Stock Card - Investment Research, Made Easy

My name is Hoda. I'm co-founder and CEO of Stock Card, and today I'm here to talk to you about how we are building the investment platform of the future. There we are. So this is, this is all of us when we hear investing and wealth management. That's how most of us feel. It's pretty overwhelming. It's pretty intimidating. But despite that, almost all high net worth individuals invest their money and grow their wealth. And that's because they are able to afford hiring very expensive wealth managers who support them and guide them through the investment process. But these wealth managers are deprioritizing the rest of us with lower net worths because we just have a smaller amount of assets that they can manage. That means a significant portion of global investable assets is left untapped by the investment management industry. And we think that's not right. We believe everybody, regardless of their net worth or their background or their education, should be able to invest and generate wealth for themselves. In order for that to happen, 3 things need to come into place. One is we need to make sure the investment process is not confusing and people have access to understandable data and insights. Second is we need to make sure the human who is making investment decision is not making those decisions based on emotions. And third, we need to remove ambiguity and unclarity out of the investment process. And that's what we actually call the investment platform of future. It's the perfect trifecta of intuitive research, behavioral guidance, and automation of the transactional part of the investment. So behind this platform that we're building sits a set of reliable APIs and natural language processing and machine learning to help build this, the whole platform. So we've been at this, this work for a couple of months and we've built the data platform side of the solution. And the beauty of the solution is once we build the trifecta for one investment class, asset, we can actually significantly scale our product by applying the same trifactor to all other investable assets that are out there. So let me show you a little bit so that you can feel what the product looks like. So far we've built the investment, intuitive investment platform side of it, the data platform side of it, and the goal there being to create an intuitive research process. So we went to other walks of life and looked for intuitive frameworks that we can apply back to investment research. So we're creating almost like an app store for all investment opportunities that people can engage with. And then if people want to get to know one investment opportunity, we use other intuitive solutions or concepts such as, you know, traffic light to just convey the quality of that investment opportunity instead of using very complicated rating system. Then although on the backend hundreds of different structured and unstructured data points are being collected and analyzed, I don't know why I lost— did I lose my presentation here? You did. Yeah, I don't know what happened.

Yeah, it looks like it just disappeared.

Yeah, okay, so I'll bring it back on. So yeah, we were— okay, backend. So yeah, hundreds of different structured and unstructured data points are being collected together and analyzed. Users only see very easy-to-understand insights in everyday language. And then really, this is the last part of what is already live, is that people are getting started to almost like a shopping cart system. The investment opportunities that they realize, they put it in their personalized portfolio. And at some point when we automate the transactional part, they can just buy the investments that they picked in one, in one shot. So as I said, we've been at it for a couple of months and we've, so far we have hundreds of users on the platform and we were able to delight them. We've received people saying that they put Stock Card as a must-have part of their investment research. Some people love the platform so much that they can't wait to pay us. They're asking for, where's the paid version? We don't have a paid version, but they're like, I can't see the paid version. So we, that's why we're very confident that we're actually gonna be able to compete in the market. I'm going to pause here and just talk about our team and then return it back to the question. Myself and my co-founder, we built the platform for ourselves and I keep losing my presentation.

That's all right. Keep going. Keep going.

Yeah. So basically, yeah, both of us, we are product managers. We've built in several different companies. We've built very successful digital consumer products, but we built the platform first for ourselves. We wanted to be able to be a better investor. And then we realized we showed it to our friends and we realized we have a them in our hands. And that's how the company came about. And we're just getting started to raise our, our angel round, about $800K. And I really love to invite everybody to go to stockcard.io and feel the power of the platform, the data side of the platform, and be in the know for the future releases that are coming on. Thanks.

Great. All right. Thank you. So Christine, if you'd like to get it started, I have questions as well, but I'll leave it to you.

Yeah, absolutely. And especially I think we'll get more questions because unlike space exploration, everyone's got an opinion about personal finance. So, so I think so. My first question to you is, given the target that you're going after, are you looking to take folks away that currently use a wealth manager or are you going for greenfield? Are you looking for people that are maybe growing out of using using a Mint.com or, you know, something from Schwab or one of the automated, uh, other automated advisors, and you're a better automated advisor, like, how are you gonna do market entry?

Yeah, so the product originally is targeted for people who are managing their own, their own wealth. That doesn't, that doesn't mean that we cannot serve people who are using other platforms. Okay, so even people who are using, um, automated funds, um, on average, after 4.5 years, they, they get out of the fund and they make something wonky. They do losing one key with their investments because they don't have the, the type of support that they need to in order to make sure that they're good over the long term. So even people who are using robo-advisors or like Vanguard and those things, they still make decisions that they're not sure about, and they, they make a lot of mistakes. And our goal is to be able to support even those that, those who are automated, using automated systems, to be able to have complete support.

Okay, and yeah, I mean, I had a related question there too. So if you're going after sort of— it seems like greenfield is really where the biggest opportunity is, right? What's, what's been kind of the main source of user acquisition so far that you've seen, you know, get some traction there?

Yeah, so we believe that every stage of our development needs its own perfect channel. It's almost like product-channel-market fit. So in the early stage we're using influencer marketing because investing by nature is a trust-based decision-making, so you need to be able to get this trust established. We've tested several ways of using mid-tier influencers, people who have blogs, people who are admins of Facebook groups, people who have podcasts about investing that a lot of people log into, and they've been able to basically just test the product, and then almost like a review, like when you send your Apple iPhone to a reviewer, they basically just review, star card, and then that is the best, biggest source of acquisition. That's for our early stage, and obviously as we grow, we find other ways of acquiring users when we get bigger and bigger.

Okay, so Abhid asks, and I saw, I think we saw the slide very briefly, but Abhid asked, what's the revenue model? I'm assuming you're taking a percentage off of, or some type of fee.

Yeah, it's a premium subscription model. So once you come to the platform, the basic data platform is free. And then when you want to use the more advanced features, so let's say behavioral advisor side of the platform, or if you want to automate the portfolio that you create and you want to automate that investment, investing in it on a regular basis, you have to pay subscription.

Okay. Anu asks, as a customer, is there any minimum or maximum in terms of investable dollars that are needed in the platform?

No. That's actually because we are targeting everybody who is starting and people who are managing their money. We see that actually the platform's minimum required investment is a barrier for a lot of people to get started, and we're moving away from that model because we are not managing your money. You are. As an investor, you are in charge. The whole purpose of the platform is to enable everybody to make good decisions, just as an advisor would do for you. So we're putting investors back in charge of the decisions. Therefore, you decide how much you want to invest.

Okay. Christine, looks like you're back.

Yes, I had to escape because bad things were happening.

Um, so yeah, we were just talking about, um, some of the user acquisition strategy. It looks like influencer marketing has been, um, really useful, uh, for Hoda.

Um, and, and so sort of to that point, because I think that, you know, like, this is one of those categories where you're going to have some instant pent-up demand, right? You're going to go out and whether it's people you know or people that are just a perfect fit for what you've built so far, um, you get— you can get more quickly. So, you know, there's that first time users, there's that 1,000 users, there's 100,000 users, you know, where do you see you are as far as, you know, how you got the folks you have now? And I apologize, this was already covered while I was restarting Chrome. Uh, you know, how, how are you going to make that progression and how are you really standing out competitively? Because you might be better, but until people come in, you, they don't know that you're better. And there are certainly products out there that have a lot more marketing dollars being spent.

Yeah, so the way we're building the platform is obviously, as you saw, roadmaps, milestones, and every milestone, it's the way we designed it, we designed it in a way that we could make it more appealing to a bigger, bigger set of audience. We started from the data platform. The data platform is obviously appealing for people who are actually interested in getting into the nitty-gritty of making their own investment decisions. So that's perfect. Like that, we build a product around them. And then as we introduce the rest of the platform, as we introduce automation of your portfolio, there will be more people, this appeals to a bigger audience because you could come one time and create your portfolio and then just automate it and let it invest for the selection that you made on a regular basis. So it suddenly becomes appealing to people who are more about the passive investing. And then as we bring AI advisory into it, which is behavioral advisory we're talking about, it's now it appeals to people who actually are not very familiar about making good investment decisions. So we help them throughout the process of making decisions. So, and then, you know, the last part of the platform, but right now we're focusing on the stock market, but once we build that system, we can scale it to other assets. Let's say we can scale it to, funds and we can scale it even like to cryptocurrencies, we can scale it to any other investable assets, then we basically just constantly increasing this target audience, this addressable market, by introducing this, this product into the platform.

And when, and I know we're running short on time, sorry, I wanna get this question in. When will you have enough of a dataset built out? You know, what critical mass do you require for a dataset for your AI to learn what it needs to learn? And how differentiated is that dataset going to be from ones that other people might be working on?

Yeah, so the AI, basically the AI is not very dominant AI as everybody does it. It has some specific set of rules that is already known, right? Meaning that, for example, we already know when the market sentiment is negative, possibility of people just cashing out of their portfolios, out of their investment is really high. We can immediately even start bringing those things into the platform saying, okay, market sentiment is high, very negative today, you are making very bad decisions, and nudge the user that this is not the right time to cash out, you know, and just kind of help them stay on track. So that part of the AI is difficult at all because these are predefined, very clear set of places that people make bad investment decisions that we could already build that. And so that will actually help us collect enough amount of data about how actually they react to these kind of nudges, and then we will personalize, and then it becomes really smart AI because it knows you, it realizes where you are more prone to make those investments, make mistakes. So it is really not that much difficult because from early on we could build this foundation of, from that preset set of things that we know, to be able to get to know you faster. That's how different from people who are starting from like from scratch and have no data. Early on, even from now, we can start getting to know the user in terms of how they react to market, which is what we're trying to help them out.

All right, thank you, Hoda.