1106
00:56:17,360 --> 00:56:19,520
Speaker 1: curious now. I think there's going to be you know,

1107
00:56:19,600 --> 00:56:23,959
Speaker 1: reasonably good need for a highly specialized l M specifically

1108
00:56:24,120 --> 00:56:26,560
Speaker 1: narrowly trained for our industry. I'm not sure the big LF,

1109
00:56:26,640 --> 00:56:28,520
Speaker 1: so maybe we'll do that at some point in the future.

1110
00:56:28,560 --> 00:56:31,600
Speaker 1: But the point is like, there's always something that has

1111
00:56:31,719 --> 00:56:35,239
Speaker 1: the potential to make a bigger impact. And you know,

1112
00:56:35,960 --> 00:56:38,680
Speaker 1: one thing that I'll say this is for me. Again,

1113
00:56:38,719 --> 00:56:41,759
Speaker 1: I don't spend a ton of time just trying to

1114
00:56:41,800 --> 00:56:44,239
Speaker 1: compare what I do compared to other entrepreneurs, so I

1115
00:56:44,239 --> 00:56:46,760
Speaker 1: can't really say, like, if there's a lesson to be learned,

1116
00:56:47,239 --> 00:56:52,000
Speaker 1: you know, broadly, But with with each venture that I've

1117
00:56:52,040 --> 00:56:54,279
Speaker 1: been involved with, I've started with a pretty simple north star,

1118
00:56:54,320 --> 00:56:56,359
Speaker 1: which is I want to help people. These are all

1119
00:56:56,360 --> 00:57:00,320
Speaker 1: missions driven organizations. I'm very passionate about that. This allows

1120
00:57:00,320 --> 00:57:03,360
Speaker 1: you to attract other people that are also mission driven.

1121
00:57:03,360 --> 00:57:07,080
Speaker 1: These are your more missionaries versus mercenaries, and we have

1122
00:57:07,200 --> 00:57:10,560
Speaker 1: some of the most incredible people that I could never

1123
00:57:10,640 --> 00:57:13,040
Speaker 1: even dream of assembling a team like what we have

1124
00:57:13,160 --> 00:57:16,040
Speaker 1: at Altrus, But it's because they share that same kind

1125
00:57:16,120 --> 00:57:22,080
Speaker 1: of core ethos of serving clients, driving better outcomes again,

1126
00:57:22,160 --> 00:57:24,000
Speaker 1: sort of being on the right side of the customer,

1127
00:57:24,080 --> 00:57:25,680
Speaker 1: doing things that really matter.

1128
00:57:26,720 --> 00:57:29,080
Speaker 2: So given that it's a huge came out, I was

1129
00:57:29,120 --> 00:57:30,920
Speaker 2: going to say, so, given that look out five to

1130
00:57:30,960 --> 00:57:35,440
Speaker 2: ten years, where's Altrus? What are you doing? How big

1131
00:57:35,520 --> 00:57:36,840
Speaker 2: is Altrus at that point?

1132
00:57:37,080 --> 00:57:41,080
Speaker 1: Yeah, it's hard to predict with precision just how big,

1133
00:57:41,080 --> 00:57:43,280
Speaker 1: but I suspect we'll be very large, you know, if

1134
00:57:43,320 --> 00:57:45,680
Speaker 1: we look at the trajectory of the business today. Again,

1135
00:57:45,720 --> 00:57:48,200
Speaker 1: we don't talk a lot about our numbers publicly, so

1136
00:57:48,200 --> 00:57:49,560
Speaker 1: people have to sort of sort of like a we'll

1137
00:57:49,560 --> 00:57:51,720
Speaker 1: take Jason's word for it, you know, but in our

1138
00:57:51,760 --> 00:57:54,280
Speaker 1: first five years of operating, from when we opened our

1139
00:57:54,320 --> 00:57:56,720
Speaker 1: first account, you know, through five years, we had more

1140
00:57:56,760 --> 00:58:02,120
Speaker 1: assets on our platform than Robinhood, Betterment, Wealth Front, Public Stash,

1141
00:58:02,440 --> 00:58:06,440
Speaker 1: m one, Acorns combined. Right, So when people wonder like

1142
00:58:06,880 --> 00:58:10,200
Speaker 1: is this working, it's scaling very very rapidly, and it's

1143
00:58:10,240 --> 00:58:13,800
Speaker 1: growing at a really really fast pace. People, I think

1144
00:58:13,840 --> 00:58:17,040
Speaker 1: sometimes don't understand that this sort of network effect you

1145
00:58:17,120 --> 00:58:20,080
Speaker 1: get when you serve advisors and those advisors are growing fast.

1146
00:58:20,160 --> 00:58:23,320
Speaker 1: Firms like yours are growing super fast, the clients are

1147
00:58:23,360 --> 00:58:26,320
Speaker 1: adding deposits to their existing accounts. That market taalwind is

1148
00:58:26,600 --> 00:58:27,600
Speaker 1: pretty material and.

1149
00:58:27,600 --> 00:58:30,000
Speaker 2: It's percent fifty and it's better.

1150
00:58:29,760 --> 00:58:32,200
Speaker 1: For advisor clients and is for self directed clients, you know.

1151
00:58:32,280 --> 00:58:35,400
Speaker 1: So these are all things that create enormous tailwinds for

1152
00:58:35,440 --> 00:58:37,680
Speaker 1: businesses like ours. So I think even ten years out

1153
00:58:37,720 --> 00:58:40,479
Speaker 1: will be multiple trillions in assets serving you know, many

1154
00:58:40,520 --> 00:58:41,520
Speaker 1: millions of end.

1155
00:58:41,360 --> 00:58:44,760
Speaker 3: Clients, and likely we'll be doing them.

1156
00:58:44,800 --> 00:58:46,720
Speaker 1: Has kind of capped out one hundred, one hundred, twenty

1157
00:58:46,720 --> 00:58:49,400
Speaker 1: five or one fifty like those things, these laws of

1158
00:58:49,480 --> 00:58:51,880
Speaker 1: physics will sort of be removed, and I think that's

1159
00:58:51,960 --> 00:58:52,960
Speaker 1: a net great thing.

1160
00:58:53,240 --> 00:58:55,160
Speaker 2: All right, I want to be respectful for you of

1161
00:58:55,200 --> 00:58:57,320
Speaker 2: your time, and I'm going to jump to our speed

1162
00:58:57,400 --> 00:59:01,200
Speaker 2: round when we do these really quickly, starting with who

1163
00:59:01,240 --> 00:59:03,320
Speaker 2: your mentors, who helped shape your career?

1164
00:59:04,120 --> 00:59:06,840
Speaker 1: Yeah, so Nick Baim was our first investor at Altruist,

1165
00:59:06,840 --> 00:59:08,960
Speaker 1: who was also a big supporter me my last company.

1166
00:59:09,200 --> 00:59:12,560
Speaker 1: He's a partner at ven Rock, and he's just awesome.

1167
00:59:13,560 --> 00:59:15,680
Speaker 2: What are your favorite books? What are you reading currently?

1168
00:59:16,480 --> 00:59:19,960
Speaker 1: So right now I'm reading Life three point zero by

1169
00:59:19,960 --> 00:59:22,640
Speaker 1: Max tech Mark. It's like a book from twenty sixteen,

1170
00:59:22,680 --> 00:59:26,160
Speaker 1: twenty seventeen. He's one of the he's a professor at

1171
00:59:26,200 --> 00:59:31,400
Speaker 1: MIT and one of the like real four like early

1172
00:59:31,440 --> 00:59:33,760
Speaker 1: thought leaders in AI and so he kind of like, yeah,

1173
00:59:33,760 --> 00:59:36,280
Speaker 1: there's three phases of AI and I'd say we're in

1174
00:59:36,320 --> 00:59:39,000
Speaker 1: like life two point zero right now, still human powered

1175
00:59:39,080 --> 00:59:41,160
Speaker 1: and like get to read the book you'll find out

1176
00:59:41,160 --> 00:59:42,040
Speaker 1: three point Oh it's a good one.

1177
00:59:42,320 --> 00:59:44,840
Speaker 2: That's that's interesting. You mentioned good to great? Anything else

1178
00:59:44,880 --> 00:59:45,439
Speaker 2: you want to mention?

1179
00:59:46,280 --> 00:59:48,120
Speaker 1: Yeah, I mean, look, these are a little bit cornier,

1180
00:59:48,160 --> 00:59:50,000
Speaker 1: but some of the most important books for me. I'm

1181
00:59:50,000 --> 00:59:51,640
Speaker 1: a total math nerd, so I can live in a

1182
00:59:51,640 --> 00:59:53,640
Speaker 1: max tech mark you know, book for you know.

1183
00:59:53,720 --> 00:59:54,360
Speaker 3: Uh forever.

1184
00:59:54,800 --> 00:59:56,800
Speaker 1: I had to learn a lot of soft skills, you know,

1185
00:59:56,880 --> 00:59:58,680
Speaker 1: to be a better entrepreneur. I learned a lot of

1186
00:59:58,680 --> 01:00:00,480
Speaker 1: those from reading Seth Godin's book. It's like one of

1187
01:00:00,520 --> 01:00:04,040
Speaker 1: my favorite amazing books. Great blog as well.

1188
01:00:04,160 --> 01:00:07,960
Speaker 2: Let's talk about what you're listening to, streaming or watching.

1189
01:00:08,040 --> 01:00:10,560
Speaker 2: What's keeping you entertained on these gross country flights?

1190
01:00:10,800 --> 01:00:14,200
Speaker 1: Yeah, so I don't watch much TV, although I did

1191
01:00:14,280 --> 01:00:15,760
Speaker 1: watch your knicks congratulations.

1192
01:00:15,960 --> 01:00:21,000
Speaker 2: I was talking about perfect timing and a fairly easy path.

1193
01:00:21,240 --> 01:00:23,040
Speaker 3: Yeah, well, perfect.

1194
01:00:22,680 --> 01:00:25,800
Speaker 1: Storm avoided my Pistons. You know, I'm a Detroit Pistons fan.

1195
01:00:25,880 --> 01:00:27,800
Speaker 1: But so, yeah, I don't watch a lot of TV.

1196
01:00:28,280 --> 01:00:30,280
Speaker 1: I do listen to a lot of podcasts, so listen

1197
01:00:30,360 --> 01:00:35,680
Speaker 1: to yours. I listened to a big fan of Henry

1198
01:00:35,680 --> 01:00:39,160
Speaker 1: Stebbings so twenty VC and I listened to you quite

1199
01:00:39,200 --> 01:00:42,640
Speaker 1: a bit, and then I listened to Lenny's podcast. If

1200
01:00:42,640 --> 01:00:44,480
Speaker 1: you're a tech person, everyone who Lenny is you're a

1201
01:00:44,480 --> 01:00:46,520
Speaker 1: product person that goes into deep I'm like how different

1202
01:00:46,520 --> 01:00:49,680
Speaker 1: tech companies are being built, especially kind of product led companies.

1203
01:00:49,720 --> 01:00:50,960
Speaker 3: So those are some things I listened to a lot

1204
01:00:51,320 --> 01:00:52,080
Speaker 3: really interesting.

1205
01:00:52,200 --> 01:00:55,080
Speaker 2: Final two questions, what sort of advice would you give

1206
01:00:55,080 --> 01:00:57,640
Speaker 2: to a recent college grad interest in the career and

1207
01:00:58,320 --> 01:01:03,360
Speaker 2: fill in the blank entrepreneurship, fintech or even financial services.

1208
01:01:03,520 --> 01:01:06,680
Speaker 1: Yeah, I think in any career, I would become the

1209
01:01:06,880 --> 01:01:10,720
Speaker 1: most ai forward person in your field that you could

1210
01:01:10,720 --> 01:01:13,560
Speaker 1: possibly be. So it does not matter if you're working

1211
01:01:13,600 --> 01:01:15,919
Speaker 1: in sales, if you're working in tech, if you're working

1212
01:01:16,000 --> 01:01:20,040
Speaker 1: in financial services. I mean there, if you can become

1213
01:01:20,040 --> 01:01:22,200
Speaker 1: the person when you walk in the room, you are

1214
01:01:22,320 --> 01:01:26,200
Speaker 1: the absolute master of claude for your you know, kind

1215
01:01:26,240 --> 01:01:28,400
Speaker 1: of job function, I think that's one of the most

1216
01:01:28,440 --> 01:01:30,840
Speaker 1: important things for any person. I think young people have

1217
01:01:30,880 --> 01:01:33,000
Speaker 1: an actual advantage there, and it's when they should definitely

1218
01:01:33,000 --> 01:01:33,520
Speaker 1: be leveraging.

1219
01:01:33,640 --> 01:01:36,160
Speaker 2: You're not gonna be replaced by AI. You're gonna be

1220
01:01:36,160 --> 01:01:38,680
Speaker 2: replaced by someone who uses AI better than you do.

1221
01:01:38,960 --> 01:01:41,800
Speaker 3: And that's it's getting cliche, but it's very true.

1222
01:01:42,320 --> 01:01:44,640
Speaker 2: And our final question, what do you know about the

1223
01:01:44,640 --> 01:01:52,080
Speaker 2: world of technology, entrepreneurship or financial technology today that would

1224
01:01:52,080 --> 01:01:54,480
Speaker 2: have been helpful back in the two thousands when you

1225
01:01:54,480 --> 01:01:55,400
Speaker 2: were first ramping, right?

1226
01:01:56,080 --> 01:01:58,560
Speaker 1: I mean, I don't know that there's necessarily some innovation

1227
01:01:58,680 --> 01:02:01,040
Speaker 1: that I wish I knew. I just I wish I

1228
01:02:01,040 --> 01:02:05,840
Speaker 1: would have spent more time getting proximate to really high

1229
01:02:05,840 --> 01:02:09,080
Speaker 1: caliber people. Now that I'm older and I've done a

1230
01:02:09,120 --> 01:02:11,760
Speaker 1: few things, I've got the chance to meet some just

1231
01:02:11,840 --> 01:02:15,480
Speaker 1: outstanding people. If you can get close to those people

1232
01:02:15,520 --> 01:02:18,040
Speaker 1: early in your career, it's just going to be such

1233
01:02:18,080 --> 01:02:21,640
Speaker 1: a massive accelerant because your way of thinking is going

1234
01:02:21,720 --> 01:02:23,760
Speaker 1: to be so much better and sharper and inspired.

1235
01:02:24,120 --> 01:02:24,640
Speaker 3: That's what I do.

1236
01:02:24,960 --> 01:02:27,800
Speaker 2: Thank you, Jason for being so generous with your time.

1237
01:02:28,280 --> 01:02:31,000
Speaker 2: We have been speaking with Jason Wanks. He is founder

1238
01:02:31,000 --> 01:02:36,840
Speaker 2: and CEO of Fast Rising Custodian Altruist. If you enjoy

1239
01:02:36,920 --> 01:02:40,080
Speaker 2: this conversation, well check out any of the previous six

1240
01:02:40,240 --> 01:02:44,600
Speaker 2: hundred and forty eight we've done over the past twelve years.

1241
01:02:44,640 --> 01:02:49,680
Speaker 2: You can find those at iTunes, Spotify, Bloomberg YouTube, wherever

1242
01:02:49,760 --> 01:02:52,960
Speaker 2: you get your favorite podcasts. I would be a remiss

1243
01:02:53,000 --> 01:02:55,000
Speaker 2: fund and thank the correct team that helps with these

1244
01:02:55,040 --> 01:03:00,560
Speaker 2: conversations together each week. Alexis Noriega is my video producer.

1245
01:03:00,640 --> 01:03:04,120
Speaker 2: Anna Luke is my podcast producer. Jean Russo is my

1246
01:03:04,200 --> 01:03:08,120
Speaker 2: head of research. I'm Barry Retorts. You've been listening to

1247
01:03:08,280 --> 01:03:11,400
Speaker 2: Masters in Business on Bloomberg Radio