- 4 hours ago
Prediction markets have become mainstream and are changing the way fans engage with music and pop culture. Kalshi COO and co-founder Luana Lopes Lara joins Billboard On The Record to discuss how the platform is expanding into new categories and giving music superfans the ability to put money behind their favorite artists and predictions. She breaks down why she believes it was essential for Kalshi to be fully government regulated, how the company views insider trading and why she sees music and entertainment as essential to the platform's future.
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MusicTranscript
00:00We did over three billion dollars last week.
00:02Just on music markets last year, we did 70 million dollars traded.
00:06And this year, just to date, over 400 million.
00:09Just on the Super Bowl halftime show opener, it was 110 million dollars.
00:14I also wonder though if it's actually telling the future or if it influences the future.
00:19Getting more information is very good.
00:20There's still the issue of potential addiction to betting.
00:25We don't make money when our users lose.
00:26I wonder how it's going to affect the fan experience.
00:29Biggest users is an Ariana Grande super fan.
00:31Found Kalshi and now he's made over $100,000.
00:34Just predicting chart positions for her music.
00:41Prediction markets are everywhere.
00:43From betting on the outcome of elections to the winner of the Super Bowl
00:46to what's going on on the top of the music charts.
00:48Sites like Kalshi and Polymarket are finding a way to monetize knowledge
00:51about anything and everything happening in the future.
00:55Today, I'm joined by Luana Lopez Lara, COO and co-founder of Kalshi,
00:59to answer the burning question that I've had for a long time.
01:02How is this going to impact the music industry?
01:04Okay, Luana, welcome to On The Record.
01:06Thank you for having me.
01:07I'm excited.
01:08I'm excited for you to be here.
01:09I hear you're a big music fan.
01:11I am.
01:11I really am.
01:12So, who are you listening to during the work day?
01:15I think this week, I think everyone's listening to Justin Bieber after the Coachella performance.
01:20Cat's Eye, Justin Bieber, just honestly doing everything I saw in Coachella.
01:25I didn't go, but I watched the videos.
01:27I did a lot of watching at home, but it actually just kind of made me sad that I wasn't
01:31there.
01:32Right, right, right, right.
01:33But at the same time, I do think that right now Coachella has done such a good job with their
01:37live stream
01:38that I feel like I'm probably getting a better experience at home than being in the crowd.
01:42I don't know.
01:43That's fair.
01:43I used to be like crazy about Coachella.
01:45I think I went like five years in a row when I was in college.
01:48Uh-huh.
01:48And there's something about the energy there that's like not in the live stream, but I
01:53see what you say.
01:53It's like, I think it was Eminem or maybe Beyonce even that I was in the very back.
01:57I was having the time of my life, but I really, they were so small, I could not even see
02:00what
02:01they were doing.
02:01But Coachella's great.
02:02That crowd is like huge.
02:03It just stretches forever and ever.
02:06Right, right, right.
02:06Okay.
02:07Well, we're not here to talk about Coachella exactly, but maybe there were some Kalshi bets
02:11on Coachella.
02:12There were.
02:12Sure.
02:13There were on like, who was going to like, which songs were going to be performed, all
02:17those things.
02:18We had markets and all of those.
02:19Yeah.
02:19Well, okay.
02:20So of course you are the co-founder of Kalshi.
02:23I said on this show in January, I had all my coworkers come on and we were talking about
02:27predictions for the year.
02:28Nice.
02:28And I said that my prediction was that prediction markets would increasingly become a
02:33part of music and about the fan experience.
02:36And so from there, I was kind of like, I need to find a way to integrate this more into
02:40the
02:40show because I'm just really interested in the topic.
02:43And then I was just like, you know what, I could just reach out and see if Luana would
02:47come on.
02:48Amazing.
02:49Yeah.
02:49And I think your prediction is right because just on music markets last year, we did $70
02:54million traded.
02:55Wow.
02:56And this year, just to date, I think it's over $400 million.
03:00Whoa.
03:01I think it's, yeah, just on the Super Bowl halftime show opener, it was $110 million.
03:08Wow.
03:08Well, wait, so what's the over, is that the national anthem that Charlie Puth did?
03:12Or is there?
03:13No, it was the first song that Bad Bunny was going to perform.
03:15Oh, the opening track.
03:16The opening track.
03:17Just added $100 million, which is bigger than all of music last year.
03:21It's one of our fastest growing categories.
03:23Yeah.
03:23Wow.
03:24That is fascinating.
03:25Okay.
03:26Well, okay, before we get too deep into all the stuff about the Super Bowl and all of these
03:30other events that people are really gravitating towards Kalshi for, I think we need to just
03:34set the tone.
03:35Most of the people who listen to our show work in the music industry in some way.
03:40They're musicians, they work at record labels, or they're super, super fans.
03:45So they might not be quite as familiar with prediction markets.
03:49That's fair.
03:49Yeah.
03:50So tell me about what is a prediction market, what is Kalshi?
03:54Yeah, absolutely.
03:55Prediction market is, you think about it like the stock market, but instead of trading stocks,
04:00you're trading what's going to happen in the future, right?
04:02So you think about buying and selling shares of future events.
04:05So for example, who's going to win an election, you can buy a share of Gavin Newsom.
04:09And, you know, as his stock goes up over the years, you can buy more or sell and make money
04:16that way or way to a settlement.
04:18So it's really a way to get exposure and make money on what you're really passionate
04:22about and know a lot about.
04:23Because in the past, if you knew a lot about companies or like what Costco financials
04:28are or Meta, you can still buy stocks on that.
04:31But if you have interests and hobbies and you're an expert on something outside of the financial
04:36world, it's very hard to find a way to make money on that.
04:38And that's what prediction markets are really enabling.
04:41So you mentioned superfans.
04:42Actually, one of our biggest, one of my favorite users, one of our biggest users is an Ariana
04:46Grande superfan.
04:48He's actually a public school teacher, but been running this massive Twitter account for
04:54Ariana Grande.
04:55Basically, every single paparazzi picture of Ariana Grande I see because of his Twitter.
05:00But he found Kalshi and now he's made over a hundred thousand dollars just predicting
05:03like billboard, like chart positions for her music and, you know, for her movies and all
05:08of that.
05:09And we have over 10,000 markets from economics to music, to movies, to sports, everything
05:14in between.
05:15Wow.
05:16That's crazy.
05:16I mean, okay.
05:17So prediction markets though, the idea of it predated Kalshi, right?
05:21Like people have been talking about this for a long time, but nothing had been like totally
05:26regulated and legal in the US up until Kalshi, right?
05:30Exactly.
05:30Tell me more about that.
05:31So prediction markets like this, this concept of information markets, right?
05:35You can trade on predictions about the future.
05:37They've been around for like many, many, many decades.
05:40There's like labs and big school, like big universities that are just focusing on researching
05:45these types of markets.
05:46But really the elephant in the room, the real problem is they weren't legal in the US.
05:50They were kind of like, is this kind of a futures market, but how do you regulate it
05:55as a future?
05:56And when we started the company in 2018, the most important thing from us from the
06:00start is if this is going to be a real market and a very big market, it needs to be
06:04legal
06:04and it needs to be regulated.
06:05Like going offshore, doing everything in like a sketchy way, which is not the way to
06:09do it.
06:10So we went and took three to four years to get regulated, convinced the governments,
06:14the Commodity Futures Trading Commission.
06:16It's funny because it's exactly the same regulator as like grain futures.
06:19So very, very different in interest rate swaps and crypto and all of that.
06:23And it convinced them that these are actually very important markets that should exist in
06:27the US and should exist in a regulated safe way.
06:30And yeah.
06:31And then when we were able to legalize it, we always say that the moment it became legal,
06:37it would be a lot easier to just, it would just grow because there's so much interest
06:41in this stuff.
06:41Yeah.
06:42Well, okay.
06:42So there are other, you know, prediction markets that are popular that are offshore.
06:47Right.
06:47Polymarket being one of them.
06:48Right.
06:49I mean, you guys took a big risk, in my opinion, in deciding that you wanted to go the route
06:53of getting legalized in the US, knowing that it would slow you down by potentially years.
06:57Right.
06:57And it did take years, right?
06:58It did.
06:58It took years and it did slow us down a lot.
07:00Okay.
07:00So one of the big things I report on at Billboard is the rise of AI music.
07:04And I was thinking about y'all's story and how long it took to get regulated.
07:09And it's not a perfect one for one, but I was thinking about like these AI music companies,
07:13you kind of have them fall into two buckets.
07:15There are some AI music companies that are more like move fast, break things, let's launch
07:21with, you know, training on a lot of copyrighted material and just hope that this fair use argument
07:26works out for us.
07:27Right.
07:27On the other hand, you have these companies that tried to go through the laborious licensing
07:31process with all the music companies and it took them forever.
07:35And some of them are, I know there's like one of them in particular, I'm not going to
07:38call them out, but they have been waiting to launch for like three years.
07:41And they'll announce that they have a partnership with the new music company, but they still haven't
07:47gotten totally across the finish line.
07:48It takes so long.
07:49Right.
07:49I'm wondering, like, was there a point in time when you're going through this process where
07:53you thought is like, have I made a mistake here?
07:57Like, is this taking way too long?
08:00Are we going to lose our position?
08:01Yeah, no, absolutely.
08:02And it's very interesting because not just us, but everyone around us thought our strategy
08:07was wrong for the longest time.
08:09All of our investors, like, not all of our investors, but some of our investors, a lot
08:12of people in Silicon Valley, because they would look at offshore and be like, look, they're
08:16able to have a market, they're growing, they're doing all these things.
08:18And you guys are still fighting regulators.
08:20Like, why, why are we doing that?
08:22And it was very tough for us to keep kind of very true, like, keep to our path in a
08:29way
08:29and keep to like what we thought was the right way to do this.
08:31And I think it panned out, right?
08:33Obviously, like immediately when we got, we got regulated, but then we also had to sue
08:37the government because they were stopping us from like, not following the law, not letting
08:41us do certain things.
08:42And we had to sue them to be able to list election markets was the first one that went that
08:46way.
08:46And then after that, we grew so much, like I think it was 12x in the past six months or
08:51something insane of just how fast we're growing.
08:53And a lot of it is because we built that trust with the users and we built that trust with
08:59all these stakeholders that are related to these markets in some way.
09:03And it's very tough to do that.
09:06It's like, it's very easy to just take the easy path.
09:09But I think if you're trying to build a long term company, especially I would imagine, I
09:13don't know enough about the AI music situation, but I would imagine that like, you don't want
09:19to burn the relationship with the people that are actually doing and producing the music that
09:23you know that it sounds like a very short sighted thing.
09:27And for us, it was very complicated to do it.
09:29I was very complicated kind of like psychologically in a way to do it that way.
09:33But I think it really panned out and it's the only way that these markets are actually growing
09:36a lot in the U.S. now is because we took the hard path.
09:39And now everyone's kind of following us, right?
09:41Everyone's trying to come to the U.S. and do these things.
09:43And in a way, it's like you need these markets to be safe.
09:46You need a ban inside of trading.
09:48You need to know who's trading.
09:49It's very like these things that make it legal and take time to get right are actually extremely
09:53important.
09:53So you shouldn't just go around them.
09:55Yeah, yeah.
09:55And I'm wondering if you can explain how this is different from gambling or sports betting,
10:00because it kind of feels like that sometimes.
10:03Absolutely.
10:03So the main difference is the mechanics are completely different, right?
10:07If you're trading on Kaoshi, you're trading against someone else.
10:10Think about it as an actual market, right?
10:12You want to buy Harry Styles having a number one album this year.
10:16There's someone that thinks Harry Styles won't have a number one album.
10:19And you guys are agreeing on some odds or the price and you're trading against each other.
10:24But all that Kaoshi is doing is we get the money from both of you, hold it.
10:28And then when one of you is right, we just allocate it to the right person.
10:32So we don't make money when people lose.
10:34There's an actual, transparent, competitive market for prices and all of that.
10:39And that's why we also can scale to so many more markets.
10:42I do think, though, there's still like the issue of potential addiction to betting on
10:48or is betting even a term that you would use?
10:51We use trading.
10:52We use trading.
10:52But people say betting in the stock market, too.
10:54So it's just like it's a colloquial term that people use.
10:56That's fine.
10:57Betting, trading, you know, using Kaoshi, it still can for someone who has an addictive
11:02personality, they might still get carried away in the same way that they would with
11:06a traditional kind of gambling sports betting situation.
11:10So how do you guys mitigate those risks?
11:14Because, I mean, addiction is certainly a big factor here.
11:18No, absolutely.
11:18And we take this extremely seriously.
11:20So there's two parts.
11:21One is we provide a lot of tools to the users.
11:23They're actually a lot more and better than any of the sports betting gambling companies do.
11:28So an example of something that I think is very bad and I learned this about the sports betting industry
11:32is
11:33you can technically mark yourself as self-excluded.
11:35So you think you have an issue and you're like, I want to be self-excluded.
11:38I don't want to participate anymore.
11:39Please block me.
11:40Mm-hmm.
11:42There's only one state that actually doesn't let you keep marketing to that person.
11:46Oh.
11:46Most states you can, even the person said, I have an issue.
11:49Please stop marketing and offer me this product.
11:51Most states actually have no regulation against you just marketing against this person or just
11:55going across state line and doing the same thing.
11:57And because we're federally regulated and I think we don't make money when our users lose.
12:02We make money when they're like engaged and actually making money and having a positive experience.
12:06We actually take protection like way more seriously on that front.
12:10So we have a lot more tools and we stop any marketing, any, you know, you won't get a single
12:16push notification if we notice in our systems that there is any type of issue.
12:20And then there's a part of the user doing it.
12:22The other side is we have a lot of AI machine learning systems that surveil all the markets
12:26and market activity looking for issues like this as well.
12:29So if we notice someone's losing a lot of money or showing any sign of an issue like that, we
12:35start stopping the user.
12:36We stop deposits.
12:37We stop this.
12:38We reach out to them.
12:39We kind of send a lot more educational materials and all of that.
12:42Cause that's not what we, we're not doing this to, you know, casinos, like house always wins, make money.
12:47That's not what we're doing.
12:48We really believe what we're building is a way for people to make money on what they know and engage
12:53and interact with the world around them and what they're passionate about.
12:56And it's all these safeguards are very important for us to take them very seriously.
13:00Yeah.
13:00And I mean, you've already mentioned it, but insider trading is obviously a big concern when you're betting, when, when
13:05you can trade on absolutely anything, basically.
13:09Um, there is certainly, you know, going to be a lot of users that might have some institutional knowledge.
13:15And I'm kind of wondering where the line is and how you guys are self-regulating and also how the
13:21CFTC, which regulates you guys are also getting involved in insider trading regulation.
13:25Yeah, no, absolutely.
13:26So insider trading is banned on Couch.
13:28So what that means is if you cannot share some sort of information, for example, if you work, um, if
13:34you were a dancer in Bad Bunny's concert and you have an NDA that you cannot say what he's doing,
13:38you cannot trade on that market at all.
13:41That's kind of like what the stock market uses for insider trading.
13:43They're like, if you have a legal like contract that says you cannot use this information, you cannot trade on
13:49it.
13:49That's illegal. That's a crime. You can go to jail.
13:51Okay.
13:51We actually take it a step further.
13:53Okay.
13:53So we actually, on top of just the legal, we have trading prohibitions that are, we enforce them.
13:58Uh, so for example, if you are related or have access to some information that way or all of that,
14:04then we are going to ban you.
14:06Even though the federal regulation doesn't say it's necessary, we take that extra step to stop a lot more people
14:11from doing it.
14:11And the way that we can do it is we have KYC information from everyone.
14:15So name, date of birth, social security number, all of that from every single person in the platform.
14:19And because we're federally regulated exchange, we can actually run investigations and put fines.
14:24And honestly, you can go up to the DOJ and you can go to jail if you're actually like infringing
14:28some of our rules.
14:29Um, and we've put a lot of cases out kind of showing these are like the, the, you can all
14:33withdraw winnings and your fines are significantly higher.
14:36Um, and all of that, but it's, it's obviously a complicated problem, right?
14:39And the stock market is the same thing.
14:40Uh, but we really going above and beyond on, on while we're blocking and how we're mitigating and looking at
14:45all the information we, uh, we have.
14:47Got it. And so how big is your, uh, I don't know, what do you call it? A security team
14:51or?
14:52Yeah. So it's around like 15 or maybe even like right now we hired so many people for the surveillance
14:56team.
14:57We call it surveillance.
14:57Surveillance team.
14:58Market integrated surveillance.
14:59Yeah.
14:59It's like 15, 20% of the company right now. It's like, Oh, it's over like, I think.
15:04Yeah. It's like over 35 people involved.
15:06Oh wait. Okay. So that's actually your, your company is smaller than I thought.
15:09Yeah. We're pretty, we're pretty small. Like, yeah.
15:11Like I think by the end of the year, if we're 200, I think that would be like, yeah, I
15:16mean, we're like 200.
15:17Like maybe 300, but we are, we're pretty small still.
15:20Man. Okay. But what, uh, I don't know if you know this off the top of your head, but what's
15:23the trading volume for like the last month?
15:25Like.
15:26Right. Um, I think we did over $3 billion last week.
15:29So I think that there's a lot of, uh, the company grew very, very fast.
15:34Uh, and yeah, but the good thing about our company also is that it's so scalable, right?
15:39Once we build kind of like the primitives of how a market can go and how to like surveil and
15:43how to like make these trading prohibitions, we can scale it very fast.
15:46Like the engineering in a way is like not. Yeah. Yeah. A lot of the things that we do more
15:49people are exactly things like surveillance and compliance and finance and all of that.
15:53Yeah. I think like my, my only concern though, is that with such a small company, I know that you're
15:59using like AI tools and stuff.
16:01You have all these different kinds of safeguards to try to automatically detect things. Right.
16:06But there are just so many people that might have connections that you just can't really know about from a
16:10KYC check.
16:11Like what if someone interned with Bad Bunny's manager and that's not listed on his LinkedIn?
16:17It's like, you know, one of those under the table internships, like they could know what the set list is
16:22of the Super Bowl.
16:23Right. And I mean, it's, it's impossible to say there's going to be no insider trading whatsoever, right?
16:27Like this, like it's the same way in the stock market. It's impossible to make that claim.
16:31However, when we, when we say like the first level of the investigation is we notice something weird and we're
16:36going to get their, you know, how, where they worked and who they are and all their information.
16:41But there's actually a compliance investigation that people need to comply.
16:43So we're going to like send them an email being like, you need to, you know, there is an investigation.
16:47You need to show up with a lawyer of these dates and there's like actual questions that they need to
16:52answer.
16:52And so proof of what they were doing and all those things.
16:54Um, but yeah, I, I will never claim that it's, there's no insider trading happening whatsoever.
16:59Um, but I'm very, very confident in our surveillance systems.
17:02We were, we just put two cases out on actually a Mr. Beast editor that bring that up.
17:08Yeah. Yeah.
17:09Mr. Beast editor.
17:10And there's also a California, um, I think governor candidate that was trading on himself dropped out.
17:16I don't know.
17:17Something like that.
17:17Yeah. I'm not exactly in the race.
17:19Yeah, exactly.
17:20And I think that the biggest thing is because it's an actual regulated exchange, like there is a process that
17:24sometimes can take many, many months to years to actually, we're actually like charging someone of a crime.
17:30Like it's, we actually need to go through a long process of giving them the chance to respond and say,
17:35and send more information and us to send more information.
17:37So there's a lot of things that the team's working on.
17:39It just takes time for it to like come public.
17:41Got it. And then what's your business model?
17:43Are you taking a percentage of, you know, each of them?
17:46Yeah. Of like, not of like how much people trade.
17:49So if I trade with you, we take a, a, a, a cut, a small cut from there.
17:52Got it. Okay. Okay. Yeah.
17:54I was going to bring up the Mr. Beast editor thing.
17:56I've also heard you guys say before that, um, there's certain like, uh, people who are involved in sports and
18:02various industries that are banned from the platform.
18:04Have you banned anyone from the music industry?
18:07We have not yet.
18:08So actually that adds to what we were talking about inside of trading.
18:11So on top of the legal standard and the trading prohibitions we put on top, one thing that we do
18:16that no one else does is we, we, for some people, we stop them from even trying to trade.
18:22So that's not even the stock market does, right? Like if you work at Facebook, it doesn't matter your position.
18:26You can soon trade on the stock market and then they'll try to figure out what's happening with us.
18:30We just stop it from the start.
18:31So for example, if you're an athlete, if you're in the NBA, you cannot trade on NBA markets and you
18:35won't even be able to attempt to do it.
18:37You're just completely blocked.
18:38Um, we haven't done that for the music industry yet, but you should, you should, because I have like some
18:44friends who have joking, jokingly, hopefully jokingly, like texted me being like, you know, should I trade on this?
18:50I'm like, don't, please don't go to jail.
18:53Yeah.
18:54Please don't do that.
18:55Yeah.
18:55The music industry is a place where everyone talks amongst each other and, you know, record labels.
19:00If you're inside them, you do get to have a lot of knowledge about when album releases are happening.
19:06Right.
19:06Maybe they do some predictions on where they're going to be on the charts internally.
19:10So they could probably predict, well, what's going to be on the charts externally on a place like Kalshi, but
19:15yeah.
19:15And by the way, that's one of the, one of the most exciting things, uh, is actually working with the
19:20industries to figure out where this line should be.
19:23So for sports, for example, is you actually work with the leagues and the leagues are like, well, these people
19:27need to be banned here.
19:28We're concerned about this.
19:30We don't want this type of market.
19:31And we work with them to figure out exactly how to have the best product.
19:33And I think that as we expand to more and more categories, that's something that like we actually should be
19:38working more of the music industry to figure out kind of a lot of these things.
19:41And I think just to draw one distinction, though, there's a difference between side information and information.
19:45Right. So if you look at the Super Bowl for Bad Bunny, there was actually a trade on Kalshi that
19:50was outside the rehearsal.
19:53I think it was on a Thursday listening.
19:55Oh, so was he outside the stadium?
19:57Outside the stadium, on the street, and he heard that Lady Gaga was in there.
20:01So that is the same way that, for example, if you look at Two Sigma and Citadel, like in Wall
20:06Street, they have like satellites looking at Starbucks locations, seeing how many people are coming in and out so they
20:11can forecast the stock market.
20:12Right.
20:13And I think there is like, um, we actually, more information is good.
20:16That's why the forecast from Kalshi is so good.
20:18Like if you look at our album sales, right, like our markets, they're forecasting album sales extremely well because people
20:25are putting money where their mouth is.
20:26So they're able to, they are looking for alternative sources of information.
20:29They're looking for different data sources.
20:31They're looking for trying to figure out new correlations between streams and other things to really try to get a
20:35better forecast to make money.
20:37Um, and getting more information is very good.
20:40Just if you have access to unfair information, that's very bad for the markets.
20:43So that's where the line, we draw the line.
20:45Got it.
20:45And I've seen reports that prediction markets can often be better than polls.
20:50So why is that?
20:51Can you explain that?
20:52No, absolutely.
20:53It's because people are putting money where their mouth is.
20:55Uh huh.
20:55So people have an incentive to try to be correct.
20:58Right?
20:58Like if I ask you, like if I, you ask me, I'm a big Taylor Swift fan.
21:02If you ask like, Oh, is Taylor Swift going to be number one?
21:04I'm always going to say yes.
21:05Yeah.
21:05But if you're saying.
21:06Honestly, yeah.
21:07I chose a bad example because she probably will.
21:10Um, or like Harry Styles.
21:11I was a big director.
21:11So like, um, but if you actually ask someone to put money on it, they're going to, they're
21:18going to take a step back and think about it.
21:19Like, well, this album, maybe it's this new genre.
21:22I'm not so sure if that's going to do very well.
21:24It's fewer songs.
21:25It's all those things.
21:26And they can take a more calibrated view of it.
21:28And they're going to research.
21:29They're going to go online.
21:30They're going to look at Twitter.
21:31They're going to like look at billboard.
21:32They're going to try to figure out how to have a better forecast.
21:34And what the markets actually do is that they get all these people that are incentivized
21:39and summarize it in one number.
21:41So you actually, instead of getting one big, great forecaster saying, I think these
21:46will be the album sales for Olivia Rodrigo.
21:47You actually aggregating all of those guys and having, bringing even like an incentive
21:52for new experts to show up and bring this, this mark.
21:54So for example, in the election market in 2024, Couch was forecasting Trump to win at around
22:0064, 65% chance the entire time, even though the polls were around 50, 50.
22:05And that's really happening in every category.
22:07The Federal Reserve also put a paper of like how on the economics, like the macro economy
22:12and all of that, our markets are a lot better at forecasting than like big economists out
22:16there.
22:17And it's just the fact that if you're incentivizing people to bring good information to the market,
22:22you just get a better forecast.
22:23Well, okay.
22:23So I also wonder though, if, you know, if it's actually telling the future or if it influences
22:28the future in a way, if someone sees on Couchy that Trump is like, you know, favored to
22:33win, are they more, well, I don't know, maybe that example doesn't make a ton of sense, but
22:38do you ever feel like it influences the future?
22:40You actually bring up a great example.
22:42It was the Mondani race in New York was where people were talking about this a lot.
22:46And I think there were, he was around that I think 94% chance of winning.
22:50And then one people were, one side people were afraid that because he's so high up, maybe
22:54like the odds are so good that maybe people won't show up to vote.
22:58Yes.
22:59Way better example than mine.
23:00But then on the other side, people were concerned that like, well, because the odds are so low,
23:04it's going to motivate all the other side to go vote.
23:06And I think it's the same, it's the same thing as a poll, right?
23:09Like if you see a poll that it's like, you know, Mondani is definitely going to win.
23:12It's, it impacts things the same way.
23:14And it's like in the, in the end, what we believe is it's better to have accurate information
23:18than not accurate information.
23:19It's better to have a market that is, we know at least is a good source of information than a
23:24poll that we don't know who paid for it.
23:25Or we don't know, like, I think the same thing in the, the, the movie industry of like,
23:29who is actually trying to make Oscars campaigns and saying certain things.
23:33It's just better to have an accurate source of information.
23:36Um, there's been a lot of research from a lot of these labs that I told you on universities
23:40looking into these markets that actually show there's actually no impact on, on like the real
23:44outcome of things.
23:45If you compare like races with markets, without markets, um, and, and, um, all of that.
23:50And in general, it's just better to have nowadays, it's all clickbait on the internet.
23:54It's a lot better to have like some like accurate source of information.
23:57Yeah, that, that's super interesting.
23:59I I've been thinking about that a lot when I was doing my research on prediction markets
24:02ahead of this interview, but also I, I recently had an episode of the show that ultimately
24:07ended up going a little viral of, um, I had on these viral marketers.
24:12Um, they're called chaotic good.
24:13They're used by a lot of people in the music industry.
24:15And one of the things that they do are these narrative campaigns online.
24:18They have a bunch of different like kind of burner accounts that they make on social media.
24:22And so if you were to go on SNL though, this was their example.
24:26If you go on SNL and you perform there, they could have essentially all their accounts
24:29comment.
24:30This is the best thing ever.
24:31I loved this.
24:32It was amazing.
24:32And it kind of influences.
24:34Exactly.
24:34Other people.
24:35Cause they're like, okay, other people like it.
24:37So clearly there's something here.
24:38Right.
24:39And it might influence your thinking.
24:40And so I wondered if maybe prediction markets fell into that same category
24:43of kind of like online, um, influence, but.
24:46Well, we almost see it as the antidote to that anyway, because I think that what prediction
24:51markets are very good at is on Twitter.
24:54If you say some reasonable take, you're going to get two likes, right?
24:58If you say something insane, you're going to get like go viral and like whatever, and
25:02all those things.
25:03But prediction markets, because you're not incentivizing virality, you're incentivizing
25:07being right.
25:08You get paid.
25:09If you're right, then you have a way more kind of like common sense, kind of like normal,
25:15like a better forecast of what's going to happen because the incentives are different.
25:19So we actually see a lot of it as like, you go to, to Twitter and they're saying insane
25:23things about, um, you know, the economy or doing COVID that was everything about was
25:27all like COVID is over or COVID is going to kill everyone.
25:30It was awful.
25:31But the markets were very good at forecasting.
25:33It's almost an antidote to the kind of clickbaity social media side.
25:37Interesting.
25:37Okay.
25:38So I know sports have been a really popular category for you guys.
25:41I think at one point it was like over 90% of trading on Kalshi, but now it's down to
25:45about what?
25:4670.
25:46Yeah.
25:47It's going down.
25:48Yeah.
25:48It's going down.
25:49I think very, very fast.
25:50Actually at the end of last year, it was around 93 or, and now it's already at 70.
25:53Oh, wow.
25:54Okay.
25:55Things are changing super, super fast.
25:57Right.
25:57And it's just because they're like, everything is growing so fast, but it's just like the other
26:01categories are growing even faster than sports.
26:03Yeah.
26:04Yeah.
26:04Well, I was going to ask, like, I mean, that doesn't leave that much space left over for other
26:08categories, including music.
26:10So I'm wondering if you have any idea ballpark of how big music is in Kalshi and the prediction
26:16markets that you offer.
26:17Yeah.
26:17I don't know the exact percentage, but music is growing a lot.
26:20I think that the example of like, just in like Q1, right?
26:23Q1 and like half of a month of Q2 is $500 million traded.
26:27Last year, all of it was 70 million.
26:29And I think that we're seeing a lot in like, um, music also movies is doing very well.
26:33We have the Rotten Tomato markets or what the scores are going to be.
26:36Those markets are very, very big, um, as well.
26:40And yeah.
26:41And we're adding a lot more markets to, for example, like number of streams on Spotify
26:44and all those things that you can have kind of like more granular view, um, of certain
26:48things and, and, you know, uh, TV shows and all of that.
26:52I think that I don't know the exact percentage of, of, of the entertainment is, but it's actually
26:57I think our fastest or second gross, fast growing, fastest growing category outside.
27:01I think crypto is number one and I think entertainment is number two.
27:03Interesting.
27:04Okay.
27:05Okay.
27:05Well, so are there any, uh, music markets in particular that you are interested in things
27:11that you find to be particularly fascinating?
27:14Oh, a lot, a lot.
27:15I think that, um, there was just a very recent flip that actually Olivia Rodrigo is going to
27:20have the top streamed album this year on Spotify that I think is because of the new album.
27:25But I think that, um, that is one that we were watching.
27:28Obviously we, everything related to Coachella, we were watching for the first, um, weekend,
27:33but some of our biggest markets are, for example, who's going to be, have a number one album
27:36this year.
27:37So you have like Drake, I think is at around 80%.
27:39And some of this is interesting because having a number one album might mean you need
27:42to release an album.
27:43A lot of it's uncertain.
27:44Will this person release an album or not?
27:46Or, you know, Justin Bieber, just because his odds are changing a lot just because of his Coachella
27:50performance.
27:51Right.
27:51So I think it's just, um, there's a lot of very cool, like every year the Grammys are
27:55very big as well.
27:56All of that.
27:56Yeah, I'm sure.
27:57I'm sure.
27:58Well, with the Olivia Rodrigo thing, I'm going to say if I were betting, I'm not for the record.
28:03I'm not.
28:04But if I was, I would say that I don't think it's going to be her.
28:08Not because I don't think she's, well, she's right there.
28:10And not because she's not extremely popular and amazing.
28:12I really do love Olivia Rodrigo, but she releases really short albums.
28:16Right.
28:16So she releases like 10, 11, maybe 12 tracks per album.
28:20And that's what she's done for the last two albums.
28:22So I feel like with this third one, I can't imagine her doing one of those like, um, Scorpion
28:28by Drake moments where she drops like 30 tracks or Tortured Poets Department, the anthology
28:32where it's like over 30 songs.
28:34That's it.
28:35And I think that that does influence like the overall number of streams.
28:39And then it does ultimately influenced her performance in the end.
28:42Um, so that's, that's my prediction for today.
28:45There you go, everyone.
28:46Nice.
28:46The other one that we're looking at is I think Lollapalooza, like the headliner.
28:49And I think Lorde is the favorite.
28:51Okay.
28:51Interesting.
28:52Well, okay.
28:52But prediction markets are super binary right now.
28:55It's just like kind of one artist or another.
28:57Right.
28:57Yes or no.
28:58Right.
28:59So what, what is that market?
29:00Is it Lorde or someone else?
29:02Oh, I think it's, I don't know the details, but from what I understand is going to, it's basically
29:07a list of artists and you can pick who you're going to be.
29:09And I think there's going to be three, maybe like Coachella, for example, there are three.
29:12So if you select any of those, if you trade on any of the three, you can make money.
29:16But if you select anyone that was not a headliner.
29:18Got it.
29:18But you mentioned something very interesting that we actually going soon away from just
29:23the yes, no, and more into like linear type of thing.
29:26So you can, for example, if you think you can trade the album sales, not as like a between
29:32like above this number or below this number, but more like, I think it's going to like
29:36go up or like be higher than this and just have like kind of a more linear payout of it.
29:40So basically we're going out of just the binary yes, no, that's probably the best way
29:42to explain it.
29:43That's interesting.
29:44Okay.
29:44So one thing that I've seen that seems very different to me than the stock market, when
29:48you're thinking about prediction markets is that in the stock market, if you're a company
29:52that wants to become publicly traded, it's kind of like your choice that you decide to
29:56enter that market.
29:57Whereas in prediction markets, we're kind of trading on everything.
30:00It's just publicly available information.
30:02Right.
30:02And so is there a reality where you start moving towards partnerships where things are
30:09kind of like official, you know, partnered prediction markets, I guess?
30:15Yeah, that is a great question.
30:16And a lot of like these partnerships are something we're very excited about to explore
30:20and do also just not, not just on like the data that we settle, but like what we mentioned
30:26of what should we, what's the best product here?
30:28What's the most interesting thing and partnering with folks that understand these interests a
30:32lot better than we do to actually get the best product out there.
30:35The way that we think about prediction markets is almost like going like a, for example,
30:39if a TV show or the news are talking about an artist or talking about something, it's
30:43kind of the same thing of like getting information about the future or letting people engage
30:46with it.
30:46So that's why I think it's, it's, it's slightly different that we don't necessarily
30:49need these partnerships to be able to offer the market.
30:52But we would absolutely love to get a lot of these partnerships in place.
30:55We're working with a lot of folks like on sports, we're working with the leagues a lot
30:59in music and, and, and, and movies and all of that.
31:02We're working with, we're starting to work and have conversations on that.
31:05It's something we're very excited about.
31:06Yeah.
31:06Cause I was thinking about how much value Taylor Swift probably brings to the platform just
31:10by having her name there.
31:11And just by having people trade on, you know, what chart position her next album will land
31:16at and that kind of stuff.
31:17But yet she's not really part of it.
31:19And I, I wondered if there's any way for an artist or a music company to be part.
31:24Yeah.
31:24That is a great question.
31:25I think we see it more as like, like if you go to like a, if, if the news is
31:29covering
31:29something, right.
31:30It's like, if, if you know, I don't know, Fox news or CNN is talking about a Taylor Swift
31:36concert, they're also getting viewership on it.
31:38And it's unnecessary that they have a partnership there.
31:40And we see a lot of the Kaoshi kind of use case as news, as forecasts of bringing information
31:45to people.
31:4570% of our users just come to Kaoshi to see the forecast more than actually trade only 30%
31:51trade.
31:51So it's like that side of it.
31:53That's very interesting to us.
31:54But we really want to work with, with, with the, like all industries and really just
31:59like be the best product that we can.
32:01And a lot of it can be a lot better if we are like with partnerships with people that,
32:05as you said, can really make the product a lot better in a crucial part of it.
32:08Trading on Kaoshi, your users are anonymized, right?
32:11There's no way to really know exactly who's being trading on what, right?
32:15We know everyone that's trading.
32:17Okay.
32:17But other users don't know who they're trading against.
32:20Okay.
32:20So is, I don't even know if this is legal, but is it possible that you could sell that
32:25data to other companies?
32:26Like for example, what I'm trying to get out with that is that record labels often spend
32:31a lot of money doing contracts with third parties that are really good with data analytics.
32:35This is a way that they get a competitive edge on signing artists that are bubbling up that
32:39the data reflects, but you might not have seen it unless you're just trolling the internet
32:43all day, every day.
32:44And so that's like a really big part of their strategy is partnering with kind of data companies
32:49that can show them what the hottest new artist is.
32:51So could you ever imagine a record label, you know, seeking information, doing a partnership
32:57with Kaoshi to figure out where their biggest super fans are, what's bubbling up, that kind
33:01of stuff.
33:02Absolutely.
33:02And actually like, they don't even need a partnership with us for this.
33:05All of this data, obviously anonymized is available in public.
33:10So they can come to Kaoshi and they can sign up as like just a data user and they'll be
33:15able to download and like really look at the data of the forecast, the trades, how many
33:20people are trading, how fast these trades are moving.
33:22Because one interesting thing, for example, is like when you look at the Terry Styles having
33:26a number one album, right?
33:27Like when he dropped his single, the market reacts to that to be like, well, I don't think
33:32this type of song or this type of album would be very popular.
33:35So it maybe goes down a little.
33:36I actually don't know the specifics about the hair styles market.
33:38But you see this kind of like real time component or forecasts that are actually very, very valuable.
33:43And we, our goal of the data is like, obviously we're a for profit company, we need to make
33:48money, but the data that really, we want the, as many people as possible to use this data
33:54because we really see this as a social good that people should have better forecasts and
33:58should have access to a better way to see the future and decrease uncertainty.
34:02So if anyone wants our data, they can actually just like email us and they'll be able to
34:06get the data.
34:06No problem whatsoever.
34:07It's something we're very, very excited about.
34:08Interesting.
34:09Yeah.
34:09So one of the biggest buzzwords in the music industry right now is super fans.
34:14Everyone wants to capture value from super fans.
34:16This is kind of loosely defined as, you know, a music fan that goes to a lot of concerts,
34:21buys merch, you know, maybe even buys a vinyl record.
34:24Um, you know, all that stuff.
34:26They're very engaged.
34:28Right.
34:28That's basically what the shorthand of super fan means.
34:31And I know that there have been a lot of attempts in the music industry to try to capture
34:36that value.
34:36So there are a few startups that have tried different ideas.
34:39Like one startup called even has tried the idea of like exclusive windows before an album
34:44comes out on streaming services that you could consume an album if you pay extra money.
34:48Um, you know, Robert Kinsel, who's the Warner music group CEO has expressed interest in creating
34:55a super fan app of some kind.
34:57It's still hasn't launched.
34:58We'll see if it ever launches, but like he's expressed that.
35:01Um, that's an interest of his.
35:03Do you see Kalshi as a super fan platform?
35:07I guess.
35:08Absolutely.
35:09I think that actually the way you described it is, is there's a side of like, how do you
35:14actually monetize the fact that super fans are like, how do you sell merchandise
35:17and all those things?
35:18But there's the side of the super fan himself or herself of like, how do I actually monetize
35:23the infinite hours I put into this, right?
35:25That I'm like reading every single gossip and, and, and analyzing every Easter egg on
35:29a song and all of that.
35:31And Kalshi is a very good platform for the super fans to actually turn a lot of like their,
35:37their time and their hobby and their expertise into real money.
35:40And, um, we talked about the Ariana Grande super fan that was able to do that.
35:43There's another guy that that's like, he is like an IT professional, has two, three
35:48twin sons.
35:49And that that's, uh, is, and he's made, I think over $380,000 just on music markets because
35:54he's extremely passionate about music.
35:56And it's funny.
35:57Cause if you look at his profit on sports, it's $3, $3 on sports and $380,000 on, on just
36:05music.
36:05And I think it's like Kalshi is a great way to, for them to make money and also to engage
36:10and meet other super fans.
36:12So we're seeing a lot of like, we have the social part of the platform that all of them
36:15are engaging with each other.
36:15So it's like the Ariana Grande versus Taylor Swift.
36:18They're becoming friends.
36:19It's like, have you seen this, um, this way or like this poll or this, whatever.
36:24And they're able to do it that way.
36:25And I think that as Kalshi grows and we have more and more of these people that are experts
36:30in music and want to make money on it, there will also be a lot of like opportunities for
36:34partnerships that we can also, um, you know, connect the super fans with, with other platforms
36:39that are, they want to monetize from them and, uh, and offer them certain things and
36:43all of that.
36:43I do have to say, I, I wonder like how it's going to affect the fan experience that now
36:48you can, you can monetize and make so much money that you're paying off your student loans.
36:53Right.
36:53I think that that's what I heard about the Ariana Grande super fan.
36:57Um, when you monetize fandom, I just wonder like how that changes, uh, the fan experience.
37:05I don't know, as a fan yourself, how do you think it will impact the fan experience?
37:09It's a great question.
37:10And I think that honestly, the, the sports industry had a very similar kind of, if they
37:14allowed sports betting, how would that?
37:16And I think that all the, the leagues, the NFL, the NBA, all of them have seen just a
37:20lot more engagement because now it's like, you have even more incentive to research every
37:25single part of, of what you could make money or it just adds to like, you can just get
37:30more engaged and more excited about things.
37:33For me, like I'm personally, I'm a very like anxious person.
37:36So it's actually good for me when I'm like, I really care about this album being the
37:39number one of Taylor Swift, every new album that she releases, we have a market on where
37:43she has the top 10, uh, uh, billboard, like the top billboard top 10.
37:48And just watching that market is just like so exciting to me to just watch it in real
37:52time.
37:53Uh, and I, I like the fact that I have a source of information on it and it's not like
37:57just
37:58me going on Twitter and trying to see who is not a bot saying things and I can actually
38:02see a market.
38:02So to me, it's been, uh, it's been great.
38:04Obviously I can't trade, so I don't have the full experience, but.
38:07Yeah.
38:07Yeah.
38:08I mean, I, I think it, it, it'll be really fascinating to see how it impacts fandom long
38:13term.
38:14I do think one thing that I've experienced as a music journalist, I know all music journalists
38:18experience is that fans are very like rabidly, you know, passionate, protective of their
38:26artists.
38:27Right.
38:27I wonder if it's going to increase that passion even more.
38:31And that can be a good thing or a bad thing, honestly, because I think there's like this
38:35increasing parasocial relationship between, uh, fans and their favorite artists.
38:40Um, I'll be curious to see if fans are, you know, betting at all on, you know, an album's
38:46trajectory, like how that will impact the fan experience.
38:49But, um, I think that's something we have to wait and see over time.
38:53Yeah.
38:53One thing that, uh, it's kind of a parallel from another industry, but in politics, what
38:58we've noticed, and we've talked to a lot of the users and surveyed them is that actually
39:02the polarization somewhat decreases because of that, the user or the trader, they're taking
39:10a step back and thinking, well, if I am going to make money, do I actually think this?
39:13And in some ways it like, even though they, he loves Ariana Grande, like our, the user
39:18as an example that I gave, even though he loves Ariana Grande, he has, you know, he is reasonable
39:23about it and see like, well, maybe she's not going to get the Oscar for best supporting
39:27actress.
39:27Cause these other, you know, these other actresses have all these things and I'm reading all of
39:32that.
39:32And in a way I think that when, what we've noticed like time and time again with markets
39:36is that when people are putting money where their mouth is, they take a kind of a step
39:40back and think more rationally about things when they're engaging on the trading side.
39:46As we get more engaged, they're excited about it, but they kind of act in a slightly more
39:50rational way, which in politics we're seeing the decrease of polarization.
39:53So we talked to people before they trade and after they trade and you see their engagement
39:57of like, well, I thought Trump, I'm a big supporter of Trump.
40:00I think Trump's going to win, but you know, like voter turnout is probably going to be
40:05a lot higher in these states that are very liberal and blah, blah, blah.
40:08And they kind of just calibrate themselves more.
40:10And that calibration is very interesting.
40:12Yeah.
40:12Well, I would love to see the stands be a little bit more rational sometimes.
40:16So that'll be interesting if that's the outcome in the end.
40:19That's fascinating.
40:21That is fascinating.
40:23So yeah, one of the things that the music industry has dealt with like historically for decades
40:27now is there's a long history of stuff like Payola.
40:31Nowadays, kind of the version of Payola in 2026 is streaming fraud, people trying to juice
40:36their numbers.
40:37I do wonder if adding a monetization and like a betting element to music performance could
40:44encourage further streaming fraud.
40:47I'm wondering what your take is on that.
40:49Yeah, that is a great question.
40:51I'm glad you asked that.
40:52So one of the reasons we kind of only like, we have a lot of requests from users using kind
40:57of like smaller and smaller platforms for like, not just Spotify and Apple Music and all
41:04of that.
41:05And a lot of our analysis always goes in like, how susceptible to manipulation is this?
41:10We don't want it to be very susceptible to manipulation.
41:12So with Spotify, we know, we kind of studied how they come up with these numbers and how
41:16they actually stop the bots and do all of that.
41:18And I think in some ways, we trust Spotify's incentive because they have to pay for stream
41:23that they're going to try to make sure the numbers are correct.
41:28But we only offer markets that we think are very hard to manipulate.
41:32Obviously, like when we're thinking about, you know, you are adding a monetary incentive
41:39for these things.
41:40But I think that the most important thing when we work with these markets is making sure that
41:44we're picking the markets that we don't think are susceptible to manipulation in a lot of
41:47ways.
41:48It's like, a lot of these kind of things, it's like also objectively, it is a crime.
41:54It is a federal crime to manipulate markets.
41:56And it's very similar to insider trading.
41:58Like our market integrity and surveillance teams, like they are looking, if they notice
42:02anything like that, if they notice, you know, we get reports all the time of like, there's
42:07something sketchy in this market, there's something sketchy in this market.
42:09And we have actually a whistleblower program that if you report something that ends up
42:13being an issue, you get part of the of the fine.
42:15And all of these things, they are financial crimes and federal crimes.
42:19So if you do any of that.
42:20So in some ways, you're correct that it's adding the incentive, but it's also adding the
42:24punishment that is significantly higher because you can end up in jail if you do that.
42:29Yeah.
42:29Yeah.
42:30It's I think my fascination with all the downstream effects of prediction markets are just that
42:35I do feel like this.
42:37I mean, you telling me the figures of just how much it's grown, even from 2025 to the
42:42first quarter in slightly into the second quarter of 2026 proves to me that prediction
42:48markets are going to play a very big role in our society moving forward.
42:53And, you know, I think there's going to be a lot of downstream effects and whether or not
42:57Cal she has anything to do with that remains to be seen.
43:00But it's just going to be really interesting to see how this impacts all facets of society.
43:05Yeah.
43:06Not to overstate it.
43:07I think I think that's completely right.
43:08I think that one of the main reasons when when we talked about how hard it was to keep
43:14the, you know, regulated path for us was that it is so important that there are the correct
43:20guardrails in place and the safeguards and we know who's trading and we can investigate
43:24these things.
43:25Like when you mentioned Polymarket and a lot of there are a lot of offshore competitors, actually
43:29Polymarket is one of them, but there's like honestly over 50.
43:32And when you don't have any information on who the people are, how are you actually going
43:36to be able to conduct an investigation of like, are they trying to, you know, break something
43:40on Spotify?
43:40Are they someone's friend?
43:42You're not able to do that.
43:43And I think that we have a lot of responsibility bringing these industries to the U.S. to make
43:48sure that it's growing in a correct and good way for the country and for everyone
43:52and the markets are safe and have a lot of integrity.
43:55And we take that very seriously.
43:57And I think that obviously, like, it's an iterative process.
43:59We're going to get a lot better as the markets grow.
44:02And we learn from from everything that we're doing and improve and work more of the different
44:06industries.
44:06But it's that's why it's so important.
44:09There is a federal regulated regulator looking over all these working with us on all of these
44:14aspects so that we can grow a lot, but grow a lot in a safe way.
44:17Yeah.
44:18And one of the partnerships that you guys do have already is CNN and Fox.
44:23As a journalist, I find this to be really fascinating.
44:25So can you talk a little bit about what that partnership means and how you see prediction
44:30markets impacting media and journalism?
44:33Right.
44:33The main reason for that partnership is because of the forecast and the value of the forecast
44:38that we're getting from the markets.
44:40Right.
44:40I think that a lot of these news platforms after the 2024 election, they started looking
44:46at prediction markets and seeing it a lot more as wait, we were only reporting the polls.
44:51The polls were telling the story.
44:52If we were reporting prediction markets, it would have been significantly better coverage
44:55and information for our audience.
44:57So they're seeing as a lot as a way of like augmenting what they're reporting on and also
45:01engaging the audience a lot more.
45:03So one example is, I think, I don't know if it was with CNN or Fox, there was like something
45:08about the Epstein files.
45:09Right.
45:09And it was like, will Congress vote to get the Epstein files released or not?
45:14And the news were reporting that it was a lot of chaos.
45:17They weren't sure.
45:18And the marks were 99 percent chance the entire time.
45:20So it's pretty clear that Congress is going to vote that way.
45:23Now, whether the DOJ was going to whatever, that's a separate problem.
45:26But it was pretty clear that Congress is going to vote that way.
45:28And when we were talking to them, they were like, well, if we had that in our reporting,
45:32would have made such a big difference because it's about people still want to hear the experts
45:37like opinion and comments and on what's happening in the world.
45:41But it's just an extra data point that they're seeing adds a lot to the reporting.
45:45So that's kind of what they're seeing.
45:46It's a way of like augmenting and engaging the audience a lot more.
45:49Got it.
45:49So it's more you see it as complimentary rather than like a replacement.
45:54Oh, absolutely.
45:54I don't think it's going to replace news at all.
45:56I think it's more about having an extra data point that we think is a way better data
46:00point to engage the audience.
46:02I mean, I'd love to see more people engage with journalism.
46:05I know that one of the one of the kind of strongholds for us on our music business reporting
46:09are investors who because there are quite a few music companies that are publicly traded
46:13at this point.
46:14And so we have kind of Wall Street type investors who are paying attention to our coverage all
46:20the time and are always looking for more information so they can make, you know, right.
46:24Smarter trades.
46:25And so I would love to see prediction markets have that effect where people are doing more
46:31research and looking for more vetted information.
46:34Right.
46:34Yeah.
46:35I just I thought that that partnership was really fascinating.
46:37Right.
46:37And at first I have to say like I was not knowing at the time very much about prediction
46:41markets.
46:42I was a little scared by seeing it.
46:44And then I, you know, your explanation is really interesting.
46:47Our, the goal of these partnerships is just to get them the data for reporting.
46:50It's not like we, we're not thinking about it as like a conversion that we're going to
46:54get more people to trade any of that.
46:56We actually, it adds to the part that for us, it's extremely important to get the data
47:01from these markets to as many people as we can because we think these data is so good.
47:05And it's about like connecting to CNN, connecting to Fox.
47:08It's just a way to get this data.
47:11Like how many people watch these two channels.
47:12So just how many, just getting this data to more and more people.
47:15Yeah.
47:15And as we wrap up, I just want to understand how you see the future of music prediction
47:21markets.
47:21What are some things you would like to add to Calci in the future in terms of music prediction
47:25markets?
47:25One of the things I'm very excited about is this, when we go out of just the direct,
47:31like the yes, no, the binary yes, no, is having ways that you can kind of invest long-term
47:36on specific.
47:37For example, Chapel Roan, when she was starting, how, if you knew she was going to be big, how
47:42can you actually get exposure to that and kind of like grow with her.
47:46So it's kind of like going more in that direction as we go less on the, on the binary side.
47:51And, and, and, and looking at some of my more traditional futures styles markets is something
47:57that we're excited about.
47:57We're also very excited about just listing more and more markets.
48:00Cause now we have more music fans and they are suggesting so many amazing markets.
48:04And it's about kind of us just taking the time to build a good experience for all these
48:08markets and getting them out.
48:09So I think in the next, this quarter, we're going to be releasing way better, way, way
48:14better music markets and also ways to interact, like hubs to interact with the music markets.
48:17Hopefully that's going to be, make it easier to onboard and trade them.
48:21Well, one more thing that I wanted to get to that I haven't yet is that I've noticed that
48:26prediction markets skew pretty male still.
48:28There's still a lot of men who are on prediction markets and in music, some of the best, most die
48:33hard fans are young women.
48:34Yeah.
48:35So I'm wondering what is this, the, the split between men and women on Kalshi right now?
48:40And how do you see music being part of the strategy to bring in more women to the platform?
48:46So women are about, I think 30% of the platform now, which is actually significantly higher
48:51if you look at, than if you look at like kind of traditional finance and brokerage, brokerages
48:56and all of that.
48:56And it's growing a lot, like it's six X their percentage over the past year.
49:00And a lot of it is because of entertainment markets.
49:03We're seeing mainly entertainment and politics to engage a lot of women coming in.
49:07Actually, one of our other very big entertainment traders, her name is Gigi.
49:11Actually, she, she's pretty much only trades music and she's been growing a lot of the platform
49:16and starting to make some money and, and all of that.
49:18And it's very important for us to get more women in the platform.
49:22And it's at the end of the day, like what we do is we expand what people can trade on
49:27from just stocks and, and, you know, crypto to almost everything.
49:32And what you do is that you actually increase the access to, to all, to financial markets,
49:37to, to, to a lot more people.
49:38Right.
49:39So when you have things that new people, different people are interested in, you can grow it in
49:43different categories and different.
49:44So it's the, it's important for us to have diversity because there's the only way we
49:49can actually grow the number of markets and, and have the markets flourish is to get people
49:53that are interested in all these different things.
49:54Uh, so that's why we see this kind of growth, um, in that I think entertainment markets are
50:00going to play an even bigger role in bringing more and more women, uh, into the space and
50:03younger people and, uh, and all of that, which we're very excited.
50:06Um, and it's, yeah, in the end of the day, if you give people an opportunity to make money
50:10in what they know and engage with what they know, and it's not like this scary alienating thing of like,
50:14I don't know anything about, you know, earnings and what am I going to do with that?
50:18Um, you're just going to see a lot more people come in and, and it's a, you know, a fair
50:22playing
50:23field in a way that they can come in and actually start making money and engaging and trading
50:27and we're seeing that already.
50:28This has been so interesting.
50:30Thank you so much for coming.
50:31Of course.
50:31I do have before, before I let you go, a couple games that we like to play at the end
50:35of every episode.
50:36Let's do it.
50:36So we'll lighten it up at the end.
50:38Nice.
50:38Um, okay.
50:39So this is my beautiful wheel that I made myself.
50:41Amazing.
50:41Um, this is, this is a game we called spin the record.
50:44So I'm just going to have you spin it twice.
50:46Whatever question it lands on, you got to give us an answer.
50:49Correct.
50:50So name a key win at your company.
50:58What was a big moment for you guys?
51:00I think winning the election lawsuit, we had to sue the government to legalize election
51:04markets and that lawsuit was like a day and night, um, situation for the company.
51:11After that, we kind of reset our relationship with the regulators and you have to follow
51:15the law, which is actually kind of basic when you think about it that way, but they weren't
51:18following the law.
51:19And that after that, we started seeing the growth in the number of markets, number of
51:22users, volume, uh, and all of that.
51:25It was very, uh, a hallmark case for, for prediction markets in the US.
51:28Interesting.
51:29Okay.
51:29Spin it one more time.
51:32See, you know what it's DIY guys.
51:35Okay.
51:37Best advice you've ever gotten as a founder.
51:41Ooh, that's a good one.
51:43I think it was actually when we were in Y Combinator and we had talked to some experts
51:48on kind of like futures industry and they told us zero percent chance that this is going
51:52to work.
51:53Like you're not, you're not going to be able to like legalize this.
51:55The government's never going to like let you do it.
51:57And then, uh, Michael Saibo who was the CEO of YC at the time, he founder of Twitch.
52:02He told us like, you know, it's like, these are just normal people.
52:05Like you are, there's no reason you should just listen to what they're saying.
52:08Like just, you know, think first principles, do what you believe is right.
52:13And you know, it's, it's, it's this concept of just everyone that achieved big things or
52:17small things are just normal people.
52:19And you have the right and the capacity to do and achieve as much as they have.
52:23Uh, and that made us kind of like build the confidence early on to be like, yeah, maybe
52:27we can take on the federal government.
52:29Maybe we can try to legalize this thing and grow it.
52:31Uh, so that was great advice.
52:33I love that.
52:34Okay.
52:34We are going to end things off with something I do every single week.
52:36It's called, what would you cue?
52:38Perfect.
52:38You're picking one song per prompt.
52:40First prompt is what would you cue to represent your favorite era of music?
52:46Ooh, probably Leila, just big seventies music fan type of thing.
52:52Love it.
52:53Yeah.
52:53Just there's something that even in Brazilian music, I'm from Brazil.
52:56That's pretty obvious.
52:57Um, even in Brazil, the music in the seventies was absolutely insane.
53:00So probably Leila is one of my favorite songs.
53:02Whenever my fiance and I went, go to any road trip.
53:05It's only like Leila cued back, like back to back.
53:08I love it.
53:09I love it.
53:09Okay.
53:10What would you cue to represent the best concert you've ever been to?
53:15Probably like, Don't You Worry Child, Swedish Child's Mafia, probably.
53:19Ooh.
53:19Okay, wait, what was the concert?
53:21When was this?
53:21It was a Madison Square Garden concert that they did, but I've been to multiple
53:24Swedish Child's Mafia concerts.
53:26It's, I really, really, like that era of EDM was like fantastic.
53:30So.
53:30Did you see Swedish Child's Mafia when they performed at Coachella?
53:34It was a couple of years ago.
53:35I did not.
53:35I did not.
53:35That's when I had already stopped going, but I did not, but I saw them at Madison Square Garden
53:43and I saw the Brooklyn Mirage in New York and then a couple other times.
53:46They're just great.
53:46What would you cue to take you back to your childhood?
53:49So I was a massive One Direction fan.
53:52So it probably would be like What Makes You Beautiful or like maybe Fireproof, like any
53:56One Direction song, honestly.
53:57Okay.
53:57Picking the big hits.
53:58I like that.
53:59Yeah.
53:59I like that.
54:00Okay.
54:00Well, who's your favorite?
54:02Harry Styles.
54:03Yeah.
54:04Fair enough, fair enough.
54:04Very basic.
54:05Yeah, no, it's fair.
54:06I tried to like come up with a different one.
54:09So I wasn't, you know, picking the one that everyone wanted.
54:12It was Liam.
54:13And then I respect, rest in peace, Liam.
54:16Yeah.
54:16But his solo career didn't end up panning out the way that I had really hoped.
54:20Right.
54:20So now I've transferred over to Harry Styles.
54:22Yeah.
54:24And then finally, we always try to throw in just like one custom one based on the guest.
54:29And so I want you to cue me up something, a song that kind of represents a song you would
54:36listen to to get yourself started in a day at Kalshi.
54:40Probably like Don't Stop Me Now.
54:42And I'll explain why.
54:43Okay.
54:44Before we raised our Series A, we were meeting so many investors back like before we even
54:49launched.
54:50And before, I was so nervous all the time.
54:52And before going to any one of them, any meetings, even like remember from Alfred from
54:55Sequoia was on our board.
54:57I would just play Don't Stop Me Now and then I'll get excited.
54:59And then I would just go.
55:00And you know, it was like, it was like kind of like taking a shot of Red Bull.
55:03It's like, it was just very good.
55:05And to today, if I have to go somewhere like big and they're scared for some meeting or
55:10afraid of something, I just listen to it and it pumps me up.
55:12So it works out.
55:12That's great.
55:13Okay.
55:13Perfect way to end it off.
55:14Luana, thank you so much for coming to On The Record.
55:16Thank you so much for having me.
55:17This was so fun.
55:18All right.
55:18Thank you so much to Luana Lopez Lara for joining me to talk about the impact that Kalshi is
55:23having on the music industry.
55:24And thank you for listening to this week's episode of On The Record.
55:27If you liked today's show, give us a follow on Instagram or on our brand new TikTok page
55:32at Billboard On The Record, where you can find new clips of the show every single week.
55:36We'd also appreciate it if you rated our show on your favorite podcast platform, because
55:39all these things help On The Record grow bigger and better than ever.
55:42Again, I'm your host Kristen Robinson and tune in next week for another peek behind the curtain
55:47of the music business.
55:47I'll see you then.
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