 So hi, everyone. My name is Didier Lobsch. I'm not used to be on stage. This is the first time I'm doing this. So if I speak a bit fast, it's not because I have a train to catch, it's because I'm a bit nervous. Today I'm going to talk with you about why proprietary investment research platforms won't last. As I said, my name is Didier. I founded OpenBB, and I'm the CEO of the company. OpenBB actually started from an open source project called GameStone Terminal. Basically, once I started getting into investment research, I felt like there weren't adequate tools for me out there. So being an engineer, I started developing that in Python. And I basically started working on a terminal in Python on my spare time. And two months later, I released the platform, and it went viral on Reddit and on Acre News. And we got published on Vice Magazine. And a couple of months later, we founded OpenBB. We raised 8.5 millions on a seed round. And here I am today. So what is the problem of proprietary investment research platforms? I can sum it up in basically three bullet points. So the first one is not customizable. This means that for companies, you cannot really add your own features to it. It's limited to what the third party wants the platform to have because you are limited on that sense. And by these proprietary investment research platforms, what I mean is the definitive icons, fact-checked, capital, IQ, Bloomberg's of the world. Again, yeah, it's not customizable. It also doesn't provide you, it doesn't allow you to add your own branding on top of it. So if you're a Goldman Sachs, a GP Morgan, you like to have your branding. You like to have your own tools. And when you pay for these proprietary investment research platforms, you are basically bounded for what they provide. And then there's no distinction between you and your competition. Everyone has the same. And you end up having to build, complement our solutions on top of that with your branding. And basically you need to build those because the proprietary platform that you are using doesn't allow you to add that. And finally, it only comes bundled. And this basically means there's no dynamic plan. Usually you pay for the full thing, regardless of whether you use the platform for only five minutes or six hours, or if you use only two features or all the features that the platform offers. I want to show two quick graphs to show what I'm talking about. So here's company A and company B. And they both use the same proprietary terminal, which is exactly the same. There's no branding. You can't add anything on top. It's just what the proprietary terminal company gives you. And then you have your own complementary software, A for company A and complementary software, B for company B, which basically is where you can add your own branding and you can add the features that you would have liked to add on top of proprietary terminal that you are paying for, but you can't because it's closed source. And here comes the talk about these proprietary products being bundled. And as I say, it doesn't matter how many features you use or how much time you spent on the platform, the pricing is the same, which is really unfortunate like in 2022 that you don't just pay for what you are using. Okay, so let's go into the solution. So someone could say, okay, so are you suggesting that we build a platform from scratch? And no, I'm not suggesting that. And the reason is because that's very, very expensive. And at the end of the day, you will be reinventing the wheel because you're gonna be doing what everyone has done and then there's a lot of money that you will have to use for engineers. They're gonna have to relearn the tech stock. It's just not a viable option. So what is the solution here? We are in open source in finance forum. So I'm guessing that all of you have heard about open source. There's Andres of successful companies from Linux, GitLab, Python, successful products like Elastic as well. But one thing that we don't really see a lot is finance commercial products. And why is that, right? Like we all know the benefits of open source. So why can't we do that for investment research platforms? And what I'm really suggesting is for companies to start building their investment research platforms on top of well-known and maintained open source terminal like architectures and open source excels at infrastructure. It's transparent and secure. It's fully customizable. You create integrated communities, like attract people from every background, the best ideas, developers from all over the world. It's just better overall to build as infrastructure. There's also a big validation by having so many people rely on that platform. And not just the validation side, but people will get familiar with the platform. So for instance, in academia, people could start building that platform and then when they go to find a job in the industry, they already know this, right? And so when you talk about these, you know, like, I'm sharing, I mean, I'm biased because my company is OpenBB, right? But OpenBB Terminal currently is the only solution that you have in open source that allows you to do these. But the message here is like any sort of, for me, I believe that any sort of open source investment research platform could allow your company to build like a better product overall. And OpenBB Terminal is just an example of what you can use. And the image below actually shows like our contributors. We are now at last check that we are like 98. And this is like a big pool of people, right? We're not talking about just like developers, we're talking about the scientists, mathematicians, finance experts, even people with backgrounds just like physics and biology, they are interested in, you know, retail investors that are interested in developing better tools for doing investment research. And the idea is really to have something that is standardized so that everyone understands the standards about it, but is customizable. So you can really take the core of the platform and tweak the endings to make it your own. You can add your own scheme, you can add your own hyperparameters to the model, you can add your own capabilities. If you don't like something, you can scrap it. If you want to add more data, you can add more data. The possibilities are limitless when we come to this stage. So now I want to talk a bit about OpenBB. So, you know, all these all came together. As I mentioned at the beginning, OpenBB, we raised 8.5 million as a seed round in September last year, following the open source project, the GameStone Terminal, which is the one that went viral on the news. Today we have 12,700 stars, a bit more I checked this morning. And our mission is to make investment research effective, powerful and accessible to everyone. On a shorter version, what we're trying to do is make investment research for everyone and anywhere. I want to share with you a bit of what the terminal looks like today. As you can see here is pretty much a beta stage yet. We're talking about a common line interface. Everything is Python end to end. And the reason for it is all of you that I assume that you're in the finance industry, you are seeing the rise of Python in this industry. Probably 10 years, 15 years ago, Python wasn't as much used, it was mostly Excel, but now things are changing. You see Python being much, much more heavily used because you can create a level of automation that Excel didn't allow you before or at least as easily. And that is the choice we made very early on to start building the terminal Python end to end so that we could have everyone that wanted to participate in this tooling to contribute. Because it's Python. It's very easy to learn. People from any type of background, any type of age can very easily add to the platform. And this is where we are right now. So basically what's happening is people are really building what's gonna be like our infrastructure. But the next step for us is gonna be built like a strong user interface so that companies can build off of our project and build their own customized solution at their own skins and their own data sources. And I'm gonna show the tools that we already have on the terminal in a couple of minutes. So just to give you a bit of an idea about like, okay, what is these 12,700 stars number means? Which I think is quite impressive when we decompose it this way. So there are currently 321 millions repositories on GitHub. GitHub is the place where there are projects open source. Out of those 321 million, there's only 1738, 1,738 that have more than 12,650 stars, right? And that corresponds to 0.005%, right? And if we filter further for Python language so that is very easy for people to add on MIT license which is the most permissive license and everyone can use it for any type of anything that they want to do with it. And then the final stack, there's only three. And that corresponds to 0.0000009%. And I swear that I multiplied by 100 to get the percentage. And out of those three, one of them is Plotly which is actually a charting library. So it's not even anything really related with investment research. On the right side, what you can see is when we search for the investment research stack on GitHub platform, we can see that in terms of the number of stars, we are the top one. And the second one is Microsoft product from Microsoft called Qlib, and we are over 3.5,000 stars above them. So the next question you may ask is, okay, what are those people that are staring the project, right? Because when people start the project on GitHub, it's mostly like developers, it's communities, it's builders really liking a project. So you may be wondering, okay, are these like retail investors, people that cannot afford like better proprietary investment research platforms? And the question is, yes, in a way, but not only, right? We're not talking about like any sort of retail investors. If we look into the top stargazers in terms of companies, we are looking into like people from Google, Microsoft, Facebook, Amazon, Uber and Airbnb, right? These are the best companies in the world and they are looking into what we are doing. They are interested to see where the terminal is going. At the end of the day, the position that we are right now, we are really the market leader in this segment because why would you start building an investment research platform like Python based with all that we offer when we already have an open BB terminal, which is like well-mounted, there's like multiple pull requests being merged like every day, the platform moves really, really fast. And the project has almost 100 contributors already. And yeah, this was released, made open source one year and three, four months ago, which is like a very, very fast rate of development. Okay, so now let's get to the more interesting area. So I talked a bit about why the property investment research terminal won't last in my opinion. I talked a bit about the open source and I talked a bit about open BB and about the open BB terminal at the very high level, okay, but what is the open BB terminal really capable of doing today? And let's dig a bit into that. And I want to start by my favorite one and here I'm gonna tell you a bit what was my pain point. So I started learning about investment probably like three years ago and I learned a lot for doing investment research from Reddit and I was learning a lot from those posts on Reddit that are like do diligence on Tesla or something similar. And those posts, what I could see as an engineer is that those posts had a lot of data that came from, first of all, they came from different data sources. So I saw that you could see that the charts came from different data sources. And then I really put myself on the perspective of the person writing those posts, right? Those posts were like really long. It was like there's no way someone could write that in under like two, three hours. And they wrote that and the week after that post would like not be valid anymore because things move really fast in the financial market. And then the other perspective is like if the person wants to look at the different asset they have to redo the entire post. There's no automation. You could see that everything was manual. But at the end of the day the only thing that should be really manual is the opinion of the person when they look into all that data, right? And for me like coming as an engineer with like limited time because I had a full-time job I really wanted to optimize the way I was doing investment research. I didn't want to spend a lot of time but I wanted to know that the time I spent was well spent and at the end of the day I would go somewhere with that time whether it was investing on a stock or a crypto or whatever. And no tool was available for me to create an automation to do that. You know, not even like the most expensive ones. They don't really allow you to do that. So basically one thing that OpenBee Terminal can do today is it can automate your investment research reports. So basically we are leveraging this library called PaperMeal which was invented by Netflix. And basically it allows us to create a template of a report that we are interested to look. And this template report I'm really saying that we basically just select the type of data that we want to see. So in here you can see those little tabs. So it says like summary, then we have overview, analyst opinions, fundamental analysis, dark pool and shorts, technical analysis, insider trading, behavioral analysis, even prediction techniques. But you can have anything and this is like fully customizable. So if you don't care about technical analysis you can just scrap it. If you care about a more macro level data of economy you can add it there. Like it's fully customizable. And this is really the idea is that I wake up in the morning and I say, okay, run this report for Apple. I go grab a coffee. I come back one minute after and I have a full report after me. And then this is what, that was the first iteration. And then I was like, okay, this is very good because it saves me a lot of time. I get all these reports in front of me. But I can still do better. And for me, the way to do better was by implementing my own rules in terms of what I would like to see in an asset before like investing. So basically what we implemented is this KPI section or we can call it rules. And these KPI section basically compares like two conditions or three conditions. And if they are satisfied, it appears green. If they are not satisfied, it appears red. And basically now instead of just running a report for instance for Apple, I can wake up in the morning, run it for Apple, Tesla, New, whatever ticker. And then when I come back, I just need to look at the rules. And if I look that, you know, it's mostly green. It means that, okay, it passes my set of criteria so I can dig further and spend time further looking at the data. But if I see that it is too much red, it's like, okay, this doesn't pass my basic like criteria. And those criteria are set by each person individually. So here as an example, we have like the sentiment data coming from FinBrain which is like one of our data providers. We have like a regression on the last 30 days of the stock whether it's going up or going down. I have RSI level which is like a technical analysis indicator but it really shows like what you can do in terms of like automation in the financial world. The next feature that we have is also I think a super interesting one. So as a retail investor, I felt like there are good brokers out there but one thing that most of them that I've tried like is a really good understanding of what you're doing in terms of performance of your portfolio and none of them really offer anything nice. Most of them just tell you, you know what is the value of your account right now but that doesn't tell me much as an investor, you know not coming from the finance background. I want to try to understand all a finance like expert would think about the problem. I want to understand all are my returns coming from are there from my crypto assets? Are them from my stocks assets? If it's from the stocks asset which is the sector and the industry? And I want to go further. I want to understand how I can optimize those weights to reduce my risk or reduce the exposure that I have to a certain industry or sector. And that's one of the things that our terminal is capable of doing today. The brokers integration is an interesting one because currently what I was telling you this is something that we have available on the terminal and the problem is you need to add it on an Excel spreadsheet but that was really like just the first stage, right? And now what we're working on is in having brokers integration. So rather than you having to manually insert, okay, I bought Bitcoin at this price on this day and I paid this fee and then I bought Apple at this price, blah, blah, blah. You can just connect it with your broker like whether it's crack and Binance, whatever and they can connect it with your stock broker and pull the data directly. So we want to automate like the way users understand their portfolios like much faster in a much faster way. Again, fully customizable. You can add like what is relevant to you. You can like, this is the power open source really. So when we talk about this portfolio optimization, all the mathematics behind it, they are the same regardless of company A has to implement it from scratch B and C, they do the same. What changes is the constraints, the risks that they want the model to be subject to. But on the open source terminal, we can leverage that and allow you to tune the EPAR parameters as you want. One of the other features that we have on the terminal and this one is actually, we have someone on our team that joined us from a big fund and the reason he joined us, this comment really attracted his attention because I remember him telling me back a couple of months ago saying like, I have friends of mine that do this for a living. What the terminal is capable to do is basically build a discount cash flow report in a matter of seconds. And these basically you can just say, okay, build a discount cash flow model for Apple. You wait a couple of seconds and you get the full spreadsheet with the regression of the valuation and whatnot. And the powerful thing here is that all the code is open source so you can see what is the model doing. You can see what are the parameters that we are using. And in this case, we even have one of the sheets is to make sure that all the calculations are adding up correctly to make sure that everything is zero in the end. And let's say you don't like Excel and you will prefer to have a PDF report, that's fine. That's something that you can do because the code is open source and it's just about the ending whether you push it into Excel spreadsheet or a PDF. But the mathematics, again, behind the FAM and French refactor model are gonna be the same like anywhere, right? So, another interesting one. This one is actually also personal to me because I'm an engineer and I'm really interested in the fields of AI and machine learning. And one thing that I felt on the financial world that I didn't quite like is that if I go into Udemy, Coursera, any online course and people talk about data science and the finance, what they do mostly to try to predict a stock price is just looking at the past performance of the historical data of that asset. But as you know, there's so much more out there. Financial markets move really fast and there's not just the past performance. It can tell you everything, right? There's news, you have insider trading, you have sentiment analysis of people on Twitter or on Reddit and there was no platform that allows you to leverage all of these financial time series. So, that's what we're meant to build on the terminal currently. So, basically, you can select like, let's say, Bitcoin and you can or Apple and you can not only select the financial time series of Apple to predict the stock price but you can add any other type of financial time series on top. And this is any other type of financial time series. We're talking about other assets. Other assets, we're talking about alternative data sets. If we're looking at Apple, we can even put like the interest on the world like AirPods on Google search, right? Because that's something that, you know, probably you think that it might be related with the sales of Apple, which may impact the stock price. And that's something that we are working on right now which is you can not only leverage all these data but then you can tune the model as you want. So, you can tune the endings, you can select the amount of, you know, notes, you can select the amount of layers, you can select which neural network model you want to use. And that's really a level of freedom that like I have never seen before and as an engineer, I'm super excited about it and a data scientist as well. Another feature that we have is econometrics. These ones, like you are more familiar with it than me even I would say, basically statistics for finance. Why would you every time like build this from scratch on an Excel spreadsheet, why not just leveraging the terminal and bringing your own data sets to understanding the connection between any sort of variable. And that's something that we already have on the terminal. Next one, again, bringing your own alternative data sets that's something that the fact that the project is open source allows you to do. So, you can bring any sort of open source data to not open source, you can bring any source of data to the platform. So, this is an example that someone other last year. So, basically Netherlands COVID rates and this, I think the person that was looking at this was interested in some ticker that was based in the Netherlands. And they thought that there was a connection between the COVID rate in Netherlands and the ticker. So, they just implemented this feature which allow them to check the COVID rate. And this is just like an example, right? But we can go further, we can add ESG metrics, we can add geographical data. We currently also have like GitHub star. So, if the company is an open source focused company. So, the possibilities here start being like limitless. Open BB API. So, the way I see this open BB API is basically what the terminal is building is really a backbone and a strong infrastructure. But on the back and everything that it is an API, right? We saw a wrapper of APIs, right? It leveraged like multiple data sets and then we process it on top and we can leverage that. And the example that you are seeing here is that data being leveraged on a Jupyter notebook which is like ideal for academia or even quant developers, right? They can have access to the data, they can transform it, they can play with it, they can test. And this is a very good use case, right? This is something that I personally use myself a lot. So, you may think, okay, but this is only for academia and quant developers, right? And the answer is no, you can go further with it and you can build custom tools using this API. So, this is like the next step as open BB is to have a strong enough API so that people can build on top of us and they can build anything that they want. So, this is a custom dashboard that some contributor added to the platform and it just displays a cryptocurrency exchange rates to USD in real time. So, it's basically like I think every couple of milliseconds like these updates. And this is just like a use case, but on the platform we have more, we have like some options pricing, we have some correlation based on a couple of like metrics, the kind of tickers and then when the data comes from to understand, you know, all things are working out. And yeah, this is really like what we are set to do, you know, is to build really like this bottom like layer of the infrastructure so that people can build on top of. To summarize, my point is that I believe that proprietary investment research platforms won't last at some point because of open source. I'm a really, really big believer of open source. Whether it is open BB or not, I don't know, but I'm just happy that open BB is helping to show that there is a better path and I just feel like the finance industry is still playing catch up with everything that is going open source. Cause if you look at all like technology, everyone is going open source, Microsoft just open source all their projects and is just the future in my perspective. And yeah, I think that's pretty much it. Here I'm just like sharing our website and then you can see that you can do slash and you can access like Discord or get our newsletter for updates or GitHub project if you want to play with it. And you can like install it and try it today for free, a completely free platform and then you can follow or social media and yeah, that's pretty much it. Thank you. And any questions? Yeah. Sorry, can you speak a bit louder? I can't hear you very well. Yeah, so we are, for the discounted cash flow, I think we are using data from Yahoo Finance but our terminal accepts data from other data source such as IX Cloud, Alpha Vantage, Polygon and I think there's another one. But yeah, I think it takes around like 50 seconds or so. But yeah, we're basically just eating the end point of the data sources and then the calculations are just streamlined. So it doesn't really matter the data source as long as we get that data and it's valid. Oh, FEMP is the other one, Financial Modeling Prep. Yeah? It's a classic use case, but what do you mean when you start it, do you see any application? What do you mean by more general? Yeah, so I can give you an example, right? For those two months, I didn't build, everything that I showed you, that wasn't me on the two months. So I actually started just with focus on stocks because for me that was the main thing. And then what's happened is when I put it open source a couple of weeks after, someone out of France has a full forex menu. So I understood that people want to dig deeper and now we have like economy, we have like crypto, we have like options. So now we start like leveraging these data because people just start relying on the platform, right? And so it just starts to evolve. So the reports that I showed is something that I wanted from the beginning. So I implemented that from the technology perspective, like the automation, but the data that we had before, that was mostly driven by the community, right? And that is why for me it's very important for us to have a strong API and infrastructure so that people can build on top and even features things that we are not even thinking right now. So let's say, because everything is vital right now, you know, which is like super easy to interact with. So let's say someone could come in tomorrow and they can say, okay, I want to leverage the platform and build a mobile app, right? And this is something that we want to allow people to develop on top because we want not to capture value but create it, we want other people to build on top of our platform. Any other question? Okay, so I think I'll call it a day. Thank you everyone. Thank you.