The Real Reason Financial APIs Are Losing Their Moat

**[00:00:00]** Hello everyone, my name is Armando Perez-Carreno, and welcome to the Web Talk Show. Today with us is Tommy Cotter from Detroit, Michigan. How are you, Tommy? Good. Good, Armando. Thanks for having me. It's a pleasure, Tommy. So, for the audience, can you tell us a little bit about what you do and how you got there? Yeah, so I work at uh Benzinga. And if you're not familiar with Benzinga, we are a financial media company based in Michigan. And so, we write stock market news that caters towards uh retail investors. So, anything about the stocks in the uh North American markets and uh global soon. Um if you're if you're interested, uh we cover those markets and and yeah, that's a high-level of Benzinga. Interesting. How did you get to Benzinga? Did you start in like the the stock market and all the financial world from the beginning? Um actually, so I I studied uh mechanical engineering in school. So, a little bit of a, you know, an unnatural course, but um but I met a friend at a at a at an event, and he he basically said, "Hey, you know, we're looking for a project manager. Do you want to come on and help?" And uh I agreed, and the rest is history. It's so funny how that works out, where you study something and then you end up doing something that's nothing to do with it directly. But at the end of the day, I mean, if you study any type of engineering, it's the logical way of thinking and the practical approach to find solutions. It all really helps. I I agree. I I think the biggest thing that I took from engineering school was uh just, you know, we're we're taught a certain way to think and to approach a problem with with almost like a toolbox mentality, right? Like I have the these tools that I can use at my disposal and and when do I need to use them? So, I you know, I **[00:02:00]** didn't I don't know if I retained much from school, but I but I did retain the the problem-solving approach. I think that's the most important part. People ask sometimes, should I go to college? Should I go to school? Well, I think school is good in general because you get to be with other people and learn about differences in how people go forward and learn tasks and and learn new skills and knowledge, etc. And then college is a a place where you're going to meet a lot of people and you are going to see how to work in teams and there's there's a lot involved in that and it's not so much how much you're going to learn, but it's more of a meta skill. You want to learn to learn and that's the same apply for school. So, if if if college is not in the cards for you, then still if you can go somewhere that can teach you or even if it's home schooled, it doesn't really matter if they teach you how to learn. That's that's the real value cuz then you will apply that everywhere because as we all know, once you graduated from school, except perhaps doctors and and people in the medical space, it's not what you learned. It's you're going to immediately just as soon as you get out, you're going to start learning something new to be able to do the job that you're going to do. So. Exactly. Yeah, you know, like I I was telling someone the other day like uh you know, being a lifelong learner is is something that everyone should aspire to do. We're never done learning. So, we should always try and you know, pick up on new skills. Um you know, times change, right? Especially with AI now nowadays. People are learning an entirely new skill set and doing their jobs completely differently than they would have, you know, 7 10 years ago, right? So. That's true. And the the speed at which things are moving **[00:04:00]** now, if you are not in that learning mindset, you're going to get left behind. Fortunately, even if you sort of get left behind, the tools are so great that you can very quickly get up to speed if you decide to do so. But like everything, it's it's all about acting, actually doing the thing, not just consuming, which is some something that that happens a lot, too. Yeah, agreed. So, on your day-to-day, what is the typical activity that you do in the role that you do? Yeah, so um at Benzinga, I'm on the um API product development side. Ooh, okay. So, um so we build API products mostly for businesses that are looking to consume Benzinga's information. Um and so we you know, at Benzinga, we have a huge editorial team and and stock market news is our our bread and butter. But aside from the news, we have all of these other um kind of adjacent products, um products that do end up feeding the news news feed in one way or another. Um and those are all delivered in form of API. Um So, um So, we we've built a lot of these products for for our brokerage partners and and we work with, you know, all of the top five uh largest banks in the US and then, you know, we we've got um you know, a a ton of smaller clients as well, mid-size and smaller clients. And we've built a a lot of bespoke solutions for them and their users. Um so a lot of a lot of my day is filled with um, you know, working closely with our clients and trying to translate their needs into um, you know, requirements for our development team. And then, you know, **[00:06:00]** building out these APIs in a in a way that meets their needs. I see. So, for someone who's listening who's not either technical nor financially inclined, why would you build an API? What's the point of people not just going to your dashboard and instead consuming an API to put what into their systems? Yeah, so so I mean, an API is really just a method of, you know, delivering data from from a database to a different application. And so, um, you know, historically, APIs were just so much simpler than building out teams internally to um, gather the data that they need needed. And it was just much easier to license the data and um, focus on their core offering, which is making their users happy, right? It it, you know, their core offering should have never been um, let's build an accessory data set. It should be What What do we need to do to keep our users happy? And so, um, and so, you know, subscribing to an API endpoint is so much easier to do that. And you know, uh, with AI now, that we're seeing so much hobbyist interest where users can quickly go into Claude, um, you know, hook up an API and start building these generative dashboards that are very tailored for for their use case And and um it's specific to their needs. It's not, you know, um a dashboard that was built to cast a wide net and meet the needs of a lot of users. Um it was it's built for for them **[00:08:00]** specifically. Ah, that's that's a great point. Cuz some people might know about the Bloomberg terminal, right? Where it's this monster of a tool that's very expensive or on depending on for what you're using it, of course, but can give you all the data you need. At the same time, has so much customization that it could be overwhelming. So, now with the LLMs and being able to tell Claude, I'm in this space, I'm in this vertical. I need this sort of information. These are the types of companies. These are the types of stocks. This is the type of information that I need that I'm interested in and this is how I want to visualize it. And then the tool being able to generate this dashboard, like you were saying, and then just call these APIs that give you the data. That's huge for a lot of companies. Yeah. Yeah, I mean, it makes it so much easier, but, you know, at the same time, um you know, a lot of the the value of these APIs is is kind of, you know, diminishing as well because it's it's easier to create the data sets themselves, where you can have agents that are, you know, um they're they're running and they're they're compiling this data. um So, yeah, I think, you know, when companies start to think about like where they want to focus their their resources, it should be on on uh you know, creating uh moats in a way where where their true value is not just, you know, creating a simple API product or creating a you know, a simple dashboard product. It should be, you know, what can we do to actually deliver uh data that's hard to hard to get. Yes. I remember this client we used to have that worked in the HR space. And while they used an API **[00:10:00]** for parsing PDFs. This is before all the AI stuff. Of course, now it's very easy. You don't need an API. But they would use an API, but then the real value was in getting the right data, understanding it, parsing it in a way that was relevant to the job applicant such that they could get the resume graded and perfected for these automated tools that the people were using in companies. And so, while like you're saying they were using an API, it wasn't just a wrapper on the API. There was a lot of extra sort of very niche specific logic there that that made it be have an added value. Yeah. Yeah, and it and it's you know, it's it's really hard to find um you know, specific uh you know, use cases now where where an API is is truly unique, you know, like there there you know, a lot of times uh data sets have been commoditized in in today's day and age. So, um you know, in the 2010s it was a little bit easier to find uh truly unique data sets and APIs that were solving a very niche solution. And and I think now it's been a bit more commoditized. Usually there are a handful of APIs that can accomplish one thing or another. Um But yeah, we'll we'll see what uh what happens in in the next era of AI. Is getting access to an API like the one from Benzinga something that the hobbyist like you said could achieve or or is it more expensive in terms of it's more like a business use kind of thing even to to get started? **[00:12:00]** Yeah, we we've made it incredibly easy to get plugged into Benzinga APIs. So, um really it's just like logging into the site, right? Like logging into any site. Um once you log in, um you know, you can you can get your API key. No no credit card required. And you can try all the data, you can, you know, explore the format. Um you can make an assessment as to whether or not it fits your fits your use case, meets your needs. And um and you know, if if you're interested in moving forward after that point, um then it's super easy to subscribe on our ends. Um we wanted to make it simple enough to where if you're vibe coding at 2:00 a.m., uh you don't need to talk to a salesperson. Yes. Which is historically how it always went. You know, if if it's Saturday afternoon, um and you want an API key, you have to fill out a a form. Mhm. And then wait till Monday till someone gets back to you. You don't get the key till Wednesday. So, we really wanted to make it simple um where anybody anytime can get their key and and start start exploring. That's great. I I know what you mean. I've had the experience when when we were building tools like stock related tools for clients, it it was slow. You're just getting those expensive also. But then it was like, "Yes, you'll get a call." And then 3 days later I get a call from London and it's like, "Oh, this is blah blah blah from whatever." And then they have this long conversation trying to understand what you're trying to do. And then eventually you get into the next and it's a whole thing. So, it's great that you're making it easier to to get into it because everyone's moving fast. And sometimes if if you're on a roll and you're you've got everything you need and you just need that connection and it could just **[00:14:00]** work, that'll get you into it. If you hit that barrier, you might just drop the project all together if it wasn't a big thing. It's too complicated. Just leave it alone. And and Well, that's not the point, is it? I agree. Yeah. You know, there there historically were a lot of barriers to entry and um and cost was a big one, too, where, you know, it was extremely costly um to plug into some APIs and now it's just become much easier. You also talked about the editorial side, right? So, so you've got stock market news and that I'm I'm not well versed in all this, but I remember that there's there's sort of this the part where you get the actual movements in the markets, right? And then all the thing and there's real-time data and all that. But then there's the the news side of it that that's based on specific things. Can you talk a little bit more about what you mean when you say stock market news for for those listening who again are not well versed in this space, it's not news like, "Oh, I'm seeing something on Fox or CBS or CNN on this TV." It's it's a different type of news, correct? Correct. Yeah, so anytime in the market where there's a movement on a on a stock that's that's beyond, you know, 5 7%, it's typically due to a a news catalyst. So, something happened related to the company, whether it was a company announcement itself or a rumor around a company that maybe exploded on socials, uh a a very um you know, specific news catalyst has moved that stock. And so, um what what we do at Benzinga is, you know, our our editorial team is they're watching the markets all day. Um we are, in addition to watching the markets, SEC filings, press releases, we **[00:16:00]** are also um you know, interviewing executives from companies. Um we are we are performing analysis on on companies and sectors. And um and we're we're covering that in a news wire format. So, we publish a lot of long-form content to our website, benzinga.com, and then we also publish, you know, news wire headlines to where, you know, if an active trader is looking to um get a quick um bite-size amount of information, they can consume the news wire headlines and um you know, get an understanding of, okay, this is the latest uh happenings from from company XYZ and and um so, it's it you know, we we have a a handful of different solutions for on the news side, you know, whether it's long-form or or news wire, but um that's kind of the gist of our news offering. I see. Yeah, I'm I'm looking at the site here. So, is it mostly consumed by people going into the actual new section, right? Or is it more of they subscribe to these feeds like you're saying such that they can ingest them into their systems and then work with that data. Yeah, it's it's a little bit of both. Um so um you know, we we've got uh you know, a handful of subscription offe- offerings where you know um pro users, professional users, not not necessarily pro versus non-pro, but users that are are um you know, active traders, they they can subscribe to to these offerings. **[00:18:00]** Um and you know, those are more advanced, right? Where we're we're covering um you know, thousands of headlines a day. Um and then we also have, you know, um kind of light pared-down offerings, which are, you know, we write long-form content um and we publish that to our dot com website. Um where users can kind of consume it on the on the open web. Um and then and then our third and and you know, our third offering and and the one that I work in is our API licensing business. So that's where we license these feeds out to to businesses and individuals. Yeah, that makes sense. So these feeds are they real-time feeds or are they sort of delayed time-based? Yeah, all all of it is mostly real-time. Um you know, we we do have some market data feeds that are delayed, right? If you know, if you want the uh stock price for Apple and you want to display it on a website that you're building, we do have delayed options for that, but most of the time the feeds are real time. Yeah. Good. Do you see right now, as as things are moving, more usage from new companies, small, medium, than than you were seeing before? Like, is it Is it that you had your base rate of people were consuming your APIs, and did you suddenly see a spike in usage, not only trials, but actually usage going forward with these people that are now like maybe some by putting some apps, some some doing legit work, but have you have you seen that? Yeah, definitely. Um I want to say we we've seen a massive spike. I I don't I wouldn't say it's hockey stick-shaped, **[00:20:00]** but I would say it's more of a gradual build-up since probably uh late 2024, where we've seen a ton a ton of users who are kind of starting to understand APIs, how they work, and um and you know, now we've got MCP servers, right, which make it so easy to to plug in an MCP server to Claude or any uh LLM. And um so yeah, we've seen a ton of interest from from both individuals and businesses alike. Yeah, I bet. I see here that you have a historical news archive of 84 terabytes. That's That sounds massive. So, what Why would someone need access to historical data, for example? What's a What's a use case for that? Yeah, so one and probably the most common and the most prevalent use case is um is for uh model training. Mhm. Um so, you know, what someone can do is they can take a news archive and uh they can train a model, you know, based on certain factors and maybe I'll just share one as an example, but you know, let's say we want to uh train a model to sell a stock um whenever XYZ happens. Mhm. You know, whenever um Let let's say or how about uh we want the model to buy the stock whenever positive earnings happen. Mhm. What they can do is they can subscribe to the news archive. They can um pull the timestamps from our earnings release news headlines, right? Mhm. And they can train the model **[00:22:00]** based on the timestamps of the price historical price data. And they can they can run some back tests and train the model to to execute that action. So, I would say that's that's a a prevalent one, but but there are, you know, dozens of of use cases. Well, that's a that's a good one. I I want to dive a little deeper into that because a lot of people will say, "Well, I have access to the API. I could just say oh, it went down or it went up. Buy now, sell, right? But it's not it's not as like you don't want to do that cuz you're going to be behind. What you're saying if I understand that correctly is you can actually use historical data to train your model to see if it would have made the right decision based on both the news and also maybe the the ticker price at that point and what was happening and all that. And then ask if it was back in the day what would have had done and and did it do it properly. Yeah, exactly. And that that's the concept of backtesting is, you know, before you deploy a strategy out into the real world, you want to make sure that it makes sense, you know, based on all of the historical context that it has. Um so so that's, you know, we we've got other archives, too. And whenever we work with hedge funds and in quant shops, they they always, you know, they the first question they ask us is what is your historical archive? Mhm. And um and do you have point-in-time data, right? And so uh so those those are you know, that those are you know, backtesting is super important. As I go through here, you you mentioned so many different things. Oh, the MCP server. I see you mentioned it here as well. The there are so many aspects of the trading world that if you're not in it, you're just not exposed as to what's happening, right? We hear about the stock market, and we might hear **[00:24:00]** about the New York and Chicago, and and basically that's it, right? But there there are many markets, right? There's there's a ton of different markets of different things, and they all behave in different ways. Yeah. Sorry, go ahead. What is the Can you give a few examples of like what we're missing out on as as the general public if we just think that the stock market is just the two main ones that we hear about in the news? Yeah. Um you know, I think you know, before someone wants to invest, they you know, they they obviously need to understand their risk propensity. Um and they want to, you know, probably outline their goals for investing. Um but you know you can get in the involved in in the stock market and you can pick the individual stocks that you want. Um that's one way of doing it and that's, you know, that's probably the most common way that people think of it. Um another way is you can you can get involved in in the market and you can kind of pick an ETF or a mutual fund where um someone else is kind of managing the holdings of that fund. Um and they're kind of making the decisions, you know, on your behalf in the background. That's another way. Um and I I think one interesting way and I'll probably just take it this direction. Just let you know, let me know if if we should come back to come back on course, but um you know, an interesting thing that that's happening right now is is prediction markets. Oh. Um you know, with with Kalshi and Polymarket, um people are kind of um you know, they're they're allowed to to bet on these **[00:26:00]** things that historically, you know, has never been has never been possible. Like, you know, they're they're investing their money in things like how many um rides will Uber deliver last quarter, right? And they're able to kind of bet on a KPI associated um with with a company and I think that's that's really fascinating and something that is kind of a I mean, it's kind of a new concept. That's very interesting. I've heard a little bit about Polymarket and we'll we'll get into that as well, but the the example that you just gave, what's the I know a lot of people will have the same question. What's the point? Like, why would I bet against that? Who stands to gain in a transaction like that? And is the company involved at all? How does that work? Yeah, the the company isn't involved at all. I mean, it's it's really just a free market, right? Where um you know, if uh if one person thinks that Uber will deliver a lot of uh rides in the past quarter and the other person doesn't doesn't think they will. Um you know, uh Kalshi, your Polymarket, or other you know, these other uh um prediction market platforms are basically just moving money around and and fulfilling, you know, some of these event contracts. Wow. That's Well, it's like a horse race, right? It's not that the horse is going to make it like it there's it's a race. Someone says this one's going to win, someone says this one says this is the other one's going to win, and you bet against it, right? It's it's like you're saying, it's a free market. I opened Polymarket here, and there's these in the hero section, they have a few that are swiping by as examples of things that are active right now. So, there's there's one that's US-Iran **[00:28:00]** permanent peace deal by, and then there's like 25% for April 22nd, 36% for April 30th. Again, these are the numbers that I'm reading here. And so, people are betting against that. And then there's like Bitcoin, whether it's going to go up or down. And And it's just And you see the graph. It's just going along. I had no idea this was just going on. This is very interesting. So, there's obviously the Strait of Hormuz traffic returns to normal by the end of April. There's There's sports there as well. Very interesting. There's crypto, e-sports, finance, where what will WTI crude hit in April. Geopolitics, tech, culture. When is Do you have an idea? It's fine if you don't, but do you have an idea when this sort of approach started? Yeah, I mean, this is a pretty um This This is a pretty recent um approach, and I would say I I don't know when when Kalshi and Polymarket came online. I think these are the probably the two as largest in the space, but um within the last couple years, I'd say. Wow. And is this I I don't know. How can this work? It's just Is it regulated anyway? Um yes. I I I don't have all the answers in this stuff either, but uh but I would say there is there is some loose regulation around it. Um I'm sure there will be more regulation tightening in the future. Um but yeah, it's interesting to see it all unfold. Yeah, especially **[00:30:00]** the types of things that are on here. It's like Elon Musk number of tweets from April 7th to April 14th, 2026. Yeah, and there's like 300 to 319, and it's 53% and then some other people are saying 280 to 289, but there's a $14 million volume weekly. What is this? Yeah, it's it's insane. The The amount of volume that's going out there for things like that is uh is insane. This is very interesting. I I recent I only have heard about Polymarket because someone I don't know, they were probably using an OpenClaw or something to try to get gains on Polymarket, right? Doing some research or whatever and trying to sell go up and down or whatever. Like and and as we know, can go go horribly wrong or or you can do well, but it's the same as having an analyst that's doing the things, right? It's just whether you program that properly or not. Um, and this is super interesting. I'm glad you brought it up. And so you can just go in and say like, oh yes, 99 cents or whatever and just put an amount of how much you're Yeah. Yeah. Um, yeah, you just, you know, you go in and and you you place your bid and uh, you know, maybe I'll just bring up another another interesting caveat related to prediction markets, but you know, a lot of people, um, have been thinking about uh, prediction market arbitrage. Mhm. And um, how they can almost guarantee themselves a profit. And um, so, you know, what they can do is um, you know, they they can find the same event on two different prediction markets. Mhm. Whether that's uh, Kalshi **[00:32:00]** or Polymarket, you know, I'll just use those two as an example. Um, I think Kalshi's maybe only available in the US at the moment. Um, and then Polymarket is the big uh, global market. But um, you know, they'll find uh, the same event on both markets. So let's use the uh, the Donald Trump uh, tweets uh, uh, you know, event. So what they could do is on Kalshi they could say, "Hey, I think that he'll have more than X number of tweets." And then on Polymarket they can say, "Hey, I think he'll have uh, less than X number of tweets." And so they can kind of hedge themselves. Mhm. And and they can do so in a way that they'll guarantee themselves a profit. And um so many people on on X and all over the place, they've been building these arbitrage bots uh to make that happen. Holy goodness. But yeah, I see Well, people are creative. And at the end of the day, it's like when you see these these VC companies go in and and acquire a bunch of companies, you think or if if you're outside the space and again, I'm no expert in this manner, but someone was explaining to me the other day, it's not like they are expecting all of them to do well. They are building a portfolio that they know at least one of them should do very well. And so even if they take losses on the rest of them, there's a high likelihood based on what they predicted that one of them is going to explode so much that regardless of if they lost on the other ones, it just doesn't matter. Yeah. Yeah, every VC I think, you know, kind of explain that's their strategy. They you know, I and I think um I think it was Bezos that said this, but **[00:34:00]** you know, if if you've got a 10% chance that that one of your investments will 100x, you should take that bet every time. And uh I think that's I mean, that's the kind of the VC VC culture. Yes. Yes. This is very interesting. So, did you immediately after getting out of mechanical engineering get into this? Like you started in the company and and that's it? Or did you get into the startup space or some other route? Yeah, so so actually, you know, my path was a little unconventional like I said, but what I did was I I went to Oakland University to to play basketball. That was pretty much the only reason why I went there. One one of the only reasons. It was a great school. Good location, too. But I went there to play basketball. Didn't really know what I was going to study, so I I studied My aunt suggested that I should study engineering and I'm like, oh, okay, you know, we'll we'll do that. And so after school, um, a lot of engineering students at Oakland University and it it's in Detroit, Michigan, by the way, not California. But, um, a lot of students go right down the street and they work at Fiat Chrysler, which is one of the big three. Um, and so that that's what I did. I followed on that kind of, you know, standard path. Um, and I worked there, you know, as an intern and so it was also COVID times, so I just, uh, I was working in the auto industry and realized that it was not a place for me. Not going to be sustainable. Um, and so I decided to jump ship and um, came over to the fintech space. Um, and that that's kind of my **[00:36:00]** trajectory. Yeah, we've we've all got got interesting ways to get to where we are, right? But everything that you do along the way helps for experience to for the next thing. Right? Yeah. What is what are the most, I don't know, interesting things that you've seen in the space where you were you came to a work one day and you you like, wow, I can't believe this thing happened." And it just blew your mind. Yeah, I I mean, I there's there's so many of these instances, I think I'm going to have to um think about this for a sec, but um I I would say just just understanding the the media landscape holistically is something that um you know, I myself didn't think about a lot before I got to Benzinga. Um I had a you know, a partial understanding of what an API was, you know, had used the Alpaca API before and you know, so I knew how they worked. Um But I didn't really understand the media space and um the big thing with the media space is it's it's all you know, most of the value is derived um from page views and impressions. So, if you can get a large number of people to see your content, um whether that's on your website or on your socials, um you you can usually monetize those users pretty well. Um and so, you know, what what media companies do is you know, they try to get as many eyeballs on their content as possible. And uh you know, some companies will run advertisements to do that. A lot of it is native. **[00:38:00]** Um and once they have eyeballs on their content, um then they can they can, you know, start selling ads. And uh so, ad revenue becomes a large uh revenue stream for for media companies. Um and that was that was really unique to me. I didn't understand um I mean I I know I you know would see ads all the time, but I didn't understand the dynamics of it. And um so you know I would say advertising is you know was one thing that I found interesting and novel. Yeah, if if you've never been in it or been exposed to how it works, you just see them splattered everywhere. You're like, "What's this? Who cares?" or whatever. But at the end of the day, an advertisement if it's well positioned and it's targeted properly then it's good. I don't mind seeing an ad for something that I might actually want. If I just constantly see ads that I don't like, then yeah, it bothers me. Yeah. Yeah. You said socials. Does a company like Benzinga also do because this uh this type of content some might consider it's like boring content, but at the end of the day it's really interesting content. It's all depends on how you frame it, right? So is do companies like yours go into actually creating I don't know TikTok videos or viral type videos where it's not just a still image or a slideshow, but but rather something that everyone else is doing in the viral space and then getting a ton of views. Yeah. Yeah, Benzinga um we are we are kind of doubling down on our social strategy. So **[00:40:00]** you know, everyone knows that you know, kind of social media and the short-form video consumption is kind of the way that people a lot of people consume information now. Mhm. Um and and we don't want to neglect that. So, um so yeah, we're we create content and a lot of it is like, you know, 30-second clips. Um and what we'll do is we'll we'll take our our news content and and transpose that into video form and deliver it via social, you know, TikTok, Instagram, YouTube Shorts. Um and so yeah, I think, you know, especially with the younger audience, Gen Z, um you know, if you say, "Hey, go read this uh go read this uh three-page research report. It's all in there. All the information's there." Um I think, you know, they'll they'll probably tell you to get lost, but um but yeah, so we we definitely do uh focus on video as well. Yeah, that's great cuz it's the news and I for one would much more likely enjoy reading about the market news or whatever as short-form content if it's well made, if it's uh it doesn't really matter how. It could be a person talking, it could be animations, graphics, or whatever, but if it's visual and auditory and and I can quickly get the gist of the information, then great and you have all the source data right there, right? So, if it's constantly pouring out, it's much better than going on the TV and going through a million commercials and just cycling through three news articles that might not be relevant at all, then yeah, I think I think uh you're definitely uniquely positioned to to have all that content. That's great. I'll I'll have to um look **[00:42:00]** look into it as well. Do you see a lot of misuse? I know you work in the API department. Is is it common to see people who are using the APIs in a way that's not allowed and that they have to be shut down, for example? Um I would say we we don't see it often. Um there are a handful of cases where um you know, individuals will or businesses, too. Um we've seen it in the past where um you know, they'll they'll exceed their rate limits on their key, and that's typically a way that we can um monitor usage, make sure that no one is abusing services. Um and our rate limits are pretty lenient, but if it ever gets to the point where you know, it's like, "Okay, this is uh this is abusive or this, you know, type of request is not compliant." We all we reach out to to users and let them know that. Um but the what one thing that I will say with with um on a business misuse standpoint is you know, sometimes what companies will do is they'll they'll try to sign up um for a service as an individual user, Mhm. and then they'll they'll, you know, use an API um to power their platform. Mhm. And so so we have, you know, systems in place to detect that type of behavior. And um I would say that that's the most prevalent um misuse scenarios when someone will, you know, kind of self-report a lower amount of users, and **[00:44:00]** then we find out, "Hey, you know, you're distributing the content to you know, your platform that has a million users. You know, what's going on? So, we we have seen that before in the past. It's not super common, but it does happen. And if you decide to do it as a business, then you can put it in to your platform and and have users access it. Yeah, exactly. And any data licenser operates this way, right? They they want to understand how their data is being used because you know, at the end of the day, the the data is their service and um in order for them to offer the best service, they you know, they need to have um terms and and uh you know, terms in place for for the usage. Yeah, well, I know embedding and that sort of thing is typically a touchy subject with certain with certain platforms. I remember one time one of our clients was doing a Tableau reporting with a lot of data, but then they wanted to put it on their website for internal access for their customers. And if they wanted to do that just to be able to do that change, they needed to pay a $113,000 license. And it was really expensive. Then we ended up moving over to Power BI, which was is more lenient in that way. But I but I have seen that where it's like some companies might be more enterprise oriented, I guess. And so so they have to protect it that way. But uh I like that you have that that ability because many people will want that. And if you're starting out, you can't pay a huge licensing fee just for your 22 users that that are on free trials, right? Um but want to be able to at some point scale it. Yeah. Yeah, scalability is key. Um **[00:46:00]** and we're we're we're the type of company where we never like everything we do is very flexible. Um so we're we never operate from a rigid, you know, standpoint where, you know, hey um you know, you have to pay us this exorbitant fee for for licensing the data. We we always want to, you know, start with a a partner. Um let's start small, you know, if they're small and let's let's grow together. Um and and so that's kind of our our motto. That's nice. If so I'm trying to determine an example here. So let's say I wanted to build a stock trading game for kids to learn about stocks and how the market works. I remember when we were in high school there there was this website or whatever and you could do like fantasy football but fantasy stocks, right? And you could sort of have a thing. But let's say I want to create my own with with my own twist and I I want to be able to teach kids how it works and and all that good stuff. So plugging into an API like this would allow me to to do that without having to generate or create or purchase a huge data set in order to do something like that. Is that Is that accurate? Yeah, exactly. Um and I I want to hear your your thoughts on what the game might be, too, by the way. But uh but yeah, it it's very easy, you know, like um you know, it's very easy to to create these apps, quickly subscribe to to an API key. Okay, let's let's five code this game. Um and then let's let's uh you know, let's see how many users we have and um and then, you know, we we always scale, like I said, with with the partner. So we'll start small and then as you grow, um **[00:48:00]** you know, fees will obviously grow, too. Nice. Nice. Yeah, well, there's there's a lot of opportunities in the space still because I I have no idea what the percentage is, but I bet the percentage of people who are actually in the market is very small. Who are actively I mean, many people through just second or third party because of retirement or whatever, then yeah, but but directly trading. No, and I don't I don't think many people understand the stock market until they're older, a lot older. And and they just see it like, "What is What is this? Why Why does it make sense? Like it is Is it a real thing? Is it imaginary?" Like they say with Bitcoin. Like there's there's there's all this. And so, having some way to to teach it, I think would be interesting if you could make it creative and and gamify it, right? But like that, there's tons of other other interesting ideas. That's cool. I I didn't I didn't know that you had this offering and and the people who I've worked with, companies that we've worked with to provide solutions for clients, they they're all like just firstly, they've fit in the box that you mentioned at the beginning. You take long time to get contract signed and API set up and all that. And then it's expensive, especially like there's prohibitive completely if you're trying to MVP something. Like it's just not a thing. So, so this this has been super interesting. Is there anything that you like to recommend to people if if they want to start maybe consuming some of these API products, if they're trying to buy of code something, any any gotchas that you might have seen that that you want to help people avoid when they're doing stuff like this. Yeah. Um I I will say just just having an under you know, a general understanding of **[00:50:00]** what an API is is a great place to start. Um you know, if you can understand that and you know, an API is is you know, a delivery mechanism for data and it'll get data from point A to point B. Um I think that's important and then the next step would be you know, understanding how API authentication works generally. You know, generally you use an API key. You don't want to share that API key with anyone. You don't want to publish it in your public GitHub repository. Um those are a couple of gotchas and and uh you know, there are even services now that'll scan GitHub for leaked API keys and and I'm sure that you know, the volume of that over the past year has exploded. Um you know, just because there are a lot of novice developers that are just getting started and and making that mistake. Um and then they check their open AI bill and they you know, they see some crazy number. So that that's a gotcha um that you want to avoid. Um but yeah, yeah, I would say you know, MCPs make it very easy now to log in. Uh okay, now the now the server is authenticated. Now you can kind of talk in natural language and you can instruct the the model on what you want to do. Um and and that's the easiest way uh uh to get started and is just you know, use an MCP server. Um talk talk to the model, explain it what you want and uh and start to generate some cool ideas. That's awesome. Yeah, just get started, right? It's it's all about not being afraid, which especially for the older crowd, and I mean older just not jet see. **[00:52:00]** Right? It's uh sometimes we hesitate to start something in new and ask it and will it break because things used to break a lot. And so it's uh it's very interesting to see that change where you just try something and it and you see the magic of it doing something. And you know that it's so quick to generate things that if it does make a mistake, you can just roll it back and just try again and it'll do it in 3 seconds. So Yeah. Yeah, exactly. Like, you know, I'm telling Cursor all the time like oops, you went too far. Please please fix that. Yes. Yes. All right, Tommy. It has been super interesting. I've learned a lot today about how this all works. And thank you for sharing about Polymarket. I really had no idea that was going on. That's that's going to be a fun thing to just look at and explore to see what people are doing cuz it also gives us a little bit of a taste as to what people are thinking, right? The fact that we see all these all these items. If if people want to learn more about uh Benzinga, where should they go? Should they go to their socials, their website? What's what's a good place? Yeah, um good good place is both. Um benzinga.com/ uh APIs is where you can find out more information about our API offerings. Um and then you can you can hit us up on uh on Twitter @Benzinga anytime. Um and also on LinkedIn and and Instagram etc. Awesome. All right, I'll put those in the show notes. Thanks again, Tommy. It was a real pleasure having you on the show. And for those listening, if you haven't liked and subscribed, please do so so that you can be aware whenever we release a new episodes. Typically, we are recording Tuesdays and Thursdays. So, make sure you're subscribed so that you see everything and new that's coming up. Thanks again, Tommy, and we'll see you in the next one. Take care. Bye-bye. You too.