Equifax Inc. (EFX) Earnings Call Transcript & Summary

Okay. Great. Thank you all for taking some time out today. Next up, we're thrilled to have Equifax CEO, Mark Begor; and Dorian Hare from Investor Relations. We're thrilled to have Equifax here at our conference. I'd like to ideally keep this as interactive as possible. We're going to start off with one question to Mark, open it up, but then we'll keep it as interactive as possible over the course of the next 30 minutes or so. So thank you all again for coming. And thank you, Mark, for your time. We're thrilled to have you.

Thanks for having us.

So Mark, I wanted to start because there's been so much transition, and you've really transformed Equifax in a lot of different ways. It's been an amazing story that we think is really just essentially beginning in a lot of ways. But one of the things I wanted to start with was -- and I think it'll just help frame what you folks have done, even if we go back to 2007 and start with the TALX acquisition because I think that was really the foundation for what is collectively known as EWS today. And I think one of the more underappreciated parts of EWS is the uniqueness of the data. I think what -- there's been a lot of investor debate over the last 24, 36 months as to how quickly the data can be replicated. We've always been of the mindset, very, very unique data sets. I think you've been able to prove that out. But maybe we can start with the foundation of TALX. And listen, 2007 was a long time ago, but that was the foundation. You built on it. You've enhanced it. So maybe talk about that and then maybe the pivot point from when you folks really made the investment to refresh the tech stack and where you are today. And the reason I want to start there is I think that's really been the foundation that allowed you to really frame out the more recent set of growth targets you've had and things like that, but we could start there.

Yes. Sure. I wish I was the one who acquired TALX. I wasn't. Rick Smith, the prior CEO did, and it was a great acquisition. It's one that really widened Equifax beyond its traditional credit bureau routes and one that we've invested a ton in over the last decade plus that we've owned it and -- particularly in the last couple of 3 years. For those that don't know it, it's our income and employment data business, very unique to have that income and employment data that we get every pay period from literally 2 million companies now across the United States that we're hardwired to either directly or through third parties to collect the data. At the end of the third quarter or roughly in the last few weeks, we were about 125 million active records every pay period. And inside that 125 million, about 97 million unique SSNs. A lot of people have 2 jobs, in this case, in our data set, 28 million of them do. So a lot of people have 2 jobs. But the value of having that income and employment data, we're the only place you can go at scale to get that and get it instantaneously. And over the last number of years, the business has performed exceptionally well. Back in 2017, that business was around $700 million of revenue. Actually, it's a little north of that, $760 million of revenue. It will end this year at $2 billion, which is about a little under 30% CAGR. So a very fast-growing business. It's a business that's growing well above the rest of Equifax. It's on its way at $2 billion to be -- and we've said this in the Investor Day we had a couple of weeks ago, that we expect Workforce Solutions to approach 50% of Equifax from a revenue standpoint in the next number of years. And what's really attractive about the business is the uniqueness of its data set, the moat around it. So I'll talk a little bit about how we collect the data. But then its performance, because of the uniqueness of the data, its top line growth is growing well above the rest of Equifax. And its margins are over 1,000 basis points above Equifax average. They're in the mid-50s. So a very attractive business. We collect the data really in 2 ways through individual company relationships. The roots of TALX or now, as we call it, Workforce Solutions was in providing employer services or benefit solution services to HR managers. So we go to individual companies, and we do a lot of outsourcing work for them, of their regulatory services. So think about unemployment claims management, work opportunity, tax credit management, HCA management, W-2 management, all of those regulatory services we provide for HR managers, individual companies. And in return -- so that's a business of ours inside of Workforce Solutions, and it's one that we like a lot, but we get records in return. And in the records, we provide the income and employment verification service to the company for free. And of course, we charge the banks, the background screeners, whoever is using the data, we charge them for the data. And of course, we also don't charge the individual employee for it. That's something that is for free. So it's been a very strong growth business. We have, as I mentioned, 2 million companies. 60% of our records come from individual company relationships we've built up over the last decade through those services we provide. So very sticky relationships. We have companies that we've been providing these services to for 10 years, 15 years, 20 years, 25 years. The other 30-plus percent, we get through partnerships with payroll processors. So we'll go to a payroll processor, and they'll go to their clients, which are individual companies, and offer these services, and of course, we get the records in return. And for the payroll processors or some software companies, we'll provide a revenue share to them. And that's how we've been growing our records. And through the third quarter, we're up on records additions, 12%. And what's really unique is if you think about the 97 million unique individuals that we have in the payroll data set we have, there's about 160 million nonfarm payroll in the United States, individuals. So the road from 97 million to 160 million is all growth for us. And we're getting inquiries every day from financial institutions' background screeners for all employees, and we're able to fulfill now close to high 50s percent. So as we add new records, we're able to monetize them instantly because we're already getting the inquiries to our data set, a very valuable way to grow the business. So if you think about growth levers for the business, they have their traditional new products. They have price. They have penetration, new verticals. But very uniquely, they can grow records. And record growth is quite linear to revenue growth. There's -- when records are up 12%, that impacts our revenue in a very positive way because we're getting those inquiries. And then last -- one last point on Workforce is we've really widened the business. Historically, it was done in financial services. Mortgage is a big vertical for us. When you think about a mortgage, it's a big ticket transaction. The underwriter -- the mortgage underwriter, the bank, financial institution will verify the credit from our credit file and our competitors' credit files, but then they also verify that the individual is working and how much they make as a part of that underwriting. We're the only place you can go to get that instantly. So mortgage is a big vertical. We sell it in auto, another big ticket transaction. You want to verify the credit. You also want to verify that they're working and how much they make when you're doing a big ticket, even though it's secured. Personal loans, increasingly in credit cards now, we're starting to see some growth in there. And then outside of financial services, we've really been investing in our technology and our capabilities to leverage the data set. I talked about the 97 million uniques we have. We have 0.5 billion records. So we have all the historical information. So we have the job history on individuals in the United States. We have an average of 4.5 jobs on the average American in our data set. So it's very valuable in many financial services use cases. Like in mortgage, a lot of times, the mortgage originator wants to know where is Mark working today and how much does he make. But let's say I'm a sales commissioned employee, and my income is high in the first quarter and then goes down during the year until I get my next commission payment. That historical data is very valuable. And we have that in 12-month solutions, 24-month solutions that we sell at higher price points. We've expanded into the talent vertical because we have the job history. You know that 75 million or so Americans change jobs every year. And when they change jobs, they generally have a background screen done as a part of the hiring process. And that's about a $4,000 to $5,000 process. We have the job history. So we're selling the job history to background screeners to use in that hiring process. And we've made some acquisitions. We acquired a company called Appriss back in October that brings incarceration data, another valuable data element in the hiring process. And then the other area for us in Workforce Solutions is government. Social services are all needs-based, meaning income-based. So if you're going to get unemployment, food stamps, rent support, medical support from the government or at the state level, there's a verification done of are you working or not. And if you're working, how much is your income, so the right level of services can be delivered. That's a fast-growing TAM for us. It's about $2 billion. We've got a couple of hundred million dollar business inside of Workforce Solutions doing that. So the diversity of that business is much more than financial services. And then I'll answer the last half of your question around cloud. I think as you recall, when I joined in April of 2018, it was following the cyber event. And we had to rebuild our security. So we invested a bunch of money in security. We made what we believe is a bold decision to not only take our security to industry-leading capabilities but to go cloud-native. And not only a cloud-native on our technology, but to take our data to a single cloud lake or a single data fabric. Today -- or yesterday, our data was in siloed data assets. We have a lot of different data elements. And the value of data is in the multidata solutions. By being a single data fabric and being cloud-based, it's really changing the products we can bring to market, the multidata solutions we can bring to market, the data we can ingest, the speed of data delivery to our customers, the uptime of our systems. And then back to Workforce, it allows us to not only go to 2 million employers contributing to us. So massive amounts of data coming in. And using Workforce as the example, every pay period, we get close to 50 data elements on an individual's payroll. So we get gross, net deductions, job title. We get how long they've been in that job. Obviously, we get their income. All those different data elements are facilitated by the cloud, and it allows us to really drive that historical information because we're now storing it in that single data lake. So the cloud is a big, big effort for ours. We're close to completing it in North America, as you know. And we think that's going to be transformational on what we can do in new products, what it will do for us from a competitive standpoint. And we believe it will set us up for a competitive advantage around data and our technology for 5 to 10 years.

Great. It's been an amazing story. And I want to really shadow these 2 concepts because I think they're so critical going forward. And just to drive the point home a little bit more in EWS, the question we'll get, and I think you really frame it nicely is, is there a finite number of records? I don't think people appreciate -- and maybe help us frame this a little bit. People that maybe are on pension income, gig economy, talk to it from that perspective. And then the other thing, I think the SKU level data, right, appreciating and maybe the market not fully appreciating gross versus net income and the delta on that...

How valuable it is.

How valuable it is and why other -- whether it's web scraping that you just -- you're not going to get the same level of detail often time needed.

Yes. So first one is the data set. I talked about nonfarm payroll, which is what we typically talk about. Think about the 160 million traditional employed individuals in the United States. But as you point out, there's another 40 million to 50 million gig economy, meaning self-employed. So a different data set to collect. We're working to bring that into our database. And there's another 20 million to 30 million people that get defined benefit pension payments. That's their income in their retirement, another valuable data set. So we've got our sights on going from, call it, the 100 million, 97 million to 160 million of nonfarm payroll, the traditional employed individuals. We also want to bring in the gig economy. We also want to bring in the pensioner income because we just see a lot of runway there. And what is really unique -- most data businesses have all the data assets. And what's unique about this business is we're able to add those data assets. And if you think about it, there was a real catalyst 24 months ago when we got north of 50% of nonfarm payroll. Again, we've been in this, as you point out, for -- the business has been around for 20 years. We've owned it for over 10. But 2 years ago, we got north of 50%. And if you think about that, it was a catalyst, and the business really started growing more rapidly because the hit rates were higher. And for a company that's using the data, when you can get 20% or 30% hit rates, you're going to invest in it, but not as much when you can have 100%. But if you're at 60%, more people are investing in the time to put it in their workflows and their technology, which is really, really a big deal and one that's really driving the growth of the business.

And I think there's such a strong endorsement in terms of the partnerships with the payroll providers that they're willing to accept that partnership and basically revenue sharing, if you would, as they...

Yes. The way we think about our relationships is the 60% from individual companies, if you're an HR manager, you're not going to give that data to companies. It's really -- it's not exclusive. We think about it as exclusive. That's how it operates. In the reality, HR managers are risk averse. They want to make sure this data is protected from a privacy standpoint. And remember, we're delivering all kinds of services to that HR manager around getting those records. That's a good business for us, attractive margins. And then, of course, we turbocharge the margins by getting the records that we can then monetize in our income and employment verification business. And then on the payroll processor side, the vast majority of those are exclusive. That's the way we want to have them. It's the relationship that our partner wants to have with us. And if you think about it as a payroll processor, their core business is processing payroll. They want to make sure they do that really, really well. When they have our service, it's a free value-added service they bring to their clients. And if you're an HR manager and you're not having Equifax do your income and employment verification for you for free, you're doing it yourself. So you're taking calls from a mortgage originator, an auto broker, an auto loan company, whoever it might be. You're trying to verify them to make sure you're not giving out your employees' confidential information. We credential those companies. We make sure that data is protected. We do it securely, and it's a productivity play for the HR manager. They don't have to manage their small call center. And then for the payroll processor, they've got this new value-added service they're bringing to their client, and we give them a revenue share. So their margins go up. It is a part of the relationship. And that's why we've been able to have the vast majority of those be exclusive, which really protects the moat that we have around the business. Of course, the scale is a big one. It -- 97 million or 125 million in total active records or 500 million total records active and inactive. The closest competitor we have would have a few million records. So very, very different.

I would say, and I love what you said, Mark and -- you said your biggest competitor is paper.

What is paper paystubs. It's a great point because while this business has been around for 20-plus years, at scale, it's only been around for a few. And as you point out, our actual biggest competitor in the increment employee verification space is paper paystubs. It's -- over 30% of mortgage originators today still manually get that income and employment data by calling the company, by getting paper paystubs for the employees. There's a lot of fraud involved in that. There's a lot of labor involved in it. We keep chipping away at that and making that -- more of them taking it from Equifax, which is really a big opportunity. The other one is the business started by having a website that you would get credentialed if you were a mortgage originator, auto company or a background screener where you could log into it because we've said you're authorized to do that. Then you would put in a name, social data birth and address and then pull down the report, a lot of manual effort. That's how the business started. We still have over 1/3 of our revenue coming from that. System to system integrations are really a big deal for us because when we move a customer from manual, makes sense, there's -- you don't get every transaction that way and move them to system to system, we get a 25% lift in revenue. And we've been growing system to system quite positively. It's still -- over 1/3 of ours is manual. But over time, if you think about the credit file, the credit file, which has been around for 100 years and has full coverage, is 99% system to system in almost every application. We believe the work number is going to get in that same direction as we grow records and as we continue to penetrate into our customers.

It's interesting. Not to get too off on the side, but obviously, Encino just did a large acquisition in kind of disruption of the application process as well, which feels like you'll tie into that. Any -- does anyone have any questions? Because -- before I go into the next phase? Scotty?

So actually, maybe this is a little bit of a foolish question given how you've talked about the diversity of your business away from the kind of core business. But I'm just curious if you have any thoughts about the buy now, pay later offering and how much effort they put in the same that they don't hit the bureau. And what do you think the risk from that is?

Yes. We -- our partners with a lot of the BNPL players. We have a big identity business. We made a big acquisition earlier this year of Kount that brought e-commerce identity data in. And when you think about the fintechs and the BNPL players, they're verifying you are you from an identity standpoint before they offer that 4 payments on a pair of jeans. So that's a business for us and where we are partnering with them. My dialogues are different than maybe you described with the BNPL players, meaning they're increasingly looking to use our data, whether it's credit or alternative data assets we have, including income and employment, as a part of their underwriting decision. It's one thing to offer unsecured credit for $100 pair of blue jeans that's going to be paid over the next 4 months. They want to move into refrigerators, TVs, bigger ticket transactions. They know they have to underwrite that transaction. And the second is they want to do multiple transactions with that consumer, so they want to get to know them from a credit standpoint. So we have active dialogues going with all the BNPL players around data. They are also, along with the fintechs, very focused on using alternative data. We've talked about our income and employment data. We've talked about the credit file, but Equifax has really large-scale data assets that our competitors don't have, like we have a database that has cell phone utility payment records on it. So let's say you're a millennial that maybe has one credit card. You're going to have a cell phone. You're going to have payment records on it. Those payment records are very valuable in showing that Mark's going to pay his bills because he's paid his cell phone bill. Same thing with rental data that we have. If you're not a homeowner, you have a rental payment that you're making. We have another data set that's a wealth data. That's very, very valuable. That's being used by some of the BNPL players in order to position and retailers on which product to offer. So down to the ZIP+4, meaning neighborhood wealth, we have all the CUSIP information on ownership of assets inside of that individuals in that ZIP+4. So that's another valuable data asset that we have. And then the last one is around data that's not in the credit file. There's about 70 million Americans that either are not in the credit file, about half of them, or have just a header record in there, meaning they don't have any financial products. So they're unbanked. We have 70 million records that we bought through 2 acquisitions, Teletrack and DataX, that are from payday lenders, rent-to-own companies, meaning furniture rent-to-own companies, showing that you make those payments on time, check cashing companies, subprime auto lenders. So very valuable alternative data. All that alternative data is very interesting to the fintechs and the BNPL players to really underwrite those consumers that aren't as banked because generally, they're higher margin if you can find the right one with the additional data. And then, of course, we've talked a bunch already about the income and employment data, which is really valuable on -- credit data -- all the data I talked about is really around do you pay your bills on time, and it's a predictor that you're going to pay them on time in the future, right? So that's all that alternative data around credit. And then if you add to that, this individual is working and this is how much they make, the predictability of their credit decision goes up exponentially. And it's just really a very valuable data set to have that breadth of data. And our cloud investment that we've done, the incremental $1.5 billion that we invested over the last 3 years to be cloud native and single data fabric is going to allow us to bring new solutions to our customers that combine these data assets and deliver higher performance, and on performance, think higher originations, lower losses, higher identity, all of those, that's the performance that we're going to deliver through the multidata solutions that we'll be able to do in a much more -- a much faster and a much more efficient and productive way with our cloud investment.

Scotty and I didn't talk, but what -- we did say we wouldn't coordinate questions because that's where I wanted to go next because it's fascinating to me, you look at Equifax and stock's up about 50% year-to-date. You've outperformed TransUnion and the other bureaus, but what's most fascinating...

Of course, we had a period where we underperformed.

For sure, for sure. No. But the point being like if you look at FICOs down 25% and you wonder if that's the market may be starting to discount the alternative data sources, deemphasis maybe not the FICO score, but the point I'm making is I think you folks are uniquely positioned to help facilitate that disruption given the alternative credit and data sources you have. And I think one of the points...

Well, data is a big macro. If you think about big macros that we talked about at our Investor Day a couple of weeks ago, you heard that data is one, the explosion of data. Now what's the challenge with an explosion of data? It's how do you manage it right. It's really hard for our customers to manage the data, and that's the role we play of, number one, owning it. We want to own as much as that differentiated data as possible. And then second is managing it through the cloud capabilities. Digital is another big macro, meaning everything going online. And when you go online, you have to verify identity. So identity is a really big macro for us. It's one that we've been investing in. The Kount acquisition, as you know, we did earlier this year. And that's a huge TAM and a big market for us that we see going forward.

And I think the one other -- and I don't think we spent enough time maybe -- unless anyone else has any other questions. The technology transformation because I think for a while, people are focused on the cost savings, which is important, but stitching in the fabric across all the...

A lot to drive the top line...

Top line. And you saw that based on the numbers you put out. And again, if you think about the percentage of the revenue today, it's borderline been revolutionary. Like if you think about what mortgage was back in '07, 2010 versus where it is today and all the contribution to EWS today relative to that. And it -- to me, it feels like you're poised to accelerate even more as you see more buy now, pay later, more transactions online. Just you're going to help facilitate that as opposed to the obsolete, like your...

Well, that's why we made the cloud investment. We think it was a kind of a generation kind of bet that's going to give us a 5- to 10-year kind of lead versus our competitors. And it was reflected in our increase in long-term framework. We took ourselves from a traditional 7% to 10% growth up to 8 to 12. So 100 on the low end and 200 on the top end and a very significant increase in how we think about the long-term ability to grow Equifax. And then as you know, we also took up our margin expectations over the long-term framework from 25 basis points historically to 50 basis points of growth. And we put a marker out there on Investor Day for 2025 that will grow from 5 billion roughly this year to 7 billion. And we'll increase our margins over the 4-year period, 500 basis points. So part of that is the cloud, cost savings coming into '22, '23, but then also the top line and embedded in that 8 to 12 was an expectation that 200 to 300 basis points of that is coming from cloud, the cloud data fabric and our new product focus. And that's a big deal.

And mind you, that 100 to 400 is off a revenue run rate 4x what it was. So there's no base effect there.

Yes. And then the last piece is that when you have that top line and that margin growth, your free cash flow expands dramatically. And I think as you know, we laid that out in the investor framework, we're going to almost double cash flow between now and 2025, $800 million to about $1.4 billion of free cash flow, and then also delever the company short of some additional M&A to -- because of our EBITDA growing so rapidly, we're going to have close to $1.9 billion of free cash flow and leverage available to us that will allow us to continue to do bolt-on M&A. Inside of that framework, we said we want to do 100 to 200 basis points of revenue growth from M&A going forward in our long-term framework, and then also at the right time, start returning cash to shareholders again through dividend growth and buyback.

Mark, I know we spent the majority of the time EWS and USIS a little bit. It's pretty dramatic, though, the blended growth is 8 to 12. But if you look at the 4 segments, if you look at consumer, international, much lower growth than EWS, USIS. How should we think about the international opportunity and then that consumer business longer term?

Yes. If you think about the pieces of Equifax, and we already talked about Workforce, our expectation is the framework we laid out is going to grow well above the Equifax average with margins that are highly accretive and a business that's going to grow to be half of Equifax or more. So big opportunities in Workforce. We're widening it. USIS should grow inside of our range at the higher end. And so we feel good about that. And then international and GCS at the lower end of our range, and good businesses that we're investing in, that we want to be in. But when you think about that portfolio, a faster-growing Equifax going forward than it was in the past. And you know this, that in the last 24 months, we've, well out -- meaning in 2020 -- in 2021, we've way outgrown the framework. We grew 17%. Roughly this year is what our expectation is in '19. Last year is well above our long-term framework. So we're showing that we've got kind of the capabilities even in a COVID environment to grow quite strongly.

And that's where I think the secular drivers are so strong. Anyone else? I always like to ask, and it's -- as you think about -- and it's been an incredible transformation, right, in terms of the tech reset, maybe close out here on the new product innovation because I think that's another part of the story, just the scaling of the numbers. And appreciating the fact that no 2 products are the same. The revenue run rate associated with each one can very dramatically. But you've kind of gone from 40 a year to upwards to north of 100 to 140. And maybe talk about the Vitality Index a little bit because I think that's another huge part to the story that gets facilitated by the cloud transition, not only from an efficiency perspective, but also scaling.

Yes. No. Totally. So new products have been fuel for growth for Equifax for a long time and our industry. And as you know, the beauty of new products in our space is you already own the data. You've already monetized the data, call it, the first time. As you come up with a new solution and sell it again, your incremental margins on that new product are extremely high, I think 70-plus percent. So it's a very attractive way to grow. And we've had a focus at Equifax for a long time around new products, and it's one that we've expanded in the last 24 months. We've added more people, more resources around new products. And the cloud also allows us in the single data fabric to do more new products than we couldn't do in the past. Think about some of the historical trended data, which is very valuable. Like how has Mark's income changed over the last 24 months? How has it changed over the last 3 years using our income and employment data? How has his credit score going up or down? Has it been steady? Or has it been increasing? Or has it been declining? All that historical data is so powerful, and you can do it with new products. And as you point out, historically, kind of pre-2017, we were doing 70 to 80 new products a year. Last year, we did 134. We're going to head to north of 140 this year, 145, north of that. So we're ramping up the number of new products we're doing. And then we're also -- we use a term we call the Vitality Index. You've heard it in, I think, growth companies, technology companies. Our definition is revenue -- percent of revenue from new products introduced in the last 3 years. And our Vitality Index last year was 5% of our revenue in 2020 was from new products. This year, it'll be north of 8 going forward. So increasing. And we laid out in our long-term framework, our goal is to get 10. And if you think about a $5 billion company, you're talking about $500 million of your revenue every year coming from new products, and that's really facilitated by the cloud. Our cloud investment that we've done and the single data fabric is really driving that. And what's equally powerful is that we haven't finished the cloud yet. We talk a lot about the cloud. We still are in the throes of completing it in North America in the coming months. And while we're getting some early benefits from it, it's still early days. And in our Investor Day 3 weeks ago, I talked about in a couple of the sessions, we feel like we're just getting started. We're a 120-year-old company. We've remade ourselves. We call ourselves internally and externally the New Equifax, but it's a company that's got differentiated data like others don't have. And now we're the only cloud-native and single data fabric company like anyone else. And as we go into '22, '23, '24, really leveraging the cloud as we complete it is really going to be exciting for us going forward.

Yes. And you really enable the fintech disruption, which is just a phenomenal place to be. Awesome.

It looks like we've run out of time.

We can go all day.

Yes. Thanks a lot.

Thank you.

Appreciate you having us.

Yes.