Title:   Braden Dennis (Fiscal AI CEO): How One Frustrated Investor Democratized Wall Street's Data
Show:    Talking Billions with Bogumil Baranowski
Guest:   Braden Dennis (founder & CEO, Fiscal AI)
Date:    2026-JAN-28
URL:     https://youtu.be/2XAMyBntK2s
Length:  76:27
Note:    Auto-transcript, timestamps mm:ss (h:mm:ss past the hour). Fillers (um/uh/you know/stutters) removed;
         wording otherwise verbatim. ASR name mangles corrected: "Bogamill Veronowski"/"Pokémon Baronoski" =
         Bogumil Baranowski; "Faxet"/"fact set" = FactSet; "Blue and Pentas Capital" = Blue Infinitas Capital;
         "ZERP" = ZIRP; "Amx" = AXP; "fintexs" = fintechs; "buysider" = buy-sider; "asmtoically" =
         asymptotically; "unear" = unearth; "cars" = cards; "40:02 p.m." = 4:02 p.m.; "0 0 0" in the Visa
         example = the round $40,000,000,000. One name is left AS SPOKEN and flagged: at (19:40) the
         chapter-two company name is rendered "thinhat" — the audio is unclear and it is not transcribed
         here as a guess.
         STRUCTURE: 00:00-05:06 is a COLD-OPEN PREVIEW that repeats verbatim in the body at 21:52-27:24;
         06:12-06:56 is the host's standard compliance disclosure, not content. Anchor analysis to the body.

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(00:00) So, real quick, you shared with me one of the biggest differences between you and a lot of competitors that are trying to take business from the incumbents. You own the data. Explain it to us why it's so crucial, so important, and why it gives you a huge advantage. I think on the surface that goes overlooked a little bit unless you're in the weeds or close to us on this stuff, but historically, us included, many have not actually been able to take material market share.
(00:30)  And mostly because they are licensing that data and don't own the content. And so if you own the content like we do, like this data layer, if you pull up all US financial statements for instance, we're pulling our own API which many other companies also license from us directly, but we're pulling our own data content that we own.
(00:56)  Yes, it's data in the public domain but we've put together the data set and own all that IP. It allows us to do things that you would not be able to do if you just licensed the content. For example, we used to get so many analysts come to us and go, I love the UI. I love the UX. This is way better, faster, cheaper.
(01:16)  You don't have the ability to audit the number where it came from. My compliance team says I need this to subscribe, and I'm a buy-sider. I need to put my neck out on this. I need to be able to click through to the filing. And so before we owned our own data content, there's no technology that could solve that problem.
(01:34)  There's nothing we could code up to solve that problem. Now that we own the data layer, we have that capability. And that just fundamentally changes our business as well as the experience that the customers now have come to expect, that you would never really think about unless you're in it, on how IP works and how you license data and the competitive nature.
(01:59)  And so in this chapter 3 that we've talked about, that data layer ownership that we have is foundational to our business and what we're doing in the future. And in many cases, the fact that your data is available so much sooner than anybody else's, as far as I know, you know better than I do, just nobody — because we do it ourselves and we fixed all the problems of the way people used to do it.
(02:22) >> Nobody has it yet. It's yours. It came through you. Which leads me to a second follow-up question, and I asked you why is that feasible today? Why now? Why is it possible for you to do it? And you have the answer. >> It's possible now without giving away some IP that my CTO would kill me for telling people on a podcast.
(02:48)  Historically, if this is done manually with people, the example I can give is they say, "Okay, Joe, you're taking the income statement this company just reported. Sally's taking the cash flow. I got the balance sheet. Let's divide and conquer and push this out." And by the way, we have 200 other companies that just reported.
(03:06)  It's earnings season, right? You can see how that leads to slowness, inaccuracies, shortcuts being made, especially with some of the smaller companies. That leads to all that. Now, what if with AI, I have a reasoning layer on what we're doing when we're extracting the data and properly doing the standardizations into the different industry templates.
(03:31)  Those things were not really possible 10 years ago for example, or even just a few years ago. And so there was no business being created with the seed round pitch going, "All right, I'm going to disrupt one of these companies, I just need a billion dollars so I can hire 10,000 people," right? That's not getting funded, and that's why the data moats were so strong. That is just fundamentally changing now with technology. So I don't know how to predict the future too well.
(04:04)  But I do know for some scenarios that that area of work is just no longer going to exist. >> Those two are really powerful. The fact that you own the data, you're not licensing it, and that AI new tools became available for you to take this massive leap. I'm thinking of an old school investment firm where indeed one person was taking an income statement, one person was taking the cash flow statement, the balance sheet, and everybody was digging in and trying to put it in a spreadsheet and work their way through it. It doesn't have to be
(04:35) done this way. We'll save it for another conversation. But I think the world of investing is changing at the fastest pace that I've ever seen. Not the core principles, but how we get there and how thorough we can be about research. Those of us that know what kind of questions to ask and those of us that want to do the work.
(05:06) Welcome to Talking Billions. We talk about big ideas, big inspirations, big topics. We take on the hardest topic of all, money. How to make it, save it, keep it. But our conversations lead us to an even bigger question. What it means to live a rich life beyond money. My guests share their practices, principles, and evergreen wisdom.
(05:28)  I'm your host, Bogumil Baranowski, author, TEDx speaker, and investment advisor to wealth creators with patient capital and an infinite investment horizon. I work with families and individuals who aspire to grow wealth over a lifetime and generations through disciplined, thoughtful investments in durable quality businesses while giving money meaning.
(05:52)  Join me on this quest to unearth and share the wisdom of the ages. Let me share with you the podcast program disclosure statement. Blue Infinitas Capital LLC is a registered investment advisor and the opinions expressed by the firm's employees and podcast guests on the show are their own and do not reflect the opinions of Blue Infinitas Capital.
(06:12)  All the statements and opinions expressed are based upon information considered reliable, although it should not be relied upon as such. Any statements or opinions are subject to change without notice. The information presented is for educational purposes only and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies.
(06:32) Investments involve risk and unless otherwise stated are not guaranteed. The information expressed does not take into account your specific situation or objectives and is not intended as recommendations appropriate for any individual. Listeners are encouraged to seek advice from a qualified tax, legal, or investment adviser to determine whether any information presented may be suitable for their specific situation.
(06:56) Past performance is not indicative of future performance. None of what you're about to hear is investment advice. My guest today is Braden Dennis. He's the founder and CEO of Fiscal AI, an AI powered financial research platform that's democratizing institutional-grade data and analytics for investors worldwide.
(07:20)  Having scaled from a side project to a venture-backed company, serving over 150,000 users, and competing directly with giants like Bloomberg and FactSet. Braden, how are you? So nice to see you. >> I am great, and it is great to see you as well. >> You know very well that I love your tool. I've been using it for a while.
(07:41)  You and I connected and you guys became a sponsor of the show which I'm grateful for and I love the alignment that people have been asking me for a long time what do you use and now I can openly say that's what I use, that's what I love. I wish you guys were there 20 years ago when I started the business.
(07:56)  That's the only thing I want to say. But yeah, we'll dive right into it. When I was making notes ahead of this call, I was thinking of Ben Graham, the father of value investing. He participated in 1955 in a Senate hearing. And he was asked about how does it really work, the market itself, the prices, the values.
(08:18)  And he told about the story of a market mystery that's resolved eventually by value recognition. And what you do, what you provide, you give a tool to more very intelligent people out there to do their thinking, to do their analysis for that to happen, what Ben Graham described, for the value to be recognized. I'll leave it at that. We'll come back to it, but I just wanted to include it.
(08:37)  The more people are capable, knowledgeable, and have the right tools, I think the markets can work just a lot better. We'll come back to it. I want to start with the early days, childhood, upbringing. Take me back. What was it like? How do you think that that time shaped you? >> I grew up in a pretty middle class upbringing outside of Toronto, Ontario, Canada.
(09:02)  Pretty normal kid playing sports, playing too many video games, the classic. And I'm 30 now and I knew from a very young age that I was a math kid. I was decently athletic and enjoyed sports, but I really knew that it was mostly math that I was good at.
(09:29)  And so I carried that through to an engineering degree knowing that that would serve probably a career with the most optionality. You can do anything when you have some of those core skills. Many of them go work in finance. Some of them stay in engineering. The list goes on.
(09:48)  You have a lot of optionality. But how I got into investing in my upbringing was I have a really big family and I noticed the people in my family, extended family, that were doing the best were not the ones that made the most money. >> Mhm. >> And I noticed that at a young age and that really shaped me to really understand money, personal finance, but then also how to grow it as well too.
(10:29)  And the folks that were aggressively investing were reaping the rewards and acquiring assets. And I think that that's so important now and is a big part of my mission outside of the tool, is how do we get people my age, younger, older, understanding that you can benefit from this system much much better if you own assets.
(11:01)  And nowadays, the barrier to entry to owning assets and participating in capitalism is easier than ever. And I think it's really really important that people understand that that's really important, and you feel like the system's cheating you if you don't own assets. >> I get it.
(11:27)  >> And so it's like how do we get more people to participate in that system? Because capitalism is not a zero-sum game. It's not because I made money and because I invested that means I inherently stole it or took it from someone else. That is not how the economy works and that is not how value creation works.
(11:50)  That's not how entrepreneurship and creating jobs works. So, sorry about this long-winded answer, but that's kind of shaped how I view the world and a big driver of why I wanted to build the tool in the first place. >> I love the sound of that. I have so many thoughts. Real quick, math kid. I loved math as a kid because I felt that it's just fair.
(12:13)  If the answer is four, and I'll get to the answer, no matter my age or however I'm perceived by a teacher, anything else, doesn't matter. The answer is four. I got it right. I got an A. The other subjects, as much as I enjoyed them, I could never predict the grade. I wrote a beautiful essay that I was in love with and I thought it was the best essay I ever wrote and I got a B minus and I never knew why B minus.
(12:36)  So anyways >> the feedback loop is not nearly — yeah. It makes sense. As a young kid, the feedback loop on something that is numerically correct versus abstract opinion has completely different incentives on how you want to study or better understand the rules of the game. >> The market offers an incredible feedback loop and we'll come back to it.
(13:02)  But I wanted to mention something that you highlighted, that sense of becoming an owner. And when I picked up my first book about investing, Peter Lynch, One Up on Wall Street, there was a lot in that book. But one thing that really hit me in the face was that I can become an owner of a business, a couple of shares with very little money, and I'll be on the same boat as the people that founded this business, as the largest shareholders.
(13:28) And it just hit me. It never left me. I get this question a lot and I'm hosting those office hours on Talking Billions where people send in questions and they ask me, "What's a good time to invest? Is this a good time? Is this a bad time because of this headline or that headline?" And I tell them what you just said, if I'm hearing you correctly, investing or ownership of assets, it's a lifelong pursuit. It really pays.
(13:54)  You get the intellectual satisfaction that I do. You get financially compensated for it, even if you just do it with your own money. And then you're a part of something. You're part of building the world into a better place, serving more people with better services and goods.
(14:10)  And you play a small role in it with a handful of shares. We'll come back to it. I want to ask you about this moment of frustration. Not many people say, "I will quit my job and build a tool." But you did that. You found something that stood in the way and you thought, "Here I go. I'm going to fix it." Tell me about that.
(14:27)  What was the moment like, you took the leap and here we are? >> I hummed and hawed on the leap for what felt like quite a while, and it's all I could think about. It's all that was on my mind in the shower, walking to work, downtime, sitting on the public transit.
(14:55)  That's all I could really think about was not if, but when. And I had gotten it to a point, if we're being totally honest about history here, I had already gotten it to a point on weekends and evenings where I wasn't having to take a complete leap into the unknown. I had already built something on the side and I think that that's a great way for anyone who wants to get into entrepreneurship to do so because you learn a lot of the skills without having to take the risk, but it's a lot of time. It's a lot of things
(15:36) that a lot of people just won't do. And I think that that's actually a really key part about entrepreneurship, is you always think, "Oh, someone's going to have that idea or I'm going to be competing with all these smart people." Well, the reality is there's just not that many people willing to do the work on some of this stuff, right? And so if you are, you're already kind of filtered out.
(15:57)  You're a podcaster. I've started a podcast long ago about finance and stocks and investing, like 10ish years ago now. And it's taken many different shapes and forms. But when people say, "Oh, aren't there so many podcasts? Why do a podcast, there's already so many podcasts," I say one, it is a tiny fraction of active shows compared to active YouTube channels. Two, most podcasts — I forget what the stat is now — but back in 2019 it was 95% of podcasts did not hit episode 21.
(16:42) So that means you're in the top 5% if you just get to episode 21, right? And so that's a really — I like that stat because it helps you think about removing all the fear and just doing it. It's like the Mr. Beast philosophy. You know, Mr. Beast, "please tell me how to make the best YouTube video." He goes, "I will give you free consulting and help you make videos after you've made a hundred."
(17:07) No one comes back to them because after they've done a hundred, they've already learned everything they need to know and they don't need them anymore. And so taking the leap is obviously important, but at the same time, you can start to work on some of the problems before having to take massive risks in your own personal life.
(17:27) >> You have to keep showing up and you have to keep showing up on days when you just don't feel like it. And we're human. There will be a day we don't feel like it. But things are scheduled. >> Yesterday, I didn't feel like it. I'll tell you that. It happens, right? All the time. >> But if you show up, just the action, just the fact that you show up, for me at least the enthusiasm comes back and I can feel it.
(17:52)  And even before we started recording, I feel like a kid in a candy store being able to talk to you about Fiscal. And I've used so many tools and I'll ask you more about it, but you created something special. It didn't happen all at once and I want to set the stage for the audience and we'll talk more about the features and everything else, but three distinct eras for a product.
(18:12) >> Yeah. >> Tell me about that. I think it will get us a better idea of where you came from, where you're headed. >> There's three distinct eras in the company and the product and we're in chapter 3 right now. And I like chapter 3. It's an area we can really build the big business in, is this era.
(18:34)  The first one was, can I build Yahoo Finance on steroids? A non-ADR-riddled experience, good data, not being limited, not feeling so retail, but still so accessible. And so that was the goal, building Yahoo Finance on steroids. The second one was the ChatGPT LLM API came out and we're like, "Oh, let's hook this up into an AI product." And that went viral overnight.
(19:05) It went crazy. Everyone was like, "Oh my god, look what these guys built." We got like 60,000 people signed up in the first 48 hours. I got venture investors calling on my door saying, "We're going to take this thing to the moon." And it was really a hot time because we're not only the first application of that technology in finance but we were also one of the first applications of that technology period, in any vertical. And so that is when the company was called thinhat. That's chapter two.
(19:40) >> In chapter two we found that a lot of the core problems in this market were actually not necessarily the way to manipulate data, retrieve, synthesize summaries and all that stuff. And we saw that that was probably going to commoditize to zero as the LLMs became better and bigger and cheaper and faster.
(20:09)  And so what we started to do behind the scenes is rebuild the airplane engine as it was flying in terms of our entire data infrastructure. >> Mhm. >> And then it hit us. Oh man, these five big multi-billion dollar incumbents are the arms dealer in this industry with massive massive workforces — the Amazon 10-K comes in, all right, data factory, let's start parsing through this and put all these data points together, deliver it in the data feed, on the terminal, all this stuff — and by the way we were consumers of it
(20:51) too as well through their data feed. So we just realized that they were the arms dealers and taking most of the unit economics of the entire industry. Financial data is a $46 billion a year business. So we said, huh, can we do this better, faster, cheaper with technology on the data layer side.
(21:15)  So we basically said this thing that's working, this AI chat experience that's working and customers are in contract ready to sign up, and we cancelled all of it. We had contracts that were about to sign that were going to take the business to multi-millions of ARR from say 1 million and we said no to all of it, in a long-term vision of there's a much bigger prize of solving the data layer here. And so we've gone aggressive into that and that brings us into chapter three, which is basically
(21:52) can I build AI native FactSet better, faster, cheaper across the board. And the answer is proving out to be yes. >> So, real quick, you shared with me one of the biggest differences between you and a lot of competitors that are trying to take business from the incumbents. You own the data.
(22:17)  Explain it to us why it's so crucial, so important, and why it gives you a huge advantage. >> I think on the surface that goes overlooked a little bit unless you're in the weeds or close to us on this stuff. But historically, us included, many of the — what I'll call air quotes right now for people who are listening, I am doing air quotes — Bloomberg killer products have not actually been able to take material market share away or compete with the FactSets of the world.
(22:52)  And mostly because they are licensing that data and don't own the content. And so if you own the content like we do, like this data layer, if you pull up all US financial statements for instance, we're pulling our own API which many other companies also license from us directly, but we're pulling our own data content that we own.
(23:21)  Yes, it's data in the public domain but we've put together the data set and own all that IP. It allows us to do things that you would not be able to do if you just licensed the content. For example, we used to get so many analysts come to us and go, I love the UI. I love the UX. This is way better, faster, cheaper than FactSet.
(23:45) >> But you don't have the ability to audit the number where it came from. My compliance team says I need this to subscribe. And I need to — if I'm going to put — I'm a buy-sider. I need to put my neck out on this. I need to be able to click through to the filing. And so before we owned our own data content, there's no technology that could solve that problem.
(24:10)  There's nothing we could code up to solve that problem. Now that we own the data layer, we have that capability. And that just fundamentally changes our business as well as the experience that the customers now have come to expect, that you would never really think about unless you're in it, on how IP works and how you license data and the competitive nature and the incestuous nature of what we do here versus working with the incumbents and trying to displace them at the same time is a very difficult task. And so in this chapter three that
(24:46) we've talked about, that data layer ownership that we have is foundational to our business and what we're doing in the future. >> And in many cases, like the fact that your data is available so much sooner than anybody else's, as far as I know, you know better than I do. Does nobody — >> That's because we do it ourselves and we fixed all the problems of the way people used to do it.
(25:15)  >> Yeah, nobody has it yet. It's yours. It came through you. Which leads me to a second follow-up question. And I asked you why is that feasible today? Why now? Why is it possible for you to do it? And you have the answer. >> It's possible now without giving away some IP that my CTO would kill me for telling people on a podcast.
(25:42)  But historically, if this is done manually with people, the example I can give is you work at FactSet and they say, "Okay, Joe, you're taking the income statement this company just reported. Sally's taking the cash flow. I got the balance sheet. Let's divide and conquer and push this out." And by the way, we have 200 other companies that just reported. It's earnings season, right? You can see how that leads to slowness, inaccuracies, shortcuts being made, especially with some of the smaller companies. That leads
(26:20) to all that. Now, what if with AI I have a reasoning layer on what we're doing when we're extracting the data and properly doing the standardizations into the different industry templates, those things were not really possible 10 years ago, for example, or even just a few years ago. >> And so there was no business being created with the seed round pitch going,
(26:55)  "All right, I'm going to disrupt one of these companies. I just need a billion dollars so I can hire 10,000 people." Right? That's not getting funded, and that's why the data moats were so strong. >> Mhm. >> That is just fundamentally changing now with technology. So I don't know how to predict the future too well. But I do know for some scenarios that that area of work is just no longer going to exist.
(27:24) >> Those two are really powerful. The fact that you own the data, you're not licensing it, and that AI new tools became available for you to take this massive leap. I'm thinking of an old school investment firm where indeed one person was taking an income statement, one person was taking the cash flow statement, the balance sheet, and everybody was digging in and trying to put it in a spreadsheet and work their way through it.
(27:49) It doesn't have to be done this way. We'll save it for another conversation, but I think the world of investing is changing at the fastest pace that I've ever seen. Not the core principles, but how we get there and how thorough we can be about research. Those of us that know what kind of questions to ask and those of us that want to do the work.
(28:11)  I'll leave it at that. The way I look at it, people say the information is public, and I saw those numbers, 96 terabytes of data stored, 2.4 million SEC filings. The numbers, and I don't know if it's the whole thing or it's been processed, whatever the numbers are, they're just staggering.
(28:34)  So, a human being cannot process it. Just cannot. And when I look at your product, I'm thinking that you allow us to have access to the information, see what really matters and interpret and analyze it. Talk to me about that. You take all that data. What is it that you do differently? Because there's a lot. I've been on calls with you before.
(28:57)  You guys showed me things. I know you do things differently than anybody else that I've experienced before. You make it better, easier, and more accessible. >> Well, I'll tell you a key example that's tangible for a lot of our clients and people who are in the investment universe or even other fintechs that want to consume our content and use it on their platform.
(29:22)  Say you're the Robinhood of country X, Y and Z. So those end users as well. Typically with a data provider, you're waiting, let's say on average, two days, sometimes longer for small caps, for the data to be cleaned, standardized, consolidated, and then through all the QA processes out the door into all the places that people consume it.
(29:49)  And those three key areas people consume it are on a terminal, in an Excel add-in type product, or on a data feed API. >> Mhm. >> And we play in those areas. But why should I wait two days for public information that the market has already gotten, for this to be available? Especially if I'm doing this in my daily workflow as a professional analyst.
(30:23)  And so, for example, in that case, what takes them two days, we do in two minutes, so that when Amazon does report their numbers at the close today — they're not actually reporting today, but hypothetically — you're going to get it at, you know, 4:02 p.m., not 4:02 PM in three days from now, right? And so that's a key differentiation in terms of the actual infrastructure of this data that is, yes, in the public domain, but how you actually bake the cookie matters in terms of how it tastes.
(31:01) >> And so that's really where the differences lie, is really in that infrastructure layer. >> If anything, I imagine there will be even more information, more public disclosure, more documents coming in the future. And if anything, I noticed that there are fewer people in the industry, but also maybe privately investing, that are capable of processing the data just with what we have between our ears.
(31:31)  We need help and we need tools and we need that superpower. What you offer is so much better than anything I've seen even on a professional level 10 or 20 years ago. And the coolest thing is that you make it available not just to professionals but to everyday investors. And I want to highlight that because a lot of my listeners are people that invest quite a bit of their own money with some guidance or no guidance.
(31:54) But you would be amazed the quality of research they do for their own benefit with tools like yours. It's just mind-blowing because it makes me think again of Ben Graham and improving that value price discovery of the market. I want to ask you about AI. You have a different approach than maybe some people thought that we will have towards AI.
(32:15)  AI is helping you do some of the things you just mentioned, but you do it in a way that maybe you run less of a risk, or maybe no risk, not immediate, no immediate risk of commoditizing what you offer. Can you talk about how AI is helping you do a better job? >> I think broadly I like the Naval quote, which is paperwork isn't work.
(32:38)  Leave it for the robots. >> Yeah. >> We're in this phase right now where it is now consensus that a lot of busy work, including the paperwork type of work, is going to get automated. And so that's now consensus in the economy and people are definitely talking a lot about that happening and I believe that it's going to happen but it's also a good thing.
(33:13)  It's also a good thing but it always feels bad in the short term with any sort of major technological revolution. There's been nine since the 1800s. There's been lots of good writeups on what those are and the major step changes — internet being a big one, rail with the railroads being a big one back in the day, manufacturing being a big one. So AI is this next big one that changes how people work
(33:57) and it's largely a good thing. Even though there'll be a change in the things that people do, because all the data that we bring in that you've seen on our product, historically this has been aggregated manually. That is not the kind of work that I envision humans using our creative brains to do. And so it's coming, we all know that it's coming and we know that all this stuff is going to get — whether you agree with me or not on how humans should work,
(34:26) it's coming, and that is very much so consensus that this stuff will all be automated. And so we've really leaned into that in our industry. Can we serve investors better with technology in terms of these data pipelines? And we think yes and a lot of people think yes. But there's still the huge value of decision-making, and the investment management industry hasn't changed that much in terms of managing capital since this technology has come out, because we know that letting GPT manage your portfolios
(35:10) hasn't really been linked to good returns and active trading doesn't necessarily lead to great returns. And so that comes back to the human element of owning great businesses. We'll give you the tools to be able to analyze what those are and hold them for a long time and participate in those assets compounding.
(35:34) That's the goal, man. So, if we can help as many people think rationally about the fundamentals of a company as they hold them, or prospective investments that they want to buy, that's exactly what we want to do. We don't provide any sort of scoring. We've steered clear of all of those features that our customers have asked us for, by the way.
(35:54)  It's so important to listen to users. It's also so important to know when to ignore their recommendations, because I don't want to build a scoring system that tells you if a stock is good or bad or valued or undervalued. I'm just here to present you all the information that you want because humans are really good at synthesizing that and making good decisions.
(36:17) >> You know what I highlighted here in my notes, that the technology doesn't allow you to outsource judgment, and I'll add to it in a second. Because it's not a place, whether your platform or any other, where you go in and it tells you exactly what to buy. I hope the audience knows that's not what we're talking about.
(36:36)  As your own analyst, portfolio manager, your private investor, you know what you're looking for. And this platform allows you to get there sooner or better, in a more thorough way, however you want to describe it. I almost see it as a zoom out, zoom in. Using your platform, I look at 20 years of financials and I see there's something funny happening in the last two, three years.
(36:58)  I can zoom in, pick up a transcript, and even listen to the audio and find a fine little remark that's making the margins go somewhere else, or a comment or something. So, I can zoom out to see what I'm looking for and zoom in to get all the way to the last document I want to look at and see. They said something at a conference. When did they say it? I find a document on Fiscal and I go in deep.
(37:21)  At the end of the day, I've been doing it for 20 years, managing money for people, mostly families, long-term patient capital, and I realized that there's no shortage of great ideas. I've met a lot of very capable investors that had great ideas. There's a shortage of the ability to hold them long enough.
(37:37)  And it's not just patience, it's the conviction. And I think having the thorough research and access and KPIs, and we'll talk more about it in a second, that your platform offers, in moments of hesitation I can get the additional ounce of conviction that allows me to hold on to the shares, and I can't quantify the impact, but I know that the impact is very significant.
(38:03)  Tell me about how you get the data. We were talking about you get it sooner, you analyze it sooner, you make it cleaner sooner. You developed your own custom KPI segment analysis. Tell us more about it. We'll show what it looks like in a few minutes, but tell us more about what you developed to allow the users to interact with the data in a more thoughtful way.
(38:25) >> The company specific KPIs has become a little bit synonymous with what we do and the differentiation factor because we've been doing it since day one, even in chapter one of the story. And the reason is because when we were building, let's say, Yahoo Finance on steroids, I thought it was crazy that I would go on to a Substack article of someone writing some really thoughtful investment research there.
(38:56)  They could be just an individual at home or it's like an anonymous hedge fund analyst that is just writing on Substack. Who knows? But it's thoughtful research. >> And what I would see is I would see screenshots of the typical financials and then I would notice that they would usually in Excel manually be pulling some of these KPIs because no one had done it for them.
(39:23)  And so I noticed that and I thought it was just crazy that the core fundamentals of the company were not accurately being tracked anywhere for people to get up to speed on something. And I'll give you an example. I said to myself Uber is a ZIRP phenomenon, venture-backed subsidized, terrible unit economics business.
(39:50)  I said that to myself when it was public for about two years, and then I was looking at the KPIs on Fiscal — about, call it two years, I have been a shareholder — and the total trips were skyrocketing, total trips on the platform quarter after quarter that were happening, while take rates were being flexed.
(40:17)  So take rates doubled while the trips tripled. That's a rare kind of KPI you see from a business, to be able to double their pricing power and usage triple. >> That's not — there's something there, right? And then I'm like, "Oh, wow. This company's actually about to get really profitable." >> And so this was right before — now everyone knows it's a very profitable company.
(40:42)  But back then the consensus on the street was that Uber's never going to make a dollar. And that's not that long ago, by the way. This is just a handful of years ago. >> And so that was an example where the data is really simple for anyone to understand. You don't have to be an investment analyst to really understand those core business metrics, and it helps you hold on to the story too.
(41:11)  I think is really important too, because if I think that's a key metric and if they get disrupted by some autonomous vehicle threat, I'm going to see it there. That's where you're really going to see things get dicey, or even worse, they stop reporting or stop disclosing the number. We flag right on the platform that they've discontinued that number.
(41:36)  So if that were to happen, I would be very much so looking for the exit before other people are, right? If they are not disclosing that metric. So these are just examples of you don't have to be a genius. You don't have to be dumpster diving into balance sheets and looking at distressed special situations to just understand some of these really core business metrics.
(42:00) >> So many thoughts come to mind. First of all, any stock we mentioned here, no recommendation, do your own research. But it's an incredible case study that you just presented, and I love the fact that in the headline numbers, whether it was revenue or whatever, margins, you might not see the whole story, and especially you're not seeing what I mentioned earlier, something is changing, something is turning for better or for worse. When I would have interns, they would tell me this is good, this is bad, and I would say, well,
(42:28) look in a more dynamic way, what's getting better, what's getting worse? Because that's the interesting thing. How much worse can it get? How much better could it get? And it puts you in a whole different mindset, and the KPIs you talk about and we'll show in a minute I think open our eyes. Give us the power to see beyond the headline.
(42:47)  I want to ask you about the users. I'm a professional. I manage money for people and I've met a lot of, well, you would call them retail investors, but they're very very capable individuals. A lot of them listening to this show. Tell me, is there a difference in how people interact with your platform? I know there's so many different ways that you can do it, but how do you see it from your experience? I know you have calls with people, you ask them questions, you're really watching how they interact with it.
(43:17) >> In terms of the different cohorts and folks that use it. Since the platform is so fundamentals focused and is completely useless if you're looking to draw some technical analysis on a chart and make some sort of prediction on price movement, like a lot of those tools will provide users — I think how many retail investors have been disillusioned into thinking that a lot of that stuff that I call astrology more than investing, to be honest. We don't provide any of that. So the
(43:54) folks that are coming, whether they are a sophisticated professional investor managing billions of dollars, work on a team, by themselves, whatever it may be, and an individual who's managing their own portfolio, they're looking at the same things. They want to deeply understand the dynamics of the businesses that they are investing in or thinking about investing in.
(44:22)  And so it's pretty awesome that I can have a product that is the exact same build for people who are worlds apart in terms of what they use it for, because at the end of the day they're trying to achieve the same thing and the use case is identical. And so I say to people, we have lots of different ways to interact with our company and lots of different ways of ingesting the information, but at its core, we are a financial data and financial information business.
(44:52)  If you want to whip that into Excel, no problem. You want to use that on our terminal and so you can get nice graphs, do it. Awesome. You want to pull it into a data feed dump and get our database on tap to do whatever you want with it. Perfect. And so there's a lot of different ways that us as a business can position the company to monetize that and build something heavy and sustainable, but at the end of the day, it's the same product just with a lot of different ways you can slice and dice it.
(45:27) >> This is incredible. And I think it's okay if I share for the benefit of this audience. You and I have spoken a few times and you were kind to invite me to small group calls with power users, and I have to tell you that you are incredibly receptive in terms of feedback, what people share with you and what you do with it and how you interact with it.
(45:50)  I've used software for many years and I have to tell you that a lot of companies are not as open to changing how things are done. This is the way it works. Use it. You actually take feedback in an incredible way all the way to the smallest grain of how the software works, how something pops up on the chart.
(46:09)  And I think it's incredible because it allows you to stay in motion and improve. I want to highlight one more thing that I don't want to forget about. Time is precious and as a stock analyst, business, stock owner, however you want to define us here, you have to choose your battles. And I'll mention that when I started in this business I was the one bringing all the software to the firm where I was and people were not very open to it at times and I was even told, what can you do with this that I could do when I was your age with
(46:37) a legal pad? And I said nothing, but I can do it with a fraction of the time. The tools that you offer now, I can do with a fraction of the time what I was doing with software 20 years ago, the software that was available. Anyways, I have a lot of respect for the innovation that came since and I'm super excited about what's next.
(46:56)  I want to ask you one kind of self-reflection question before we jump in and show the platform. Once you use certain tools, the experience has an impact on how you operate as an investor. You are an investor. How do you think that using Fiscal on your own for your own benefit has changed how you interact with data, information? Maybe even changed what kind of an investor you are.
(47:21) >> I will say that it has forced me, running this business, to turn over a lot of stones that I wouldn't have normally turned over, and be open to new ideas. But what it's also done is it's also simplified my process a lot in terms of there's just a few key things that I really want to track and focus, and we've made features that people have that similar approach where they say, okay, these are the eight things I care for every company, I want to create that as a template as a
(47:58) starting point for each name. And I'm the same way because you can drown in — I love that I have the ability to pull all the data, but in that Uber example, I also want to just pull up a view and be narrowly focused on what I think matters. So, it's forced me a lot as an investor to really isolate what I think is important and what I should track and block out a lot of noise that you'll see in headlines.
(48:36)  Like for instance, I've been a long-term shareholder of Visa and Mastercard. I've owned them both for a long time. I think they're probably two of the most brilliant businesses ever created. Of course, none of this is investment advice. I've been a shareholder a long time. Just recently, there had a lot of negative news about a potential cap on interest rates.
(48:59) >> Massively hurt the banks that administer those cards and it would hurt the end consumers that can't get that information. >> And so, you see a lot of price action in Mr. Market all the time, a lot of headlines, especially in today's market. And so for me to really zoom out and go, look, I am tracking total transaction volume at the 27 to I think combined 30 trillion scale across those two companies.
(49:30)  I have a dashboard where it's payments, which stacks up total transaction volume for Visa, AXP and Mastercard. And I really track that as my dashboard on the industry, as well as total cards in force across those three companies. >> Mhm. >> And if that is playing out at those margins, I think I can pay a reasonable price, which I think they are, I think it's going to work out, right? I think that long term is going to really work out just because of how great these businesses are from a unit economics perspective. So, there's
(50:05) going to be noise, there's going to be volatility, there's going to be headlines, it's going to be all this stuff that happens. And if anything is threatening those two metrics for these three companies, then I'll pay attention, right? Something structurally that's going to change the game for those businesses.
(50:22)  But until then, I'm just holding them for, you know, decades potentially, right? So, I think to answer your question, is finding the simplicity in the data as well too is really what makes you a long-term patient investor. >> I love that. And being able to see those numbers, whatever numbers you're paying attention to for a particular business, in an easy accessible way over a long period of time. >> And we're all tracking the score every quarter, right? So it's just the right
(50:55) amount of frequency to stay on top of the story every 3 months without being spoonfed it every single day so that you have decision paralysis. >> I think it's a beautiful system. Let's see it. How about you share the screen and show us how it looks and how you interact with it. I think this audience would love to see it.
(51:16)  And for those of us listening only, let's be as descriptive as we can with what we're doing so people can go home and check it out once they safely get home. >> Absolutely. So I'll pull it up here and yeah, for those listening on audio only, I'll be as descriptive as I can. And you have this video posted on YouTube and Spotify and stuff as well, right? >> It will be everywhere.
(51:46)  A lot of listeners, but a lot of people that listen and then watch, and wherever you guys are consuming, wherever you find a moment to be with us today. >> So I will say, to ease people's minds, on the top right of the platform once you're signed in we have a help center but we also have specific feature demos for the feature that you are on specifically that'll come up, as well as at any time you can look up a full demo of every single thing inside the platform. But the key thing
(52:21) that I really want to portray today, outside of portfolio management and dashboard and tracking of positions that you own, is really looking in at a specific business. I was just talking about Visa, so let's use that. On this overview page, you're going to get all the top level ratios and metrics, descriptions of the businesses, what's happening from a news perspective on a trailing month basis, and kind of a bulls-bears overview.
(52:48)  So, this is a really nice place to just get up to speed on what's happening. The second tab is the financials tab, and this is the guts of where most time is spent on the platform, to pull up all three statements, all the ratios, all the KPIs, the adjusted metrics, any custom metrics that you want to build, as well as forward estimates, for the last 20 years.
(53:14)  I can also bring that data out quarterly. The reason people like it and the reason you see it in so many places like Twitter and Substack is because of how visual it is. If I click on a number inside of here, boom, it builds you the exact data visualization. So here's total topline revenue quarterly for Visa over time.
(53:35)  Let's overlay that with diluted EPS for example. So you can see a long-term trajectory of the company. And if I even do that annually, you can see I have estimates for it. That's why this orange line wasn't there. But now on all historicals, you get a really nice view of this data over time.
(53:57)  Now I want to pull up the segments and the KPIs because we talked about it a lot. We're going to give you each revenue segment by geography, by line item, as well as — I was talking about total transaction volume. So this is that business that rolls up on these two line items, get your total transaction volume. >> So, get a sense of the scale of some of these companies that are outside of a traditional financial statement.
(54:22) >> 16.7 trillion dollars of transaction volume just really gives you a sense of scale. And now I might say, okay, this is what the business is reporting as a core KPI. How has that related now to revenue for example? And let's toggle it on a separate axis so I can see them side by side. >> You start to see some things that really matter inside of the company.
(54:49)  Right? So I'll pause there if you have any thoughts or ideas here. >> To me there a couple of things that are very powerful. One, the minute you show up on Fiscal, you can see a lot of the numbers, the charts, the information. Kind of a quick start on a company you own, on a company you just heard about, you know nothing about.
(55:09)  It's just one place, one stop. Leave me here for a few minutes and I'll know something about the business. Right. For me, that's the first experience. Second layer that you just described and the listeners that are not watching can see it at home. You get all the financials for many, many years, 20 years you said, and then quarterly.
(55:28)  So you can look up, and on top of it I think the way our minds work, and you and I love numbers, to put those numbers into a chart and actually see what's happening, especially the relationships, correlations that you showed, they really speak volumes and you can see that something is happening, whether it's the particular KPI or the revenue or the margins. There's a story there, right? There's a dip, there's a quick recovery, there's a story, and it allows you to zoom in and see what's going on.
(55:59) >> Yeah, I just pulled up as you were saying that some of the travel names, whether it's like a cruise line — I just pulled up Southwest the airline. It's interesting visually. You pull up Airbnb, look at bookings or something. It's interesting to really — it's one thing to know, okay, there was a huge dip in 2020 and then the recovery started.
(56:21) >> Yeah. >> It's one thing to see it in a table, but then also to visualize the level it drops and then the level it quickly recovers and builds off that base. That's how I really recognize things and remember data points, is visually. >> Walk us through the tabs that are available.
(56:44)  What else can people find here? I love the part that you're just opening up the transcripts from conferences, earnings, and anything else. And you can listen to it, which by the way, I think it's a secret weapon for anybody listening. The way two words can be written and actually pronounced and said with a human voice, the voice itself tells a story.
(57:08)  But I'll let you walk us through it. I'll add in a minute what my thoughts about it. >> Yeah, this tab which we broadly call investor relations, which has a very similar look as filings, is an important place to just understand what we call all the unstructured content. That's a fancy word for saying everything that you'd find on a PDF or written, transcribed from a transcript of their earnings call, into one nice PDF viewer.
(57:38)  But on the right, we also have a panel to do some kind of generic AI one-shot summaries on, but also custom summaries. So, if I'm looking at Southwest here and I want to write a custom prompt specific to that piece of content, this is really handy because I know that traditionally a lot of investment analysts have gone, okay, I found the transcript or I found the report or I found the slide deck.
(57:59)  I'm going to download this and now bring this into some sort of LLM. And that process is fine, but how about if I just have them side by side and I can query exactly this piece of content? That's going to save you a ton of time and be specific about what we're looking at. I don't want to reach in the mind of the entire LLM.
(58:24)  I want to reach into the mind of the LLM's extraction of this specific document. And so I think that this is quite powerful. There's one thing that I forgot to mention that we just recently brought into the financials. So for those listening who are professional analysts will know what I'm talking about. So I'll go back to Visa.
(58:49)  Every single number we trace back in the cell to where it came from in the filing. And this isn't just for US companies. We have it all for Canada, UK, and Europe too. >> And so this is really powerful where you're going to be able to see where the number came from. There's no such thing as a perfect data set in the world, but we're asymptotically have kind of the most institutional one now.
(59:19)  And trust is built over me showing you instead of me telling you. And so linking each filing and number from exactly where it came from is a huge step in terms of us building a professional workflow here as well too. >> This is so important and I'm thinking of working with a junior analyst and the junior analyst brings you the number and part of you says, this looks off.
(59:49)  Do you mind showing me the filing? How is it actually? And here you can click without a trip to the other office and finding the filing. You can just click through it and see something funny is happening. It's like the debt doubled or whatever it is, right? And you can look up the filing and see, ah, that's what happened.
(1:00:07)  And then you can interpret. But the key word here is trust, right? We want to trust the numbers. And the more tools we use, the more we might feel removed from the original source. You take that distance away by us being able to click through and see exactly what the page looks like in the filing.
(1:00:27)  Do your own reading, do your own research, and then decide, this number actually makes sense. I know why it doubled. And here you go. >> Yeah. And here's an example on Visa. So the September 25 quarter, the number, it almost looks fake. It is 40 billion. Not 40 billion 362. It is 40,000,000,000.
(1:00:54)  And you look at that number and it just looks fishy, right? The human brain's like, "Ah, this must be rounded or something." No. And you get the actual 10-Q and here it is, 40 billion as net revenue, 40,000,000,000. So that's that kind of building trust element to what we're doing, right? Because you see this number and you're like something looks funny with this, right? >> It never happened.
(1:01:16) >> And so that's another — yeah, it's super rare. It's just like a complete coincidence. >> So we have lots in here that you can work through, but I think this is a really good start of what we're about, how we get the data, how it can be visualized, and what we're working towards in the future.
(1:01:40)  I mean, I don't know how long you've been using the platform, but I'm sure you probably notice every single week that this version in the top left changes. So, we post in the top left. You can actually click on this button and see everything that we've pushed through. So, we just pushed in last week all of these new changes, right? >> Real quick before we move on to the next part, there are many different tabs for people to go through, right? You have research estimates, news, ownership, industry, dividends. You can
(1:02:10) find a lot more. And then you have the filings and the investor relations part. People can screen for stocks. People can narrow down their universe that they want to look at. So couple of words about that. How powerful that is that you have numbers that you trust and that you can audit on your own.
(1:02:30)  And based on those numbers, you can narrow down your universe to a list that you can manage, that you can actually look at if that's how you operate. >> I love stock screeners. I always have, even well before I built this. Not because, oh, here's a list of things that I should invest in, but here's a list of things that I know I might be interested in.
(1:02:53)  And it's really helpful to filter not what's in the screen, but filter out what's maybe not a good use of my time. For example, just my investing style and the way that I like to own businesses and be in them for a long time is somewhere in that growth at a reasonable price type area. >> Yeah. >> So, if the company's not — has a steady history of growing that topline revenue, I'm very very unlikely, unless this is some special situation or spinout situation, going to be a long-term shareholder of the company.
(1:03:34) And so, I can just filter all that out, right? Or I don't really like — personally I don't like junior mining. I think it's just so boom bust, hard to make money. It kind of feels more like a lottery ticket unless you're in the industry. I want to exclude those industries.
(1:03:53)  So, I can do that with this button. So, I can go in here and exclude metals and mining and now rerun the screener. So, it's such a powerful tool to not just, oh, here's a bunch of stuff that could be in the strike zone, but also just remove everything that you know is not going to fit your style and criteria. >> Mhm.
(1:04:14) It's super helpful. And the more you interact with the numbers, my screening has improved because of this level of depth and thorough interaction with the numbers. So, it makes the screening experience so much better than very simple screens that maybe some of us grew up with.
(1:04:35)  And fine-tune it to the point where you have a really promising list of companies to look at and a fresh list every time, and spend more time on fewer names that actually make sense. Highly recommend for this audience to check out the screening. Tell me about the charting part, the charts. There are many different ways that we can interact even outside of the original view with numbers.
(1:04:59)  What do we have to know? How to make the best use out of that section? >> I have a brilliant one I've saved up. Oh, I just pressed back. I have one that I've saved up here that I just called the travel aggregators that I pulled up. It was already up on my screen. So, let's use this as an example.
(1:05:19)  I have lots that are like trading platforms. I have that payments one that I was telling you about before, which just tracks transaction volumes on Visa, Mastercard, American Express. So, this chart, this feature is where I'm going to now be able to cross compare against a bunch of different companies. I'm no longer just in that view of Visa view or the Southwest view.
(1:05:37)  This is one where I like to keep track of gross bookings across Expedia, Booking Holdings, and Airbnb and see which ones have grown the fastest. Airbnb has been a company that's starting to look pretty interesting for me. So, I've been doing some more research, and this is one thing that I've really liked looking at, is going, okay, our gross bookings across the aggregators, which one's growing the fastest, off which base, off which take rate? And they disclose all of these numbers for investors. They disclose all of those
(1:06:07) metrics across all three of these main travel aggregators. And this gives me an idea of like, oh, I think Airbnb is growing the fastest, but what I actually realized is Booking's growing the fastest off the COVID lows. That is not a thesis that I would have come in with. And if you were to ask 10 people off the street, which one do you think is growing faster, the Booking.
(1:06:32) com conglomerate or Airbnb? I have a feeling most people would say Airbnb. >> Yeah. >> The data tells you otherwise. And so this is a really nice place to understand narratives and real factual numerical data. >> This is so important and so powerful because as a practitioner I find that I might own one company or maybe two companies from a particular industry and time is precious.
(1:07:02)  I can only that often look at the peers, what the peers are saying and doing. So at some point I think it happens to all of us that we rely on a take on what's going on in the industry from the one representative of the industry we have in the portfolio. But this tool very quickly allows you to cross-check with what one company is telling you and how everybody else is doing.
(1:07:23)  If one company is telling you, we're struggling to grow, we can't push our pricing, and you look at the other three peers, they clearly are growing volumes and their pricing went up and margins are improving, maybe the company you're paying attention to is facing some other challenges that the other ones are not.
(1:07:40)  Anyways, it allows you to zoom out and see a bigger context of how everybody else is doing. And it's a great case study that you pointed out, the recovery from COVID as a historical case study of what happened and our perception and reality. A great check before we move on. I'm curious if you have any other feature you want to show or explain to this audience, or maybe tease something that you're working on that will add a lot of value but it's not ready, if you can, as much you can share, or maybe a
(1:08:16) general idea of what else you're working on that will make this experience even better than it is today. >> The last thing I'd mention is our dashboard which I skipped over just because it's very specific to the user. This is where you're going to come in, you're going to build the dashboard of certain watch lists.
(1:08:35)  You can even add ownership breakdown and get the portfolio. It's really nice because you can put in all your ownership of all your positions and get an aggregated view over time of what that would look like if it was a specific business, for example, like here's what my portfolio weighted would look like for one company.
(1:08:58)  And you can see what all the businesses are. And then from a watch list perspective, you're going to be able to build the columns that you want to track. Okay. So I'm looking at forward, or EV to EBIT. I can sort by that one. And then I can also get a notifications panel on. Okay.
(1:09:17)  Taiwan Semiconductor just posted this event. Okay. Let's look at what that is. Oh, it's their Q4. Okay. Awesome. Interesting. Let's read about this and let's figure out what the company just reported. And so this is a home base for a very personalized investing experience, is the dashboard. In terms of what's coming —
(1:09:42) >> Mhm. >> a lot of the work being done on what's coming relates back to that personalization layer that we just talked about, as well as more data, more data that we can start grabbing from other geographies. There's this non-symmetrical experience if you're looking at a US company versus some micro cap in Taiwan.
(1:10:09) And so really a lot of data engineering in the pipeline to make that experience uniform across all of these different companies. It's a massive universe of businesses around the world that we want to look at and we don't want to just be focusing only on the US, Canada, UK for example.
(1:10:28)  We want to have a really robust experience for every market as well as every person that might want to use the platform no matter where they're located. >> Very exciting. I'm very inspired to see how you take feedback and how you want it to be a better tool, how you are using the tool yourself, so you're fully immersed in the experience, and I can only tell that it's going to get better and better and hopefully we can all become better and smarter investors as we're up against, I think, a shortage of active thinking participants in the
(1:11:03) market, and it's a whole separate topic but I'll leave it at that. Before we wrap it up, I have one last big question for you. How do you think about success, whether for your business, you personally? I'm just very intrigued how you think about it. >> There's been this moving goalpost of what I want out of the business.
(1:11:29)  And I think it's helpful to have some gratitude and look, okay, now I have 50 employees now and see how far we've come, and all this stuff is certainly — I try to remind myself of those moments that I'm kind of living the dream of when I was thinking about making the leap we talked about earlier today.
(1:11:50)  But I'm also just — I don't have that personality trait. And I'm very rarely looking out the rearview mirror and always forward. And so I have to battle my own psychology when it comes to the moving goalpost of success. I wish I was better at this honestly, but it's just not who I am. And I think recognizing that is probably better than trying to fight it.
(1:12:16) In terms of success, it's a constant battle of us being really content with where the product is and people just recognizing it and voting with their wallets, too. I've talked a lot about how we're doing all this stuff to empower the investor and that's true, but I also want to build a really sustainable heavy business
(1:12:45)  that is the next really big powerful business inside of financial data. And when our customers vote with their wallets on how things are going then that brings us obviously a lot of monetary success so we can keep building what we're building, but also I want to make sure my shareholders are really taken care of, all my employees — every single full-time employee has some equity in the business too.
(1:13:14)  And so I think what success really looks like for me is that all of those people get really good outcomes and not just me. Whatever that outcome may be. >> I love the sound of that. And we went a full loop. We started with business ownership and your employees being owners in a business that's serving others to become better business owners.
(1:13:34) I think >> it doesn't get better aligned than that. >> But I love the sound of it. And I feel like in the world that's very short-term focused, there's a lot of noise, a lot of distraction, and people are asking me, is this a good time to invest? And seeing investing as something that you describe as business ownership, asset ownership over a lifetime.
(1:13:54) And yes, it will bring financial benefits if done right, but it's also intellectually stimulating to discover the things we even talked about today. How do these businesses work? How do they succeed? And you give us access to public information but in a way where I can interact with numbers to the point that was very hard to do if at all possible, and not as frequently and not for as many companies, at least at a level that I've been exposed to.
(1:14:20)  So anyways, thank you so much for today. What a wonderful conversation. I highly recommend for this audience — and there will be notes and links in the notes to this episode for people to explore. Try it, see it. The trial is free. You can see if you like it, if it belongs in your process, but I think a lot of people will be really blown away and surprised how much is available and possible even for the smallest investor all the way to the largest one.
(1:14:45) >> And we just recently made the free plan — so throw away the trials, say the trial ends and you're still on a free plan — we now give everyone 10 years of data. >> Incredible. >> It used to be just four or five. I forget what it was before, but we just made that to 10 because we figure we just want it to be well known that if you're using a free platform, there is absolutely no reason you shouldn't be using our free platform.
(1:15:14)  Of all the ones that exist there, no one is offering 10 years of historicals. There is not one of them doing it. And so that's — we're proud of that as well, too. >> I think Ben Graham would have been really impressed with what's available to us these days compared to what was available when he was playing this game.
(1:15:36) Thank you so much for today, Braden. What a pleasure and I really really appreciate this conversation and everything you're doing for all of us. So, thank you. >> Thank you for having me. I hope people enjoyed the conversation. >> You were listening to Talking Billions. We talk about big ideas, big inspirations, big topics.
(1:15:56)  We take on the hardest subject of all, money. But our conversations lead us to an even bigger question, what it means to live a rich life beyond money. If you enjoyed the show, please take a moment and follow, subscribe, rate, and share with friends and family. We rely on word of mouth to promote the show.
(1:16:15)  One click for you means the world to us. Thank you. Until next time, your host, Bogumil Baranowski.