John W. Gamble, Jr.: Just in terms of pacing, you covered it, right? It’s just it’s very difficult to forecast, right? So although we did see lift from redeterminations, it wasn’t to the level we expected, and we certainly saw that to a degree in the third quarter and the fourth quarter. But we still think we’re the best solution and expect to get the revenue related to redeterminations, as Mark said, by the time it completes at the end of the second quarter. But as we said, in the third quarter and certainly in the fourth quarter, a little lower growth than the level we’d expected.
Andrew Steinerman: Perfect, thank you.
Operator: Thank you. Next question is coming from Kelsey Zhu from Autonomous Research. Your line is now live.
Kelsey Zhu: Hey, good morning. Thanks for taking my questions. I think on the talent vertical, you talked about 20 percentage point outperformance if I heard that correctly. I was wondering, between the different factors that was driving that 20 percentage outperformance what is the biggest factor and how durable is this 20 percentage point outperformance over the next few quarters?
Mark Begor: Yes, the 20% we were pleased with the market — the business is up 6%, the talent vertical and from our measure, the BLS market was down 10%. We think the white collar market was down double that. So that’s how you get close to double that. So that’s how you get to the 20 points of outperformance. And there isn’t really — I wouldn’t characterize a single lever that’s really driving that outperformance. It’s really similar in all our businesses. In talent, we’ve got the ability to drive price, which we do every year. We expect to do that as we go into 2024 in the talent vertical like our others because of the value we’re delivering. In talent, quite uniquely, we have the ability to drive penetration. That’s a big multibillion dollar TAM in a business that’s roughly $400 million at run rate.
So there’s a lot of customers in talent that are still doing manual verifications of employment history that our 640 million jobs that we have in our database are just immensely valuable from a speed and productivity standpoint. So that’s a lever in talent that we think is quite durable along with price. Product is another big one. You’ve seen us roll out almost every quarter, a couple of new products from EWS and the talent vertical really to get more narrowly focused around products that match kind of job categories. We rolled out an hourly solution, I think, last quarter for hourly workers to try to drive some growth there. So new products are clearly a growth. And then the addition of records. And as you know, with the 50 attributes we get every pay period, we get job title and 75 million people a year or roughly that number change jobs in the United States.
So having those new jobs from our record additions every pay period is a very valuable asset that just drives higher hit rates, which drives revenue going forward. So we have a lot of confidence in our ability to outperform the underlying talent market, just like we do with the rest of our markets because of those levers.
Kelsey Zhu: Got it. That’s super helpful. Thanks so much. My second question is on mortgage. I was wondering if you can talk a little bit about the spread between kind of the increased trend versus origination and how you calculate the mortgage outperformance for EWS?
Mark Begor: Yes, I’ll start and let John jump in. We’ve been consistent really. There’s been a phenomena that’s a major change, a meaningful change in the mortgage market over the last, call it, 12 to 18 months, where when rates were starting to increase consumers did a lot more shopping and that benefited our USIS business. Meaning that the consumers would go to multiple mortgage originators and as you know, as a part of that process, when someone applies online, the first thing a mortgage originator will do is determine is that a consumer that can qualify for the loan they’re trying to get, meaning are they going to invest that 5,000 or 6,000 or actually 7,000 of COGS in that mortgage process. So there’s an inquiry that goes into or a pull on the USIS side.
And that’s why inquiries versus originations or closed loans have really separated. There’s been an increase in originations. And we expect that to continue with these high interest rates. Consumers, they’ll be more deliberate around their shopping behavior. And that’s why there’s a positive, if you will, for USIS in inquiries or credit polls in this environment where EWS typically in the back end of the mortgage process in — really around closed loans.
John W. Gamble, Jr.: Just broadly, right, we’re finding it difficult to get good market data that we can correlate across applications and other measures, including originations. So as you know, for USIS, right, we determine our outperformance based on our own internal volume data. And we share that internal volume data, obviously, with you every quarter. And then going forward, what we’re going to do is we’re going to provide outperformance for EWS also based on our internal volume data, which are actuals, which we can actually measure. And as we’ve been talking to you about for quite some time, right, our outperformance is driven by record growth, which is more specific to TWN, but then also product price and mix. And as we said in the script, those are things we can measure together, understanding the difference between our volume and our overall revenue.
And that’s our outperformance. And I think going forward, we’ll use that measure because it’s all based on internal data that we can validate each quarter. And again, what we — our internal volume data is transaction volume data, it’s the transactions that are related directly to mortgage application approvals, doesn’t really include things around batches or monitoring so that the data stays pure. And we feel like that’s a much better measure of the level of outperformance driven by record growth, product, pricing and mix that we can deliver each quarter, and we’ll continue to share that with you.
Mark Begor: Maybe just one more point, John, as a reminder, as you know, we get mortgage originations because we have the credit file on every consumer. So we see the actual new mortgage originations, but they’re typically on a what five to six-month lag. So between that five to six-month lag, we’re forecasting based on MBA data, based on our own tracking, based on our own run rates, we use multiple inputs to try to forecast those originations. We obviously have been challenged by that in this current environment with interest rates increasing. But we have a lot of data around mortgage originations.
Kelsey Zhu: Got it, thanks so much.
Operator: Thank you. Your next question is coming from Andrew Jeffrey from Truist Securities. Your line is now live.
Andrew Jeffrey: Hi, good morning. Appreciate you taking my questions this morning. Mark, I mean, I get there a lot of moving pieces here outside of mortgage, especially I’m thinking about EWS verifier government, a little bit weaker maybe than you thought and you enumerated the reasons. I guess my question overall is do you think that, that EWS non-verifier — sorry, non-mortgage verifier business has perhaps gotten a little more difficult to forecast as you do more business with the government and all these different programs, appreciating the new contract wins and do you think you’re going to take that into account when you start to think about guiding for 2024?
