“Everyone views their underwriting model as their secret sauce,” according to Kenneth Lin, CEO and founder of Credit Karma, speaking about banks reluctance to work with the startup.
“Banks need to get comfortable working with Credit Karma to unlock value with consumers. Our data says that 60% of loans get declined.”
Lin spoke with Nathaniel Popper of The New York Times on stage at the CB Insights Future of Fintech conference.
He started Credit Karma nearly 10 years ago to give customers information on better financial products they’re eligible for based on robust data. The company, which works primarily as a lead generation tool for loan and credit origination, earns revenues off financial institutions that pay Credit Karma to market directly to their core loan demographics instead of blanket advertising to customers more broadly. In 2016, Lin said, the company made about $500M in revenue, nearly 50% YoY growth.
While the company started by providing customers with insight into their credit score and access to loan products, the company has recently expanded into tax return preparation as well. In the six months since its inception the tax preparation program has assisted in 1 million tax returns, making them No. 5 or 6 in tax prep software offerings.
On a ten-year time scale Lin hopes Credit Karma acts as a digital assistant and platform that processes millions of data points on changing interest rates and financial products and updates customers in real time on the best kinds of financial products for maximum savings. “If you can (improve) financial services, that would make the world of difference, in which consumers would have frictionless experiences in choosing and evaluating credit, loans and mortgage offerings.”
One of the largest barriers to this, though, is the pace of the industry. Financial services moves at a glacial pace, according to Lin. “The vision is not different from where it was 10 years ago. There’s rules and stipulations about how this industry works but we have to move the ball forward.”
Transcript
Nathaniel: I’m sitting here with Ken Lin, the founder of Credit Karma. I know when I moved over to covering this whole realm within tech from covering Wall Street, I think a lot of the conversation at that point was on, you know, Lending Club, some of these other brand names, Venmo, obviously, PayPal, that stuff. But I kept being drawn back to and hearing a lot about Credit Karma just because of the sheer numbers. I mean I think at that point you guys had 60 million members, account holders, people who’d signed up. I mean that just dwarfed anything else in this space in terms of the number of people you were dealing with. So I guess the place to start with that is, how did you get that many people, and how do you make money from them?
Ken: Sure. So for people who aren’t familiar with Credit Karma, you know, we’re a business that’s been around for 10 years now. I think to your point, in the last five years or so, we’ve actually added about 70 million users on the platform just in the last five years alone. But the business model really predicated on this idea that consumers are desperately craving an understanding of, you know, credit, their finances. And I would argue, for a long time that’s been really an area that’s been ignored by many financial services companies, by many startups.
So our approach is pretty straightforward. Give people access to their information, give them education, and really focus on giving them better products based on that data. Right? I mean I think that’s the trend that you see in the space, is that data really matters, right? So whether you take a look at a Google, a Facebook, even an Amazon, you know, this idea of data being the ultimate driver of, you know, sort of the next wave of the economy, I think, is pretty powerful.
At Credit Karma, we focused on how do we do that in the financial services world? So our business model is to show people their credit scores, help them understand how to improve it, let them know when they’re over paying for a loan product. And when we do that, we make revenue from facilitating a loan, consumers should save money, banking partner should get a new customer. Business model is pretty straightforward. I would sort of add the last thing that we don’t do which I think a lot of people think we do, is sell consumer data. Right? We’re in the business of being a consumer advocate. We’re in the business of making sure people are in the right loan products.
Nathaniel: So you guys obviously began with the credit score. That’s sort of, I think, basic product that most people are probably familiar with. Recently, you’ve been moving to do a lot of other stuff as well, adding on to that. I guess take us through what the big ones are at this point that you’ve added on recently, or the big one if you want to just focus on that.
Ken: Sure. So you know, in, I think, October or November-ish of last year we actually announced our move into the tax space. So I think that is very aligned with our strategy, with this idea that data is tremendously important. If you think about what data is today and really the outlook for us is that credit is a view into the liability side of consumers’ balance sheet. Taxes, basically a view into the income and assets side, and with that, you have a very powerful picture of how consumers are thinking about their finances, when they’re paying too much, when they’re perfectly priced.
So that’s the opportunity for us. So we thought, “Well, that combination of data is tremendously powerful.” So we through strategically it was a great check box for us. I think moreover, for us, you know, we have this really strong mission at Credit Karma which is to help people move forward in their lives. And we looked at the sector and said, “Wow. Here’s an industry that looked a lot like credit scoring 10 years ago when we entered, which is notably, you know, 10 years ago if people remember that credit scores were ”free” but no one actually made it free, right? Free meant $20 a month historically.
And we changed that, I think, over the course of the last 10 years. And we think there is certainly an opportunity in parallel in taxes because everyone today claims that, you know, there are new filing costs or, you know, tax return software that’s free. But the reality is just like in credit scoring 10 years ago, the fine print is if you have a state return, if you make more than $62,000, it’s not actually free.
So we thought synergistic, you know,parallels to the business that we started 10 years ago, other side of the balance sheet, a real compelling reason to actually do something meaningful for consumers. So if we were able to, you know, help 10 million consumers file their taxes each year, you know, that’s some hundreds of millions of dollars of money that is going back into savings account. It’s not going to, you know, tax return software, right?
So for all of those reasons we thought taxes is a pretty powerful initiative. And over the course of the last six months we went to the space, we bought a company. We scaled it to the extent that we could, and you know, we’re excited to be in a spot where this year we’ll do about a million returns. And you know, that’s pretty meaningful. We think that will put us into number five or number six position in all of the DUII software players in the space and when you take a look at that top five, I think, the median age of that incumbent group is probably about 35 years. So it’s a group of people who’ve been doing it for a very long time. So my interpretation of that is not a whole lot of, you know, innovation relatively stifled in a captive audience or a set of players who play their incumbents. And our goal is certainly shake it up a little bit and do something more interesting.
Nathaniel: Okay. So you’ve done returns for a million people at this point?
Ken: Yeah.
Nathaniel: Okay. And then I guess…beyond that, I guess going back to that first question is, so you’re giving people free credit scores, your tax software. How do you make money?
Ken: Sure. So we look it as a lot different ways, right? So our primary way is we help people get into better loan products today. So my textbook case of a consumer on Credit Karma is maybe you come to Credit Karma because you’re generally just curious about your credit score. When you register, we’re able to see every trade line on your credit report. We’re able to understand the credit history. We’re able to understand whom you’ve borrowed money with, what interest rate you’re able to borrow that money with or at. But at the same time, we actually have integrations with most of the major lending platforms and banks to understand at what rates they’re lending.
So you come onto Credit Karma. You have an auto loan at 19%, that loan might be 19% because you didn’t shop, because you had poor credit at the time you took it out. But we’d instantly say, ”Wow, you’ve got a 720 credit score. You’re paying 19%. There’s three players who are willing to give you a loan at 11%, 12% and let’s say, 13%.” The consumer says, ”I didn’t know that.” We do the math for them and say, “Well, one, you’ll save $75 a month. In another example you’ll save 85 and so on.” Consumer picks the loan that they want. We help them through the process. Today, you still have to fill out some pieces of information. We certainly see a world in the future where a consumer doesn’t have to fill any information out. They just have to consent because if you think about it in the world and the strategy that we’re going after, we’re gonna know your credit history, we’re gonna know your income, we’re gonna know what the asset is, or collateral is through the car itself.
So really, the consent and knowledge and the consumer picking and the choice, is really all we need to make a difference. So in that world, we help them find a lower cost loan. Consumer is happy because they came to Credit Karma to find out the credit score. They found a way to save $75 a month. Our banking partners are generally happy because they would spend several hundred dollars on television, on Facebook, on Google to find new customers. We were able to facilitate extremely high quality consumer onto their platform. They pay us some form of that, and then we’re able to take those dollars to provide more credit scores, more free tax services and so on.
So you know, we think it’s a pretty virtuous cycle. I mean, arguably, the only loser in that equation is the bank that was originally charging that consumer too much and you know, we don’t particularly have a bunch of sympathy just we think that’s sort of a better efficient model.
Nathaniel: Okay. I guess you’re getting money from the people who are giving the loans, who you refer them to. I guess can you break down at all sort of how much you’re making, and you know, any breakdown on the sorts of loans that that’s coming from?
Ken: Well, I mean, it varies. So you know…
Nathaniel: Let’s start with the overall, kind of, you’re bringing in how much a year?
Ken: Yes. So I think…so for 2016 we did a little bit more than half a billion dollars in revenue, and also about…you know, about 50% revenue growth from the prior year. So it’s a really meaningful business in space, and I think that it just speaks to the opportunity. Banks spend an inordinate amount of money marketing their wares at a year to year basis and then get through that, you know, television, Facebook, Google, radio, you name it.
So our platform facilitates an opportunity for them to be much more efficient so they can find exactly the right type of customers that they want. I mean I think one of the big inefficiencies in marketing and financial services marketing, specifically, is that it’s really hard to find the exact type of customer you’re looking for. Right?
So imagine that you are a super prime lender in the space and you spend $100 million a year. Well, only a third of U.S. population is super prime, so you waste $66 million against a group that if they were even to apply in your site you’d have to decline them, it’s a terrible user expense so we’d make it more efficient. So that’s our revenue model. That’s sort of our average revenue. It varies in terms of what the, you know, economics are.
Generally speaking, it’s, you know, more expensive to get super prime users and we price appropriately. And it’s a little bit cheaper on a separate subprime side of it. In terms of verticals, you know, we have four verticals that we primarily monetize on today which is credit cards, personal loans, auto loans, and mortgages.
Nathaniel: Okay. So, what, I mean, 10 years down the line, how big is the vision here? Are you gonna continue sort of rolling out piecemeal free services? Obviously tax feels like it’s pretty separate from credit. I can see how they fit together, but what’s the big vision here that unites that? Sort of, what are you driving towards?
Ken: Well, I think if you look at sort of the great innovations on the internet, you know, data being the common theme, is that from a financial services perspective, it’s historically been very challenging to service anyone who isn’t at the top 1% from the law of perspective, right? You can have private bankers at that level. You can have literally someone who sits and watch your finances and tells you when rates change, tell you when a new market entrant comes in that might have, you know, better quality or better yield. It’s hard to do that for the 99% because of scale, and I think that’s where the technology…that’s where Credit Karma comes in.
So, we think about how do you build the digital assistant that can think about all those things, right, who can actually look at, you know, billions of data points, and say, “There’s, you know, all of your credit components that really matter, all of your asset components that really matter,” and in real time, push out things that change. So, for example, you know, if you’ve been, maybe following our advice, or you know, on your own imperative, you’ve wanted to increase your credit score, and your score goes up 40 points, well, that automatically makes you eligible for new loan products.
So we monitor that on a day to day basis. We monitor not only your own credit score, but all the players in the space. And we would be able to instantly send out a notification that says, “Wow, your score has gone up 40 points. Congratulations. That makes you eligible for X, Y, and Z loans. That will save you, you know, A, B, and C dollars,” and a thumbprint is what we need to actually facilitate that transaction, because we already know your name, your address, your income, and your credit. And, you know, I think that’s a pretty powerful platform. That’s a powerful tool.
I oftentimes think about, you know, the magic of Rideshare. To me, it’s never been the fact that I can get my neighbor drive me or I drive my neighbor. It’s always been about the fact that that magical app was…you know, I could pull out my phone, push a button, car shows up, I get out, I never took out my wallet, and it seemed quite frictionless. And I think if you could do that for auto loans, if you could do that for mortgages, if you could actually move your dollars around to the place that give you biggest yield or the place that lowered your interest rate the most, think about how much more efficient financial services would be on a personal level. I mean I think, you know, you might have to not detract or sort of take a step back from what it means from a banking perspective. I think banks will find ways to make money.
But from a personal consumer perspective, I think that makes a world of difference, and that’s really the platform that we’re trying to build with Credit Karma which is, you know, very much one around helping consumers. And, you know, we wanna help everyone, but I’d say, you know, the 99% are the most vulnerable, and that’s where technology can really step in. And, you know, our platform I think goes like 2 billion models each day around the data points to understand what is going on in the space in terms of our users, what credit scores are changing, you know, what to recommend, what people might be interested. So, that’s where the common theme that you see in the internet today, and we’re very much focused on it from a technology perspective.
Nathaniel: Yeah. I mean I think the thing that interest me about what you guys are doing and the potential there seems to be a sort of central place in a person’s financial life where you can sort of monitor all your accounts and move between them and figure out what you should be doing. I mean do you think there is room for that? Do you think there is a room for that sort of central dashboard, or are there gonna always be 15 different apps that I have to go to do payments here to figure out, you know, “What’s in the check-in account here to monitor my investments here?” I mean how centralized do you think things can become?
Ken: Well, I mean there hasn’t…I mean I think, in this space, there could be very much “a winner takes all,” “a winner takes most type of opportunity,” right? I think that historically it’s…I think part of the reason why the industry has not been particularly disruptive or innovative is because it’s hard to get to scale, right? We have a lot of incumbents that make a lot of money in the space, and the only way to move the needle is to actually have the scale, the sheer number of users to actually facilitate change.
So, you know, I think that ultimately this space will be dominated just like most verticals, right, if you think about whether that was search, whether it was about social, whether it was about ecommerce. You know, I think critical mass matters a lot. Economy is a scale matter quite a bit, and ultimately that behooves the data aspect of it. And, for us, you know, we think that, sure, you know, credit scores are ultimately going to be a commodity.
And, for us, it was never about credit scores. It was about this ability to build a brand to engage with consumers to show the value proposition of what happens if you could build a business that was consumer-centric, not being adversarial to banks and financial institutions. I think that, for us, that’s all the combinations of the product. So whether that is the tax returns, whether that’s our ability to give you credit scores, and, you know, probably the other half dozen other ideas that our team is, you know, working against, it’s all in that common theme of, “If you get to scale, you have the most amount of data. You have the most amount of integrations.” You tend to have a pretty interesting ecosystem, and you see it in communications with WeChat in China. You see that in social in, you know, United States with Facebook, and we certainly think that there’s an opportunity to do something in the financial services world.
Nathaniel: I mean how much harder is that in finance, you know, to create a sort of…I guess the way I think of it is a sort of search engine for financial products. I mean I’ve just been through this. We’ve talked about this. I just moved, got a mortgage, and, you know, there is almost no transparency in this market to figure out, you know, what kind of interest rates are out there. I mean it’s kind of astonishing, and I guess… I use Credit Karma, and even on Credit Karma, I didn’t get much of a window into what kinds of loans, you know, what kinds of rates might be available. I mean how hard is that? How much are you pushing against, and how is it far away from really knowing, you know, being able to figure out without going through the loan process itself which nobody wants to do? You know, what are the rates that are really available to somebody? It seems like that’s still quite a ways away.
Ken: Yeah. I mean I think that is the biggest challenge, right? I mean I think this space moves at a glacial pace for the most part, right, because there’s not a lot of initiatives or impetus to create a lot of change. Ironically, I mean the vision of Credit Karma is not very different than what it was 10 years ago. I think we’ve come a long way from a scale perspective for some of our integrations, but you’re absolutely right. So, our mortgage product that, you know, we talked about, it’s only, you know, six months old, and at six months old because we actually didn’t like the way that transparency exist in the space. We didn’t like the way that there were still a lot of paper collection going around in the space.
So we actually were a little hesitant to enter the space. We weren’t sure how much further and how much faster we could push the innovation envelope, but we realize if we didn’t step in, you know, then it would still be a bunch of people calling you when you’re looking for a mortgage rate, and the first person to call you oftentimes would get the business. So we thought, “Well, why don’t we start somewhere? Why don’t we actually start, you know, sort of the transparency process? And how are we going back to our overall strategy and this notion that data is ultimately the thing that will unlock the value for both Credit Karma and the consumer? How do we take the tax information, the credit information?”
The reason why, you know, it’s challenging today is you actually need 30, 40 data points to give you a relatively accurate quote process, right, in terms of your mortgage. Do you really wanna do that at 10 locations? Well, our view is, “Well, you probably don’t even wanna do that at one location. So, how do we facilitate that in Credit Karma? And then, how do we take it so that we can actually give you as much of a transparent view into the all the lenders in the space with as much ease and talking about that magical experience?”
So, that’s our goal. It’s slow. It moves a lot slower than I particularly want it to move, but it’s also challenging because there’s, you know, GSEs, there’s Fannie, there’s Freddie, there’s all these rules and stipulations around how this works. But with that said, I think that we have to continue to dream and move the ball forward.
Nathaniel: I mean if you wanna sort of think about breaking all this data open, and making it available to people, you know, what rates can they really get on loans? What products could really be available to them? If there were one or two changes you could make with the lenders to break that open, what would it be? I mean is it…do they have the data? Do they have to make some change, or are they just unwilling to provide that, or what are the changes that need to happen to kind of, you know, loosen that DAM of data?
Ken: Yeah. So, it’s a fascinating question, right? And our observation space is that, you know, the opaqueness of everything in financial services are [inaudible 00:19:15] and financial services really revolves around this notion that everyone views their underwriting model as the secret sauce, right? It’s why I think a lot of, you know, banks would say, “This is why I make $5 billion or $20 billion a year because I have this really proprietary underwriting model.” The problem with that is it’s proprietary. No one actually knows how it works.
So, that is the thing that I think banks need to get comfortable with. Now, I think what Credit Karma is trying to do is to act as an intermediary, right? Our perspective is, “We don’t care what your underwriting model is. We don’t care about the secret sauce. We’re not actually here to become a bank or lender, so we’re not a competitor with you at the end of the day,” right? What we’re trying to do I unlock a value for consumers. Our data says something like 60% of loan applications get declined, right, and this is in a world where we have autonomous cars or nearly autonomous cars, and we still can’t figure out, you know, 6 out of 10 times when you’re not gonna be approved for a loan product. So that’s a real consumer issue.
So, unlocking and serve our… You know, if we were in a king or queen for a day, we’d focus on this idea of, “Is there a way to solve that problem? Because if you could do that, then all of the rates become transparent, then consumers have real choice, then consumers understand that, ‘Oh, I actually have, you know, a thousand loan products that are available to me. And in the past, I would apply for two, maybe get approved or not, but now I can actually see all thousand. I can see all the interest rates associated with it.’ ” So that’s, you know…
Nathaniel: Is there something that you think is stopping that from being unlocked?
Ken: No. I think partly it’s sentiment. I think it’s partly trust. I think it’s partly, you know, the certainty of the unknown here, right? You know, I think that everyone that we’ve spoken to has a real fear of, like, “What happens in that world if consumers? Are we really able to understand credit underwriting?” And I think it’s pretty fascinating.
So, if you take a look at, you know, four years ago, credit scores were all that mattered, right, because the construct of a credit score was, you know, a loan officer would look at your credit report. You would be a loan officer. I’d be a loan officer. We might look at the same exact credit report, and you might decline it. I might approve it. And the credit score was born, because, you know, [inaudible 00:21:24] to actually determine somebody’s credit risk.
Fast forward four years, we’re in a space where big data really matters. Credit scores don’t really matter. So, credit decisioning is, you know, maybe a hundred; at times, a thousand data points. If you think about that from a consumer experience, it’s a terrifying notion that there’s a thousand things that determine your eligibility for credit, and you actually have no visibility into how that works. So, you know, again a little bit of our vision is, “Well, if you solve that, isn’t that what consumers are really asking for when they’re asking for their credit score? Aren’t they asking for, like, ‘Tell me what I can either buy today or buy in the future from a credit perspective or a financing perspective?’ ” And it’s getting more complicated, not less. So, our goal is to solve that problem.
Nathaniel: All right. So let’s talk about one sort of rub in your business which is that… You know, I used Credit Karma when I was going through this mortgage process, and I found it was really helpful for sort of monitoring the credit score or thinking about how to lower it. But when it came time to get recommendations from you guys, it felt a little bit like I was getting a few recommendations from the credit card companies that paid you guys to give me those recommendations. And that was my assumption, you know, Credit Karma’s getting paid by Capital One and so they’re recommending me a Capital One credit card. I mean that tension sits at the center of your business. How do you deal with that so that a customer can feel like I’m really getting honest advice that isn’t just about, you know, who’s paying Credit Karma?
Ken: Sure. So we’ve always been very transparent. As I sort of described our business model at the very beginning, we make money from the banks, right? We help facilitate loans and that’s how we get paid. And, you know, as a company, we spent hundreds of millions of dollars on providing the service [inaudible 00:23:15] and so on.
Our goal is to provide the very best offer. Now the way that we currently do our ranking is we actually focus most importantly on your chances of being approved. It doesn’t matter how great the rate is if you can’t be approved. So that’s the first thing that our algorithm looks at is, “What are the probabilities if you’re going to be approved?” Now, it just so happens that we know those best when we have volume and we know that best when we actually partner with people who are reporting back approval and declinations. Now that coincidentally happens to be partners who paid us or sort of pay us or have a partnership, but our goal is to actually have every product on the platform, right? Ultimately, we don’t care if you are the smallest credit union in the corner. If you have the very best product and the very best rates, our goal is long-term to have those particular products.
So I think it’s a little bit of a journey. Our goal is to make sure that consumers have much choice as possible, but certainly you know we worry a little bit about free rider problem, right, because if we made it completely free or if we didn’t have a revenue component or if we didn’t think about the partnerships, there’s very much this race to the bottom where no one is paying and we basically aren’t able to provide the service. So there’s an important balance here, and I think a level of practicality that has to happen. So, we try to… Our solution to it is be very transparent, make recommendations first on the probability of what you think you’re going to be approved secondary on the price of the product, and then third if there’s a tiebreaker which is sort of the, you know, payout to that particular product. [inaudible 00:24:42] from Google.
Nathaniel: And will you recommend products where the company is not paying you to recommend it?
Ken: We don’t have a philosophy against it right? We have not found products particularly that are price competitive that aren’t marketing, right? So, said another way, we have not found products that are the best in the market that are not marketing, right? So, is there a product out there that’s yielding 4% and from a APY perspective? We don’t know about it. And if they were, we’d probably have more platform, but it’s always a balance.
Nathaniel: So, another I guess another thing to think about here on the consumer side is, you know, their financial health. And I mean a lot of consumers what they do not need is more debt. And I am using Credit Karma. There were times where I was offered, you know, a personal loan from Lending Club to consolidate my credit card debt. And I actually don’t have…I mean I just had my monthly revolving, you know, debt, but I was offered, you know, take a loan out to finance this debt. How do you think about the financial health of the consumer and whether they need to take on more debt or whether they should take on more debt?
Ken: So we have a perspective. We never will promote a product that we think is worse for our consumers, so first and foremost, right? Now, I think also behind that, we actually think a lot about transparency. When we do comparisons, you know, we actually get criticism from…I’ve had investors like, “Why did you show me products that were,” like the math on mean like, “losing $300?” Because we wanted to be transparent about it.
So our perspective is not to get people into debt. Now, I think in your specific case and example, you’re talking about this is where better data helps us. Right now, some of our partners don’t actually report whether or not…or in the credit bureau, whether you’re actually a revolver transactor, meaning we don’t know whether or not you’re carrying a balance month to month. So in that particular case, our model probably said, “We think Nathaniel is carrying a balance. We would assume it to be at 14%-15%. Here is a personal loan at 9%.” I’m sure the calculation did the math right.
So that’s an example where you’ll ultimately need more data to make better predictions. So you know, it’s two billion calculations day to day. We could see it going to 10 billion in the future as we collect more data so that recommendation can get more precise.
Nathaniel: And how far are you on the customer side from having enough data to make real, you know, solid recommendations across the board and how much more data do you need to get? I mean if you get their tax…if right now you have their credit score, you have tax data on a million of the 70 million, I mean how many more do you need to get? And…well, yeah, how far are you on that side?
Ken: Well, I think it’s pretty specific by use case, right? So I think that there’s two ways of doing this. One is we can obviously continue to build out new products. The other is still actually self-reporting information. It’s pretty powerful, right? So for example, there could be a simple IP in my credit card balance often full each month where I carry a balance. That actually gives us a piece of data to unlock the recommendations for you.
So there’s two ways to go and pursue it. So that one is, you know, when we continue to add on features. But you know, we think for some meaningful percentage of our users we actually have a really great profile and we can actually be very precise in what we recommend and have a high degree of confidence. So for example, some of our auto loan partners or our consumers who have auto loans, you know, we have models that are like…we are like 95% sure that they are overpaying for this loan by $200 each month. And you know, our goal there is, all right, product team, let’s be particularly aggressive…aggressive isn’t the right word but let’s be really poignant about this idea that this person is really overpaying.
So for that class of consumer, we’re really sure, we’re abundantly sure. And then I think there are a lot of others where like, well, you know what, we actually only have credit score and credit report. We can’t really triangulate in that. I think the recommendations get a little bit looser, but that’s the value of over time building the asset.
Nathaniel: But it seems like you have consciously decided not to go the route of mint and other aggregators where you just ask to log into people’s accounts. You could go that route and you haven’t.
Ken: We actually have that feature. I mean our observation in that space is that, you know, I can’t…I don’t know of any company or person who’s actually done it has gotten past single-digit penetration rate. I think the traditional budgeting tools has been a single-digit penetration type of use case. And we at Credit Karma, just to get to scale, we think about, how do you actually affect tens of millions of people over time?
So we could do that. I don’t know if there’s enough value in it from a consumer perspective today, but we actually have the functionality. So for some percentage of our users, we have it. I wonder if it’s actually a long-term value proposition.
Nathaniel: Okay. Last question. When do you IPO? How long do you remain a private company?
Ken: Yeah. I’m not trying to be quiet. I actually don’t know. I mean I think that you… An IPO is a beginning, not an end. Right? I think that really to be successful in the eyes of investors, in the eyes of your shareholders, and in the eyes of your employees, there has to be a long-term sustainability about going public. And I think that that’s what we’re ultimately optimizing for. So it’s not like I’m trying to avoid the question, but you really want, “Hey, do we have great visibility into our revenue streams? Do we know the products that we’re expanding into? You know, what do we think about the market?” Those are all instruments, and I think they’re just a little bit too murky right now. So you know, nothing this year for sure.
Nathaniel: All right. Great. Thanks so much. Thanks, everybody, for listening.
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