# Creating prediction markets (and suing the CFTC) with Tarek Mansour and Luana Lopes Lara

- **Show:** Cheeky Pint
- **Published:** 17 Mar 2026
- **Source:** https://share.transistor.fm/s/237b9821
- **Transcript:** https://podcasts.opennash.com/shows/cheeky-pint/creating-prediction-markets-and-suing-the-cftc-with-tarek-mansour-and-luana-lope-056cb4/
- **Provider:** OpenNash Podcasts (machine-generated)

## In brief

Kalshi's co-founders argue that a regulated, onshore prediction market is better than offshore rivals or traditional gambling. They say that putting real money behind a forecast rewards research and truth over clickbait and partisanship. Their aim is to build a 'New York Stock Exchange of events', starting with elections and sports and moving toward futures on things like computing power.

The central tension is how a company that insisted on doing everything legally ended up suing its own regulator. Two rejections of election contracts, layoffs and doubting investors nearly broke the company before the court win in 2024. The rest of the conversation tests the consequences: insider trading, sports gambling harms, whether markets distort politics, and who gets displaced.

## Key insights

1. **Suing the CFTC became the company's turning point** The regulator blocked election contracts in 2022 and again in 2023, forcing layoffs and investor doubt. Winning the lawsuit in late 2024 proved the law only permits bans in narrow categories like war and assassination, and growth took off.
2. **Most liquidity comes from individuals, not Wall Street** Luana says fewer than 5% of matched maker orders come from big institutional market makers. Over 2,000 individuals and small shops provide liquidity, because prices must be set hourly across thousands of new topics.
3. **Kalshi earns fees, so it wants winners to stay** Tarek contrasts a bookmaker, whose revenue is customers' losses, with an exchange that charges transaction fees. Kalshi says it does not limit winning traders and uses fee discounts to reward people who post prices.
4. **Prediction markets need new margin and contract types** Today every trade must be fully funded up front, which makes contracts like 'will a hurricane happen this year' uneconomic. Luana says futures, swaps, options and cheaper margin are on the roadmap, along with compute and GPU markets.
5. **Insider trading rules are the hardest unsolved problem** Kalshi follows federal law, banning trades by people bound by confidentiality, and goes further for officials and staff. It says it fined two insiders more than five times their profits and refers cases to the CFTC.

## Questions this episode answers

### What is Kalshi and how is it different from other prediction markets?

Kalshi is a US prediction market, a marketplace where people trade contracts on whether future events will happen. Its founders say it is federally regulated and that every contract is filed with the CFTC, which has 24 hours to stop it.

### Why did Kalshi sue the US government?

The CFTC, its regulator, blocked contracts on who would win elections in 2022 and 2023. The founders sued because the law only lets the government stop contracts that fall in categories like war, terrorism or assassination, and they won in late 2024.

### How does Kalshi make money, and is it like a casino?

Tarek Mansour says Kalshi earns transaction fees rather than profiting from customers' losses, so it does not limit winners. He contrasts this with sportsbooks, which John Collison says take about 10% versus a few percent on prediction markets.

### Who actually provides the trading liquidity on Kalshi?

Luana Lopes Lara says over 95% of matched maker orders come from ordinary people and small shops rather than big firms. She says more than 2,000 people act as market makers, meaning they post prices so others can trade.

### How does Kalshi handle insider trading?

Luana says Kalshi follows federal law and also bars government officials, candidates and their staff from trading related markets. A surveillance team reviews flagged trades, and cases are referred to the CFTC; she says two insiders were recently fined over five times their gains.

## Facts

- **Luana Lopes Lara** [0:03:06]: "we started the company in 2019. We started in my seat in 2019. And then it took us three years to be able to get regulated and launch."
- **Luana Lopes Lara** [0:04:56]: "Every single contract we file with the CFTC and they have 24 hours to stop it."
- **Tarek Mansour** [0:06:59]: "By the end of 22, they sort of like delayed the approval till after the election, what we call a pocket veto. That was brutal."
- **Tarek Mansour** [0:08:22]: "so we try again end of 23 they block it again and I was really at the point where I'm like"
- **Tarek Mansour** [0:08:41]: "the only thing we can do right now out of the entire range of possibilities is we've got to sue the government"
- **Luana Lopes Lara** [0:10:42]: "the government cannot stop any type of contract unless it makes a finding that's against public interest and it has to fall within certain categories of war, terrorism, assassination."
- **Luana Lopes Lara** [0:03:06]: "we won the election lawsuit at the end of 2024. and that's when we really started ramping up"
- **Luana Lopes Lara** [0:19:08]: "In the beginning of last year, we launched the first broker partner that we had was actually Robinhood and then Webull."
- **Luana Lopes Lara** [0:22:16]: "we don't pay them for it. We just rebate fees, but they have very, very hard conditions to meet. They need to have uptime of certain amounts, spreads, and top of box size, and all of those things."
- **Luana Lopes Lara** [0:26:59]: "the biggest percentage on a platform of a traditional market maker is less than 5 % of the maker orders in that market that have matched"
- **Luana Lopes Lara** [0:27:34]: "There's over 2 ,000 people that are market-making. People slash small shops, yeah."
- **Tarek Mansour** [0:28:14]: "It's this guy who lives in Kansas, never traded financial markets before, just likes to read the news and just knows how to predict inflation."
- **Tarek Mansour** [0:30:01]: "he actually read a bunch of tax codes and a bunch of statutes, just like dug extremely deep and then realized there is no way they could hit the targets"
- **Tarek Mansour** [0:32:44]: "we launched Kalshi Research recently which and one of the threads that we want to work on is we're talking to some of the research labs to create a new benchmark around which models actually predict the future better"
- **Tarek Mansour** [0:35:40]: "gambling is this idea where the business model is you are the house and your revenue is your customer's losses"
- **Luana Lopes Lara** [0:36:45]: "if we're providing liquidity, you're taking a lot more risks because you're putting yourself out to be sniped, then we're going to lower your fees."
- **Luana Lopes Lara** [0:41:16]: "The third one is really margining systems. Right now, it's very bad. You have to put all the money up front."
- **Luana Lopes Lara** [0:43:32]: "But it is tricky because we're still like 120 people to do it."
- **Luana Lopes Lara** [0:43:41]: "It's a very institutional way to do it that I can call you and negotiate a trade, and then we go and put it in the exchange"
- **Luana Lopes Lara** [0:48:15]: "The line that we take now is that we follow what the federal law is. So it's basically if you have an agreement."
- **Luana Lopes Lara** [0:49:32]: "we put out two cases two weeks ago of two insiders that because we're also regulated, we're able to charge them a lot of fines. So we charge them over five times what they made"
- **John Collison** [0:55:44]: "the order of magnitude rake for sports betting companies is around 10%. And the order of magnitude for prediction markets is, you know, 1 % or a few points."
- **Luana Lopes Lara** [0:55:55]: "the first thing that they're going to do is give you a bonus. They're going to give you $1 ,000 for you to come back or like a deposit boost"
- **Tarek Mansour** [0:58:07]: "there was a paper written by Kevin Hassett around this idea that like as society gets increasingly more complex our asset prices our understanding of asset prices will naturally decay like entropy will go up"
- **Tarek Mansour** [0:59:46]: "And that impacted markets, right? Like the stocks got, you know, there was a sell-off. And so we launched a prediction market on that."
- **Tarek Mansour** [1:00:15]: "if three out of these five conditions hit, you could reasonably say that, okay, this outcome has somewhat materialized. And it's just 10%."
- **Tarek Mansour** [1:08:03]: "So you saw Mamdani when his odds were 94 % on Kalshi. The thing that he was messaging pretty consistently, and I think there was a little bit of worry there, it's like, you got to show up."
- **Tarek Mansour** [1:13:27]: "And again, we spent four years getting regulated up front."

## Transcript

**[0:00:01] John Collison:** Tarek Mansour and Luana Lopes Lara are co-founders of Kalshi, one of the new prediction market firms that rose to prominence in the November 24 elections. They spent four years pre-launch fighting for regulatory approval to build the first onshore prediction market in the U .S. and now trade more than $10 billion each month in prediction contracts. Cheers. Cheers to you guys. What is this that we're drinking, Luana?

**[0:00:22] Luana Lopes Lara:** It's a Brazilian beer. It's our most famous Brazilian beer, I would say. Very light. I don't know if you like it. I like it.

**[0:00:29] John Collison:** So what is the split between you guys? Maybe in terms of responsibilities, but more interestingly in terms of outlook.

**[0:00:34] Luana Lopes Lara:** Well, we actually come from the exact same background. We studied math and CS at MIT, same internships, everything. But I'm a very, very optimistic person. Love taking risks. I think everything's going to work out. He's very paranoid, more on the negative side. So it's always like a very good, I think, balance. And I think that realists, outside of what we do day to day, that's really the difference between us that works out.

**[0:00:56] Tarek Mansour:** I mean, there's a little bit of background. So I was going to be a trader. That was really what I was going to do. And, you know, when you're a trader and you probably, I don't know if you've ever met sort of or spent enough time with the persona, but it's like a very.

**[0:01:08] Matt Huang:** John is a secret trader. At heart, yeah.

**[0:01:12] Tarek Mansour:** But if you're a trader, you're like an expected value calculator. Like I think about these sort of tail really bad outcomes all the time. And Luana oftentimes doesn't. And I think this is the thing that actually leads to great outcomes.

**[0:01:24] John Collison:** Okay. So I want to ask about that starting out because this is really interesting. You guys started Kalshi and for several years were not able to operate until you got CFTC approval. And that's interesting where just most companies don't start out that way. And secondly, I feel like the Silicon Valley standard that people sometimes trot out as a criticism is sort of the PayPal, Uber early days model where you start doing the thing and maybe retroactively a structure is put on top of it.

**[0:01:55] John Collison:** but you do a bit of ask forgiveness rather than permission in the very early days. And so can you just tell a little bit the story of how you started and that approval process? And then I want to get into whether that generalizes to other companies.

**[0:02:09] Luana Lopes Lara:** Yeah, I think that the approach we took from the start was that financial services or healthcare, I think you can't ask for forgiveness. I think there's a big difference between losing people's money, see what goes wrong, like an FTX example, that can go very wrong. with healthcare. There's a lot of other massive examples of it going wrong. And we wanted to do things the right way because also when we look at the market, we thought the biggest question to be answered was not, is this going to grow?

**[0:02:34] Luana Lopes Lara:** It was, can we do this legally in the US? And we were like, let's just actually address the biggest problem first and go from there. And I think the strategy for a long time, people looked at it as the wrong strategy. I think up until we won the election lawsuit, everyone was saying the folks that went out offshore, they're doing a lot better, they're growing a lot more. But I think once we won the election lawsuit and proved that the legal interpretation we had was right and we could do the company as we wanted in the U .S., I think it just really, really took off.

**[0:03:03] John Collison:** What were the timelines here? So when did you start and when did you win the election lawsuit?

**[0:03:06] Luana Lopes Lara:** Right. So we started the company in 2019. We started in my seat in 2019. And then it took us three years to be able to get regulated and launch. I think it was 2022 at that point. And then we won the election lawsuit at the end of 2024. and that's when we really started ramping up.

**[0:03:24] Tarek Mansour:** There were a lot of like Elon, I mean, there's some overlap between the timelines. But maybe going back to the question and maybe we can talk a little bit more about the sort of history afterwards. But I think it was like a twofold sort of, or two-step process. Like one, it was a pragmatic thing, which is we felt like to get proper mainstream adoption and institutional adoption, the elephant in the room was like, could we do it in a regulated, credible and safe way?

**[0:03:55] Tarek Mansour:** Because it's a complex marketplace. You're moving people's money. And we're like, we have to solve that problem first. That is the hard problem to solve. And that will be the road to success. The second thing was a bit more principled. We were, what excited us, like when we created this doc, one page on Google Docs, and we wrote a set of things like, why should we do this company? And why are we so excited about this?

**[0:04:18] Tarek Mansour:** we wanted to build the next generation New York Stock Exchange. We wanted to build a financial market that is in the U .S., that is credible, that is regulated. We were not very excited about this idea of building something offshore. And so that was really important because it's like, what kind of company do you want to build? And why are you doing this in the first place? There's many paths to success. We just weren't very excited about the other idea.

**[0:04:44] Tarek Mansour:** We wanted it to be here.

**[0:04:45] John Collison:** You're the first CFTC approved prediction markets at any scale. Yes, yes. And still to this day, all the contracts are individually approved. And so...

**[0:04:56] Luana Lopes Lara:** Yep, yep. Every single contract we file with the CFTC and they have 24 hours to stop it.

**[0:05:02] John Collison:** Yeah, yeah. Okay, so they get kind of a real-time feed of the contracts. Exactly, exactly.

**[0:05:06] Tarek Mansour:** Yeah, and it was a very long journey to sort of get to where we are in terms of the contract process and how it works. because you got to imagine the first time we walked into the building, actually the picture is right here. This is the first time we ever walked into CTC. You know, you walk in and you're talking about this idea and it's, you got to imagine the regulator's head starts spinning. It's like, you know, you're talking about things that don't have a financial underlying and then there's this idea of like potentially hundreds of, tens of contracts, hundreds of contracts a week.

**[0:05:38] Tarek Mansour:** And I mean, now we're like, you know, but there's all these things where the model wasn't really set up for this. So a lot of the process was actually like this iterative process where you're trying to figure out how to actually regulate this as you get feedback from the regulators and what can we do to satisfy the concerns. So it was a bit like building a product, but you're not building it for a customer. You're actually, you know.

**[0:06:01] Luana Lopes Lara:** A regulatory market fit in a way.

**[0:06:03] Matt Huang:** And so now you've gotten them comfortable with you shipping them unless they know. Have they said no to anything recently?

**[0:06:12] Luana Lopes Lara:** Not, well, the biggest they said no to was the elections. That's why we had to end up suing them. They said no for two years. But at this point, I think we've worked with them for so long that we know exactly kind of like they trust us as well as a self-regulated entity to know kind of what we can do and cannot do so we don't do anything around war, assassination, those things that we don't do.

**[0:06:32] Luana Lopes Lara:** So within the parameters that we've worked with them, it's a lot faster.

**[0:06:36] John Collison:** So sorry, the election lawsuit was, they were willing to approve contracts generally. they were not willing to approve contracts around who would win the election, which is a pretty popular prediction process, right? Contract, yeah, yeah, yeah. At the U .S. presidential election. And so you sued the CFTC? Our own regulator. I mean, and...

**[0:06:54] Tarek Mansour:** Which is generally not considered a best practice. It was, I mean, okay, so...

**[0:06:58] Luana Lopes Lara:** It worked out.

**[0:06:59] Tarek Mansour:** We started talking about the election market at the end of 21. And we started talking to, started engaging with policymakers, like talking with Congress a bunch and the regulator. And like, yeah, I think it's a good idea. It's a good idea. but then they weren't moving. We started noticing like, okay, something is off. By the end of 22, they sort of like delayed the approval till after the election, what we call a pocket veto. That was brutal.

**[0:07:22] Tarek Mansour:** So that was one of the hardest times in the company where we had to lay off a bunch of people. But the harder part of this is that your team and some of your investors or majority of investors kind of stopped like - Believing the idea. Yeah. Believing in the strategy, the idea, And it's a bit like this is getting a little bit unhealthy. You know, you guys should do something else. Like, you know, clearly it's not going to work out.

**[0:07:49] Tarek Mansour:** But we could not, we couldn't get ourselves to do something else. We just couldn't. I mean, and so we're like, okay, we're going to try again. And end of 22, so imagine the team is at an all-time low in morale. They're waiting for a new strategy. A bunch of people left. A bunch of people, you know, got laid off because we had to downsize. and you know our message in that next stand-up was actually guys here's the 23 strategy is we're gonna try again we're gonna do the same thing same thing but this time it'll work and exactly but this time it's gonna work even though every inch of evidence was pointed in the other direction and and

**[0:08:22] Tarek Mansour:** i will say a lot of this is is her like that you know i wanted this to happen so bad but i'm like my rational brain was like gotta listen to these people and and luana is much more dogmatic so we try again end of 23 they block it again and I was really at the point where I'm like

**[0:08:39] John Collison:** okay these prediction market things are just not going to work yeah

**[0:08:41] Tarek Mansour:** it's just and then and then when I was like well the only thing we can do right now out of the entire range of possibilities is we've got to sue the government and I mean yeah at the beginning I was like this is crazy and we took it to the board and you know we had Alfred and Michael at the time and they're all like well Alfred Lynn and Michael Seibel from YC and I remember like that board meeting it took a few board meetings but it took you know a few times at the beginning I was like well we have to tell you guys it's a bad idea like you know these are all the ways it's a bad

**[0:09:16] Tarek Mansour:** idea because you're a regulator you're like now a 25 people company like they the government can do anything like they can shut you down take out the license I mean it is true so so where does it work and even if you win you will probably lose like you will end up getting killed in the process. And it took a few times. And I remember very vividly, there was a meeting we had internally before talking to the board.

**[0:09:39] Tarek Mansour:** And this was the night before. We had lined up the lawyers and everything. And I got like cold feet. I was like, let's just focus on getting like a clearinghouse where we can focus on financial products. We can focus on all these other things. We don't need to sort of tank it all on this and really bet the farm on this. And I remember Luana in that call, I forgot the exact word. but it was something along the lines of like, are you fucking kidding me?

**[0:10:04] Luana Lopes Lara:** That sounds like me.

**[0:10:06] Tarek Mansour:** And I realized like, all right, I'm not going to win this fight. But the other part of me is like, we got to do this. Like I knew it. And so we go on the board and the response was basically, it's an antipattern, it's a bad idea, but a lot of great companies are built by an antipattern. There's something off that is weird that happens and maybe this is yours.

**[0:10:27] John Collison:** Yeah, it's a good way of putting it that every company is different in some new way. And so, yeah, this could be yours. What was the basis for the decision where you won the election last year? Like, was there any interesting policy angle?

**[0:10:42] Luana Lopes Lara:** Right. So the whole point is that the government cannot stop any type of contract unless it makes a finding that's against public interest and it has to fall within certain categories of war, terrorism, assassination. And the CFTC was taking this stance and they were trying to fit elections into any of these things. They're like, oh, elections might be illegal under state law. And, you know, because betting on elections, there's this one state that in bucket shop law, they try to find something to stop it.

**[0:11:10] Luana Lopes Lara:** And we knew we were very, very clear on the law, like elections have economic impact. If the elections have economic impact, they need to be allowed to trade on a futures exchange or derivatives exchange. And it was basically, I think, what the lawsuit did is it told the CFTC that they couldn't just do whatever they wanted. And that kind of like -

**[0:11:28] John Collison:** The categories of prohibitors, it needs to actually fall under one of the prohibited categories. Exactly.

**[0:11:32] Luana Lopes Lara:** Which elections did not. Right, exactly.

**[0:11:34] Tarek Mansour:** And I think that's important because the law, you know, the thing that we always say, like, the law applies to companies, but it also applies to the government. Right. Right.

**[0:11:40] John Collison:** But you should make your point about maybe suing the government's under reason.

**[0:11:44] Matt Huang:** Well, I think certainly in crypto and in prediction markets, it's sort of this unique thing of suing the government. But I was sort of surprised to realize that Coinbase has sued their primary regulator. And GovTech, SpaceX, and Earl Palantir all had to sue for various reasons. So it seems like it's actually more common than Silicon Valley conventional wisdom. So what, I guess, advice would you have having dealt with that GovTech to people out there trying to build businesses?

**[0:12:15] Matt Huang:** is like what sort of situation would be, you think, ripe to actually make that kind of challenge?

**[0:12:22] Tarek Mansour:** I think it's a sort of no other option situation, right? So it's still painful.

**[0:12:29] John Collison:** But did you actually have no other option? Because couldn't Kalshi have done fine without elections? I mean, elections are obviously very helpful because they're such like a big shiny thing. But I presume elections are not a majority or contracts today.

**[0:12:39] Luana Lopes Lara:** I think it was just too important. And maybe that's the dogmatic or whatever. but it's like, it is the Holy Grail of Mark. It is like, that's the one that you can see the use case of the data the best and you can see the use of the, and you can see the 2024 election, right? Like the polls were completely wrong and the markets were so much better at bringing that sort of information. And I think that it's the shining example of why these markets are forced for good and we need to have them in the US and regulated, which other markets are just won't have.

**[0:13:07] Matt Huang:** So to John's point on PayPal and Uber and asking for forgiveness, there were other prediction markets operating and showing real usage offshore. And so I'm wondering how much did that help demonstrate that election markets weren't against the public interest? Like, did that factor at all into the court case? Like the fact that people were already doing it?

**[0:13:30] Tarek Mansour:** I don't know. But, I mean, specifically on the court, it was much more grounded in sort of like— In the law. Yeah, the law. Like reading our law is the Commodities Exchange Act. So that's one of the financial like statutes. The other one is the Securities Exchange Act. And sort of reading it and really interpreting it and is the regulator overstepping. Now, I think for us, it was like a good way to learn, right? Because we could not learn about our product because we took this sort of regulatory first approach, like where we will ask for permission first before doing something.

**[0:14:06] Tarek Mansour:** And so in some ways it was helpful that you could have some data, some evidence that could guide our decisions over time. And I think it also helped educate some people about the existence of prediction markets. And, you know, they are here, here's how you can use them, et cetera. But I don't think like on regular offshore players really help from a policy perspective. Right.

**[0:14:30] John Collison:** Could Kalshi have been started 10 or 15 years prior? or was there some moment of openness in the CFTC? Was there some tech enablement that was required? Were stable coins required?

**[0:14:43] Luana Lopes Lara:** I do think that there is a part of it that crypto at the time was auger and there was like some very early prediction markets. I think that the existence of that made the CFTC also be like, we need a legal regulated alternative to this because before you could just say no to things. I do think that that played a role, but maybe like 5%, maybe 10 % I don't think it's more than that

**[0:15:04] Tarek Mansour:** the broader thing is like I think you know there's always intellectual interest in prediction market and I think that starts in the 50s it is a better source of signal than most other mechanisms of getting signal right but there wasn't a real pain I think 10-15 years ago in the way there is pain in the last few years and that pain I think is a sort of I think the country is more polarized I would say the world is more polarized social media has really bifurcated social feeds you know Clickbait is rampant.

**[0:15:33] Tarek Mansour:** The incentive structure for most things that we read these days is clickbait, whether it's a lot of traditional news or social media or other. So there was more of a pressing problem, I think, that helped create the wave and this sort of adoption that you're seeing in prediction markets that I don't think happened or would have happened 15 years ago because the problem wasn't that painful.

**[0:15:55] Luana Lopes Lara:** Yeah, and that's because most of our users, like 80 % of our users are actually just looking, like consuming information. They're just coming in and seeing who's going to win the Texas primary yesterday and seeing like, okay, the polls are saying they're tied, but they're not tied and all those things. And that consumption of information is way more important and relevant now.

**[0:16:14] John Collison:** Okay, so you were saying like algorithmic feeds, CalShield markets do very well on algorithmic feeds and just maybe people wouldn't have been as interested 10 or 15 years ago.

**[0:16:24] Tarek Mansour:** Yeah, I just think that sort of there's a meaningful and accelerating rise of distrust in traditional sources of information. And so you need a new one. And this does work, right? Like the incentive structure for a prediction market is truth, right? It is more volume. It is more liquidity, which translates to better and more accurate forecasts. and it took a few iterations for people to start trusting it. But like, you know, as you start building a track record, people start trusting it and they're never going to use a better product, right?

**[0:17:01] John Collison:** Well, to the point of substantive volume, can you guys give us the outline of, it seems like it's grown very quickly.

**[0:17:07] Tarek Mansour:** So volume in February was 10 .4 billion. Dollars of contracts. Yes, traded. and that's up 11x over six months, I think. Wow.

**[0:17:22] John Collison:** It's going so quickly, you don't even bother to go back a year because that's just ancient history.

**[0:17:27] Luana Lopes Lara:** I mean, a year ago, it really is. It's like we just had, for example, one sports market. We only had the Super Bowl.

**[0:17:33] Tarek Mansour:** In February, yeah, I mean, it's growing very fast.

**[0:17:36] Matt Huang:** Fastest growing company outside of AI.

**[0:17:37] Tarek Mansour:** Yes, I think so. And we compete with, I think, even some of the top AI companies. I don't know what Cursor and Anthropics' latest numbers are. I think 11x is very quick, even in AI. It's quick. And I think because it's an... So we are a marketplace. It's a true marketplace that has all the attributes of... It has network effects. So what happens in those situations is that users retain better because there's more diversity and more liquidity.

**[0:18:10] Tarek Mansour:** their participation and volume grows over time, which obviously grows their usage, but it also grows other people's usage because there's more liquidity in the system. And then they share it more with other people because the product is getting better. And so the sort of trifecta of factors is leading to this sort of growth.

**[0:18:27] Matt Huang:** When some of your early growth depended mostly on other brokers, and I think you've evolved that mix today, like what's the broker mix and how do you think about that? Sorry, what's a broker in this context? Like Robinhood. I don't know. I don't know. I don't know what you want to say.

**[0:18:41] Luana Lopes Lara:** Well, she explained what that is, which is interesting.

**[0:18:43] Tarek Mansour:** I mean, the...

**[0:18:45] Luana Lopes Lara:** Well, I can explain the broker part, but I don't know what we want to share on the numbers part. But basically... That was a tough one. That's why we looked at each other. I was like, ugh. All right. So because we're an exchange in Clearinghouse, we basically function like the New York Stock Exchange. You can never be here for her. Yeah, exactly. The Chicago Work and Style Exchange. So brokers can connect to us, right? So you can go to Robinhood to trade stocks.

**[0:19:08] Luana Lopes Lara:** You can go to Robinhood to trade on Couch. You can see it with Coinbase or whatever. And it's always been part of how we think about we always wanted to be in an exchange in a clearinghouse first. And actually connection to a Goldman Sachs or a Robinhood is very important for how we thought about this ecosystem as a whole. In the beginning of last year, we launched the first broker partner that we had was actually Robinhood and then Webull.

**[0:19:31] Luana Lopes Lara:** and at the start actually when we were starting to ramp up, the brokers were a very, very big part of kind of how we started growing, which was actually very great because the brokers bring so much demand and then we get all the market makers to come in because they want to trade against the retail flow and then we could kind of like buy ourselves time to ramp up the direct product a lot to where it is now.

**[0:19:49] Luana Lopes Lara:** But basically how you think about it is, well, we really are the cores and exchange and the clearinghouse and then you can access us through our app website API, but also any broker. We're investing more into institutional now. international brokers, so you can be in Brazil and you can trade on Kalshi, all those things, they're coming soon. But on the numbers, you can take it.

**[0:20:07] Tarek Mansour:** I mean, maybe we won't share numbers, but the direct, what we call direct, Kalshi Direct, which is our Kalshi .com, Kalshi app, the consumer business, that has grown, you know, that has sort of dramatically outpaced the rest, our other, the sort of intermediated or broker business. And I think it's just that the brand has gone mainstream. I think people, when they think about they have a difference of opinion on something, it's sort of becoming synonymous. So like, oh, let me pull up Kalshi and see the odds or let me sort of place a position on Kalshi.

**[0:20:41] Tarek Mansour:** And there's just a lot of organic growth now. And I think that's going to continue over the next few months.

**[0:20:47] John Collison:** You're describing how you grow the individual retail kind of side of the market, whether people are coming through brokers like a Robinhood or people coming directly to the Kalshi website. There is also, when you're in exchange like this, you have to spin up market making. And, you know, in the end, like, you know, the New York Stock Exchange doesn't have to think too much about market making because just the economic incentive is there. And so when something is at large scale, that's not as big of an issue.

**[0:21:15] John Collison:** But I'm curious what that was like in the beginning. Like, were you guys doing the market making? Did you work with market making partners? Now, how do you incentivize market makers to participate? I'm just curious what the market making scale up has looked like.

**[0:21:27] Luana Lopes Lara:** So there's actually two groups of contracts on markets on Kaushin. They behave very differently, and the market-making incentives are actually pretty different. So you have the long tail of markets, right? Like the ones like, well, One Direction have a reunion or, you know, all those things. And they are actually very hard to price. And because there's not necessarily a lot of demand, we actually have to incentivize market makers to come in. And there's like liquidity incentives, all those things for them to come in.

**[0:21:53] Luana Lopes Lara:** And I think it's actually how we think about how to build our remote long term. is actually how do we get very sustainable, solid liquidity in this long tail of markets. So we can get like, we have like, I think 10 ,000. How do we get to 50, 100 ,000 markets with still? But on the other side, you have the more classic like crypto sports, all of those guys. And on that side, it's actually a lot easier to market make because you have very clear proven demand.

**[0:22:16] Luana Lopes Lara:** It's a lot easier to price. So the market making incentives on this side is actually, we don't pay them for it. We just rebate fees, but they have very, very hard conditions to meet. They need to have uptime of certain amounts, spreads, and top of box size, and all of those things. Because we see it more as like incentivizing stability of the book than it is incentivizing them being there.

**[0:22:35] John Collison:** So what does incentivizing stability of the book mean?

**[0:22:38] Luana Lopes Lara:** For example, if you think of a live game, or like if you're trading like an hourly crypto.

**[0:22:42] John Collison:** You actually don't want the price flying around a whole bunch if there's no new information?

**[0:22:48] Luana Lopes Lara:** Right, exactly. Or even if there is, right? If someone is about to sort a touchdown, you don't want the book to just have like no liquidity whatsoever. You want it maybe to go a little bit wider, but you want people to be able to trade. And actually, when we go into the intermediating model, the brokers come with expectations that they have from traditional markets. So they're expecting, we want this spread and this size at any point in time.

**[0:23:08] Luana Lopes Lara:** It doesn't matter. So we need to go to the market makers and we're like, how do we incentivize this? Even though if you think about you should just let the markets do whatever they want to do, and if they're going to go way wider because they need to, it is. but we have to kind of play with incentives in a way to for all of our users including the brokers

**[0:23:24] Matt Huang:** but during those moments when the spreads would normally blow out wide are market makers losing money then and they're cross subsidizing to the other parts where like it's more

**[0:23:34] Luana Lopes Lara:** stable? Well now there's so much demand that I don't think they're like you can make money on spread even if the spread is like a little lower but that's the point of the program right is like you have to think about all the benefits you get in this program and then And even if you're losing a little bit in this time, having the benefits is worth it.

**[0:23:52] John Collison:** So you want tight spreads all the time for the major markets. That's what market stability means. And that actually takes work to engineer. It's hard to get there.

**[0:24:01] Tarek Mansour:** But there's more to it, which is, so I think the magic and the uniqueness, or the special thing about prediction markets is that a lot of the liquidity is not what you consider a market maker. Right, right. It's people. And so this goes back to the whole point. So let's just go back from first principles, right? Like, you know, there was, okay, the regulatory thing that we figured out, but then there's a liquidity problem, which is historically, it's like, a bit like we said, the New York Stock Exchange or the CME, okay, they're like, we're going to create a grain future.

**[0:24:34] Tarek Mansour:** We're going to take two years to figure out what it looks like, and we're going to call all of our buddies, like, you know, the 50 market makers that we all know, we all, you know, hang out Christmas parties together, et cetera. We're going to get them ready and they're going to start helping us get this product launched and then we're going to market it for the next three years and then it's just the same thing.

**[0:24:54] Tarek Mansour:** The liquidity is there. But prediction markets is really different because now you have to create liquidity in these products on like a weekly, daily, maybe even hourly basis. Like how do you do that, right? It's much more dynamic. There's new things all the time.

**[0:25:07] John Collison:** I think it's counterintuitive to people that you have to incentivize market makers to create liquidity. Because in the stock exchange, you don't have to incentivize high-frequency trading firms to create sub-second liquidity. They are very excited to take on that project themselves and build the high-speed interconnect between New York and Chicago to accomplish and everything like that. And so is this just the stage that prediction markets are at, or is there something fundamentally different?

**[0:25:34] Tarek Mansour:** I think this is where I was talking about, which is this idea that you need. So maybe finishing that sort of line of thought and then I'll get to the answer there. You now have a model where you need liquidity to be built on the fly, much faster, much more dynamically. And the market makers, the traditional Wall Street market makers are not geared up for that. It's not like they can spin up a new desk to price like politics or price culture in an hour.

**[0:26:00] Tarek Mansour:** right and so but this is the part that gets really interesting which is like and this goes back to the foundational principles around prediction markets is like a lot of these markets the people that will price them the best may not actually be the experts or the authority figures that you usually would think about it's actually random people like you know that live right internet anons yeah exactly the super forecasters those are it's like extremely dispersed you cannot find like a clearly defined the demographic or who they are and and i think that the thing where we got to now and that took a very long time and you had to incentivize is we have the community right a strong

**[0:26:41] Tarek Mansour:** community of super forecasters that are on calcium that can help price these things extremely effectively and fast where you know you don't have but but it took a while to kind of get them incentivized and come in and and spend the time and resources to take it from a hobby which is it was a hobby to a part-time job now it now it's a full-time job because the pie is so big.

**[0:26:59] Luana Lopes Lara:** And a metric that we can share is actually the, when you think about traditional market makers, the biggest percentage on a platform of a traditional market maker is less than 5 % of the maker orders in that market that have matched.

**[0:27:11] Tarek Mansour:** Of the liquidity.

**[0:27:12] Luana Lopes Lara:** Of the liquidity.

**[0:27:12] Tarek Mansour:** Sorry, say that again?

**[0:27:13] Luana Lopes Lara:** Yeah, so less than 5 % of the order, so people come and make orders, less than 5 % of the ones that match actually come from the big institutional market makers you'd think about. I see. Over 95 are just like peer-to-peer. Peer-to-peer, like, or funds to have like two people that just got stuck.

**[0:27:29] Matt Huang:** Which is unusual for you. How many of those small full-time little shops are there?

**[0:27:34] Luana Lopes Lara:** There's over 2 ,000 people that are market-making. People slash small shops, yeah. Yeah, on like a specific...

**[0:27:39] John Collison:** I think what Matt's getting at is like, who is a market-maker on Cal Street? Like, you know, there's all these Jane Street conspiracy theory memes. Is it like Jane Street? That's my Twitter feed. Or is it like some guy in his garage, you know, drinking Red Bull at 3 a .m. Right. Market-making. The guys in the garage are the most commercial. And you're saying

**[0:27:56] Matt Huang:** those are 95%.

**[0:27:57] Tarek Mansour:** of the flow. They're extremely crucial to the ecosystem because they price fast. They're monitoring the situation all the time, right? They're the original situation monitors. Yeah, yeah, I see.

**[0:28:09] John Collison:** Kalshi is built on people who are monitoring the situation.

**[0:28:14] Tarek Mansour:** So one example I'll give, and I've given this in the past, the best inflation forecaster on Kalshi over the last few years is none of the institutions or the big name hedge funds. It's this guy who lives in Kansas, never traded financial markets before, just likes to read the news and just knows how to predict inflation. He can feel it. And you have so many of these people. Now you have, I would say a few thousand that are formally committed, but there's tens of thousands of these people that know a bunch of different topics.

**[0:28:52] Tarek Mansour:** And they're actively pricing these things. And they do it as a full-time job and they get rewarded for that.

**[0:28:57] Luana Lopes Lara:** You need to talk about my favorite user.

**[0:28:59] Tarek Mansour:** Oh, yeah. Well, I have a new favorite user, by the way. Okay, each of you can tell it's your favorite user. I was thinking about this this morning.

**[0:29:06] Luana Lopes Lara:** Who's your new favorite user?

**[0:29:07] Tarek Mansour:** The Wall Street Journal article about the tax guy. Oh, yeah, that's true.

**[0:29:11] Luana Lopes Lara:** He's a good candidate. But no, my favorite user is this Rihanna Grande super fan. And he found Kyle during the election season. He's like, I don't like the elections. Like, whatever. Then he found our Billboard ranking markets of, like, charts.

**[0:29:23] John Collison:** He's going to work on important markets.

**[0:29:25] Luana Lopes Lara:** Important markets. to me very important and he's made over 150,000 he's getting every single thing he paid back student loans he put himself for a master's degree bought a car and all those things and he just like loves these markets and he's never really traded never done anything like that before but it's the first time that he actually has a way to monetize this very compulsive hobby that he had on you know music charts uh and he's able to do it and he's also very very nice to us on twitter so

**[0:29:53] Tarek Mansour:** So I had many over the years, but maybe I shift a lot. He's not loyal.

**[0:29:59] Luana Lopes Lara:** See, I'm loyal to my guy.

**[0:30:01] Tarek Mansour:** Well, I love all of our users. But there was an article last week in the Wall Street Journal about a tax accountant who was very active on Kalshi, Alan. and he, you know, when Doge came around and like there were a lot of sort of talk about how much they could cut, he actually read a bunch of tax codes and a bunch of statutes, just like dug extremely deep and then realized there is no way they could hit the targets.

**[0:30:37] Tarek Mansour:** Like, and even if, like, he really kind of deterministically realized and then he basically talked to his wife and he's like, I have extremely high conviction in this trade. I know I, you know, and you know, it's a bit like Michael Berry with the big short. So this guy put a big short but on Doge this time, right? And it was big. Like he really kind of went all in and, you know, he won. And it's just like one of those like amazing sort of showcases of what this can do.

**[0:31:06] Tarek Mansour:** Like now you have a market that like if you have that sort of knowledge, which maybe oftentimes is esoteric, like I'm assuming none of us have read all these tax codes, you can actually go out in the world, do research, get smarter about the world, and then, you know, get rewarded for that. And that's awesome, right?

**[0:31:21] John Collison:** You know, an early field of AI was poker bots. Are you seeing any good AI market makers? When you say no one's read all these tax codes, I mean, no one except Claude.

**[0:31:32] Luana Lopes Lara:** That's fair. That's fair. We should ask.

**[0:31:34] Tarek Mansour:** We are seeing more, like, increasingly more people using agents to trade. So that's definitely...

**[0:31:39] Luana Lopes Lara:** Especially on the API side.

**[0:31:40] Tarek Mansour:** On the API side, it's very big.

**[0:31:43] John Collison:** Do you have users who are successfully running market-making businesses that are mostly agentic? Users don't exactly tell us their strategies.

**[0:31:50] Tarek Mansour:** But you talk to them. Generally, yes, yes, yes. But the way I think about it is, do we think Rentech back in the days was using agentic models? I'm talking about Renaissance to trade. Yeah, the early versions of them. And so I think they're just evolving and they're getting better. And like most of our traders in their stack have some sort of like summary and synthesis module that's AI driven.

**[0:32:19] John Collison:** Yeah, I guess what I'm curious about is fully autonomous, no human in the loop, consuming information and providing a market based on that. Like that feels like it's coming quite soon if it's not like your cloth making a market.

**[0:32:32] Luana Lopes Lara:** Yeah, I don't know if there's a full. I know that for example there's a lot for international elections just on like for example translating all documents polls and being able to kind of do all of that but I don't know if it's all

**[0:32:44] Tarek Mansour:** we're doing so we don't know if the models are there yet right that's and I was so you know we launched Kalshi Research recently which and one of the threads that we want to work on is we're talking to some of the research labs to create a new benchmark around which models actually predict the future better which could be a unique benchmark around like are these models developing some understanding of the world that goes beyond memorizing, you know, old patterns.

**[0:33:12] Tarek Mansour:** And I'm honestly excited to see how it goes. And what's the eval for that? We don't know yet. But I think you could roughly kind of let the models run for, you know, make predictions on same set of markets for like a month or two and see which ones performed that like, you know, percentage of predictions that were correct, P &L over time, et cetera. Yes.

**[0:33:31] John Collison:** Okay, another market making question. So sports bookies have this need to crack down on what in their industry is called sharps. You know, people who are too good. Where, like, I think people don't think so much about this dynamic, but for a sports bookie, the best possible punter is someone who is kind of unsophisticated, bets on like their home soccer team's game. Inrespected with the odds. Exactly, and just wants the home team to win or whatever.

**[0:34:04] John Collison:** And the worst kind is someone who's like super sophisticated, finding the narrow markets, because for a bookie, you know, maybe they're making odds on 10 ,000 different markets. Like they only need to be wrong once or twice for, you know, people get to choose which they play on. And so they presumably can't be right on all the odds that they're offering. And these sophisticated people go find those. And so what happens is they basically use behavioral signals to identify if you are just signed up and you're betting on your home sports team's game, that's good.

**[0:34:37] John Collison:** And if you appear to be really sophisticated with all the signals that they would use, exactly, they shut them down. But it's interesting, right? You think like I'm just booking on the bets that, you know, on the odds that you're offering. But like if you're too good, they'll shut you down. It's maybe like car counting in Vegas. Do you have this dynamic with sharps? Like I would have thought no, that you just are fine with it.

**[0:34:57] John Collison:** But, like, do the market makers worry about two sophisticated counterparties on the other side? The Sharps are the market makers. I mean, they're super forecasters.

**[0:35:05] Luana Lopes Lara:** To be clear, we don't limit any winners. We don't have any of the, like, we want all the winners. Okay, the specific dynamics.

**[0:35:11] Tarek Mansour:** Well, we need the Sharps because how do you get market accuracy without the Sharps? This is the difference of, like, the...

**[0:35:18] John Collison:** Well, yes and no, right? Because what you want is different. Because the Sharps can snipe. They can just turn up once when the odds are wrong, grab a big win, and then disappear. Whereas what you're describing is you want, during the game or during the election, you want narrow spreads all the time. And so I feel like providing good market making is different than being right.

**[0:35:40] Tarek Mansour:** But a lot of the sharps can actually do better if they provide market making and, you know, like become part of the liquidity. So this is the big difference, which is very important. Like, that the, the, it may be a disclaimer. Like, I don't gamble. I trade. which I've always found a difference. And I think gambling is this idea where the business model is you are the house and your revenue is your customer's losses. So a lot of the dynamic that you describe has to be true because your incentive is like, well, somebody's making money, I got to stop them because they're making me lose.

**[0:36:12] Tarek Mansour:** That's just going straight from my bottom line. And the opposite is true. If somebody's losing money, I got to figure out how to bring them back. That's a very different model from like traditional financial markets where like the structure is you have to incentivize fairness and transparency. That's the structure. Like you want to create fair rules of the game for people to participate. Maybe Matt is better than Luana and maybe Luana is better than Matt and like they can battle it out.

**[0:36:34] Tarek Mansour:** They can figure it out.

**[0:36:35] John Collison:** You think the incentive system is very different where you do not like a casino or something. You do not monetize on some zero, some other person losing. You monetize just on transaction fees.

**[0:36:45] Luana Lopes Lara:** Yeah, the best outcome for us is people are like, this is fair. They have good prices. They have stable liquidity. I'm going to go there. But of course, for us to get there, we also need to incentivize different players differently. So that's why, for example, a lot of the liquidity programs come into effect. They're like, okay, if we're providing liquidity, you're taking a lot more risks because you're putting yourself out to be sniped, then we're going to lower your fees.

**[0:37:02] Luana Lopes Lara:** But if you're taking and you're going to snipe, you're going to have higher fees so you can pay for that activity. So in a lot of ways...

**[0:37:08] John Collison:** You'll use fees to incentivize pro-social behavior?

**[0:37:10] Luana Lopes Lara:** Exactly. And I think that that's actually how we see a lot of, how financial markets actually do the same thing.

**[0:37:14] Tarek Mansour:** Financial markets are the same.

**[0:37:15] Luana Lopes Lara:** The same thing.

**[0:37:16] Tarek Mansour:** It's more balancing out the marketplace so that people that are providing value to the marketplace have some, you know, a little bit more tilt. And then people that are like taking away value have a little bit less.

**[0:37:25] John Collison:** What behavior is pro-social and what behavior is anti-social?

**[0:37:28] Tarek Mansour:** Well, insider trading is anti-social.

**[0:37:30] Luana Lopes Lara:** Right, that's a big one.

**[0:37:32] Tarek Mansour:** Yeah, yeah. And illegal. Yeah. But, you know, but it's, and look, sniping is part of, is part of it, right? You need people that like, all of a sudden have gained some information edge and they do it in traditional financial markets all the time, right? Like that, and, And but to have liquidity and make sure that people are there and they're investing the resources, they have to get, you know, as you said, some incentives. But the interesting point, I think, and I think this is part of why prediction markets are being adopted so much is people like this idea that if like your edge is proportional to your research, how informed you are, how much time and energy you put

**[0:38:11] Tarek Mansour:** into this. and I think that only exists in prediction markets or traditional financial markets, except that for a lot of people, traditional financial markets, they're just less interesting, right? Like in here, you're researching about Doge and what's going to happen or what the election and how people think about elections and how they vote. That, at least to me, feels a little bit more interesting than like anything about IBM's quarterly earnings every quarter.

**[0:38:37] John Collison:** Kalshi has built a new kind of marketplace where real-world outcomes are traded, like whether the US will confirm whether aliens exist before 2027. You have thousands of participants opening, transferring, settling their positions, all in real time. And underneath it, as you can imagine, there's a complex multi-party flow of funds. That choreography on Kalshi is powered by Stripe Connect, onboarding participants, processing payments, routing funds, managing payouts. When money movement becomes programmable, new products or even new market structures become possible.

**[0:39:07] John Collison:** So if you're building something new with complex money flows, Stripe Connect was built for you.

**[0:39:15] Matt Huang:** Let's talk like different market verticals. And I think today everyone gets elections, they get sports, they get economic indicators. But I think you can look at prediction markets as this kind of search function across the set of interesting markets humanity wants to trade. And it's kind of a weird artifact that like the CME used to green light like wheat and oil and corn. But now you get to green light 1 ,000 markets a day. So what do you think we're going to find as we do that?

**[0:39:48] Luana Lopes Lara:** One thing that we're very excited for, we're actually starting to go in the direction of, for example, things like watches and bags and all of those things that are more going to the collectible side. They're actually able to do derivatives on those things. One thing that you should talk about is the GPU. I feel like compute could be a huge market. And I think the compute, what we're thinking a lot about is that there's a lot of these types of things that they function better as a more traditional future.

**[0:40:13] Luana Lopes Lara:** So things that don't have a binary, will it be at this price? Yes, no, but it's more like an actual future. You can have margin. You can have more like institutional grade liquidity and all of that. And I think that that's a great example of when we start going more outside of binary markets and more into the traditional ones, then what we're doing is expanding kind of that from grain to compute.

**[0:40:36] Matt Huang:** So it strikes me that obviously the futures markets that have worked best are these large commodity categories. Because we're sort of in an era where humanity is spending more money than it's ever spent before on a new commodity category. And the other traditional markets don't seem to be attacking compute.

**[0:40:57] Luana Lopes Lara:** So the way that we think about, we want to be the biggest derivatives exchange in the world, right? And for that, when we think about product roadmap, there's four things that matter. The first one is breadth of topics of markets, right? So we think about compute, we think about sports, we think about elections, We think about securities. We think about all of that. The second bucket is really market structure. So right now, we only have the binary yes-no.

**[0:41:16] Luana Lopes Lara:** We want to have things like futures, like swaps, options, all of that. The third one is really margining systems. Right now, it's very bad. You have to put all the money up front.

**[0:41:24] John Collison:** You have to tie up all the capital.

**[0:41:25] Luana Lopes Lara:** Right, which makes a lot of, for example, will a hurricane happen this year? Very, very bad for you to be actually market-making or selling those contracts. It doesn't make almost any sense capital-wise. And then the last one is liquidity. And what we think about is if we win these, we have the broadest set of markets, we have the broadest set of market structures, we have great and very, I don't want to say cheap margin, but in a way around that and then good liquidity, we're going to win on everything that we do.

**[0:41:52] Luana Lopes Lara:** So everything that we do in the company is like, it needs to be in one of these four buckets. And I think a lot of the topic side is like, how do we actually match the right topic with the right market structure, the right margining, and how do we make sure that it's all coming together? But you're completely right. I think that being able to build all the margining systems, all those things from scratch, we're going to be able to do margin models a lot faster and list a lot of these kind of new markets a lot faster.

**[0:42:18] Matt Huang:** Because of your direct mobile app interface and the fact that you target a lot of retail, do you worry that sort of the markets you're going to gravitate towards are the ones that are most interesting to just retail? And how much do you think about...

**[0:42:34] John Collison:** As opposed to like the pro markets?

**[0:42:35] Matt Huang:** The kind of institutional markets. I think of compute as much more of an institution-to-institution market. So yeah, how do you think about building liquidity and interest upmarket?

**[0:42:43] Luana Lopes Lara:** Yeah. We almost divide the company again in a way. We divide the markets in sports, crypto, and everything else. But how do we make what we have great but very new things? Because I think what got Kalshi here was not the regulatory side. It was really that we were just really pushing what is the next thing. It was elections and then after elections, sports. And for us, it's like we need to be pushing what the next thing is and doing that very well.

**[0:43:08] Luana Lopes Lara:** And I think that if we stop doing that, we're not going to win. The company's kind of structured that we have the market operations. We have the engineering side, all of that, that's set up for maintenance and improvement of what we have. And then the new teams like institutional, the margin team, international that are kind of pushing forward. And we just try to kind of find a balance on like those teams and then a platform layer that is like the core exchange and compliance and all of that.

**[0:43:32] Luana Lopes Lara:** But it is tricky because we're still like 120 people to do it.

**[0:43:37] Matt Huang:** Are you seeing pull already on the institutional side in certain topics?

**[0:43:41] Luana Lopes Lara:** Yeah, no, for sure. And I think that we actually just launched a week ago this thing called BlockTrades. I don't know if you know BlockTrades. It's a very institutional way to do it that I can call you and negotiate a trade, and then we go and put it in the exchange versus trying to do everything that way. So we're trying to build a lot of features to start getting more in the institutional side.

**[0:43:59] Matt Huang:** So are they trading the same things that are on the Kalshi retail, or are you offering new types of products for them?

**[0:44:05] Luana Lopes Lara:** Yes and no. So whenever they're interested in something like the – there was a lot of interest on the tariff situation. Is there going to be a tariff or not? A lot now with the petroleum, like the reserve, and kind of how that's going to go. So whenever we hear we want to trade this market, we just list it directly, and then it's accessible to everyone. But I do think there's going to be a very big gap on what the institutions are going to end up trading versus not.

**[0:44:28] Luana Lopes Lara:** But we just list it to everyone. It's very cheap for us at this point to lease new markets.

**[0:44:32] John Collison:** In the early days of Uber, it wasn't bad for the taxi business because it was just excess capacity and, you know, it was serving unmet need. But then after a while, it was bad for the taxi business. Are there existing businesses that will feel the effects of Kalshi and other prediction markets because it's a bigger market, there's more liquidity? Like I can think about just existing futures exchanges, like maybe Kalshi is a better place to hedge your soybean prices or what have you.

**[0:45:02] John Collison:** There's sports bookies, obviously. There's political polling firms where maybe you can get kind of the same information way cheaper. So who do you think will start feeling the effects of prediction markets because they have been in some way superseded?

**[0:45:16] Luana Lopes Lara:** Yeah, there's that funny meme of like the guy knocking on the door and it's like, who's the next one? The Grim Reaper meme, yeah, yeah. So you don't want to do that. But I think that a lot of volumation, right? I think that just traditional betting that we talked about, all the issues that that industry has that we're very different from. There is a traditional futures now are going way more into their space. So I think there's going to be a difference there.

**[0:45:39] Luana Lopes Lara:** There is a political polling that I think since the last election, there's just a lot of campaigns are using our data and all that. There's parametric insurance. Once we have margin, we can start going to more hurricane, natural disaster insurance, all of that side.

**[0:45:51] Matt Huang:** Is there a tragedy of the commons with the polling? Like part of the reason the prediction markets are accurate is because they interpret the polls. Right. So like if people stop using polls, like in some sense, polls are the sensor that you get of what people's opinions are. And then the prediction markets are like the mathematical interpretation of the polls.

**[0:46:13] Luana Lopes Lara:** Yeah. My take is that polls are just going to get a lot better. Because what people are going to be is like, OK, I can make money if my polls are right. So I'm just going to commission this poll and I'm going to do this. and now you can actually like compete a lot of polling models into one market.

**[0:46:26] John Collison:** It's like 538 did kind of the meta poll interpretation. Exactly.

**[0:46:29] Luana Lopes Lara:** And you can kind of have one number that's kind of aggregating all of that. And even in the last election, there was someone that actually did this. They commissioned a specific poll to do like nearest neighbors type of thing. It was like, I don't know how it was, but a different type of poll. And then they were able to make a lot more money in the markets. And that's the whole point of like having money and skin in the game aligns the incentives with truth and then the polls are not just paid for like, tell me what I want to hear, but the real number.

**[0:46:56] Luana Lopes Lara:** So I think it's complimentary. Same with the news. A lot of people are like prediction markets will destroy the news. I think it's way more complimentary. It's like when you're talking about an election, you're going to give your opinion. The market's not going to give you an opinion. You still need the commentators, but they're going to be able to show a number and be like, this is what the forecast is and this is my opinion on it.

**[0:47:14] Luana Lopes Lara:** I don't think the opinions are going to disappear.

**[0:47:17] John Collison:** You guys referenced insider trading earlier, and there's just the policy question as to what the right policy should be around insider trading when it comes to prediction markets. I think it's pretty nuanced. Like it's nuanced in the stocks case, right, where famously there's lots of, you know, you see SEC enforcement actions all the time against, you know, the things that aren't allowed. But there are cases like a hedge fund can have proprietary satellite data of the Walmart parking lot and use that to trade earnings.

**[0:47:48] John Collison:** And that is information that only that hedge fund has. But, you know, that is permissible. And so similarly, I think there's just like a complex set of line drawing exercises here where presumably we don't think government officials should be trading in advance of military actions. What about leading up to the Super Bowl, you know, predicting the Bad Bunny halftime show length? I mean, you know, people have that information. And so where do you think the lines should get drawn on insider trading?

**[0:48:15] Luana Lopes Lara:** Yeah. And you said it perfectly. It's a very complicated question. And it's a complicated question for stocks way more and to a bigger scale than it is in prediction markets. The line that we take now is that we follow what the federal law is. So it's basically if you have an agreement.

**[0:48:31] John Collison:** These are CFTC rules?

**[0:48:33] Luana Lopes Lara:** Well, CFTC and SEC. They both have it. So basically, if you have signed an agreement that says you cannot share some part of data. So if I work at the Bureau of Labor Statistics and I have in my confidentiality, then I'm not able to say what the inflation number is before. Then it is you have like you cannot be sharing that data. But if you know if you know that they're going to be rehearsing the Thursday before the Super Bowl and you're outside and you're like, I hear Lady Gaga's singing.

**[0:48:56] Luana Lopes Lara:** That's fine. And that's the same thing that, you know, a lot of hedge funds do with like Starbucks and people know there's more people, fewer people in the store. And that's the point. Markets are very good at incentivizing information. We want information to come to the markets, but we don't want it to be unfair. And if you have access to it in an unfair way, you should not be trading on it.

**[0:49:15] John Collison:** Okay, so you cannot trade on information or you have some duty to hold that information confidential.

**[0:49:20] Luana Lopes Lara:** We actually take it even a step further. For example, if you are a government official, you cannot, like if you're in Congress, you cannot trade on bills passing, even though I don't know if they have an agreement.

**[0:49:30] John Collison:** Famously, Congress people can trade on stocks. Right, right, right.

**[0:49:32] Luana Lopes Lara:** Right, so it's like we're actually taking a step further there. And we're working a lot of the regulators, because obviously it's a very new problem for them and for us, but we have an entire, part of being regulated, we have an entire surveillance division that is looking at every single flag. They pretty much don't sleep, and they're just trying to figure out everything. And we put out two cases two weeks ago of two insiders that because we're also regulated, we're able to charge them a lot of fines.

**[0:49:58] Luana Lopes Lara:** So we charge them over five times what they made and all those things they banned and all that.

**[0:50:02] John Collison:** What's very interesting to me about these stories is that you guys were doing that, where with the public equities markets, the SEC is extremely enthusiastic about enforcing their insider trading doctrine. What has the CFTC been like on this topic?

**[0:50:19] Luana Lopes Lara:** It's a great question. So, obviously, the CFTC, you can think about it at three steps, right? The first step is our own surveillance and enforcement. Then the next step is it goes to the CFTC and their own surveillance and enforcement. The last step, if you go to the Department of Justice, you can. And I think that the biggest difference is when people look at the SEC cases, most of the time they take a long time because the exchanges that their research and their investigation and they put some fine, they block some on, and it kind of goes through the process.

**[0:50:48] Luana Lopes Lara:** So it's still like that. Like every single trade on Kalshi goes to the CFTC. They have every single thing. Every single case goes to the CFTC for them to review. So they might take action. We don't know. But now the ball is in the court.

**[0:50:59] John Collison:** Okay, so you refer cases.

**[0:51:00] Luana Lopes Lara:** We refer cases to them. But we kind of do our first step of our first level of protection there.

**[0:51:07] Matt Huang:** I'm curious, there are clearly markets where nobody knows the answer yet of some event in the future. So, like, it's sort of impossible to insider trade. And then there are markets where a single person can change the outcome. Like the mentioned markets in a speech or maybe a sports player doing a specific number of shots. So, like, how do you think about kind of that spectrum?

**[0:51:30] John Collison:** Like, are mentioned markets a bad idea because they're just so inherently gameable?

**[0:51:33] Matt Huang:** Yeah, or are they, like, limited in scale fundamentally?

**[0:51:37] John Collison:** Mention markets like the Brian Armstrong Coinbase earnings thing and stuff like that.

**[0:51:41] Luana Lopes Lara:** That's the worst example. But, yes, I think that, well, inherently, I think mentioned markets are actually great. If you think about the Fed, right, like the amount of hedge funds that are just sitting down being like, is he going to tilt his head this way or this way? And if he does that, it means he's not very sure.

**[0:51:55] John Collison:** Fed meeting minutes are the original mentioned markets. Exactly.

**[0:51:58] Luana Lopes Lara:** That's actually pretty much the, and it was because we just know that specific words being used mean very specific things and it can move the market so much. The same thing with Trump, right? If Trump says, we're going to war, that's going to move the markets a lot, right? Or if he says a lot of things, like tariff that everyone else moves the market a lot. Even in, yeah, just a lot of everywhere, things that people say move markets and move a lot of different things.

**[0:52:25] Luana Lopes Lara:** So I think the major mark is very important. Obviously, the person that is working on the speech or that is saying the speech cannot trade. And that's kind of how we enforce it. Like if you are Gavin Newsom and there's a market on what you're going to say, you cannot trade it and your staff cannot trade it. That's part of the political kind of cuts that we do there that they cannot trade. But I think that's the point.

**[0:52:46] Luana Lopes Lara:** is like if there is a way to restrict some players in the market so that the market's fair and the market's positive and there's an economic utility for it, the market should exist. We shouldn't say like, okay, there are five people that could manipulate the market and the market shouldn't exist. Then you say the stock market shouldn't exist, right? So I think it's more about how do we build a system that is strong and resilient enough and with the right prohibitions that you can have the market.

**[0:53:10] John Collison:** The other big debate you guys are in the middle of is just that about sports contracts generally. And, you know, I was trying to reason about my own thoughts here on this debate where, on the one hand, you know, the criticism is that with more sports gambling comes proven bad effects. You know, you can measure some of the bad effects that it has on people. And, you know, we have this, especially in the U .S., where there was a lot of legalization of sports betting over the past 10 years.

**[0:53:44] John Collison:** And there's some data on that. On the other hand, you know, I have no real issue with alcohol, despite the fact that it has kind of a similar distribution where many people enjoy it, and then there's a very bad set of outcomes for a small fraction of the population. And so I feel like the societal discussion of, you know, the morals of alcohol and the morals of betting are different, despite the fact that, again, it's similar shape to the distribution.

**[0:54:08] John Collison:** And, you know, also just thinking from my experience, And online sports betting has been legal in, well, legal is a complex term, has been available in Europe. Right, for a very long time. For a very long time. Basically, since the start of the internet. I knew there was all these cross-border hacks in Malta, and now it's a bit more regularized. But it's been available to people who wanted it for a long time. And life goes on.

**[0:54:32] John Collison:** You know what I mean? And it hasn't led to any kind of major societal collapse over there. But clearly, this is one of the big debates that rages around Kalshi. And so I'm curious how you guys think about increasing access to sports contracts and the effects there.

**[0:54:48] Luana Lopes Lara:** Well, there's a lot of parts to what we're saying. I think that the way that we think about sports, how we decided to first list sports, is obviously something that a lot of people are interested in. That's unquestionable. But also there's something that a lot of people do a lot of research and know a lot about. And there aren't traditional ways for you to make money on that that are actually good. or we talk about the winners, they get cut and all those things, and it doesn't really work.

**[0:55:11] Luana Lopes Lara:** And regardless of whether people like that some people bet or dislike that some people bet, people bet. And it's just about what is the best way for them to have access to something that they can get exposure to sports. And I think that the whole point of markets versus a bookie is that markets are just objectively better. I think that it's almost, I've never heard someone make a case that a state-by-state regulated casino is actually a good thing.

**[0:55:36] Luana Lopes Lara:** I'm actually hearing nowadays that a lot of like the paid propaganda by the gambling guys trying to say that. But if you push them to questions.

**[0:55:44] John Collison:** And just to put numbers on that, the order of magnitude rake for sports betting companies is around 10%. And the order of magnitude for prediction markets is, you know, 1 % or a few points. Right. Is that the right numbers?

**[0:55:55] Luana Lopes Lara:** But the predatory part doesn't even come from that. Like for sports betting, if you start losing, because they want the losers, they don't want the winners. If you start losing, the first thing that they're going to do is give you a bonus. They're going to give you $1 ,000 for you to come back or like a deposit boost and all those things so that they can hook you to keep you coming back because they want to incentivize the losers.

**[0:56:13] Luana Lopes Lara:** We don't do any of that.

**[0:56:14] John Collison:** The people losing the most money are the most profitable for sports bookies, which creates a bad incentive.

**[0:56:23] Luana Lopes Lara:** Yeah, and we don't have that at all. And I think that the whole point is like, there's a moral question. Like some people are going to go into Robinhood or Coinbase or whatever and speculate on stocks and speculate in crypto and whatever. they want to do and some people want to speculate on sports and they should have the best the access to the best possible thing for that and right now it's just the sports books are just not it and we we really firmly believe that what we do in our markets are significantly safer uh for all of that and if you if you just take a stance of prohibiting it's like similar you said alcohol right it didn't change

**[0:56:55] Luana Lopes Lara:** people just went to like a speakeasy and drink and people are just going to go offshore when there's way less protections there's no none of the self-exclusion the positive limits all those things that we do don't have any information about them and they're going to actually it's actually very bad uh bad for them so i think it's just this like prohibition concept

**[0:57:11] John Collison:** just never really works it's also the whole policy discussion around this stuff is also very interesting when uh kind of reminds me of in canada um all the um liquor stores are run by the government or at least in british columbia and um uh you know you have the government saying this must be very carefully controlled but also we will sell it uh to have the revenue source and Obviously, that's much more of a factor in lotteries and things like that.

**[0:57:34] Luana Lopes Lara:** It's all about money at the end of the day. The states won their money. The casinos won their money. It's just, yeah, it is what it is.

**[0:57:40] Matt Huang:** Speaking of sports, one thing we were talking about was just what interesting new verticals are there going to be? And so I'm just curious, like, which ones are you most excited about?

**[0:57:49] Tarek Mansour:** Well, I think that anything around dissecting, like, a stock into its sort of, like, more atomic components.

**[0:58:00] Matt Huang:** So this would be like betting directly on NVIDIA GPU shipments versus…

**[0:58:05] Luana Lopes Lara:** Or like Tesla deliveries or whatever.

**[0:58:07] Tarek Mansour:** Like their earnings, you know, because like the… And then you can expand that to things like, okay, dissecting sort of the macro economy. Like what are the main sort of like factors are influencing the economy broadly? Like AI and like have a series of questions to price what's going on with AI. things like you know health scares like COVID and so on but the sort of where things get really interesting is this idea where so there was a paper written by Kevin Hassett around this idea that like as society gets increasingly more complex our asset prices our understanding of asset prices will naturally decay like entropy will go up because the things that influence or the sort of vector that,

**[0:58:56] Tarek Mansour:** you know, like the number of factors. Much higher dimensional vector. Becomes very high dimensional, right? And if those dimensions, you don't have a good understanding of X1 to Xn, you cannot get a good estimate of Y, right? And so the paper basically says that you need infinite markets. And prediction markets are a disnotion of infinite markets, which is like you have to have a market for each one of these Xs so that you can then take that back into pricing traditional asset, getting good traditional asset prices.

**[0:59:28] Tarek Mansour:** And an example of that this last week, so you know, there was the Citrini put out a research report, right? And it got a surprising amount of -

**[0:59:38] Luana Lopes Lara:** People got obsessed with that.

**[0:59:40] Tarek Mansour:** Yeah, I would say it got a surprising amount of love and interest. This is the AI 2028s we're all doing.

**[0:59:45] Luana Lopes Lara:** Yeah, like 38 % in Bolivia.

**[0:59:46] Tarek Mansour:** And I think, look, I think there's a little bit of like a society wants to believe if the AI is going to end us all. I think right now there's a bit of that. But this is where, you know, and that impacted markets, right? Like the stocks got, you know, there was a sell-off. And so we launched a prediction market on that. And well, before that, Citadel came out with a rebuttal and we launched a prediction market on that.

**[1:00:05] Tarek Mansour:** And, you know, the odds are 10%, right?

**[1:00:08] John Collison:** Of the economic scenario that they predicted being true as it turned to me.

**[1:00:12] Luana Lopes Lara:** It's three out of five things. So they have like five conditions if three hit.

**[1:00:15] Tarek Mansour:** Yeah, if three out of these five conditions hit, you could reasonably say that, okay, this outcome has somewhat materialized. And it's just 10%. Five out of five is much lower, right? So that is important. If you can put that back into pricing models, maybe the markets wouldn't have reacted that. Like maybe people wouldn't have sold off DoorDash because at least I believe, but you don't have to trust me. Maybe you should trust markets that this sort of analysis around DoorDash was actually quite poor.

**[1:00:40] Matt Huang:** So one thing you're sort of envisioning is this world where everything has a price all the time. and I'm curious like is that a good world to live in and I would note that uh Stripe I think benefits from being private and not having the real-time price and smoothness for employees and comp and all that which is by the way there's some noise in the you know because like sub-second pricing sentiment swings publicly like there's on average in the long run it's a truth-telling machine but in the short run can be a panic so just curious for you guys to think about yeah Is that the world we want to live in?

**[1:01:16] Luana Lopes Lara:** I mean, we're obviously biased because we love markets. We think markets are good. So we're definitely biased here. But I think our view on this is that it's always better to have more data than less data. If you don't think the data is good, if you don't think like whatever, the second by second stock price is good, you can just choose to ignore it. The world might not just ignore it.

**[1:01:37] John Collison:** I think CEOs of public companies would say it is not always possible to choose to ignore it.

**[1:01:41] Luana Lopes Lara:** I guess that's fair. but in a way it's like it's it's better to have the data and then use it as an input to something than than not but it when we say like um you know we want to have prices on on a lot of things it doesn't mean everything there are a lot of things that we wouldn't do like wildfires we don't do war terrorism assassination those things are bad and like there's a moral side of these markets and we're not gonna ever go there but in general it's in a world of social media is like you don't know what's true anymore my feed is like is it real is it not real did this happen it's just

**[1:02:12] Luana Lopes Lara:** better to have a source an unbiased source of information that you can kind of use it for other things and i think that that value um is is is there but i don't know well i mean i think

**[1:02:21] Tarek Mansour:** that like i don't maybe the simple frame for this is like you are uh increasing market efficiency for all these questions right like that's what this what's happening right it's um including potentially some events or things that relate to maybe private companies and i was thinking about the question is an interesting question like um why do companies go public right and why is it important to get like a you know real-time market price because there are downsides sometimes markets are erratic sometimes they overshoot in either directions but um the market on the long enough time horizon is a good sort of allocator it's a good weighing mechanism it's a good allocator of capital.

**[1:03:07] Tarek Mansour:** And I don't really see that, like, I just think that, like, pricing a lot of these questions will just increase efficiency, make our function, our allocating function better over time. And there will be some net losers, right? Like some people that maybe capital shouldn't be allocated to, right?

**[1:03:24] Luana Lopes Lara:** It's also a good feedback loop, right? Like if you're a CEO of a company and you announce something and it just keeps going down, you're like, okay, maybe I'm wrong. And I think the same thing you see with politicians where you can see in the live debate, if they say some answers and they see their price is going lower, they're like, well, maybe the answers aren't great. And I think a lot of these things, when we see even, for example, the use case of prediction markets in government, a lot of it is conditional markets, right?

**[1:03:47] Luana Lopes Lara:** They can say, if we pass this bill, will unemployment go up or down? And you can price these things for better decision-making and just like a tighter feedback loop tied with good incentives.

**[1:03:58] John Collison:** Do you guys feel like we have started this? Like, clearly we have seen the effects of social media on politics, where politics is a different game now, and different politicians are popular, and the political discourse is changed by the existence of, I mean, first Twitter, and now, to some extent, short-form video. Do you guys feel like we have seen the effects on politics of prediction markets yet?

**[1:04:25] Tarek Mansour:** Definitely. I mean, what are they? Well, the candidates are using the prediction market prices to inform.

**[1:04:31] John Collison:** Sure, but that could just be a handy thing, whereas again, I think with social media, like the candidates are different. The debates are different. Reflexive. Yeah, yeah. Reflexive.

**[1:04:38] Luana Lopes Lara:** I do think that what the markets are good at is that they are more unbiased by party dynamics. So if there is an underdog that the public really likes, there's a lot of like, maybe there's like a party that's like, we don't like this guy, we like this guy from the establishment, but the markets are very good at actually showing the real odds for that person.

**[1:04:57] John Collison:** Okay, so you think the party machines have lost a little bit of power?

**[1:05:00] Luana Lopes Lara:** I think you can shine more light into what people really want, which might not be necessarily what the parties want to put forward. I don't think we've seen that necessarily, but I feel like if I were to say, there was, for example, the Texas primary and I think that the polls were saying one person was really going to win, another person that was way higher in prediction markets won, and I think, right, and I think a lot of it was more of like, they give a more, a fairer view of the state of the race than a lot of the parties who closed.

**[1:05:29] Tarek Mansour:** I think that we do see this a lot with also So, well, there's sort of the piece where people use it and that's sort of reacting real time to certain things. But I think there's some degree of depolarization. That's what Luana is alluding to. And in some ways, it's an antidote to social media. Like social media has really polarized. Like when you have two candidates running for a Senate race, we're sort of set, right? Like your feet is set.

**[1:05:54] Tarek Mansour:** Like either your feet is saying the Republican candidate is awesome or the feet is saying the Democrat candidate is awesome. Prediction markets don't really have that. Because the people that are engaging in this are not in the sort of like who's great and who's, you know.

**[1:06:09] John Collison:** I think what you're saying is social media feeds ultimately try to resolve up front. They're like, I need to figure you out. Are you a Democrat? Are you a Republican? Like, what post should I show to you? And pretty quickly, I mean, you know, people have complained about this phenomenon where you end up down a, you know, particular rabbit hole because they have pigeonholed you as kind of this type. And you're saying just prediction markets do not have that phenomenon.

**[1:06:29] Tarek Mansour:** There's a little bit of a reverse phenomenon. Are we feeling too certain about this person? And I think that depolarizes things because the dimension is not, we're not one-dimensional anymore, which is like Republican-Democrat. And that's what you're seeing and what you're hearing about. Now it's like, well, this guy is kind of cool. And that's Calarico. And maybe he might do good in Texas even though he's a Democrat.

**[1:06:51] Luana Lopes Lara:** The same thing happened with the New York mayor situation, right? Like everyone was like Cuomo is going to win 100%. 100 % Cuomo's going to win, there's not even a chance. And we were just seeing Mondani's odds going up. And I think it's just the progressive message was really working with New Yorkers and the markets were really seeing that uptick. And that decrease in polarization really comes from people taking a step back and being like, what do I actually think is going to happen?

**[1:07:13] Luana Lopes Lara:** I'm incentivized the right way.

**[1:07:14] John Collison:** There's a bit of like an Iowa, New Hampshire effect here where in presidential elections in the US, there's like some big name leading into the election. Maybe it was Hillary Clinton in 08. and then Iowa and New Hampshire are measurements of the sentiment of those two states, but they also create narrative. And I think what you guys are saying is prediction markets create this Iowa-New Hampshire effect where they can create narrative in a way that changes the ultimate outcome.

**[1:07:42] Luana Lopes Lara:** I don't know if it changes the ultimate outcome. I think it sheds light into what the ultimate outcome is going to be.

**[1:07:49] Tarek Mansour:** And potentially changes it. Well, I think... There clearly is some flexibility, right? There's always, but it's like with the polls too, right? Like the, yes. I mean, there's polls.

**[1:07:58] John Collison:** Aren't you guys hiding your lamp under a bushel here? You're like, well, we're not changing anything here. You're just like.

**[1:08:03] Tarek Mansour:** I just think that the one thing I will say, the reason why we're like. Like prediction markets are a big deal. It's okay to say they'll change things a little bit. High odds don't always correlate to like a good outcome. So you saw Mamdani when his odds were 94 % on Kalshi. The thing that he was messaging pretty consistently, and I think there was a little bit of worry there, it's like, you got to show up.

**[1:08:23] Tarek Mansour:** Right? Because if you're very high odds, that could also lead people to be like, okay, this isn't it. So it's not as clear. And I don't think this changes things more than polls changes. Does that make sense? So the response is more like in a vacuum, yes. If you had nothing else, if you didn't have social media, if you didn't have news, if you didn't have any of that, yes. But because we have all these other things and you add prediction market to it, like the impact market.

**[1:08:44] Tarek Mansour:** But I want to make one point that I think is actually very interesting. And we're seeing this often. We'll be the judge of that. Okay. You can judge that. Let me know if it's interesting. but a lot of times when you see people start participating in prediction markets they get more engaged in the underlying they legitimately just get more informed it pulls people in it pulls people in but to do research now you have because you have some skin in the game or you're about to put some skin in the game you read everything changes you're not just like saying something crazy on Twitter anymore you're putting money and now it's like let me read let me actually figure out

**[1:09:16] Tarek Mansour:** oh who's this person what's happening

**[1:09:17] Luana Lopes Lara:** it's like are they pro this are they against this what's their view and everything and you go

**[1:09:20] Tarek Mansour:** because you know it's like amazing because this happened a bit in the New York race right like or it happened a bit with Brexit people voted for Brexit because oh no we want Brexit and after they voted for it they're like oh god wait I don't think we wanted this wait wait we didn't even understand what we were voting for right like and I think this heightened engagement is very good like you know like it engages people further to like learn and understand you know in sports basically if you ask sort of like a lot of the leagues they would tell you the same thing where people got more engaged with the statistic which player is good what's happening and

**[1:09:50] Tarek Mansour:** I think that will happen is already happening in politics, which is a good thing.

**[1:09:53] Luana Lopes Lara:** I think that the... I'm going to say something and then I'm going to call it fine. I'm saying, I think that politics is going to get better because you're going to have a way faster feedback loop on the messaging and the policies. Right now, when a candidate says 10 things and they win or they lose, you're trying to make one assessment of so many things that the candidate did and did that go well or not and which point was it?

**[1:10:18] Luana Lopes Lara:** Even if you do a poll, it's like always delay it is a very specific sample. But now you can have real time of like, they said this, what was the response? And you can get that and kind of like that faster feedback loop, which I think makes startups great, right? You're able to iterate very fast. And I think if candidates are able, everyone wants to win at the end of the day, and if they're able to optimize their message to what really people want and what policies people want, I think they're going to end up being better because they're just going to know what people want better.

**[1:10:42] Tarek Mansour:** It's like you get a score on all of the different things you've done, not one score that encompasses the good end of the bad, yeah.

**[1:10:48] Luana Lopes Lara:** When you ship a new feature, you're able to have like 10 metrics and you're like, okay, this went up, this went down. And you're able to, markets can kind of contribute to that, but also like, I think to a lot of other things as well. Music with like charts, when someone listens to the song and they're like, definitely not going to hit number one. You're like, okay, that was that song, so we should do something else.

**[1:11:07] Matt Huang:** Do you guys try to use prediction markets in any way internally to make decisions?

**[1:11:12] Luana Lopes Lara:** Every single decision we make is always probability. Even the election lawsuit, right? When we're doing it, it's like.

**[1:11:17] Matt Huang:** But that's you guys evaluating the probability. Do you ever think about creating markets for your employees to participate in?

**[1:11:24] Tarek Mansour:** So we have one net, which is as a regular exchange, we can't trade.

**[1:11:31] Luana Lopes Lara:** But we're doing like internal policy.

**[1:11:32] Tarek Mansour:** There's like a separation of church and state thing there. Exactly. And so we've been asking that, we've been working with regulars, could we do something small? Like could we do small dollars where, so that, you know, because obviously that's one that we want to implement. And you can't even dog food the product, I guess. And then dog food the product. Which is a big deal. It's been hard. It's hard. Everyone's on demo.

**[1:11:51] John Collison:** And I'm sorry, employees cannot train in their personal capacity? They can't. Not at all. Wow, interesting. But yeah, that makes it very hard for you. As you say, you just can't dog food. You can't try the product. People at Facebook use Facebook, and that's how you make the product good. Right, right.

**[1:12:04] Luana Lopes Lara:** So that's why it's so important for us to just be asking the users all the time.

**[1:12:07] Tarek Mansour:** Yeah, yeah. That's so interesting.

**[1:12:10] Luana Lopes Lara:** It sucks.

**[1:12:10] Tarek Mansour:** But the power users, the super forecasters, are a lot of what influences where it goes because they're very engaged.

**[1:12:15] John Collison:** You guys presumably spend a lot of time with those power user super forecaster types and just have them on speed dial.

**[1:12:22] Luana Lopes Lara:** They're there day one. So you want to make sure they're happy.

**[1:12:26] John Collison:** Last question. Where do you guys want to see prediction markets policy go? Like when you're talking to someone in government or if you had a magic wand, what are you arguing for?

**[1:12:38] Tarek Mansour:** Our sense as a company, and I think this may differ a little bit from like, I would say like your average tech company. or big tech company. So we are pro-innovation. Innovation needs to happen in America. You know, we have to lead and we have to do it right. And we have to win. Like we have to be, you know, all the things that Americans want to do or we need to win as a country we should have here.

**[1:13:03] Tarek Mansour:** But we're also pro-regulation. And so at a higher level principle, like there's usually this tension that, you know, generally it's like, you know, it's like the policymakers like want to regulate.

**[1:13:13] John Collison:** I think you're maybe more like a traditional financial firm in that way, right? Where maybe Silicon Valley, you know, a lot of firms grew up in an unregulated way, but financial firms have always had a regulator and that's just a fact of life. It's just a constraint for you to work with.

**[1:13:27] Tarek Mansour:** So it's part of the culture. And again, we spent four years getting regulated up front. So it's part of, but we believe in regulation. Like I think it's important because, you know, regulation is a bit like insurance. It's like it's protecting you from things going wrong and bad times. And so when I think about like, okay, where this lands? I think anything that is oriented around preserving these in America and making sure we win, but then elevating the fairness and transparency of the markets.

**[1:13:52] Tarek Mansour:** Anything that's oriented, like how do we make it more fair? Ban insider trading. Add more restrictions on, for example, like, you know, government officials, members of Congress trading on, like, you know, information they shouldn't trade. I'm obviously a big fan of, like, banning insider trading for members of Congress.

**[1:14:05] Luana Lopes Lara:** We talked about it.

**[1:14:08] Tarek Mansour:** Presumably you mean just banning trading, period, for a member of Congress.

**[1:14:10] Luana Lopes Lara:** I think it's not a bad idea. Yeah, that's how we kind of think.

**[1:14:14] Tarek Mansour:** But I think, and then things around like, you know, creating also social fairness and transparency because of all the questions that we asked. Like if people are basically trading on politics, let's have all the trade data be as public as possible so anyone can audit it, anyone can see it, which is a good thing, right? Now you don't know, like imagine a poll where you can check every single person that basically got, and the general public can check who was polled and what the sample was like.

**[1:14:40] Tarek Mansour:** and and then anything around customer protection and because that is important long term um in the sense that like when you build a consumer product and it goes mainstream there is like a massive sort of like burden on the on the other companies to educate and you've seen it like you know over and over um and in our case you know you want to make sure that people like know what they're getting into they're not like overextending themselves in terms of like how much they're sort of trading.

**[1:15:09] Tarek Mansour:** They're not like getting into an area of discomfort. And how do you kind of like, you know, we can do as much as we can do on the marketing and on the product side, but like we need policymakers and regulators help to basically make it an industry standard, but also help us elevate ours.

**[1:15:22] Luana Lopes Lara:** By the way, we're pro that. I think that like even the classic retail broker just should also be adopting a lot of these customer protections that we're talking about that they don't. I think that every retail trading platform should be taking a lot of these steps.

**[1:15:35] Tarek Mansour:** Yeah, I mean, And that's sort of our general view. And we hope that this is sort of the direction that things take. Because, you know, there's kind of, you can have a variety of views, right? And some people believe that like, hey, like, you know, any type of speculation should be banned. Whether it's in the stock market or crypto or prediction market, we don't believe that. Like, you know, we think that would be a bad outcome for all the reasons.

**[1:15:55] Tarek Mansour:** Because there's a lot of upside to having liquid markets and a variety of different things. But also because if you ban it, you're actually heightening the risks that you're trying to prevent. because now that activity is going offshore, right? And you cannot monitor it or police it or do anything to protect it.

**[1:16:11] John Collison:** Awesome. Well, thank you, guys. Thank you.