Fair Isaac Corporation (FICO) Earnings Call Transcript & Summary

Okay. Good morning, everybody. Thank you for being here. My name is Manav Patnaik. For those of you who don't know me, I'm Barclays' business and information services analyst. But we're very pleased to have with us today Will Lansing, who's the CEO of Fair Isaac Corp. More commonly, we just refer to them as FICO. So Will, thank you for being here.

It's great to be here.

So Will, there are some new faces to the name, so perhaps we can just start with a broad overview of what are the different businesses that FICO is involved in and kind of the mix of each of those businesses.

So we're about $1.4 billion in revenue and split almost evenly between a software business and a scores business. And maybe the best place to start is a little bit of history, how we got to where we are. Because we really have these 2 businesses, but they have kind of a common heritage. So the business was founded in the mid-1950s by a mathematician and an engineer. And their thesis was that, by applying analytics to problems, they could make superior decisions and help their clients make money. And so it was really an analytics consulting firm. It was a body shop, and we did a lot of custom analytics for whoever was interested. And it was actually a wide range of industries, but we quickly settled into financial services because that's where the money is. That's where you have high-stakes decisions. And it made sense to apply analytics and expend energy in doing analytics to get to a better answer. Well, so that went on through the '50s and '60s and '70s. And the people running FICO at that time got this idea that, if they could get some of the analytics into software, we could get returns to scale. We could get higher margins, and we wouldn't just be a body shop. And I think that was really the genesis of the software business, moving from consulting and professional services to a software business. And so we built some applications for banks that were pretty effective. And then we also bought some companies. And so the software business developed through the '70s, '80s and '90s. And we wound up with some very strong franchises with financial services, including Falcon, which is a transaction fraud detection and originations, collections and recovery and customer communication, customer management. So these were big franchises for us. At the same time, we were building these scorecards for banks, helping them to make their lending decisions. And so these banks would approach us. We build them a proprietary scorecard. And in the '80s, the mid-'80s, we had this idea that, if we could build an industry scorecard, it could be used much more widely. And so we partnered with Equifax and developed something called the Beacon Score, which was the very first FICO Score. And what that was all about was, if we can put the algorithm on top of the credit file and score a large population, we have this low-cost way of evaluating risk in a large population and lots of lenders could use it. And so they did. That worked out pretty well. Well, then we got this idea that we could put the same kind of a score on top of not just the Equifax credit file but all the other bureau credit files. And so we went and we did that for Experian. We did that for TransUnion. And lenders really liked this. I mean the value proposition started out by being pretty effective as a low-cost way of evaluating risk. And it also gave them a little bit of flexibility in terms of where they were and how they managed their credit. So that's kind of how this thing developed.

Got it. And so just on the FICO Score itself, I mean, I think some people don't appreciate the benchmark industry standard nature of it, the regulatory aspect of it. Can you just elaborate that -- on that a bit more?

Yes. It's kind of a case study in how do you become an industry standard, and it happened for us over 30 years. So I mentioned we started out by having a good value proposition for the lenders. Here's a very efficient way to evaluate credit risk, but what happened was the regulators saw this and they said, "This is a pretty good tool for us." And so when we -- when they regulate the banks and they want to understand what's the risk of this portfolio, what's the profile of that portfolio, how will they behave in a downturn, it turns out that a very useful metric for them for evaluating that risk is the FICO Score. And so now you have this constituency of lenders using it because it's a good value proposition. Now you have a new constituency, the regulators, who are relying on it. And then the investors get into the act. So a lot of the lenders securitize their paper, and the investors say, "How do I evaluate the risk of what I'm buying?" And again, the FICO Score becomes a very effective tool for doing that. And so now we've introduced a third constituency that's interested, and now you're starting to see the network effects of using the score. And then finally, about -- some 5, 6, 7 years ago, we introduced something called Open Access, where we provide the score to the consumer. So we told lenders that they should feel free to share the FICO Score -- this was in the U.S., predominantly, feel free to share the FICO Score with consumers. And they do. And if you're a U.S. consumer, you will typically get your FICO Score from the bank in your statement every month. And so there's a fourth constituency relying on it, the consumer. And now we have consumer pull through the score. And so we've become very, very embedded in the ecosystem. And then we don't charge a lot, I mean, it's a good value. And so the combination of all those things kind of puts us right in the center of the ecosystem.

Got it. So it's interesting because you're still saying you don't charge a lot. Five years ago, you used to charge a lot less. And before that, you didn't -- I guess FICO never changed their pricing before. So again, just for a little bit of history, why did it not change for 40, 50 years, and suddenly, in 2018 things began?

Well, I -- we believe that there's a very big gap between -- there's a big value gap. We don't charge anything like the value we provide. The reason that pricing was so low for many years was that we don't sell directly to the lenders. We sell through channel partners, the credit bureaus. And for over 25 years, the prices were fixed in contracts with evergreen renewal provisions and so we just never changed the price. That was under prior management. And then we decided back in 2013 that we should have price changes. It's -- there was something off about freezing your pricing for 25 years and so we started to raise prices.

Got it. And I want to get back to the pricing and stuff first. But just to stay on a more broader picture, the hot topic nowadays is around generative AI and the potential opportunities, but also, from the investor perspective, who's at risk. So first, let's just touch on the Scores business. I guess you guys have talked many times how the FICO Score has been AI or machine learning for a long time, but where do you see the risks and opportunities?

We -- there's really 2 places where AI touches FICO. One is the large language models that we're seeing today, obviously, have all kinds of implications for cost reduction and for productivity improvement. And in that respect, we're like every other company. So call centers and those kinds of things will be affected that way. Sales force management will be affected in all the ways that you read about. I think the more interesting use of AI is when you get into the core of our business, which is risk. When you get into originations, when you get into underwriting decisions, how does AI play there? And remember, we're in a highly regulated industry, highly regulated environment. We have -- in the U.S. and in Europe, we have all kinds of laws that protect the consumer and policy decisions, and AI violates a lot of that, right? You can -- you could have redlining kind of embodied inside of AI and not be -- not have it very visible. And so that's not a good thing. We, at FICO, spent a tremendous amount of time thinking about this problem, anticipating this problem. And so we've got a number of patents in the area of explainable AI, and so we can explain how the AI works and make sure that it conforms with policy directives and with regulation.

Got it. So maybe just on this XAI, this explainable AI component, because that's important in the regulatory framework, but just talk a little bit about the patents and maybe a little bit more on what explainable AI really means.

I wish I had my Chief Analytics Officer here to really answer that question, but I'll give you a kind of a lay answer, which is we -- essentially, what we have is a [ breakdown trail ] that lets us understand how it is that the AI got to the decision that it got to. That's the explainable part.

Got it. Yes, makes sense. And then just before moving to this topic, for other companies, I guess, the investor questions are how much of your data is proprietary or not? You guys do not own any data, and I think that's been deliberate. So can you just explain why you believe in that strategy?

Yes. We have a little bit of data in our myFICO business. But we are, in general, the math, the IP, the algorithms, the analytics, but not the data. And we do that because we're not a credit bureau. We're not a credit repair organization. We don't want the liability of holding that data. But strategically, it's because we know where our scale is. We focus on what we're good at, which is the analytics piece. And we've never really been in the business of trying to build a competitive edge by having proprietary data sets. It's perfect business, it's just not our business. And we partner with the bureaus on that and with others.

Got it. Okay, fair enough. On the software side, again, ever since Gen AI has come out, a lot of software companies have been under pressure. So what is it about your software portfolio that you feel like is more an opportunity than a risk?

Well, so maybe it's worth taking a step back and talking a little bit about our software portfolio, and then we can talk about that. Because we are fortunate that we're under a lot less pressure than some other software companies today, and I think it's because our software is really strategic. We're really meeting the market need. It's very strategic for our customers. But for the benefit of people who aren't close to what we do, I said that our software -- the software business we built up was designed around the credit risk life cycle, and it was very specific point solutions, applications that banks, lending institutions would use to make these risk decisions. About, oh gosh, 10 years ago, we came to a view that we should broaden it. We should really think about ways to make all this work together. And we -- and it was a journey. So the first thing we did was we identified kind of an R&D opportunity. We had a different decision engine in each one of our software applications. We said there's a lot of commonality here, and we could definitely have some returns to scale if we could just put the same decision engine into the next generation of each one of these applications. And so that was a big push in 2012, 2013, 2014. We got this kind of common decisioning. And then we noticed that all of these analytics engines required ingestion of data in similar ways, and yet we did it differently in every one of our applications. So could you standardize the data ingestion, the wrangling, the cleansing, the manipulation of the data to feed into our analytic engine? And so that was kind of the next step. It was around 2014 when we started talking about the FICO stack and -- if you remember the terminology from those days. And then we also noticed other similarities across the applications and came to a view that really, what we were doing is building a platform, that really, we were now combining all of these applications in a way that was really a platform business. And so we became much more deliberate about getting all the components of our platform so that it would really support the needs of our customers. If you kind of peel back what it is that we do, what we -- people think of us as decisioning. They think of us as superior analytics. But what it really is, when you think about it is, it's really kind of next-generation CRM. What we do is we use data and apply analytics and make decisions about how to optimize an interaction with a consumer or customer. So for our bank customers, for our lending customers -- and it could be any B2C company, but we tend to focus on financial services. For them, it's all about how do we optimize that interaction with the consumer. And the difference between the way we do it and the way it's historically done is, most of the time, interactions with consumers are based on segmentation. And we say here's consumers, here are some soccer moms, let's treat them a certain way. Here's a different segment, let's treat them a different way. But you're treated as a member of a set, and you have some rules around how we're going to treat those people. The FICO approach is personalized. It's customized. It's one to one. It's leverage all of the data we have about a particular individual, the last 25 transactions we've seen. We understand their price elasticity. We understand their brand proclivities. We understand what makes them tick, and we know what they'll respond to. And so we build a relationship, a digital relationship with the consumer based on everything that we know about them and then applying the analytics. So if you're a bank and you're wrestling with, "How am I going to change my business from waiting for people to walk into a branch," and kind of the old-fashioned way of doing business, to a future business which is, "I need a digital relationship with the consumer. Everything has to be relevant. I can't do something in the call center or an e-mail or by text that conflicts in some way with something else I just did with this consumer." Let's not trip on ourselves. These are not separate activities. It's all got to be integrated. You want a 360-degree view of the customer, and you want it to be digital. And you want every single one of those touch points to be optimized. The best way to do that is with our software. That's what our software does, and it's great for banks and financial institutions. It's also great for other verticals, we just tend not to focus on those right now.

Got it. And so let's stick with software. And the platform business grew, 60%, 6-0 percent last quarter. And the nonplatform also grew, I think, 7%, if I remember that correctly. So it's not like you're moving from nonplatform to platform driving the growth. So what is driving that 60% platform growth?

Well, the big growth is coming from a few things. It's -- the first is, this really is strategic for banks. So your bigger banks are looking at fintechs who are developing these digital relationships with their customers, and they feel like they need a really strong digital relationship, too. They don't want to be left behind. And frankly, they are leading the way on this. So there's a strategic need to do this, but then there's also costs. I mean the return on investment is really terrific. It can be as little as inside a year for a return on investment with our software for our bank customers. The cost of entry is quite low, so they don't have to convert everything in their entire bank. They can try it in one business or in one portfolio. They can try a few use cases and see how they like it and then expand from there. So low cost of entry. And those are really the -- it's rapid payback, high ROI, low cost of entry and strategic imperative. And we add them all up, and we got a booming business.

And how about competition? Like is that -- I mean in -- with FICO, the -- with the score, I should say, there is no competition, but how about on the software side?

I think that competition on the software side is really from internal, so it's build your own. There's really no other company out there that does quite what we do, the end-to-end next-gen CRM. But it's so much more cost-effective for a customer to use FICO than to try to build it themselves, that, as they explore the options with us, they decide to use us.

Got it. So 60% growth, easy to integrate, to use, no competition, but break-even margin. So when do we see the margin as well?

Well, that's the debate internally is -- and this is debate in every software company, is margins versus growth. And clearly, there's a swing, a pendulum swing in the direction of margins right now from a fashion standpoint. But I would say that, because we have this commanding lead in the space, we're well ahead of our -- of any competitors, and we love the growth rate. We're going to continue to focus on the rapid growth for the next few years. I think margins will come naturally with scale. R&D is essentially a fixed expense. And so as we get bigger, our margins will improve. And then I think we'll be more deliberate about margin in the future. But the primary goal right now and the next several years is growth.

Got it. And what are the main areas of spend in the software side? I don't think R&D has changed a whole lot. So where is a lot of that money going?

Well, R&D is a big piece. I mean, we're building features and functionality, and that's the biggest piece. And we're actually investing heavily in the platform, in enhancing it and making it stronger and more powerful, more capable. But there's also spend in direct sales and distribution. There's spend in partnership and indirect distribution. We have a little bit of spend in retiring technical debt, some of our legacy systems. So there's spend across the board. And then there's obviously professional services and installation, although we try to give that to partners as much as possible.

Got it. You explained the history of how the 2 businesses came about. There doesn't seem to be a lot of connection or business need for the 2 to be together. So how should we think about how you think about that portfolio in the next 5 years?

I get asked that a lot. And we do run them as 2 businesses, and we kind of report the numbers separately. But there are synergies, for sure. There's opportunities in analytics where we work together. And then the customers for scores and for software are the same customers, not always the same person inside a bank, but it's the same customers. Our sales force is a common sales force, global sales force that supports both businesses. So there are some points of integration.

Got it. And then maybe one last point on software. Most companies we've talked to are talking about sales cycles lengthening. But on the last call, you told us your sales cycles are shortening. So why is that? Like what's the difference there?

Yes, that's a -- that's quite fortunate for us. I think it's what I said before. I think it's because it's a strategic thing. It's not being postponed. So obviously, these are tough times and people are tightening their belts and tech companies are laying people off. But there is tremendous demand for what we do. Now some of it is because the return on investment is very rapid, so it's easy to justify. But I think the bigger driving factor is the strategic nature. I think it's just -- it's something that banks feel like they have to do, and they have to do it now. They can't postpone it.

Got it. Okay. Let's go back to scores. And first question is more from a macro picture. You had a mini banking, whatever you want to call it, crisis, failure, session. You've had -- lending standards are tightening. What are you seeing in terms of some of the lending environment dynamics out there?

We haven't seen a lot of change, frankly. We -- I mean we -- you can get into -- drill down into categories. And obviously, refi is almost dead and -- but -- and other, mortgage volumes are lower, much lower, than last year. But I -- we think they've kind of stabilized at the level they're at, and eventually, they'll go back up. But I don't think that the banking crisis such as this really affected things very much.

Got it. Card is typically your biggest volume, so do you see any big risks? I mean, it's obviously growing really nicely. But in a potential, whether it's a mild recession or worse, like, how do you think about how that portfolio moves?

Look. I think we have to be realistic. If we have a recession, I think that you'll see card volumes come down. They always have. But so far, we're okay.