How Kudos built a consumer data moat on top of credit card rewards

Speaker A: Before we get into it, a quick word about something we've built at, uh, Tearsheet. If you're a senior product leader at a bank or fintech, you know how hard it is to find peers who actually get what you're dealing with. Not vendors, not consultants, people doing the same job at the same level who can tell you what's really working. That's why we built the Teracheet Product Leaders Council, a peer network of heads of product from across banking and fintech, major banks, fast growing fintechs. The company is reshaping how uh, financial products get built. We meet regularly, we go deep, and everything stays off the record. If that sounds like something you've been missing, go to Library Teresheet co counsel to learn more. Welcome M to the Tearsheet podcast where we explore financial services together with an eye on technology innovation, emerging models and changing expectations. I'm Tier Sheets Editor in Chief Zach Miller. Most people leave money on the table every time they swipe. Not because they're careless, but because the credit card rewards ecosystem is genuinely complicated. Thousands of cards, millions of merchants shifting bonus categories, buried benefits. The promise of AI is that can do that optimization work invisibly in the background. Today I'm joined by Tiku Anazodo, co founder and CEO of Kudos, an AI powered smart wallet that tells you which card to use at checkout, recommends cards based on your spending habits and layers on additional rewards on top of what your cards already earn. Kudus has raised over $17 million, is backed by QED investors and was named to Forbes Fintech 50TQ. Welcome to Tearsheet. Great. So who are you and what do you do?

Speaker B: I'm Tiqua Anazodo. Um, I'm co founder CEO of Kudos. Kudos is a wallet that helps people earn and save whenever they spend, starting with your credit card rewards. Um, but ultimately Kudos analyzes all your spend and helps you figure out additional ways to help and earn and save money and uses AI agents to actually execute for you.

Speaker A: Awesome. And this the holy grail, I think for consumer finance. Right? Um, love to hear how you got to this point. Can you talk, tell us a little bit about the founding story?

Speaker B: Yeah, so my, my background is. So I started at Kudos with my co founder Ahmad, and we both actually worked at all of the same companies for the last like 12 years at this point. Um, I started off at Google Pay where I helped launch the initial Google Pay online product, scaled that in about 12 markets in Asia Pacific, and then went to a firm where um, I was hired to, to lead the launch of a firm on Amazon and to help lay the foundation for a firm's initial expansion in Canada and Australia. And the thing I learned during that process was I've always wanted to build a wallet that works for consumers. But a lot of the wallets I had been building through my career were really focused on the merchant and helping merchants drive more conversions. So Kudos was really about how do we just give the consumer a lot more power when they spend money. And my co founder's background similar, although like at Google he was working on ad systems and at a firm he was helping build ad systems systems to monetize, um, purchases. And so one of the insights that we had when we were thinking about Kudos was there's a product that works for consumers and there is a business model that leverages all the context that we know that can create a win, win, win for both the consumer merchants and the card issuers that we work with. And that was really the founding story of Cudos.

Speaker A: So do you mind if we double click on that? Because I think that's a really important point that you make the difference between a wallet that's aligned for merchant use versus a consumer oriented wallet. Can you talk about what the would be?

Speaker B: Yeah. So the difference is when you look at something like Google Payer firm, um, or PayPal, you, there's a button that a merchant has to integrate into their website. And when the bet is that whenever you get to checkout, the user is set up across one of those buttons so that they can click purchase and they finish their purchase. But in general there's really not very much else that the consumer can do beyond just paying faster or paying with a payment plan. And so with Kudos we, the first principles approach that we took was the shopping component of Kudos actually works through a shopping extension, which means that the merchants actually don't need to do any work, it just works by default. Um, whenever you're shopping across any store, you set up your Kudos wallet, you add your cards and whenever you're shopping it works. And what that let us do from day one was start to focus on all the other ways we can add value for the consumer. So the first way we added value for consumers was by giving them um, the recommendations and the best card to use for every purchase that they make and actually showing them the math on this card has benefits and this card has purchase protection plus you earn $25 in benefits versus 5%. And then the second thing we did was we Added the traditional cash back that you get from things like Rakuten, but we actually gave 100% of that to the consumer. And the reason we were able to do that was because we were building on a foundation where we were going to layer on additional business models. And the merchant shopping business model was really not the core thing for us, a revenue model standpoint. And the last two years we've built out other capabilities like um, we match. We're the only tool right now that matches premium prime consumers to credit cards based on their actual spending habits. So when they connect their accounts through Plaid, we analyze their Plaid purchases and we analyze their credit score credit history and we match them to cards that exactly match the gaps in their wallet based on their spending habits. Um, and then in the last year we've really double down on those capabilities where we, we now have this very robust understanding of a consumer. We're the only tool that has an understanding of every historical purchase Through Plaid. We know your credit score, credit history, we know what you're actively shopping for and we are able to make these very personalized recommendations on things that you can do to earn and save more money. One feature that we launched about two months ago is an AI bill negotiator that sees that you have an Xfinity bill and actually sends an AI agent to go negotiate your bill for you. And with a lot of these AI features that we're building, we are charging the consumer. We do have a premium tier that we launched about four months ago which we charge the consumer for. So that's the core foundation really is. It's not really just about pay faster, it's about our uh, how can we just help you earn and save across every spend journey that you have both online and offline.

Speaker A: So you mentioned it's a browser extension and we have seen other models crop up through the, as I mentioned in our pre call gray hairs here. Like we've seen browser extensions launch to try to help people make better shopping decisions or get more rewards or a variety of different things there. How do you think where Kudu sits is different from some of the other um, models that have been launched previously? And how do you avoid sort of how do you stay top of mind for your users?

Speaker B: Yeah, that's a great question. So with the browser extension was our first Surface. We do have an app, we have an app in iOS and Android and we have a web portal and a lot of the capabilities beyond just paying faster, paying with the best card and earning cash back actually live in the app. Portal. One of the things that we do very differently from like a honey for instance, or Rakuten, is when you, we don't just live in the moment when you're actively shopping for things. We also live in the moment when you have historically shopped for things offline. So we um, like one thing that we see with our merchant partners, like when we started working with merchants like ebay and Expedia, um, the big question was always what is incrementality that you're driving to us as a merchant? Because if people are already shopping and you're giving them cash back, they maybe were going to convert anyway. And something that Kudos does differently, that we've actually proven from an incrementality standpoint is because we know a lot more context about you, not just what you're actively shopping for, but we know that you moved into a home from your credit report and we know that you've been buying furniture from our house. And um, Wayfair, whether it's offline or online, we are able to very proactively analyze that behavior and make recommendations and things that you might want to think about in that journey. Uh, you just bought a home. So um, here are some furniture stores in our network that actually might be a good place for you to actually buy furniture or you just bought a home and we know you're about to buy a lot of furniture, but the only cards that you have there is a card that could make this purchase journey a lot simpler for you that maybe gives you over $1,000 across $20,000 worth of furniture spend incrementally. Those are things that we can do in a much more nuanced way than the companies that really just live in the extension at ah, checkout with the only context they have being just your shopping journey.

Speaker A: And this level of I guess proactivity is that one way you could call it is like you guys kind of going the extra mile to figure out what are the needs of our users and how do we help given where, how do we help provide them? That um, that's sort of like we talk about like cross selling opportunities in banking. It's like, well my bank knows that I just, I took out a mortgage, which means I just moved. But they're not really connecting the dots to say, okay, help me, help me fund a move, you know, help me fund the furniture as you're talking about a furniture purchase. How, how receptive are you users to, to that type of um, I guess guidance? Yeah.

Speaker B: So I think the, the initial skepticism always comes from, ah, the position of are you going to sell my data? And the general thing that we are very firm on is that we never sell consumer data. Every piece of data that we get from a consumer is really about helping unlock value. And if you look at where all that skepticism comes from, like consumers, Right?

Speaker A: I guess. Yeah, yeah. From Mint.

Speaker B: Exactly. Yeah. They've interacted with historical products like this that have sold their data. And the thing is, the reason you sell data is because you don't have a business model that actually works beyond selling data. And so something that we're very upfront about is that we do have business models that work. We have merchants pay us.

Speaker A: It's more than just. Uh, I'm sorry to interrupt. It's more than just the fact that you're selling my data. It's that I'm skeptical of the whole transaction because you're just. You're. I feel like you're recommending to me what's good for you, not necessarily what's good for me.

Speaker B: Yes, that. That's a very fair point. And so something that we do also differently from, uh, I'll give. Like with credit card marketplaces, for instance, if you go to Credit Karma or Nerd Wallet, you would see 150 credit cards that pay them commissions, and those are the only credit cards that they ever recommend to you. If you come to. Kudos. Kudos, actually. Because by virtue of being able to recommend from your wallet the best card to pay, we do support all 3000 cards in the US by default, and we configure them. We have all the benefits and credits and everything always up to date because we had agents that are actively updating that data. Uh-huh. And what we are able to do is when we do recommend a card to you in our dream wallet, a lot of the cards, like 95% of the cards that we recommend are cards that don't pay us any commissions. And that's something that we also see upfront in our experience and that we will tell you if a card pays us commissions. And we would love if you get that card that pays us commissions, because that's how we keep the lights on. But we also show you a whole pool of cards that don't pay us commissions because we are matching you based on your spend, and we're actually showing you the math on how much more you would earn based on your historical spend. And then similarly with the merchants, when you shop at Kudos, we have a network of 15,000 merchant partners that you can earn cash back on. But Kudos actually helps you across over 5 million stores where you shop. Uh, if you think about a honey or a rakuten, they only shop on a partner site. Kudos shows up when you're shopping on Amazon. Amazon is not a partner, but we are able to help you navigate that Amazon purchase, even whether or not we get paid. And I think part of that philosophy kind of boils into we or we were growing into a product that was going to eventually just charge certain users for certain capabilities. And so by building enough value where regardless of what we do, we figure out how to make money, um, we have that ability to not always just show you products that are in our service for our partners.

Speaker A: So it's like Kudos is way more than just a rewards optimization tool. Meaning you're basically sitting on top of a massive data layer about consumer spending, right?

Speaker B: Yes, yes, we're sitting above a data layer that includes, um, all your historical spend, um, your entire credit report credit history, which we get from Spinwill, and then your actual active purchase intent and purchasing behavior.

Speaker A: So how do you think about, um, what that. Owning that asset or at least having access to that asset, how that evolves over time and what that enables for you guys to do over time?

Speaker B: Time, I think when I think about like what is happening with AI right now, data I think is going to be the moat for specialized use cases like fintech. And so there are a lot of things that OpenAI and anthropic can build the best models in the world, but the best models in the world in themselves cannot give consumers nuanced understanding of their money finances and help them execute without fully understanding the consumer's intent and understanding the consumer at the level that we understand the consumer at. And so where we see our themselves playing a role is as we start to do things that are a lot more predictive. Um, and we are building trust with the consumer. We're letting the consumer, the consumer is letting us do small things for them, like letting us go negotiate your bill with T Mobile, which is generally low stakes, as long as we don't break your plan or sign you up for something long term. And the idea there is, as consumers actually start to see us as a system and service that understands them well enough and that executes accurately enough on smaller things, we hope that the consumer starts to let us do bigger things for them. Like, hey, we noticed that this is not. You have a card that you're overpaying for in your wallet and we think you should like close this one and open up this other card instead. Or we see that your mortgage or your loans, or you're paying 3, 4% APR is higher than the ongoing market rate. Let us go do that. Let us go fix that for you. The goal for Kudos has always been we want to get to a place where the wallet actually starts to execute for you and work for you. And we think to get there, we need extremely accurate data, extremely accurate understanding of the consumer. And that gives us the ability to go execute very accurately. Because again, executing wrongly for a consumer in the finance space is probably the worst thing do across any vertical. I agree that if you book the wrong flight in travel, they just cancel it. But if you go open a whole financial instrument for a consumer that does not match their needs or intent, that is a disaster for the consumer and loses trust.

Speaker A: Agreed. Um, well, what's interesting is we've had a lot of conversations over the past, I call it 18 months, um, with different firms in the financial ecosystem that are kind of gunning for the consumer in the same way that you are. How do we provide that sticky concierge layer using agentic AI to be able to actually be that initial touch point through which customers will now execute their financial lives in the future. And so we've seen banks are going after that. Um, you guys are going after that. Some of the closest closed loop systems are going after that, like a, like a Square or a PayPal. Um, like it's. First of all, do you think that's an accurate way things are shaping up? Like people.

Speaker B: Yes.

Speaker A: Like, oh, plus the general GPTs are going after that too. Right. So, like the questions, who am I as an end m consumer, who am I more likely to use in the future to trust, as you said, to be able to execute for me. Yeah.

Speaker B: So I agree with the direction that everybody is working, building towards that because it is probably one of the most lucrative things that you could do in the world. If you get to a place where consumers trust you with their money and opening components around their money, you're in a very good place. But if you look at the, like the general GPTs, I think the thing that they will struggle with is getting to the nuanced understanding of the consumer and the data. I mean, there's already so much that Claude does right now where I think having Claude connect with your finances at the depth that makes sense might actually be overwhelming relative to the use cases that you use it for. I think with the banks, there's an inherent bias and that kudos is a neutral arbiter. For your wallet. Uh, Amex will tell you Amex things. Amex is not going to tell you to go to another financial company. So it is hard for you to see the bank as that thing. I think where it gets really interesting is with some of the larger fintechs like Square that are also still founder led and also still move really fast and actually understand that this is a big wave, um, and that there's a moment happening right now. I think there is an opportunity for them to figure it out. But I would say my bet would be on a smaller company that has a lot less baggage and is able to move extremely fast with the context that we have.

Speaker A: As you said, it sounds like you'd need somebody who sits on top of all the stacks to be able to have um, an objective view of how everything is playing out. That said, some of the institutions, the role of the bank may change in the future with agentic AI. I don't know. I mean that's a big bet. But I want to talk more about Kudos now you've got a couple different products you alluded to in the introduction. Can we talk about what those products are and how they fit together as a system?

Speaker B: Yeah. So the first product we have is a shopping extension. What it does is it works on mobile, um, web and desktop web, uh, across all major browsers. And what it does is whenever you're shopping you get to check out. It helps you um, autofill the cards that maximize your rewards. It gives you additional cash back at thousands of stores if it's a partner store. And then extension also automatically activates all the card linked offers in your issuer portal. So if you log into your Amex, whenever you log into Amex you can say automatically activate offers and it just goes and has an agent in the background. Go click all those 5,000 offers that nobody ever clicks um, on. But the crazy thing about those 5,000 offers is that it actually saves our users an average of about $130 within their first month. And kudos because many of them are actually personalized. Um, and it reminds you to use those offers when you're shopping. So there's this three way stacking of here's your credit card and all the benefits in it. Here are your car linked offers and here's cash back if you're shopping with a Kudos partner store. Second layer is just the financial recommendation stack. So we have a product called Dream Wallet that analyzes your spending habits and makes recommendations on credit cards to get based on how you actually spend and based on your credit profile and credit history. Um, and then the third product, the third set of products that we have are the more proactive, agentic, um, tools. So we started with our Insights product that analyzes your spend and every week it looks at all the data that Kudos has and every week it shows you about 12 different things that we notice as patterns that could help you earn and save more money. It could say, hey, we noticed that your T mobile bill is actually 30% higher, um, than other people's T mobile bills.

Speaker A: Or it's like you look across all users. Yeah.

Speaker B: Because we see it across other users in your location that have similar profiles or that we notice that your, your mortgage or your loan, your personal loans are like some percentage higher. We see that in the last um, month you've actually been spending a lot in a specific category, but you don't actually have the right financial product for that category. And we think you should actually make a change. And we're going a layer further with that and actually starting to do things for the consumer. Starting with um, doing things like lowering your bills, all in issuers to dispute charges that might have been wrong on your card. And we're going to expand on that set of things that we do for the consumer over time and all these things in that third bucket, our paid features. Because the theory there is that we save you and earn you money automatically and we can actually show you the math when our agent goes and executes with Xfinity and calls them and saves you $400 in your phone bill. So it's actually not that crazy for you to pay us uh, $72 a year to get that service over a 12 year, 12 month period.

Speaker A: Very cool. I, I guess that's, that's the next generation wallet, right? The wallet is proactive on my behalf, like representing.

Speaker B: Exactly. That's the next generation wallet. The wallet is proactive on your behalf. And something that people ask me a lot is, so how is that different from like Rocket Money or like Monarch Money or one of these PFM type of tools? My general philosophy or our philosophy starting Kudos, is that we don't want to build a product that has a bunch of graphs that you have to go look at every week. We just don't think. I think one of the challenges that the PFM category has had is that people actually do not want to manage their finances.

Speaker A: They don't.

Speaker B: The average consumer just doesn't.

Speaker A: They don't want to pay for graphs.

Speaker B: Exactly. They don't want to Pay for graphs. But what I think the average consumer wants to pay for is something that just does stuff for them. And so that's what we lean very heavily into. We. And the data layer that we have really helps us be more accurate at figuring out what are those things that we can do for you to help you earn and save money.

Speaker A: So the paid product is. You said $72 a year?

Speaker B: Yes.

Speaker A: Okay. And what is the, the um, the upgrade cycle look like? How, how do, how does a free user come in and how do you guys kind of prime people moving through your funnel?

Speaker B: So the free users come in typically for products for features like just the shopping feature that gets them the helps them pick the best card or our in store cheat sheet that recommends the best card when they're shopping in stores or just discovering new cards in a more personalized way for the prime users. And then many of the other capabilities are paywalled within the app and the portal and um, they just gradually upgrade within those.

Speaker A: So you can see them actually and they're kind of grayed out or something like that or.

Speaker B: Yes, you can see all of them but they're kind of grayed out and you can even in many of them you can see examples of what it could look like for you.

Speaker A: So you're sort of teasing it a little bit.

Speaker B: Exactly. Mhm.

Speaker A: Have ah, you shared with uh so I noticed the user counts is very impressive. How many users do you have and have you shared how many paid users you've had?

Speaker B: So we have ah about half a million users right now. Um, we have not disclosed closed the paid count but it is growing pretty rapidly. We just launched the paid tier about three and a half months ago and it's been, it's become our. It's actually now larger than the revenue we make from card issuing and by the ah, end like within the next two. Not, not card issuance sorry from recommending cards and um, within the next two or three months we actually expect that the paid tier will be the largest revenue stream for kudos because it's actually something that a lot of people will. Our existing users are opting into.

Speaker A: Awesome. Um, and do you see um, banks and I guess other card issuers as. Clearly they're watching what's happening in the space and hopefully they're watching what's happening with kudos. Do they think you're a threat? Are they a tool? I guess. How do they see you and how do you see them?

Speaker B: So I think um. So when I was at Google Pay there was this notion of, um, there in the fintech ecosystem, there are a lot of frenemies where it's just there in reality, there's places where there's value and there are places where there's like, you might not like the value. And in the case of Kudos, the place where we deliver value for issuers is when we originate cards for our members, like when we actually recommend new cards. Um, we do partner with some issuers to recommend some of their cards. I said we recommend 3,000 cards. But there are a subset of those cards that are Amex and Cap 1 and Chase cards that we get paid for when people open them. And so that's a good part of relationship. Another thing that I think is good is people have these premium cards like the Amex Platinum that has expensive fees, like 800 fees. And the decision point that every consumer. All my friends have this question for me every year, should I keep this card? And kudos to your friends.

Speaker A: I know those types of friends.

Speaker B: Yeah, they always ask me, should I keep this card? Ah, know that you could use Kudos. It will tell you. But we actually have tools that help you use the benefits on your card and at the end of the year show you the math and like, hey, is this card worth it? And today my Amex Platinum and my Chase Sapphire Reserve tell me within Kudos, this card is worth it because you earned $1,000 more than the annual fee. And that's another way where we actually add a lot of value to the issuers because we help their consumers answer those questions cleanly and prevent them from churning on the cards. I think one general concern that the issuers have with a product like Kudos sometimes is, hey, are you bringing in the churning crowd, the people who are just coming in for the welcome offer bonus? Reality is what we found is that those people don't necessarily like Kudos, um, because they 1 prefer to use their spreadsheets. It's just a fun game for them. It's not like the Kudos tool is more. Kudos is more about simplify money and for people. But the people who want to use spreadsheets to churn, use spreadsheets to churn. The second thing is the way we actually recommend cards and financial product actually fits a lot more to just a regular person's shopping behavior, not a churner's behavior. Because if we're recommending cards based on your spend, a person who has 20 cards already is not looking for cards based on their spend. They're looking for just the next welcome offer, which is not something that Kudos is uniquely positioned to do. So as a result we don't really attract that consumer. We actually attract the general um, high spend, high FICO prime consumer who just does not have the time to think about this thing but has always had the question in their head, um, am I leaving money on the table? What card should I have? What card should I use?

Speaker A: And do you imagine we're getting near the end of our conversation so I want to continue to, just as we close up the conversation, figure out like uh, are you Planning also a B2B model? Is there or B2B 2C model? Is there a role where you see yourself partnering with other apps or other tools or other institutions that have audiences that would, that would, you know, the partnership would make sense.

Speaker B: A great question. So we actually announced a partnership with Samsung back in November. So Kudos now part um, now powers um, Samsung shopping extension, um, called Samsung pay benefits, uh, which is in Samsung Internet and Samsung phones. And that was not a, that was actually a little bit more of an inbound relationship. And I think over the course of. So we don't necessarily have a full blown B2B 2C motion, but with that we have actually built our product in such a way that we can white label to certain partners that have distribution or plug into people's distribution. So that's something we're thinking about. But beyond the Samsung partnership there's nothing else to announce today.

Speaker A: I guess that's a challenge also as you're building your own brand and your own, your own direct relationship with your users. Like does it make sense to white label and go B2B? It sort of feels like it's a different business.

Speaker B: Exactly. Yeah. I think there is, there uh, there, there are exceptions that we have made. Right. Samsung is the largest device OEM in the, in the world. So that is distribution that makes sense to, to pay attention to, but we don't, I don't necessarily. At least not in the next year or two. I don't see us having just an out of the box B2B 2C offering that anybody can plug into. I think it would be really on a case by case basis for extremely large players.

Speaker A: Last question for you Tigu, um, what are your big audacious goals for the rest of the year?

Speaker B: So the biggest thing for us this year is we think we're leaning really heavily into that premium tier that unlocked, that has these AI agents that do things for the consumer. So the biggest goal is really expanding the use cases that our agents can execute on behalf of the consumer. Um, and, yeah, so that's really going to be our major focus for the rest of the year.

Speaker A: Got it. Thank you for joining us on the Tearsheet podcast.

Speaker B: Thank you, Zach, for having me.