Did you just come in from Montana or something? What happened? I did get in last night. Oh, okay. Well, it's funny 'cause, is it still the case that FICO is the only S&P 500 company headquartered in Montana? I don't know if that's true anymore. I think it is. It might be. I mean, Snowflake is there, but I'm not sure they're in the- I don't think they're headquartered there, yeah. Yeah. I think they have no headquarters. They may be virtual, indeed. Okay, so, why don't we just have you start us, Will Lansing, and welcome to the conference- Thank you ... with a little bit of a story, just to orient us around the journey of FICO. 'Cause you've been CEO for 12 years. Yes. You just had your 12th anniversary, but you've been affiliated with the company even longer as a board member, right? So- That's right. What's your high-level take on the journey to date? Well, I'm glad you gave me that opportunity. I'm gonna start 67 years ago, when the company was founded, which it was in the 1950s by a mathematician and an engineer, Bill Fair and Earl Isaac, and their game was analytics. It was really a consulting business, and they quickly gravitated to high-stakes decisions, banking decisions, and they built proprietary scorecards for banks, and that's pretty good business. We did that through the 1950s and 1960s and 1970s. And then they had this idea that if somehow we could get the analytics into software, we could get returns to scale. And so they went down a path of trying to achieve that. Very difficult to do. As you guys know, analytics is kind of a custom, bespoke business. You know, what's the decision you're trying to make? What question you're trying to answer? You bring together data and analytics to do that. So it's hard to do, but over the course of 30, 40 years, we've built a number of pretty successful franchises that were software franchises aimed at answering very specific questions. Originations: who should we lend money to? Who's gonna pay us back? Customer line management: how do you manage the risk? Fraud, credit card fraud detection. So we built these franchises. Well, I joined the board in, oh, I don't know, 2007. I became CEO in 2012. In 2012, when I took over, we had these five or six very strong franchises that were growing a little better than GDP, but not fast. We had this idea, besides the obvious idea, which was, "Let's go to cloud," 'cause everything was on-prem then. You know, we made this cloud migration, but beyond that, we had this idea that if we could put the same decisioning engine into each one of these applications, we could save some money. There'd be some returns to scale in the R&D if you could have the same decision engine in each one. So we did that, and we thought, You know, they all need to ingest data somehow, so maybe we could just ingest it the same way, cleanse it, wrangle it, orchestrate it, do things with it in that way. That would work. So we did that, and piece by piece, we assembled a platform without calling it a platform. We called it the FICO technology stack, but basically, we were building a platform business, and that's how we got to kind of where we are. You know, now, now we have a platform business and it's... You know, it all hangs together, and what we do is take data from all different kinds of places, apply analytics, turn it into a decision, operationalize that decision, and then communicate it out, so that you can optimize the interaction with the consumer. That, that's the FICO business- Right -software. Let's go into scores and software slash platform. Right now, scores, it's effectively industry standard. It is that, yes. How did it get to be that? Well, so our scores, most people are familiar with our scores business, and I am often asked, "How, you know, how do you become an industry standard?" It took 35 years. It started out with a good value proposition, so it was a low-cost way to make a credit decision about a consumer. And it was also applicable to a very broad population. So we used the credit file that the credit bureaus have. Why? Because if you wanna know if someone will pay you back in the future, best question you can ask is, "Have they paid you back in the past?" So that's the credit file, and so we built a score around that, and the lenders found it very useful, very cost-efficient and broad population scored. Well, then what happened was the regulators started to rely on it. They said, "Wow, that's a really useful measure of risk for us, and you can tell us what the average FICO Score is for different portfolios and how it'll behave in a downturn." And so now we have a second constituency, the regulators, in addition to the lenders, who like using the score. Then you get the investor community, who says, "I'm gonna, I'm gonna buy your paper. What, what's it worth? I'd- I'd like to understand the risk in the paper I'm buying." So now you have the investor community. And then finally, we brought the consumer into it with a program called Open Access, where we said to the banks who were buying the score, we said, "Look, if you wanna share the score for free with your consumer customers, we'd be delighted." And they did, and so now we have 250 million accounts who get their FICO Score free every month. Is innovation still happening in scores? Oh, it certainly is. It certainly is. You know, we are now on FICO 10, 10 and 10 T, which is the tenth generation of the general FICO Score, and then we have about 50 other scores that are focused on various markets. For FICO 10 T, like, what's the incremental differentiation? You know, I think you can look to... from 9 to 10, we got a, about 5% lift. Mm-hmm. So there's, you know, and I think it's like that. I mean, there are people still using FICO 4 because, you know, you get a lot of benefit out of that, but then each generation, there's a little bit more. Mm-hmm. And then there's this, FICO Resilience or Resiliency Index? The Resilience Index is an interesting one. That's a new score we brought out a couple years ago, and that tells you how a consumer is likely to behave in a downturn. So you can take 2 FICO 680s, and you can assess, as between those 2, who's a better and who's a worse risk in the downturn. That's what the Resilience Index does. Talk about competitive dynamics and scores. ... Well, you know, it's we don't rest on our laurels. There's always efforts to displace us. The bureaus developed an alternative score called VantageScore that about 15 years ago, and they've been offering that to the market. You know, I'm pleased that the market still relies predominantly on FICO scores. We are the industry standard. But you know, the trick is to continue to innovate. You can't just sit around and rest on your laurels. We also try to go out internationally with scores, and so, you know, there are different dynamics in every market. But we're busy, you know, penetrating international markets with scores as well. To what degree are various lenders required to use your score? I, I'm- To what degree are various lenders or people who care about it required to use FICO? For the vast majority of our scores, it's kind of voluntary. No one's required to do anything. You know, it's an arm's-length transaction, where the lender has elected to use the score because it's low cost and good decision, and the regulators like it, and so on. There are a couple of markets, and mortgage is probably the most notable, where it's required. So if you're a mortgage originator and you want to sell a conforming mortgage to Fannie or Freddie, you're required to provide a FICO score. You mentioned a competing approach, Vantage, and there's no reason somebody couldn't use both Vantage and yours, but then also some of the fintech names have suggested they can innovate in a way that obviates the need. Yeah, you know, it's interesting. I remember seeing some kind of derogatory stuff on television, and there were a couple of bad Wall Street Journal articles several years ago, and all having to do with this idea that fintechs and new credit evaluation technology was gonna make the FICO Score obsolete. And we didn't believe it then, and it turned out that it wasn't... It hasn't transpired that way. But you have to ask yourself, why? Why is that? And the reason is, you know, it's what I said before about if you wanna know if someone's gonna pay you back in the future, look to the history of whether they've paid you back in the past. The single data set with the most predictive value for that question, which is a very important, high-stakes dollar decision, that the best data set for that is the credit bureau credit file. That's where, that's where the data is. That's where the highest caloric value is. Now, can you get a better decision if you add other data sets, if you bring in other data with some kind of caloric value that lets you make a somewhat better prediction? Of course you can. And banks do it. They bring in their first-party data. They look in the checking account, say, "Oh, this person, a lot of overdrafts, not such a good credit risk." So you can bring in other data and make a better decision, but if you had to pick one data set, you would pick the credit file, and you build off of that. So even if you're a fintech, if there's a credit score available, start with a credit score, and then put your secret sauce on top of it. You don't say, "I'm not interested in the payment history." So, you know, what's happened is, you know, I think people recognize that it's the cornerstone of the credit system, and you just start with that, and then you bring all your innovation on top of that. You can't just ask ChatGPT? Yeah, you can ask. You might get a different decision every time. Right. If you turn somebody down, you have to tell them why. Yeah. You can't actually ask ChatGPT, so I'm kidding around. And the truth is that heavily regulated business, and we have fair lending rules, and among other things, when you turn someone down for credit, you have to be able to explain why you turned them down. And so that's problematic for AI, that's problematic for black box decisioning. Yeah, there's some real challenges around it. Right. So you have a fixed data set that you go to, and you have to be able to, post facto, explain how it worked. Yes, you do. And so... Well, most people don't know this, but with the FICO, just to take the credit score for a minute, before you go to our software, which is, you know, has a lot of flexibility, the FICO Score has 32 reason codes built into it. And so if a lender decides not to lend to a particular consumer, they generate a turndown letter, and they explain why it is that they're not gonna increase your credit line or why they decided not to give you a credit card. That is pulled right off of one of the 32 reason codes that come along with the FICO Score. Got it. You have to be able to explain it. Mm-hmm. How about just remind us the philosophy on score pricing versus value delivered? Well, you know, we believe that there's that we think the scores are very valuable to the lenders who use them. I mean, it's just incredibly low cost. I mean, our scores cost between basis points and single-digit dollars. That's the range on what we charge for a score. And we think that the value of a quality decision around lending hundreds or thousands or tens of thousands or hundreds of thousands of dollars, the value of getting that right is obviously very high. And so, you know, what we charge relative to the value produced, pretty big gap. So of course, we're in the business of trying to close that gap, and we're constantly looking market by market at where there's opportunities for us to raise price. At the same time, we have to do it responsibly. We recognize that we're such a core part of the ecosystem, we're such a, you know, a critical piece of it, that we don't want to rock the boat and shock the system. We want to do it in a way that's predictable and that works within the system. Okay. You may not want to comment. I think it's your practice not to, because you're a lagging indicator relative to things going on in the scores business, mortgage, auto, et cetera. Any high-level observations on state of play with macro in the markets? ... Yeah, we are truly a lagging indicator, so anything that I say now will be just me making stuff up as opposed to working with FICO data that you don't see. We, we're a lagging indicator. I think the bureaus are 6-8 weeks ahead of us on what they see. You know, I think some of us are surprised that rates haven't come down more quickly. I think there was an expectation that rates would come down more quickly three months ago than today. I would say that FICO built a lot of conservatism into our guidance around that. And, you know, we typically discount the industry forecasts a fair bit. You know, you gotta believe that in an election year, some good things happen. But set against that, you know, half the world's in recession already. So that, you know, there's, I think we have forces going both directions. Right. Well, you, you brought it up. So the guidance from the recently announced quarter, you didn't bake in a change in trajectory in mortgage or pricing, or? That's correct. So what you didn't see yet... We really don't give quarter-to-quarter guidance, we just do things on an annual basis. And the price increases for 2024 don't take effect until January 1, which is actually our second quarter. So nothing in our first quarter reflected 2024 prices. So that will now be reflected going forward in our 2024 numbers. So next quarter, there may be an update? Next quarter, you'll see that, but it's kind of baked into our annual guidance. Mm-hmm. Okay. Well, and is there anything else to talk about on scores right now, or should we shift over to- We should talk software. Okay, let's talk about software. You alluded to it before, it's kind of been on its own journey. What's the state of play now? Well, we're really pleased about where we are. It's. We think of our software business, this is our platform software business, as being next generation CRM. So our goal was to provide this data-driven decisioning to optimize interactions for B2C companies who are talking to their consumer customers. And it came out of our competence around predicting consumer behavior and, you know, that's what we've done for 30 or 40 years. We've been on that path. But now you can take that same kind of decisioning, precision and bring it down to lower stakes decisions. So it's not just should we or should we not make this auto loan, where the stakes are high, but it could be a marketing decision. It could be, you know, it could be, what offer should we send? What should we be discussing as a next best offer with a customer who shows up at the call center? So taking all that, we kind of put together this decisioning platform that enables any B2C company... We focus on financial services, but it's a horizontal play. It's really IP that can be applied across many different verticals. You know, we focused on how do you do that for the consumer? And it's working. I mean, you know, we really are in this place where if you are... I mean, we'll just talk banks, because that's most of our customers are banks. During COVID, most banks figured out that people aren't coming into the branch anymore. We have to have a digital relationship with our customer. And they have chief digital officers, they have digital transformation officers, and these people, and the C-suite, are very focused on: How are we gonna have this digital relationship with a consumer and optimize everything we do with that consumer? And our solution does exactly that. It's purpose-built for doing that. And so what's happened is, we're seeing tremendous adoption by the large financial institutions around our decisioning platform. You've been in the software business a really long time, but what's, and others have had their own version of this, but you're moving from on-prem to cloud, from one-off to real platform and productization. Correct. You've been in the banks a long time, kind of doing, in the past, bespoke solutions. Like, this is not new, it's just that you're trying to platformize this. I think, you know, most banks, certainly the big banks, I don't wanna say siloed, that's kind of an old way of looking at it, but I think there were some divisions in the businesses, and I think often business decisions were made in one part of the bank, you know, independent of decisions being made in another part of the bank. And although the Chief Risk Officer was tasked with trying to understand the risk across all of the different areas of exposure, they didn't all play well together. We weren't busy optimizing. And so you had lines of credit that were open that weren't gonna get used, which, you know, chews up capital that's, that's unnecessary. You took risks in other ways where you probably shouldn't have, and you weren't getting the conversion rates on the interactions with the consumers that you might have liked. And so I think now, you know, we're really focused on how do you make all that play well together. So it's not just, "Let's reduce fraud in our credit card portfolio. Let's get originations right in this portfolio. It's about real-time, instantaneous interaction with the customer. The real-time thing is a pretty interesting piece of it, because you have a consumer shows up somewhere, some point of interaction, and they expect a real-time answer. What's a little bit at odds with providing a real-time answer is, if you want to analyze a tremendous volume of data to capture the most caloric content, so that you can make the smartest decision possible, that kind of bumps into your ability to do it real time. FICO has been in this business a really long time. We spent a lot of time figuring out, how do you do that, and where do we really learn that? We learned it in our Falcon Fraud business, where-... You know, we have to turn in a decision on, is this a fraudulent transaction or not fraudulent transaction, in less than 15 milliseconds, because you're- someone's standing there drumming their fingers on the counter at the retailer. So we have to do a 15-millisecond decision, typically less, and we have to boil the ocean to get to that decision. So how do you do that? Well, we have IP to do that, we- you know, we're really, really good at figuring out which bits of data do we need to use to make this particular decision at this moment in time to do it in real time. So, so we're good at the real time thing. It's important to be able to do it. Give an example of what real time means in a customer experience context. Well, it's everything from the offer that populates the screen for a call center operator when someone calls in, which has history and has, "Here's what, here's what we're gonna work on, and here's what we're gonna offer next." It could be when they show up at the website, it could be if they walk into a bank branch. Mm-hmm. And it—like, it could be, "Hey, I've got a customer, I know they got a raise 'cause I see it. Oh, I see what you're saying. You know, Yeah. Yeah. Yeah, so, you know, there's degrees of knowledge about a customer that you can bring to bear on a decision. So for our bank customers, the most sophisticated of them, they, they have a lot of visibility. They see when you got a raise, because they see what happens in your checking account when the direct deposit number goes up. Well, that can inform your decision about should you be making an auto offer? They, they see, they see all those kinds of things, and, and so you can bring all that to bear in the decision. Right. And then you're not constantly spamming the consumer, and- Exactly ... they turn off and tune out. Okay, let's go into the whole idea of the software platform and the opportunity to go deep in the vertical in financial services versus horizontal for other industries. So that was a big strategic question for us a couple of years back, where, you know, we have historically focused on large banks, and we're pretty good at it, and we have a lot of market share there, and we have a direct sales force that understands that well and has relationships with all the large banks. But as we thought about where does the growth come from, do we go down market to tier two and tier three in financial services? Do we go to adjacent verticals like insurance, or do we go more horizontal? And I think that the, you know, going down market, we rely heavily on our processor partners for second and third-tier banks. We've elected to go the more ambitious route, which is to go horizontal, and the reason is that we think that our IP is so... It really is, it's vertically neutral, and any B2C company can leverage our IP to make optimization decisions with their consumer customers. The challenge is, we don't have a sales force that knows how to speak the language of these different verticals. We don't have the domain expertise, and scaling up a direct sales force into all these other verticals is kind of beyond our resources and ability. And so we decided the way we were gonna go at it was with indirect. We were gonna build an ecosystem where, through indirect support of partners, we could get SIs and ISVs and, resellers and VARs to, to come and use our decision platform with their domain expertise to produce solutions for their customers in other verticals. That's, that's worked out pretty well. I mean, that's, you know, that's kind of the path we're on. Today, we have, we have APIs that are made available to our large bank customers, and they have engineering departments who know how to use our platform and know how to build solutions in our world. But we don't have, yet, well-documented APIs that can be used by the public, and so that's coming this year. We're on a path to providing, providing open APIs, and that'll happen certainly in 2024. And I think that's a pivotal moment for us because that's when the ecosystem really starts to form around the decision platform. And we're pretty confident it's gonna occur because nobody has a platform like this. This is fairly unique. And then for the big banks, you know, where you're very entrenched, are we talking tens, hundreds? Like, for that top tier, what is—how do you size that? Well- I mean- ... the way we think about our immediate market for our direct sales force, we think about the 300 largest financial institutions globally. We have about a little over 100 quota-carrying salespeople who cover that universe. We're penetrated, we're in about 100 of the top 300, and, you know, our intent is to continue to serve directly the next 200 that we're not in yet, and then really rely on partners for the rest. Okay, so you've landed 100. You're trying to land the next 200. Correct. Where are you on the expand motion for the first 100? Well, so if you go... If you, you know, if you take a customer that did a $3-$4 million deal with us three years ago, they could be at $15-$20 million today, three years later. That's, I think that's typical of a mature, maturing platform customer. Got it. So if you think the down-market opportunity in financial services and in the horizontal and all these other industries, like, what's the near medium, long-term TAM? Is there a way to size that, or? Well, I don't know. I think you have to look to some of the really big guys like Salesforce, and say, "What's their TAM?" Because their TAM is our TAM. Right. I mean, it's as big as the B2C market for CRM. How big is the software business now? Our software business is $800 million, of which $200 million is the platform business. Right. So we have a lot of room. Right. You added how many to the business in software last year? ... We're growing a little over 40%. Yeah. Yeah. No, I mean, in people, headcount. You-- There's, like, 100 people or something? Oh, yeah. Yeah, we do it. We don't need a lot more people. Right. Right. And then how do you think about the international vector? Well, so, you know, we work international on both the score side and the software side. The software business is already very international. It's about 50% outside the US. And then the scores business is predominantly a US business, but we're, you know, through innovation and partnership, we're putting scores into other countries, too. Right. At this conference and in the market, you know, there's, in SaaS, you know, a lot of focus on how many solutions are really optional and nice to have versus must-have. How do you characterize what you do for the big banks in terms of their, their digital replatforming? I think it's must-have, and I think we're seeing that even in a time of somewhat constrained IT budgets, the fact that we're continuing to grow the way we are is a reflection of how must-have it is. We, you know, we. There are some decisions you can put off in tight times, you put off for a year or two or three, and you know, even some of the problems that our legacy solutions address, you know, you can postpone an upgrade in one of those solutions for a year or two. But I think that the digital transformation is such an imperative for our big customers, that it's just not being put off. It. You know, this is a top priority, get it done. You know, it's not just because it's such a top priority to get to digital transformation. It actually does save a lot of money. The return on investment is tremendous, and word gets around, and so the payback is very rapid. Then how about the competitive dynamic for that digital replatforming or transformation opportunity? You know, what we are mostly competing with there is homegrown, built inside. And not that it can't be built inside, I mean, you know, you can build anything, but I think that it would take $100 million to build inside a large financial institution what we will sell you for $4 million. And, you know, I think that's where it is. You know, we've taken that cost of the development cost and amortized it over, you know, hundreds of customers, and so I think that's a big part of the winning strategy we have here. Great. Anybody have questions for Will? If so, we'll pass the mic around. Anybody? Up here in front. I think it was him. You mentioned that FICO Score is in a 10 and 10 T version right now, but how far is within financial vertical that they adopted 10 and 10 T, and how should we think about the pricing uplift from there? It's very early days for 10 and 10T. So I think what you have to recognize about our scores business is, it takes a very long time for a particular generation of score to be adopted. So going from FICO 8 to FICO 9, it took four years before 50% of the market was on FICO 9. And I think you'll see the same kind of thing. It'll be four years again before FICO 10 is half the market. So it's a very slow adoption rate. From a pricing standpoint, we don't charge more for the newer generation of scores. We want to encourage adoption, and so we charge the same thing. If you're paying X for a FICO 9, you can have FICO 10 for the same price. Just with your commentary around not wanting to push the boat too much on pricing, any additional thoughts you could give us for the feedback you're getting, the thinking? I understand there's a giant value gap, but just the pacing of that closure of the value gap. Well, you know, as I said, we try to be reasonable about it, and we try to be predictable about it, and I think that the markets and our customers understand what's likely to occur, you know, as they look out over the next several years. You know, we're pretty transparent about the prices. We've taken more recently to actually publishing our prices around... Not, not everything, but some things we publish the prices, so there's a lot of transparency and no shock. Like in mortgage, you collapsed all the tiers, right? We did collapse the tiers in mortgage. Now, in a lot of markets, we have tiered pricing, time-honored approach to reward larger customers and larger volumes with lower prices. We did that initially in the mortgage scores market, and we did get a lot of kind of, pushback from the market, from small guys who said: "It's just not fair. It's not fair that the big guys get a better deal than we do." And so we collapsed the tiers, and so there's a single mortgage price. Can you just spend a little bit more time on international and, you know, are there countries where you do better or have bigger market share, or where there's a bigger opportunity, like Canada or India or... You know, can you just spend a little bit more on international? Sure, absolutely. And again, different story in software and in scores, but let's go through it piece by piece. On the score side, it depends a lot on the environment in the country. So is there a credit bureau there? Is the credit bureau owned by the government, or is there some kind of competitive dynamic around the credit bureaus in the country? Did someone else get to the country with a score before we have? I mean, so that's kind of the competitive dynamic there. We're, you know, we're pretty big in Canada. Not as big in India. But we're, you know, we have a pretty good presence actually in scores in China, because we built the score there. On the software side, it, a little of it depends on AWS. You know, so we are pretty much partnered with AWS for the platform. AWS just kinda opened up in India, and so now we have customers there that we'd never had before. So there are some gating factors for our international expansion, but they're, you know, they're not significant, but there are some. ... Well, on that one, it also ties to your CapEx load, right? Yeah. So we are, you know, we don't love CapEx. We like high returns, low assets, and low CapEx. And so we've been in the process of closing down data centers and moving things to public cloud. There's not much of a difference even then between operating margin and EBITDA? That's correct. Right. That's right. Right. And some of it was regulatory driven, right? Yes, some of it is. That's right. Yeah. That's right. There's rules about that. Yeah. Okay, well, how about since so many of the customers are shared customers of the big banks, is there good market leverage or is there any advantage Scores and Platform together for those customers? Like, how do you think about that? A little bit. I think there's more connection on the product and analytics side than there is. I mean, obviously, the customers who buy Scores often buy Software, and vice versa. We see a lot of that together, especially in the U.S. But I would say that, you know, I'm often asked, "Do these businesses have to be together or not? Are they can they be separated?" And the answer is they can be separated, but there are advantages to having them together. We, we- Well, like, like, for example, the profit and cash flow from Scores helped fund and get Software- To the point we're at right now. I mean, Software is today, even fully loaded, it's a break-even business. Right. So, it doesn't demand it in the way that it did, but certainly, there was a subsidy from Scores to Software in years past. Mm-hmm. Well, okay, and then that provokes the question of the Software business, and it's obviously early days. What might it look like in terms of Rule of 70? Well, you know, if we, the Platform is. I like to break out the legacy business- Mm-hmm ... from the Platform business because the future really is the Platform business. So that's $200 million of business growing 40% a year, year-over-year. It's been growing over 50% the last four years, but it, you know, as it gets bigger, it'll slow. So call it 40s or even 30s. And if it's a break-even business fully loaded today, it's gonna get more profitable as we scale up. It's, it's designed to become more profitable as it scales. So, you know, a Rule of 40 is pretty easy to achieve in the new business, probably even higher. Right. So you can maintain Rule of 40 with a different mix? Yes. The business overall is more than Rule of 40- Yes Given the profitability of Scores. Absolutely. Yeah. That's right. Okay, got it. Well, we talked about AI not really being a thing for Scores. How about AI for Platform? Well, so we have, you know, we have patents in AI, and I think the challenge when you're dealing with financial services, when you're dealing with lending decisions, very heavily regulated and has to be explainable. And so we've put a ton of energy into explainable AI, ethical AI, responsible AI, being able to explain how the technology worked to arrive at the decision that it did. And I think there will be a time where that comes into, you know, into lending way down the road, not right now. There's places to use AI in our business today. We use it for synthetic data. I mean, there's places to use it. And then generative AI, which is all the rage, you know, we're very careful to keep it within kind of our closed system because we're careful about our IP and copyrights and all that. So, you know, it, it's a part of our business. I just think it's gonna be a while before you see AI used in underwriting. Mm-hmm. I mean, for example, Upstart had a no-action letter to do some stuff, and that's since been revoked. Mm-hmm. But on the Platform side, there's just more opportunity, right? There's a lot of opportunity, for sure. Yeah. Yeah. Okay. Why don't you talk a little bit more, anything else we should be covering on the regulatory front, either side of the business that's interesting? You know, we're very mindful of the regulations that affect our customers, and I think AI is probably the place where it's most sensitive. But no, I think we've covered it. Okay. How about the unmentioned part of the business so far, professional services? Well, so we have our professional services business has gotten smaller over the past few years by design, and our goal there is you know, we love being an IP company. With Scores, we have 90%+ margins, and the reason we do is it's all IP. It's essentially a licensing business. We'd love for our Software business to get more and more IP-driven and have less and less body business. And so we've been working over the years to reduce the need for PS. Now, we will always have some level of PS to do, you know, the high-end piece, the more interesting and difficult pieces of it, but we have a lot of partners who are willing, happy, thrilled to do the PS work, and so we're moving it in that direction. We're moving it to partners as fast as we can. Presumably, it's easier for them to stand up practices around what you do because of the SDKs, the simplicity you're introducing. Exactly. Exactly. Okay, good. Okay, why don't you hit the high points around capital structure, debt, cash, buyback? Oh, good, good questions. So, you know, sometimes people think of us as kind of a public LBO. We were 76 million shares at the high point, and 36 million shares when I joined the board, and 30 million shares when I became CEO. We're 25 million shares today. And so we, you know, we have done a tremendous amount of share buyback by design. The main reason for it is we haven't found any acquisition targets that we like as much as our own business. And so as long as we love our business more than everybody else's, we'll just keep buying back our own stock. And so that, that, that's the world we live in. We don't need a ton of capital to support this business. We don't need a lot of equity to support this business. We're comfortable with leverage in the 2.5-3 times range. It could go higher than that. We have very predictable cash flow and are happy to do it. But the, you know, the, the short answer to the question is, plan on more buyback. We're still a bargain at $1,300 a share, and plan on leverage kind of in this range to a little bit higher. And, if you have any, acquisition candidates that are more attractive than FICO, please bring them to us. We'd love to see them, but we haven't seen one yet. All right. Any other questions? If not, I will give you an opportunity to put a plug in for FICO World. For FICO World. FICO World. So we have an annual event called FICO World. It'll be in San Diego in April this year, and it's a different kind of a customer event. It's really, it's built for showcasing our product, but we don't showcase it, we have our customers do it. And so we invite everybody, and we figure out, you know, customer by customer, what it is they need to buy from us, and then we introduce them to other customers who've already bought that from us. And so they get together, and they sell each other, and we just, we facilitate. But that's FICO World, and it winds up generating well over half of our pipeline every year. Awesome. Thanks so much, Will. Thank you! Yeah. Great.