Latest / AI for Founders with Ryan Estes / Building the Next-Gen Retail Investing Platform: Tradesk

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Building the Next-Gen Retail Investing Platform: Tradesk · AI for Founders with Ryan Estes

0:00
Welcome back to AI for Founders. I'm Ryan Estes, and today we're
0:02
diving into the future of investing with my guest, Eric
0:05
Chu, CEO of Trade Desk. Eric has one of those incredible
0:09
careers that stretches from engineering to Wall Street to
0:12
hedge funds to CFO of a major venture firm.
0:15
And now he's building what he calls the next generation
0:18
investment platform. Think insider trading monitors,
0:21
thematic investing bundles, recurring investments, and now
0:25
AI powered research and insights.
0:27
Eric has raised over 12 million, spent years building the
0:30
platform from the ground up, and he's on a mission to democratize
0:33
finance for busy professionals who want to grow their wealth
0:36
without drowning in complexity. This is going to be a fun and
0:39
eye opening conversation about where markets, AI and investing
0:43
are headed. Let's get into it, but first,
0:45
some business. This episode is brought to you
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2:30
Eric, how are you? Thanks for coming on the show.
2:33
Thank you, Ronnie. Great to be here.
2:35
Nice. Now quick question before we
2:37
dive in. I I've been flirting with this
2:40
new fashion for the fall. I'm calling it casual Friday
2:43
Estes. So I've got the button up, but
2:46
the all white button up. I feel, I kind of feel like I'm
2:50
a waiter. So do you think this is a good
2:54
attire for the podcast or do you feel like I should be bringing
2:58
you a bottle of wine? Hey, a bottle of wine always
3:01
works, right? Nobody would say no to that for
3:03
sure. But you know, I think, you know,
3:05
if clothing wise, whatever you feel comfortable with and that
3:07
this is what I did today, you know, fairly casual, sort of a
3:10
business casual shirt. But you know, that's what I wear
3:12
to work. That's, you know, sometimes I
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wear to to some events, you know, so whatever it makes you
3:16
feel comfortable. Amazing.
3:19
And to that point, you're right, everybody loves a good waiter.
3:21
So if I'm coming in with hospitality energy, that's how I
3:24
want to show up anyway. Eric, I really appreciate you
3:27
being here. Give us a quick introduction to
3:30
your Company Trade Desk. Absolutely.
3:33
So Trade Desk, we we think about the next generation investment
3:37
platform. We pride ourselves in terms of
3:39
technology, in terms of lower barriers to entry, because we
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have spent the last four years building up essentially from
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ground up, a platform that incorporates a lot of the
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features, functions, tools that traditionally were only
3:56
available to the money managers to watch it guys.
3:59
But over the last, you know, few years, we, you know, we, we were
4:02
able to put a lot of those in our platform in a way that is
4:07
not overwhelming. Very straightforward, very user
4:10
friendly to a wit to to the to to the point that you know a lot
4:14
of people can just sign on with the and then start using right
4:17
away. Amazing.
4:20
So is it safe to say that this is a a retail investing
4:23
platform? I can go on.
4:24
I can purchase stocks. I can I can purchase different
4:31
investment vehicles. Absolutely.
4:33
So for now this is we we focus primarily on retail.
4:37
You know customers once they on board, once they deposit the
4:40
money, they can start right away, you know, purchasing
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stocks, options, buy and sell ETFSADRS, all those stuff.
4:47
And we're in the process of adding additional products as
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well as features. But also next step, we're moving
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a little bit towards the institutional side of things,
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but for now, we're more retail focused.
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Incredible. You know, in this kind of like
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explosion of like retail investing options, I feel like
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it's just democratizing capitalism in a way, you know,
5:11
like, to your point, how has it changed?
5:13
How has it become? How is your tool like enabling
5:18
more people to get involved in the stock market?
5:21
Absolutely. So I'll, I'll, I guess I'll give
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you a little bit of a longer answer, longer story.
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So I myself used to be working on Wall Street, used to be a,
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you know, a stock analyst, research analyst when I first
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started after Business School, you know, did that for a number
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of years and also working on hedge funds right now.
5:38
These are institutions, obviously institutional money
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managers on the sell. We call sell side or buy side
5:44
where you know you have the smartest people with the best
5:47
education working 14-15 hour days.
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The the objective of all those hard work, right is to be able
5:55
to do all those research on companies, on industries so that
5:58
we can put out those research notes to institutional money
6:02
manager. Now Fast forward today with some
6:06
other products and other platform, especially with ours,
6:09
we are able to offer customers access that traditionally only
6:14
available to those, you know, institutional money managers.
6:17
You can look up companies fundamental information, you can
6:21
look at the business information, you can look at
6:25
inside the trade and monitoring, you can look at investment
6:28
themes, right. A lot of different, you know,
6:31
very cool, very informative tools on our platform and the
6:35
people traditionally are only available, you know, to the sort
6:38
of institutional analyzers. Yeah, it's incredible.
6:43
Walk us back a little bit. So you're working on Wall
6:45
Street. You have a storied 15 year
6:47
career. How did you have the inceptive
6:50
or how did you incept the idea for Trade Desk and what how did
6:54
that kind of move forward? How did you bring the idea
6:56
forward? Yeah, absolutely.
6:58
So I guess it went back to the origin of Trade Desk, right.
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You know, we, you know, I'm actually a engineer or in
7:05
training originally, you know, I did my master's degree, engineer
7:08
and practice a number of years in the industry.
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However, you know, I found myself increasingly excited or
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more excited about investing about, you know, Wall Street,
7:17
about stocks, to the point where I, I quit my job as engineer and
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then went to do my MBA full time at NYU Star.
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And then after that, you know, worked on Wall Street investment
7:28
banks, hedge funds and, and later on became the corporate
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CFO of a very large venture capital with top private equity
7:35
firms in the, in the world. Now, Fast forward to 2020211,
7:40
right? Everybody knows COVID hit, you
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know, everybody had a little bit extra time in addition to
7:46
playing golf on on the course. And also for us, for me
7:49
especially, you know, I had a little more time reflecting of
7:53
what I've done before as an engineer before and also working
7:56
on Wall Street throughout the tour.
7:58
I think I'm also talking to a lot of friends, families back
8:03
then during COVID, right when everybody had a little bit more
8:05
time. I think increasingly what I
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found is thinking about what I before my Wall Street days and
8:12
also talking to my friends. The pain point for a lot of them
8:16
is these are working professionals, right?
8:19
They are very busy building their career at whatever
8:22
profession they're in. They are very busy raising a
8:25
family, raising their kids and, you know, taking the kids to
8:30
soccer practice, there's golf practice, what have you, right?
8:33
But in the meantime, these are very intelligent people.
8:37
They all want to do really well in their financial the future,
8:42
right, either for college education, for their kids
8:44
college education or for their own retirement, but they just
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don't find the time, the interest or, you know, the, the,
8:53
the, the knowledge to be able to to be able to to do a lot of
8:57
that. I think that's where kind of a
8:59
know the trade desk idea came together.
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A few founders that we put together in a week debated, we
9:05
discussed and then we think that building the next generation
9:08
investment platform that would allow people, especially busy
9:13
working professionals to be able to access tools in a way very in
9:17
a very efficient, very cost of efficient, very friendly way.
9:21
That's not overwhelming. That's sort of the idea of of of
9:24
tree desk. It's amazing.
9:27
And that's, that's so incredible.
9:29
An engineer and MBA. As you were making Trade Desk,
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did it feel like your worlds were merging?
9:35
Did you feel it did feel very satisfying?
9:37
It it does, I have to say it does because we as I mentioned
9:41
before, we built the platforms from from grand up all the way
9:45
from back end, all the technology operations to the
9:49
front end customer facing the app, right, a lot of features
9:52
functions UIUX, all those right. You know, it takes a lot of
9:55
engineers engineering to do and also a lot of knowledge in
10:00
finance either, you know, trading, compliance operations,
10:05
what have you. So it takes all of those
10:07
knowledge and experience and to put a investment platform
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together. I, I think, I think my, my
10:13
background kind of what I was able to leverage to a lot of my
10:17
experience and my background as part of this sort of a building
10:20
process for, for the platform. We, as a matter of fact, we have
10:24
more engineers, you know, with the company than the rest of all
10:29
other departments combined. So we're very proud of that.
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Yeah, it's incredible in the beginning.
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I'm sure there's a ton of compliance and security that
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have to go into this. Tell me about the the beginning
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from idea until you actually ship the product.
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How much did you raise to to get the thing off its feet?
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Yeah, absolutely. So a few questions there.
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First of all, the easy one, right.
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You know, it took us roughly about you know, twelve,
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$13,000,000 to in total capital in the to to fund the platform
11:02
so far. A lot of a lot of compliance, a
11:06
lot of engineering. So as you know, we operate in a
11:10
highly regulated industry, security services in the US we
11:15
are registered with SEC, we're also member funeral and SIPSIPC.
11:20
So a compliance is just part of the daily operations.
11:25
It's a very actually very, very critical part of the daily
11:28
operations. Everything we do, you know, in
11:31
addition to driving a crime, customers, you know, serving
11:34
customers to marketing, to operations, to technology,
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whatever you do, compliance is always part of it just because
11:44
we because of the industry that we, we, we operate in.
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So we spend a lot of time and money and, and for a good reason
11:50
because we, we serve the retail customers by by definition,
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these are protected by securities laws, regulations and
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those are the things that we have to follow.
12:02
Yeah. Amazing. 1213 million and so I
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is this what took 12 months, is that what you said basically to
12:08
get the product on its feet? So we, we actually, we have a
12:13
global footprint. We first actually started in the
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Asian market about four years ago.
12:19
You know, we, so it took us about, I would say about 12-18
12:24
months to get the product into production because a lot of
12:27
internal testing, a lot of the evaluation was regulators as
12:32
required as part of this, this, this process.
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So once all of those are done and, and also a lot of
12:39
integration testing with clearing firms with different
12:42
vendors, we, we are essentially fully automated.
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So for a MLKYC customer onboarding, depositing and then
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you know, after that, you know, customer can start right away
12:55
trading everything, all the process are automated.
12:58
So it took us, it took us a while to, you know, get through
13:01
everything and get everything tested to a point that's that's
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where ready to to release to the production environment.
13:09
So it, it was really kind of the retail apps, it was Robin Hood
13:14
and. We both Fidelity, fidelity.
13:18
Fidelity, that got me into it in the beginning.
13:21
Now most of my investments have always come in the form of
13:24
either real estate or startups. And believe it or not, I was
13:28
like stock market Too much to learn, too much to think about.
13:32
But the apps and the ease of use is really what got me into it.
13:36
So when you're thinking about your customer, how do you kind
13:39
of differentiate between those platforms?
13:42
Yeah, very, very, very good question.
13:43
So you know every different platform has its own different
13:48
focus approach. So I think for us, if, if you
13:51
were to use at the analogy of a student, right, we think who are
13:55
not, you know, elementary school student or not college student
13:59
were somewhere in between, right?
14:01
If you had used another platforms, for example, Robin
14:05
Hood, right, for a couple of years, right?
14:07
I mean, you know, don't get me wrong, there are very good
14:09
platform to get started fairly easy, very straightforward.
14:13
Once you do that for a couple of years, then you start to come
14:15
across questions like, Hey, what if I want to do a little more?
14:18
What if I want to, you know, dive into a little more of
14:21
companies, fundamental information of the financials,
14:25
right, of the news items of the, you know, sort of detailed
14:30
moving pieces in the industry, right?
14:33
So that's where, you know, some of our customers, they start to
14:38
look for a little bit more advanced tools, but not to the
14:42
point where it's so advanced it's overwhelming, right?
14:45
I would say some of the other platforms out there is they
14:48
have, you know, hundreds of products, right, hundreds of
14:51
features to the point that's this is too overwhelming for
14:54
average for for the regular retail investor.
14:57
But I think we have come across to a good balance of in terms of
15:02
accessing the features that customer need very commonly need
15:08
and and and and also there's enough depth for customers to go
15:12
deeper if they want to. Yeah, this is, you know, and I
15:16
feel like I would be the perfect customer for Trade Desk for a
15:21
couple of reasons. One, I really enjoy learning
15:24
about companies, investing in companies, and I love money, but
15:29
also I really need the education component.
15:32
Typically how I've invested in companies is, you know, dump the
15:36
big nut into mutual funds and then give myself a little
15:40
leeway. I'll just invest in my own PNL.
15:43
You know, I look at the tools that I I use and like, well, I'm
15:45
going to use those. I'm tired of those guys already.
15:48
And then the other way is I just ask my kids what they're into,
15:51
like, Hey, what, what apps are you using and things like that.
15:54
Because I figured that's what's coming around the corner now.
15:56
A lot of that just becomes comes from ignorance of like, boy, I
16:00
just don't have the time to do the kind of research on the
16:03
companies that align with probably my values is probably
16:06
important to me, but also maybe my sphere of expertise, you
16:09
know, like tech companies and things like that are basically
16:13
I'm at least able to speak the language.
16:15
And so I feel more confident investing in those companies.
16:17
So when I'm thinking about using Trade Desk to to, you know,
16:21
invest in companies, but also do the research on the companies,
16:24
what, what is Trade Desk providing for me?
16:27
Absolutely. So I think I briefly mentioned
16:29
those, you know, we have built quite a few very, very good
16:32
features, very useful features, for example, inside our trading
16:38
monitoring. So you know, for all the public
16:41
listed companies, you know, the, there are clear definitions of
16:44
insiders, right? Either you're CEOCFOS or, or, or
16:47
core stakeholders, right? You know, if you're insider,
16:50
you're treating the company stock, you know, by definition,
16:52
per regulation, you need to disclose all those.
16:55
And then we have built a tool that automatically monitor
16:58
tracks all those insider trades by all public related companies.
17:02
And obviously based on whatever, what companies you put on your
17:07
watch list or in your portfolio, you can cut, customize it to the
17:10
point that's useful to you rather than being overwhelmed
17:13
by, you know, hundreds of notifications everyday.
17:15
So that's one very, a very good tool.
17:18
The other one is thematic trading, right?
17:21
You know, be it we're in a very new era of technology, either AI
17:26
or crypto or aviation or EV, right, what have you.
17:34
A lot of new things going on, a lot of new trends going on.
17:37
You know, we have built this tool thematic investing.
17:41
You can pick by industry, by theme instead of picking
17:47
individual companies where you don't, you know, to the point
17:50
where or in financial theory, finance theory, there's
17:53
something called diversification, right?
17:55
You know, in layman's worth, don't put everything you want
17:57
basket that's sort of follow the same idea.
18:00
You know, you pick certain investment theme where you can
18:04
have the choice of investing in 2030 companies simultaneously
18:09
rather than instead of picking one or two or try to pick the
18:12
winners, right? Because you know, that's takes a
18:14
lot of work. It's just for most of the
18:16
people, they just don't have the time to do that.
18:19
But I mean, with this tool, you can then invest in in, in a
18:22
batch of companies with certain industry value that you're
18:25
interested in. And we have actually coupled
18:27
that with, with recurring investments.
18:32
That's another idea that's built on top of finance theory.
18:38
So instead of trying to time the market right, even, you know,
18:41
the most renowned investor, Warren Buffett says he doesn't
18:45
know how to calm the market. Frankly, nobody does, right.
18:48
But with the recurring investment, you don't have to.
18:52
And you know, you just put in a, you know, threshold amount on a
18:56
weekly basis or monthly basis or quarterly basis.
18:59
What are you feel comfortable with?
19:00
What are fits into customers budget, right, you know, and,
19:04
and then you can put that into specific companies or into
19:07
specific investment themes. And then the process, the, the
19:12
the app will does all the investment automatically for you
19:16
per your guidance, per your instruction.
19:18
So I think those are just to give an example of a few, a few
19:22
tools features that would help average investors to to be able
19:26
to kind of a, you know, learn about the market and and also
19:29
kind of a putting some things into action along the way more
19:33
exciting. Yeah, it's really cool.
19:37
It it seems like a lot of consideration has gone into
19:40
people being a little bit of a novice with trading, which is
19:43
like me, you know, where, you know, if I'm looking at CNBC or
19:47
I'm watching the the stock ticker, I'm looking at
19:49
candlesticks. It's overwhelming and it freaks
19:52
me out. You know, what I want to do is,
19:54
is, you know, have great signal like you're talking about.
19:57
So if you know, there's some kind of inside mood from the
20:00
CEO, OK, that that may trigger action for me, you know, invest
20:04
in bundles where I can be like, OK, I really.
20:07
Into equestrian activities. So give me that equestrian
20:11
bundle. I don't know why I'm investing
20:13
in horses, but maybe I want to. So I think it's helpful for
20:17
people to, to limit the amount of information because obviously
20:21
it can be a big information overload.
20:23
And that's a little bit different maybe from people who
20:26
are traders who, I mean, I've got a couple of buddies that
20:29
they have, everyone's got their like their algorithm and their
20:32
theory of what they're going to do and, and how they're going to
20:35
do it. But for the, for most people, it
20:37
really is going to be a consideration of how much
20:41
information to give them and how you can kind of adapt to their
20:44
behavior. How do you poll your customers?
20:48
How do you learn kind of what customer demand is for, for for
20:52
the platform? Yeah.
20:54
So, you know, a few different approaches.
20:58
You know, for one, you know, we have had customers on our
21:01
platform already. So you know, based on, you know,
21:04
their feedback, they, they constantly give us feedback.
21:07
So all those feedbacks are very, very valuable.
21:10
We take them very seriously, you know, either good or bad, right.
21:14
So those are a very good direct source in terms of customer
21:18
response, customer feedback. The other one is we do we have a
21:23
marketing program, a very comprehensive marketing program.
21:27
We leverage search engines, affiliates, so on and so forth,
21:32
right? And also AI as part of our
21:35
marketing to attract customers, get access to customers.
21:41
So just to give you a few example.
21:44
Yeah, I'm really interested in the marketing too, because the
21:47
onboarding is, is pretty tricky, right?
21:49
You got to get somebody onto the platform.
21:51
You have to have them connect their financial, their bank
21:54
account, their credit card to make sure that everything's in
21:56
place. There's like all the terms and
21:58
conditions. There's quite a few steps people
22:00
have to do before they get in and all that's just predicated
22:04
that they trust. You know, I'm really happy that
22:07
you're, you know, you take founder LED marketing really
22:10
seriously. I mean, you're out front.
22:12
And really, I think as a founder and CEO, especially in something
22:15
like this, the, the, the essence of that trust is based on the
22:18
founder who's going to go out there and throw the whole
22:21
company on their shoulders and be like, Hey, I got you.
22:23
You know, you got to do that. Now when you're thinking about
22:26
using AI different platforms for marketing, what are ways that
22:29
you build trust into the platform to get people on
22:32
boarded properly? Yeah, absolutely.
22:34
So a few things for one, you know it's kind of a because as I
22:37
mentioned we are a operating in the regulated area in the
22:41
regulated industry. So by by by regulation we have
22:44
to follow very strict, you know industry regulations either from
22:50
SEC or funeral. So this is I think first level
22:54
of, of comfort. You know, the, the other one is
22:59
I think as you mentioned, so we don't, I wanted to be upfront
23:02
with, with customers, you know, going customers who we are, what
23:05
we're about, what we have done, you know, finance, you know,
23:09
after working on Wall Street for, you know, 15 plus years, I
23:12
understand finance financial industry has all about trust,
23:15
right? It's really you know, whether or
23:16
not, you know, you have done business with certain people,
23:19
whether or not you have built the trust along the way.
23:21
I think with customers, with retail customers, we wanted to
23:24
provide you know value to them. I think the first one trust is
23:29
the sort of the, you know, all the way for front on that, on
23:33
that approach. So I think, you know, it's
23:36
either by providing them with tools or features that they
23:40
would not otherwise be able to access and also provide sort of
23:44
accurate information on our platform, be it, you know, stock
23:48
quotes or company news or you know, regulatory filings, what
23:53
have you, right. You know, that's a very, very
23:55
important part as well. Yeah, it's got to be interesting
23:59
too, because I mean, you're an analyst and an engineer, so
24:06
you're the, what's probably interesting to you about the
24:09
market is much more, you know, is much deeper than what, you
24:15
know, kind of a retail investor might want.
24:17
What are some of the limitations you put on maybe the UI or the
24:20
product itself where you're like, boy, I would love to have
24:22
this, this and this, but like, let's make sure that it's not
24:25
overwhelming. Is there something on your
24:27
product road map that you're like, boy, if this, if I built
24:29
it just for me, I would add these things?
24:32
Yeah, absolutely. Great question.
24:35
So as I mentioned, and as a former research analyst, you
24:37
know, I used to spend 13/14/15 hour days, right, you know,
24:42
working at investment bank, you know, digging into companies, 10
24:46
Q's, the regulatory filings, right, the 10 Q's, the 10K's,
24:49
the earnings transcripts, reading financial models,
24:51
talking to company management, right?
24:54
And, and all those things today, very interesting and for me
24:58
personally, very exciting is can a lot of those very manual,
25:03
repetitive work can be replaced by AI, right?
25:07
You know, a lot of the things all you have to do is to put in
25:11
a few prompts in into the in into the AI engine, which, you
25:16
know, by the way, we are in the process of putting one out by
25:20
tree desk. We're about, you know, a month
25:22
away from releasing a beta version of that.
25:25
Super excited about that. But anyway, so once that you
25:27
know, beta version of AI engine is, is is is available for
25:31
customers, literally you have to put in prompts, for example,
25:37
what's the competitor of Tesla, right?
25:39
Give me the competitive advantage of Tesla versus, you
25:43
know, Caribbean, right? Give me the most earnings
25:47
summary highlights of Apple, right?
25:51
Give me the last three months performance of My Portfolio.
25:58
Give me, you know, just to give you a few example, right, All
26:01
those things without AI needs a lot of manual work.
26:06
You have to go go in there and dig through a lot of the
26:09
documents or build a model in order to do that.
26:11
But these days, you know, all those AI engine is able to do
26:16
all of those for you. Now for us as a platform, you
26:20
know, we have to put in a lot of checkpoints in order to provide
26:26
to make sure a few things. One, you know the information is
26:29
accurate and two, for us in the in the, in the investment
26:33
industry more specific, you know, we were not currently able
26:38
to provide a specific investment advice that those are by
26:42
regulation. So we cannot say OK, buy this
26:45
stock or buy that stock. So we have to put, but if one
26:49
customers to ask those questions into our AI engine, we have to
26:53
have a certain way to sort of a you know ring fence those kind
26:57
of questions. So you know, we are, we're in
27:01
the process of getting additional regulatory approval
27:05
to be able to provide those services, but that would be a
27:07
little bit down the road. But you know, back to your
27:10
point, to your question recently, I think that would be
27:13
something that I would be very much looking forward to.
27:17
We, we want to be able to offer all sorts of customers our
27:22
services, not only to look into specific companies information
27:27
right you know what we call self-directed trades, but also
27:31
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27:34
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27:37
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there's so many opportunities to do really cool, make really cool
28:54
tools that are coming with AI. I'm really interested in the
28:56
product that you're getting ready to release, particularly
28:59
around the the guardrails that you have to put in that because,
29:02
you know, the way I'm using LLMS more and more is to kind of
29:06
defer their their creativity and place of mine.
29:10
So as opposed to saying like, you know, give me earning
29:13
reports for Apple, it asked a contextual question like do you
29:17
think I'm leveraged to considering what's going on in
29:20
the news with Apple in my leverage too far in My Portfolio
29:24
with Apple stocks now a response to that, Can they, is there like
29:28
some kind of compliance that you have to be careful with that
29:31
it's not indicating that you should make a trade or not make
29:35
a trade because then that gets a little bit dicey, right?
29:37
Of like, OK, how is the LLM affecting?
29:40
And what's kind of prompting is going into the back end of that
29:43
to suggest or make recommendations?
29:45
So how do you set up guard rails on kind of AI when people are
29:49
going to create a kind of personalized relationship with
29:52
it? Yeah, those are those are that
29:55
some of the challenges we're facing, but also some of the
29:58
opportunities to be honest. So we we have been working with
30:01
a vendor that's specifically specialized in in finance
30:07
related AI. So we are working very, very
30:09
closely testing this, you know, as we speak of different, all
30:13
sorts of different scenarios, right, you know, related to how
30:17
customers ask those questions and how the AI engine provide
30:22
answers to those questions. And and also how those questions
30:26
because we would be able to allow customers ask questions
30:29
related to their portfolio. To your point earlier, how that
30:33
portfolio is related to what's moving in the market, what's
30:38
going on in the market. So we just have to be very, very
30:42
careful that we are not, you know, moving into those sort of
30:47
the word they use dicey sort of situations where we provide in
30:51
inadvertently provide, you know, some advice.
30:55
So, you know, these are what we have spent a lot of time on, on,
30:59
on this new product, new feature.
31:01
So AI just like any other tool, right?
31:03
You know, they provide value to customers if they are useful, if
31:07
they are used properly and if they are designed properly.
31:11
So that's, you know, that's kind of the, the, you know, the
31:15
things that we're going through right now.
31:18
Yeah, OK, I've got a product request.
31:23
I'm gonna walk you through it and I want you to tell me how
31:25
close we are to making something like this happen.
31:27
So I, I was kind of describing how I'm qualifying companies to
31:31
invest in, which is like my kids 16.
31:33
Like, hey, what do you think is cool?
31:34
You know, and I say that because it's kind of silly, but also not
31:38
a bad idea. Let's say it's a genius idea.
31:41
So we're in the in the near future and my glasses are
31:44
recording everything I'm seeing, everything I'm touching.
31:47
I want to be able to automate that every time my son mentions
31:51
a, a company four or five times and I see it at three times that
31:55
it's going to automatically start investing in that company
31:58
10 bucks a month. Now, how far away are we able to
32:02
do that? Because, OK, I'll start with
32:04
that part of the question. Oh, I think, I don't think we're
32:08
too far from that at all. It's really, I think that
32:11
technology is there is available even today.
32:16
But I think the challenge is because you are crossing over
32:20
quite a few different areas, right?
32:22
You know, first of all, you would allow there's privacy
32:25
concerns, right? Because by taking that you know,
32:29
words from people's casual conversation, you got to allow
32:34
take privacy into consideration, right?
32:36
Is that allowed is an opt in, right?
32:38
So that's probably the biggest hurdle right now.
32:42
You know, the technologies, they are the voice recognition
32:45
technologies definitely there. So that's the first piece.
32:48
The second piece is once, let's say once you figure out that
32:51
piece, the the machine or your computer is able to take those
32:57
pieces of information from people's conversations and
33:00
convert them into essentially cult, computer cult, right?
33:04
Then you would be able to put that into a investment platform
33:09
to be able to, you know, generate those trades for
33:12
people, you know, either no one time trades or recurrent trades,
33:16
right. And then at that point you
33:18
gotta, you gotta give people options, choices of what to do,
33:22
right, How much to buy, what's the frequency, whether or not
33:25
customers understand what they are about to put in, in, in, in,
33:30
in terms of instructing the, the computer what to do.
33:33
So there's that piece. And and then finally, you know,
33:36
all these, as I mentioned, who would be, you know, securities,
33:41
right? So these would be 100% regulated
33:46
by FEMA, by SEC. So there's a lot of compliance
33:49
issues that need to be mutually resolved and then reviewed and
33:55
looked at before this becomes reality.
33:57
But I think we're, we're not that far.
33:58
We're not that far. We're pretty close, you know,
34:01
and it's interesting because what what AI is presenting, I
34:04
think is like a whole new interface for everything you
34:07
know, of like how how are we engaging with the world?
34:10
And so I think part of my practice is like deferring
34:13
creative capital to the machine, so to speak, is largely because
34:18
it's going to know me better than me.
34:19
It may never be smarter than me, although that wouldn't be too
34:22
hard, but it's going to know me better than me because it has a
34:27
sterile linear memory of everything that's happening,
34:32
assuming that it's capturing everything that I'm capturing,
34:35
whereas I am distracted, I forget what I say.
34:39
I double the things I say all the time.
34:42
So like literally you could set up these kind of parameters to,
34:45
to do diligence on companies just based on your own
34:48
engagement with it, how it is, Is it coming to you?
34:51
And I think this is going to be kind of revolutionary largely
34:53
because, you know, financial investing comes from very
34:57
conservative background where it's like, you know, I buy
35:01
Johnson and Johnson because my grandfather bought Johnson and
35:03
Johnson and we're Johnson and Johnson kind of family, you
35:06
know, but now you, you have much more adaptability.
35:09
You have much more kind of maneuverability to use these
35:13
tools as they kind of evolved. Now, of course, boy, the the
35:17
compliance for that seems pretty crazy.
35:19
What, what are you excited that AI is bringing to kind of
35:25
investing in financial markets? Yeah.
35:27
So I, I think for me personally, especially given my background,
35:30
right, I, I think AI to me in the financial services industry,
35:33
the most immediate impact would be able to substantially
35:37
increase people's efficiency, be a doing research or looking at
35:42
names, looking at companies, look at portfolios, right.
35:45
All those things that, again, you know, used to be done
35:48
manually by analysts, right? You know, by MSN bankers, by
35:54
traders, right, you know, on a spreadsheet, on whatever
35:57
software they create. And now all of a sudden they all
36:00
can be done fairly easily, efficiently, you know, in AI
36:06
through prompts, right? So that's, I think that's the
36:08
most, most exciting part. Just traditionally, you know,
36:12
all those access to those information would not be
36:15
available to retail masters to average master who may have just
36:19
a few $1000 in their in their account, right?
36:22
Because those were just thinking about the resources it would
36:25
have taken for those money managers to, to, to be able to
36:30
implement something like that before say even, you know, as as
36:33
as late as 10-15 years ago, it really takes a lot of resources
36:38
and hence the privileged access for, for those kind of services.
36:42
But today, you know, you know, with fairly minimal amount of
36:46
monthly subscription, you can, you know, access to those same
36:50
technology, that investment and those, you know, money managers
36:54
have access to in a fairly, you know, straightforward and easy
36:58
way. So I think that's the most
37:00
exciting part. And, and then, you know, to be
37:01
honest, I think we're still at the early innings of, of this
37:04
game, right, Maybe the first or second inning.
37:07
You know, I, you know, I've been in the sort of in the data
37:11
center world for a long time, about 15 years, pretty much
37:14
throughout my, my, my, my years on Wall Street, you know, on the
37:19
South side by side, the corporate side.
37:22
As part of that, I got to see, you know, the boom of Internet,
37:28
of mobile computing, of cloud computing.
37:31
And now in a world, the 4th wave or 5th wave of, you know, AI
37:35
crypto, right? I got to see all those, you
37:38
know, sometimes from boom to bust a couple of cycles.
37:43
But now I think we're really on to the next wave of of sort of a
37:49
technology innovation revolution to some to some point.
37:53
I mean, there's gonna be a lot of new applications that will be
37:56
built right after some of the basic functionalities that are
38:01
are essentially enabled by, you know, very by the AI
38:05
infrastructure, AI data centers, AI infrastructure, base
38:08
technology, technology, right. Once that's in place, a little
38:11
bit more mature, I think you're gonna see the huge boom in
38:16
additional applications that would be able to add leverage
38:19
those AI technology more and more comprehensively.
38:23
Yeah, and the the kind of user computer interface is just, it's
38:28
just wide open terrain as we move into like, you know, smart
38:31
glasses and like wearables and, you know, narrow link that's
38:35
going to be, you know, implanted in our brains.
38:37
I mean, we're going into some some wild times.
38:40
It's really exciting. I want to ask you about your
38:42
confidence in the LLMS in doing diligence.
38:46
So like you're saying, it's the second inning, but like kind of
38:50
where you're standing. So if you're doing diligence on
38:53
a company, now you go, what's going into that is a whole lot
38:57
of expertise, experience, which is to say you trust your gut.
39:02
If you're coming up against kind of analysis from, let's say,
39:05
ChatGPT, that kind of goes against your, your gut feeling
39:10
about a company, your gut feeling about the future, How,
39:14
how do you reckon that? What's your next step?
39:17
Very, very good question. So you know, AI, you know, as
39:20
part of the reason why there are we're still in the early earning
39:24
innings, right? You know, it's because there is
39:26
still certain issues, for example, hallucination, right,
39:30
by a is for one reason or another.
39:33
There's that, and there's also sort of the compliance issues,
39:36
right? The accuracy issues.
39:39
We're not 100% there yet, although we're definitely moving
39:42
in the direction. But in the meantime, I think use
39:45
AI as a tool rather than as the perfect solution, right?
39:50
Just like Google when it first came out, right?
39:54
You want to use Google as a tool to replace Yellow Pages, not as
39:59
the perfect solution to do anything to give you the perfect
40:02
answer. A lot of times, as we found out,
40:05
it doesn't give you the perfect answer, but it gives you a very,
40:08
very efficient tool to access information.
40:11
Traditionally, it will take you too long to collect together,
40:16
right? So I think that's the same thing
40:17
for AI. Use that as a tool to collect
40:20
basic information as the first step.
40:23
That traditionally would take you 3 hours to do, but now it,
40:26
you know, it's down to 3 minutes.
40:27
But beyond that, especially if you are, you know, looking at
40:32
something very sensitive, very critical, very important, double
40:37
check it, right. Use as another source, you know,
40:41
use search engine to double double check it.
40:43
Use another AM model to double check it.
40:46
But I think that's, you know, it's again, it's a very, very
40:49
efficient tool for people to be able to, you know, increase
40:52
their efficiency, at least at the current stage.
40:56
But I'm sure, you know, after this, after a few years, you
40:59
know, we're going to get to the next level would be able to
41:02
provide more and more accurate, you know, solution the answers
41:06
to people. Yeah, that'll have his downside,
41:10
Bill. I mean, the contrary information
41:12
is kind of nice. You know, if I'm, like asking,
41:15
you know, GPT about my diet, it's like, well, boy, if you
41:18
want to lose a couple pounds, you should probably stop eating
41:20
all that pizza. And I'm like, boy, this thing
41:22
just can't stop hallucinating what it's talking about.
41:28
Amazing. You know, I'm really interested,
41:30
Eric, in the way that you choose companies to invest in.
41:33
Maybe you could walk us through step by step on the process you
41:37
take in doing diligence on a company you're considering
41:39
investing in? That's a good question.
41:42
So you know, as a former, I guess I could analyse myself,
41:47
you know, this is what I typically do, right?
41:49
You want to start from the basics, you know, if this is
41:52
brand new industry, brand new company to you, you know, do
41:56
cover the basics. For example, you can in this
41:59
scenario, you can use AI, you can use ChatGPT or other AI
42:02
tools to get the basic information.
42:05
What, what does the company do? You know who are its
42:08
competitors? Who are its customers?
42:11
You know, who was the financial strength of the company?
42:14
What company have have have have done historical like how was the
42:18
operating history of the company right now?
42:21
If you want to dive a little bit deeper, then I would say, you
42:25
know, diving into the financials, diving into the
42:27
quarterly earnings, you know, the comp.
42:29
Has the company met it's expectations in the last few
42:34
years? Has the company's management
42:36
being consistent? You know, has the company
42:41
essentially done what the company said it's going to do
42:44
right? I mean, it's a very important
42:46
for my in the financial services industry public, especially
42:49
public companies, you know, if they if done, they say they
42:52
would and especially if and then and their promise over deliver.
42:57
I think typically those companies are relatively, you
43:00
know, more solid companies. But I guess on Wall Street, the
43:04
interesting part is everything is about expectations, right?
43:09
Just as you think you have spent hours, right, you know, weeks of
43:14
doing fundamental research, right?
43:16
You know, checking the downstream, upstream customers,
43:19
you know, financials, right? You know, the 10 QS, 10 KS, you
43:21
know, that's all built in, right?
43:25
The, the market prices have reflected all those information
43:29
already, right? So that's kind of the
43:31
interesting but also the challenging part.
43:34
Now the opportunity is sometimes sort of take a take a quote from
43:40
Warren Buffett, right. Sometimes you do have
43:43
opportunities in the market where as mispriced for one
43:47
reason or another, maybe the entire market is down and
43:50
dragging down the company, you know, in a prolonged period of
43:55
time to the point that the price itself offers you a big cushion
44:00
in terms of potential risks, right.
44:02
Everything is risk reward. If just so happened that you
44:06
know, there are certain factors that temporary prices down the
44:10
company's shares, then I'd say you know, that might be a better
44:13
time to buy than company, you know, a hot in a red hot company
44:17
at the very, very peak. So again, what has been factored
44:21
in the expectations versus, you know, the reality, I think
44:25
that's that's a tricky part. Are there any kind of
44:29
unconventional red flags that would unqualify a company you're
44:33
considering? I think the tenure of of
44:41
management team is a good one. If you see a company that
44:45
constantly or fairly regularly changes it's management, I think
44:48
that's probably a potential red flag.
44:51
Accounting firms as a publicly listed companies, if you
44:56
typically these companies rarely change accounting firms that do
45:00
their books and audits, if you see changes there that could
45:04
potentially be a red flag. These are kind of couple of
45:09
things that kind of came to mind.
45:13
This has been so cool. I just have a couple more
45:15
questions for you. 1 is just kind of like your, your feeling
45:19
on the, the future of the market now.
45:22
It seems like the big tech companies are moving slower and
45:26
slower towards an IPO. It seems to be the trend is to
45:29
stay private longer, which absolutely drives me crazy
45:33
because I would love to be able to invest in SpaceX.
45:36
You know, I, I would love to be able to invest in open AI.
45:39
I mean, I don't know if if that's a nonprofit or for profit
45:43
or what kind of going to happen there.
45:45
But what do you see in the future?
45:47
Are there ways that like we can incentivize some of these big
45:51
private companies to to go public and and give us retail
45:55
investors an opportunity? That's a good question.
45:59
I, I think I'll, I'll, I'll answer that question in two
46:02
ways, right. One is, you know, a lot of these
46:05
companies, some or some of these companies, they choose to be, to
46:09
stay private for a good reason, right?
46:12
As a public company, you need to follow rules, regulations, you
46:19
have to for disclosure for management or 10 KS, 10 KS, all
46:24
those, you know, fun stuff, right?
46:27
Some companies, they just choose to not to, you know, go down
46:30
that route. They would rather focus their
46:32
attention on building the business, on growing the
46:35
business rather than, you know, spending the time and effort and
46:39
and capital on say, you know, meeting investors needs.
46:43
So that's I think that's one sort of consideration.
46:46
I guess on the flip side of of that question is more and more,
46:53
I think smaller investors, retail, even retail investors
46:57
can potential access non public companies, you know, through
47:01
crowdfunding options, right, Even including, you know, on the
47:11
on the crypto side of things, right, You know, there could be
47:14
some certain ways, for example, SpaceX, right, open AI, these
47:20
non public, but very large companies, you can potentially
47:24
access them in certain platform, right, Even though they are not
47:28
yet private, they are not yet public.
47:31
So these are sort of also involves with some of the, you
47:34
know, modern technology and also involves some certain newer
47:39
regulations. So these are the things kind of
47:43
for every two masters to to to look out for.
47:47
Cool. Yeah, it would be nice, but
47:51
we'll see. Amazing.
47:53
Eric, where can people connect with you online?
47:56
Absolutely. So you know, we are, you can
47:59
look, look us up on our company's website,
48:02
www.tridat.co. That's where you know, we have
48:06
all the public companies, public information and all privately.
48:10
You can, you know, look me up and connect with me on LinkedIn.
48:14
Just look me up, look my name up on LinkedIn.
48:17
There will be, you know, look forward to connecting with
48:20
people. Amazing and I will link all that
48:23
in the show notes for sure. You guys can just Scroll down
48:26
and click on that to check it out and get signed up with Trey
48:29
desk. I hope you do.
48:30
I know I'm going to, I'm, I'm going to do a little clandestine
48:33
investing because my son's 16. But you know, we've been
48:36
thinking about like, given getting him account where like
48:39
he can make the pick so we can kind of follow the market
48:42
together. I think this would be a great
48:44
opportunity for that. And I'm really excited to check
48:46
it out because from what I see, it's absolutely beautiful and
48:50
I'm just like a sucker for a great UI, you know, so I'm
48:54
really excited about it. Eric, where are you located?
48:57
Where based in New Jersey, NJ Central.
49:00
Amazing. Well, if you ever come out to
49:02
Denver, you got a friend in Denver.
49:04
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