For 10 years, all we heard again and again was that it was impossible to compete with any bank, that we were going to get crushed, and that we had no shot at being successful. Today, we have 140 million customers with 10,000 employees. Our competitors have 100 million customers with 100,000 employees and 6,000 branches. So our cost to serve a customer is about 3% of what a traditional incumbent bank is. That's pre-AI.
So the last time we did this, I think you had 35 million customers. Now you have 140 million customers. So, well done. Well, well done. Busy five years.
Yeah, busy five years. One would be tempted to think that with that kind of growth that we've sort of saturated the potential of fintech as a category to create a new platform, digital, mobile-first, this sort of thing, and that we're maybe in the later innings of the fintech technology transformation. I know that you think it's sort of the exact opposite, and I'd love you to detail exactly why, and what you think we can expect in the next five years, not just for Nubank, but for digital financial services globally.
If you look at global consumer financial services, it's about a $10 trillion industry, and still something like 90% of that industry goes through banking branches.
And it's owned by incumbent banks. So while there are a lot of neobanks and fintechs across the world in a number of different areas, you add up all of those fintechs and all these neobanks together, and we're less than 10% of that entire market.
So it's still, in financial services, it's still almost as if 90% of the world was going to Blockbuster to get VHS and DVDs, and Netflix-like services still had something like 10% of that industry. So that transformation, that migration that you've seen in other industries—in media with Netflix, in retail with Amazon over the Barnes & Nobles, in transportation with companies like Uber—that migration from incumbents to digitally native companies is still very, very early in financial services.
I think Nubank is very unique, specifically in Brazil and Latin America, because we are really the only neobank in the world where we've fully surpassed the biggest incumbent bank in terms of scale. We now have in Brazil close to 120 million customers. So upwards of 65% of the Brazilian adult population is a customer of us. So in terms of sheer scale it is very large. But even more than that, we've become the primary bank account of the entire country. So about 60% of our customers use us as their primary bank account. We replace the incumbent bank. We're not a secondary wallet. We're not some money that you leave there. We are the primary institution where people are really banking day-to-day. And that is very unique to Nubank in Brazil, and increasingly we're doing that also in Mexico and Colombia.
We think that this is a little bit of seeing the future of what will happen around the world over the next 10 to 20 years, where you would expect a lot of shift in market share from the still-incumbent banks to the digitally native companies, and that is just migration of market share, but also you'll see a significant increase in market size as billions of people across the world enter the banking system. You still have three billion people that are completely outside the banking system, don't have access to credit.
I'd love to break this into two components. You could imagine if you froze the product today and just worked on getting it in more people's hands. That could be one dimension of expansion. But then, of course, I'm sure you're thinking carefully about all the wonderful things that AI will allow you to do and technology will allow you to do for customers that you don't yet do today. Can you talk through each of those levers to achieve this, you know, Blockbuster-to-Netflix transition?
The first phase of transformation that enabled a lot of the migration in other industries was the smartphone, and this is sort of the same thesis you see repeating. The smartphone is the moment that we get to serve consumers without all that physical infrastructure. We have such a gigantic cost-structure advantage that we could pass that efficiency to the end customer via lower fees and better product. Just to give you a data point, we have 140 million customers with 10,000 employees. Our competitors have 100 million customers with 100,000 employees in 6,000 branches. And you start thinking about what the cost of real estate of those branches is—gigantic. So our cost to serve a customer is about 3% of what a traditional incumbent bank is. That means we have so much margin to give back to the customer via no fees, better experience, better interest rates, and overall a better product. That's pre-AI.
We're still here in phase one of what a smartphone enabled. AI will be an additional multiplication on that efficiency, because then you get to choose whether you want to have much more efficiency and you could automatize a lot of areas of the bank. You could imagine banks that have 500 million to a billion customers with 5,000 employees—like, that's totally within sight. Or you can just decide to increase your level of ambition, and for somebody like us, especially when we look at how early it is in the transformation, for us it's why don't we go to 100 countries and try to accelerate this transformation, with Nubank being one of the leading digital financial services firms in the world.
What are the craziest things that you can imagine the product or a bank like yours doing for the customer in three or five years, because technology has made new things possible that weren't before, just like mobile made a lot of new things possible. We've got an even bigger, much bigger wave now. Like, if you really dreamed about what could be possible, what are some of those ideas?
We like to categorize the problems we see in financial services in three buckets. One is access, one is cost, and the third is intelligence. On the access side, again, you still have three billion people in the world that don't have access to a credit product. It's crazy. It's almost half of the world does not have access to credit. Even in countries like Mexico or Colombia, 13% credit-card penetration. Why hasn't that happened yet? Because you needed the creation of a lot of data, you needed sophistication in credit underwriting, you needed the digitalization of these systems to happen. And this is happening. Cash goes away, disappears. You enter a number of real-time payment systems, as you've seen in Brazil with Pix or India with UPI.
So there is a lot of transformation and catalysts that are accelerating the rails on which you increase access to consumer banking for the world, and this is going to be a massive, massive opportunity. So 10, 20 years from now, 100% of the population has access to banking services, 100% of the world population have access to credit, 100% of small businesses have access to credit. This is an insane push to global GDP. I mean, I don't think it's really understood how big of a motor this could be for every single economy as you get half of your entire population in some areas access to banking. So that's the access side.
Cost is the one that tends to be more hidden, especially in developed economies. The US is generally well served by banking services, especially if you're a high-income consumer. But when you look at the cost of that banking system, it's pretty significant in ways that are not readily apparent. So, for example, there's about $15 trillion of retail deposits in the US banking system, but banks pay on average about 40 basis points of yield a year. In a world where your interest rates are four and a half, 5%, you look at the calculation of those 15 trillion—that's more or less $600 billion that are going to banks to pay for banking branches.
That in a digital banking environment would actually stay in consumers' pockets, right? So this is a massive wealth tax—the fact that banks don't pay any yield. If you're high income, you do. If you're the lower your income, the less you get paid. That's a huge tax and that's a huge cost. And then you look at remittances, for example. In the US, $100 billion go out of the US; people pay 5 to 10% per transaction. That will go to zero. Remittances—moving money is you're moving bits—that will trend towards zero in a more competitive environment, right?
Monthly account—people are paying $5 to $10, $15 per month in the US banking system for a bank account. And you look at Europe or developed economies, Japan, same thing. You see a huge amount of cost that consumers are paying that will eventually, with models such as ours that come to compete, be competed away. And then finally, intelligence. I think this is also the one that is less understood and is beginning to be discussed with the advent of intelligence.
If you are in the top 1% of income, you have access to the best financial advice, right? You probably will have a private banker. That private banker is understanding all the bank accounts that you have, is optimizing your deposits, is thinking about what is the right tax-efficient structure. If you need a loan, they're going to go and compete a bunch of different banks with each other and get you the best yield. But if you're in the other 99%, especially the more you go to the bottom, you have access to nothing.
Historically, there's been a lot of conversation about, like, education is the answer. You just got to educate people. People don't have financial education. That never worked. People don't sit down to, like, do classes. You're not going to solve this problem of intelligence through education. You can solve it through AI. And that's where I think AI will really be transformational in financial services, because it's almost providing every single person around the world super intelligence to be able to optimize their financial life on their behalf and remove a lot of these profit pools that exist today in banking that, in an environment with intelligence, will be competed away.
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Flesh that last piece out a little bit more. Wealthfront used to have this idea of self-driving money, which comes to mind. Like, okay, I've got some money. Either I don't have it in the banking system, which is the worst. So I come into the banking system, I'm earning 40 basis points instead of 4%. So I'm in a lousy starting position, but I certainly don't have investments or tax-loss harvesting or all this other fancy stuff. What do you think that ends up being for the average person in a couple of years because of this intelligence bucket?
The first obvious rearrangement is those $600 billion that banks are keeping in their balance sheet to pay for banking branches get rearranged, get forwarded to all the banking consumers, right? Because suddenly they realize, what am I doing with my money, leaving it at zero, right? Like, especially when you think about compounding, what that means for savings and compounding interest. This is a lot of money being sent ultimately to pay banking branches. You look at really any country around the world, any structure. You look at Mexican banking balance sheets, for example, or Brazilians, where it's exactly the same thing. The big incumbent banks—about 70% of their deposits they pay zero, and 30% they pay some yield, generally to the highest-income population or the corporates.
Then the second one. One of the things that you see in banking is, in a perfectly competitive environment, the best product should win, right? If you're charging no fees and you have the best experience—banking is a commodity product ultimately. So you should be able to get 100% of the market share. That doesn't happen because there is a lot of inertia in the system. With the combination, the multiplication of intelligence with open banking, for example, Plaid can connect 120 million accounts, and you put intelligence on top of that, you're effectively allowing each customer to know how to optimize their financial life and what are the fees coming.
So I'll give you an example. We're doing this in Brazil today, where about 15 million of our customers, every day, we're telling them: hey, your bank account, your credit card in that bank is due tomorrow, you don't have any money there, and they're going to charge you a 15% interest rate per day. Let us give you some money so you can pay that credit card or refinance. You have this loan at 10% interest—let us refinance that at 5% interest. So it's ultimately a drive towards optimizing and removing a lot of those profit pools on behalf of the consumer.
In some products, like small businesses, people do want to sit down with a banker, with a human, and have that conversation. If you have millions of dollars to invest, you still probably want to see a human on the other side of the table and have that conversation. So for certain consumer segments and for certain products—if you want to get a mortgage or certain sophisticated products—there is value in having a physical space. But that might be 5% of the cases today, versus if you have a savings account, a credit card, or a loan, you just don't need that anymore. So I think the rationale would be effectively, yeah, we're trying to serve these customers, but it's ignoring that for the majority of people, especially the mass market, increasingly you just don't need it and you don't go to that physical infrastructure anymore.
One of the questions that I think lots of investors and founders are wrestling with is what will be the best competitive advantages or moats in this new AI era when the cost to build new stuff digitally is much, much lower. If you had to imagine it like you're some new founder—I strip everything away from you and your only goal is to kill Nubank, is to like build a new company to attack Nubank, let's say in Brazil or in Latin America—what do you think you would do? Like, what would be the vector of attack on your own business?
Which, in a way, was what we did to the incumbent banks years ago, right? We were the disruptor going after incumbent banks. So I think the early-stage startup today that is AI-native, their biggest advantage will be speed, right? The ability to move extremely quickly and launch a number of different products, especially if you're born unregulated, then you're going to be able to move fast. By now, we are fully regulated. We have banking licenses in a number of different countries, and so we have to go at a certain pace. We have to be checking with regulators. Now, I think specifically in financial services, specifically banking, that will only get you up to a certain point, because eventually you're going to need to be regulated as well.
And so I think in some areas there's been a lot of conversation about how AI disrupts software, and that you know, you can ask ChatGPT or Codex to rebuild an entire software strategy, but you still cannot really get ChatGPT to get you a banking license, right? And you still cannot really get them to have regulators give you a license in six months instead of two, three years.
Specifically on credit or in certain products that we operate in, the amount of data that we have is pretty significant, right? So we have about 140 million customers. For each customer, we have something like 20 to 30,000 data points across 13 different years. So this is a huge, massive amount of information that allowed us to build our own foundation model. We built our own foundation model for financial services, for credit, and this gives us a significant advantage in making credit decisions, for example, or collection decisions. The early-stage startup entrepreneur, while they would have the speed, they would have a much harder time getting to that level of data, and so data becomes a significant moat now for the incumbents.
And I think companies like us, we're sort of in the sweet spot of benefiting the most from AI, because in one way we already have the scale and the data and the brand and the trust and the licenses that will be hard for the early native startup to move, but also we still have the technology angle and technology infrastructure to allow us to benefit from AI and what AI is creating and move even faster than we were moving before.
Can you build a pretty detailed timeline of maybe when you first had the thought like, wow, AI is a thing that we need to take really seriously, and then as the leader of the business, how you have thought about rolling it out and being more aggressive with it over time? And I'm interested in the details—like you said you have your own foundation model. Like, how's that built? Is it open source that you've, you know, tuned based on your own data? Like, who do you work with? How did you think about it? I'm really interested in your personal timeline, like how far back it goes and what the major hash marks have been.
We started using machine learning since we started the organization, right? So, since the beginning, since 2013, when we looked at Brazilian interest rates for consumers paying 500 and 600% a year, we said there's an opportunity here to use better data and analytics and machine learning to price credit risk. And different than a lot of fintech, we decided to take balance sheet, to take credit risk, and to be capital intensive by default. And so we had already an organization that was very optimized for making decisions based on models and data.
When the kind of ChatGPT moment came about, what, three, four years ago, we started paying significant attention around how technology was going to facilitate some of the decisions, and we acquired a company called Hyperplane in Palo Alto that was already working on doing foundation models for financial services. They were having such a hard time selling to the big incumbent banks—sales cycles were two years—that they were not really able to move, while the technology itself was fairly forward-looking. So we bought that company, we integrated the team.
We think we were the first financial services firm in the world to build their own foundation model with its own proprietary data to do credit decisions specifically. We even published all of our own research in this area. We developed a kind of early advantage. By now, we're now using our foundation model for fraud decisions for Mexico, for Colombia. As we launch the US and our international markets, we can day one already come in with our own foundation model and understand how to use the data for making basic decisions. This should accelerate our ability to come in.
The data thing is such a good example of the scale advantage. And you were an investor obviously before starting Nubank, and so I'm sure you've thought about this endlessly. It sounds like scale is maybe the most important thing that will make neobanks so competitively advantaged for the next 10 years or something. Is that right? Like, does that feel like the right one to pick?
I think scale is important, but you need it also with the right culture and the right systems. So one of the things we heard a lot in the early days was, well, how are you going to compete with the banks? The banks have scale, right? They have a hundred-year history with 100 million customers. How can you replicate that data? You know, and going back to the analogy of Blockbuster, my answer was always: well, Blockbuster had a huge amount of data, right? Imagine the amount of people coming into Blockbuster and seeing if they were looking at that VHS or that DVD or not, or renting. Did that data help them build a better search algorithm? No. Because they were not capturing the data. They did not have the right systems to capture data. They didn't have the right culture, data culture, to be making decisions based on data or based on models, and somebody like Netflix was able to come in with no data and build a better algorithm and ultimately use that scale.
So data is important, but equally important is your systems and your culture—ultimately being a culture that is using a lot of this data to make the right decisions. And this, I think, is what differentiates neobanks or more digital-native organizations like ours versus the more traditional incumbent banks that are still operating with 15 different systems as a result of a huge amount of acquisitions that they did over the years. And there's still, if you look at a lot of the AI applications, it's how do we transform, how do we use AI to transform COBOL, how do we get away from the mainframe. You're talking about 10, 15-year histories of going to the cloud. They're still in that process of going and putting systems on the cloud.
How do you run that, like tactically in the culture, to make sure you don't fall in the same trap that like all the big players before you have fallen into, which is that you're sub-optimally using your advantages and you don't have a good algorithm? Like, what is the tactics of you making sure the team doesn't mess that up and actually, you know, does the opposite?
I think the biggest difference is that historically a lot of traditional banks saw their basis of competition as a lot of banking branches. That literally, how consumers used to pick a bank is: I'm going to pick a bank that has a banking branch very close. And so that's why there was a huge amount of effort and energy into real estate and physical infrastructure, and obviously a lot of focus on building brands and building trust with consumers. Banks, in financial services especially, you need to protect that trust with consumers—that's very critical. So when we began the company, we did not have to spend energy or focus on an offline world; it's more an online world, and we saw technology and data as a way to build comparative advantage.
And so since the beginning we saw ourselves as a technology company, not a bank—a technology company that happens to be in financial services. And therefore the culture itself has a culture that uses data and analytics consistently for every single decision. And what our own foundation model has enabled us is the cost of putting a feature into a model has gone down significantly. Pre-AI, you had to spend six months adding a new feature. If you wanted to test a new feature in a model, you had to spend, you know, several weeks working, testing this feature, putting it in the model, testing it around. With our own foundation model, you can test a number of different approaches much faster.
Then the cost of creating a model—do you have an email that has purple letters or yellow letters? The cost of doing a specific experiment has gone down significantly. And so every decision in the organization can now be automatized and be done by model versus a human. That's what AI is also enabling. So for us, AI kind of let us do what we were already doing at a much more significant scale. But the culture itself already existed since we saw this as a way to differentiate ourselves since the very beginning.
How do you think the global financial system will change the most, or needs to change the most, in the next five years, totally away from your business? Like, what are the exogenous changes that you're most carefully watching that you think matter?
One of the most transformational technologies in the world, in financial services, is going to be—the first one is kind of the end of cash, and this is happening really everywhere. There is a lot of big cash-heavy economies like Mexico, for example, or Indonesia, or a lot of African countries—Brazil used to be like that—where that cash will go away and will digitalize mostly through real-time payment systems. And I think the implications of this, some of them are obvious: you don't need banking branches, or you need less. Some of them are less obvious, which is what happens to the economy, for example, the efficiency of banks when they don't need banking branches, the speed at which money moves in the economy, the amount of data that gets created in an economy that then can be used, for example, to provide access to credit. So that's a big catalyst.
The second one is open finance and open banking across the world. This is basically the concept that you, as a consumer, own all the data that you have across all institutions, and you're able to grab that data and share it with anybody else. So one of the biggest sources of inertia in financial services, but also let's call it telecom, for example, or utilities, is that you have a history with a specific company and you cannot transfer that history with somebody else that comes new, and incumbents have benefited a lot from that inertia of data. The moment that you can connect all your history from all your services and pass it to somebody else, you're reducing that inertia and you're enabling more competition for your data.
And you can monetize that data as a consumer. You can grab your historical information with a bank and offer it to somebody else that is willing to pay for that, if you decide to do so. Right now, social media does that without you deciding to do that. Increasingly, you're going to be able to do that as a decision. And the reason why open banking is important is because then it will decrease that inertia globally and will increase significant competition in banking. Banking today globally really is still very much an oligopoly structure. You have five, six banks in the US that own 60, 70% of all the assets—same in Europe, same in Asia, same in Latin America. So that will mean a less concentrated banking industry, much more fragmented, much more competition, and obviously that translates into less fees and less cost.
The other big trend that has a couple of decades is the role of crypto and stablecoins around the world. And what will eventually happen with increasingly people that are much more mobile in nature is that you operate in a combination of the fiat system in your country with a global offshore system. Your lives kind of go in between without you even realizing this. For a lot of countries around the world, it's really important. You've seen with the usage of, access to Bitcoin, for example, stablecoins—increasingly they want to bank in the offshore system. They don't trust their banking system. They don't trust their fiat currency.
I would say today there's about 190 currencies around the world. My view is that 10, 20 years from now, those 190 will be maybe 10, because the fiscal situation in so many countries around the world is so dire that a lot of that fiat money is not real money; it's tokens, it's basically crypto tokens. And so increasingly, billions of people are going to be banking on the offshore world—US stablecoins, but also Bitcoin and other types of assets. And so you see these two parallel systems interrelating with each other across the world.
If you had to think about the US dollar and its importance in this—if it goes from 190 to 10 or something—do you think the US dollar is the reserve currency 10 years from now? Is it one of a few? Like, what do you think its role will be in the world?
There are two sides of that argument, right? You can make the case. I think the US stablecoins ultimately will be the big savior, or one of the biggest saviors, of the US dollar, because it democratizes access to the US dollar. And while the fiscal situation in the US is not great and is deteriorating fast, it's still better than the fiscal situation for the other 100-plus countries around the world, right? You look at the balance sheets of a lot of the central banks or countries in emerging markets in Latin America, it's way scarier, and you don't have the sovereign capabilities. At least there's a lot of demand for the US stablecoin. There's very little for the Brazilian stablecoin, unfortunately.
So I think the fact that stablecoins exist for the US dollar will ultimately mean that the US dollar maintains its power as a reserve currency for a very long time. But it won't be unique. I think you'll have other, maybe five, six fiat currencies that people will be saving in, and then a few crypto tokens where you'll also be diversifying. And I've always been a Bitcoin fan, and I think it plays a role in a diversified investment portfolio.
What's the most surprising thing, do you think, about the move away from cash? What would I not appreciate about like the implications of that or how long it would take? Like, what's surprising about going cashless?
The main one is what this means for credit markets. The majority of the world and the majority of the world economy still are economies that are very much offline. And just think about this situation where you have a taco stand in a corner in Mexico City, and you're selling through cash—that transaction is not being recorded anywhere, right? That's a transaction that you're selling to somebody, and it goes away, and that taco stand cannot get credit today. Now, that person has a history where every day they go and sell tacos and there's a cash flow that's being recorded, but nobody can underwrite on top of that.
The moment that that transaction goes into a digital ledger, that transaction happens digitally, then suddenly that taco seller can take that information to a bank and say, 'Hey, look at my cash flow. Give me access to credit.' And if you give me access to credit, I can now have two taco stands, or I can have five taco stands. Digitalization of the economy and what that enables for credit for a significant percentage of the world population is something that is not very well understood today and is a huge accelerant.
And again, you look at economies like Brazil, for example—something like 70% of all the employment in the country is still in small businesses. It's not the big corporate; it's small businesses. The same thing happens in India, for example, or Southeast Asia. You know, a lot of these small businesses historically also dealt with cash; now they're digital natives. So this is trillions of dollars of credit being enabled for billions of people around the world. This could be a significant economic shift for economic mobility across the world and is a very exciting opportunity.
Do you think that you can create creditworthiness versus just predict or measure it once you have all this data? Like, is that one of the goals, to like help people become more creditworthy somehow?
Yes, absolutely. I mean, the first thing you have to do is kind of measure or record a lot of those transactions into a ledger, and that's what the digitization of cash enables. And then with better algorithms—and this is where AI plays a role here—and then also with better products, you can enable people to start building that credit history. So I'll give you an example. We were the first credit card for 30 million people in Latin America. And when we used to ask banks why so many banks didn't give access to credit, what we heard is: people don't want credit. People don't want a credit card. They are scared about paying taxes, and so they're never going to use the product. But what really mattered, what we realized, is that what they were really lacking was a product that really matched their needs.
And so we started, for a lot of people, with a product that had a—the first line was $20, a $20 credit line. When banks saw that product, they thought it was absurd. But in reality, people really appreciated that the $20 were better than zero. And those $20 became a hundred, and the hundred became a thousand over a period of time. And so you enable them to create a credit history through the right product.
And then you enable an AI copilot for that customer that tells them all the different moves and what they need to do in terms of spending and investing and savings to gain points and become more creditworthy. And that's again the concept of you providing a coach to somebody to improve their ability to access credit and improve their financial picture. So absolutely, I think that that's going to be a big enabler.
How siloed are the individual countries in terms of how useful what you learn in one is helpful in another? Like when you went to Mexico from Brazil, how much of the learning from Brazil was portable versus something about Mexico that's just distinctive about that country? And then how do you think about all the countries you've learned in so far and exporting those learnings to other geographies?
It's more exportable than we would have expected. And the part that was less exportable—the biggest difference between at least a country like Brazil, Brazil was actually much more banked than unbanked. And so when we went to Mexico, a lot of the conversations that we heard is like, well, but people in Mexico like cash, they don't believe in digital payments or credit cards or debit cards. And that was initially, in the early years of Mexico, that was the biggest difference.
When you go from a banked customer or banked country to an unbanked country, it's harder to compete. I always say that we're a shark in digital waters. When we are forced to compete in the offline world with banking branches, we're much less competitive. We don't have banking branches, we don't have ATMs. And so for a couple of years it was harder for us to compete. Even though we became the second-largest bank in Mexico by now and the largest digital bank there, but as these countries digitalize also, including Mexico, then the world starts looking closer to each other.
And that's ultimately what you actually see across any other industry, right? You look at social media across the world, it's the same product. You look at Netflix, the same product. You look at Spotify, the same product. You look at Uber, the same product. Amazon, generally the same product. So I would say historically there were a lot of particularities, and the cash part was a specific one. The future looks much more homogeneous than the past, even for financial services.
If I force you to put your investor hat on, thinking about fintech kind of at large and where there might be other opportunities beyond the ones that you're focused on addressing. You know, if I were to adopt the phrase of our great mutual friend Mickey Malka, who said a couple of years ago like fintech is dead—you know, maybe he's the best fintech investor ever, and now he's doing less of that and more things in AI and power and data and things like this. How would you frame the global opportunity to invest in fintech businesses, of new companies, of startups, versus companies like yours that, you know, have the scale, can go take advantage of a lot of this thing? Like, if I think about that battle between if I want to invest in fintech, should I do it in the incumbents—you're a new incumbent, let's call you—and pure startups. Like, what do you think the landscape, the opportunity set looks like?
I actually asked this question of Mickey last week because I saw him, and he spent a lot of time in AI and investing in AI companies. I was like, what, are you done with fintech, really? And I liked his answer, which is: no, we're not. We are just doubling down on the larger neobanks or neofintechs.
That are now riding the sweet spot between maintaining the ability to transform themselves through AI, but now have access to these moats of scale and data and brand and licenses. And so he continues to be an investor of us; he continues to be an investor of a number of other startups. And so for the early entrants, I think it's going to be in areas that are potentially less obvious as an entry path. It becomes a little bit harder, and you're probably applications on top of AI models that you do. So there'll be specific applications, I think, of an entry path, but I think building a consumer brand with hundreds of millions of customers at this stage, unless you come up with something completely fundamentally different, is going to be harder.
Can you talk about this big announcement that you just made and why you're so excited about it? Kind of what it means for the business.
I think most people still identify Nubank as a Brazil neobank or Latin American neobank—which is what we are. But when you go back in time and look at our seed deck in 2013 and the way we thought about the opportunity, there's nothing specific about Brazil to Latin America around the thesis. The thesis really is that global retail banking will be transformed by digitally native companies. And this is because digital-native companies can solve the problems that financial services have better—and these are the problems: the cost, the access, and the intelligence.
And so we're excited about this announcement as we launch the US as a market, and we also announced launching to upwards of 35 different countries a stablecoin-backed account, because this is the beginning of continuing to play this thesis that is a global thesis in nature. We think about our past 13 years as proving this model in Latin America, in the countries that we operate. And I think we did. We're now the largest private financial institution in the entire continent. We have the highest net promoter score. From a profitability perspective, we have the highest return of equity in a country like Brazil. So we kind of did all the checks, and now is a moment to continue executing this multi-decade vision of taking this model global. So we're very excited.
The US is obviously a very competitive market. It is the biggest market in the world. There are a lot of very strong neobanks and fintechs in the US that we'll be coming to compete with. But in reality, it's a market that's still dominated by big incumbent banks. So while there is a lot of fintech, you look at where is the market—the market is still dominated by a few incumbent banks and some community banks. Most of the banking in the US is still happening through banking branches, as if most of the video and media were happening through Blockbusters.
They still need to charge a lot, and they need to pay zero yield effectively to be able to fund this physical infrastructure. And there is a lot of comparative advantage that we bring to bear, like our ability to do credit for the mass market or our ability to do payments globally—and that's something that we also announced with the feature—and the ability to really make customers love us fanatically, to build a consumer-obsessed culture in an industry where customers just don't really care about their banking relationships, especially for the US mass market.
What do you think is going to be the hardest part about competing in the US?
Building a very strong brand will be one of the hardest things. US consumers mention brand as one of the key attributes to choose banks, and it's not cheap. And we want to do it in a way where we obviously have a lot of financial resources as being very profitable, but we want to do it in a way that is smarter and more capital-efficient than simply coming in and investing a ton of marketing all over the place. So building an organic brand in an environment where there's so many strong banking brands might be one of the most difficult challenges that we'll do. And that's critical to build trust with consumers, because we want to become their primary bank account. That's what we aspire to do.
If I had every buy-side analyst that covers Nubank here, and you got to sort of convince them of how they should think about your business through financial metrics. You mentioned return on equity earlier. Is that like the metric that you would point them to as the barometer of how well you're doing? Are there other metrics that you would hope that investors would use to assess like how good a job you're doing that are financial? How do you think about that?
Obviously, growth of number of customers and net promoter score and the cost to acquire that customer. So when you look at figuring out have you hit a vein and are you growing in a way where you found an underserved market and...
You're able to offer a product that nobody else was able to offer. That is the key. That's one of the key metrics: number, user count, NPS. But then, are you doing it at a sustainable pace? Because you can buy your way into growth by spending a lot of money on marketing. So what is the equation there? What is your LTV to CAC, and ultimately what is your return on equity? And the return on equity kind of exemplifies the advantages that the business model could have when you compare us with the big incumbent banks in the countries that we operate. We don't charge a lot of fees. We literally charge no fee. So we have less revenue, but then we end up with a return on equity that is two to three times their return on equity.
And so that basically means that you found a cost structure advantage. You found a way to offer a product at better quality at a much lower cost. And if you find that generally is through technology, then you found yourself a moat. You found yourself a comparative advantage, especially in markets like banking that are in ways commoditized. So I think it would be also looking at that combination of return and equity.
Talking about the US, one of the most interesting, least appreciated aspects of it is that by now some of the US incumbent banks have higher return on equity, are more profitable than emerging market banks that we compete with. That means there is the 'your margin is my opportunity,' right? The typical Amazon view or Bezos view of that incredible ROE that even incumbent banks have, even on top of the huge amount of cost that you are using to provide your product, that means there is a significant opportunity to undercut.
Who are your biggest influences? I know you've learned from some of the great entrepreneurs, some of the great investors out there. When you think about your whole Nubank chapter of your life, who are the people that jump out that have most actually influenced how you think about something? Who are they and why did they influence you the way they did?
We began the company as a reaction of a consumer pain, of me realizing how bad consumer banking in Brazil was and how painful it was, and then realizing that this was a proxy for what the majority of the country was actually feeling. And so we've always been, we'll always admire companies that are very consumer obsessed, that know that to win they need to just be able to offer the best product and best service in a way that creates almost fanaticism.
And so from that perspective, we were very inspired by Amazon since the very beginning. Amazon being the more traditional consumer-obsessed company and how they built this consumer obsession and how they thought about that. We studied Disney very carefully because this is a company that wants to create magic experiences. Maybe it's not super obvious, but even in banking, a boring banking product, we want to create a magical experience for customers.
What did you learn from Disney? That's an interesting one.
