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Market Pulse is a monthly podcast by Equifax, in partnership with Moody’s Analytics. Equifax hosts bring you interviews with industry experts on the latest economic and credit insights that can help drive better business decisions. Whether you’re in financial, mortgage, auto or another service industry, we help make sense of the latest economic conditions that impact you. This podcast series supplements our Market Pulse webinars, which occur on the first Thursday of each month.
Market Pulse Podcast
Ep. 59 Transcript
Emmaline Aliff (00:00):
Welcome to the Market Pulse Podcast. I'm your host, Emmaline Aliff, leader of the Equifax Advisors. As a group, we identify economic considerations and leverage data and analytics to translate into industry insights and recommendations. Our goal is to support our clients during economic uncertainty, while uncovering growth opportunities in consumer and commercial markets throughout the customer lifecycle. Before we jump into our conversation today, let's do a quick economic overview with our friends at Moody's Analytics. Thank you Moody's. And with us we have Justin Begley.
Justin Begley (00:33):
The US government shutdown has entered its sixth day, and there seems to be no light at the end of the tunnel at this point. The standoff on Capitol Hill has resulted in the closure of several statistics agencies resulting in the, the delay of key economic data. The closely watched September jobs report was due on Friday, but data has yet to be released because many workers at the Bureau of Labor Statistics were furloughed. This comes at an unfortunate time as the Federal Reserve is in the middle of a monetary policy transition and is relying on timely data to inform its next policy decision risk of a monetary policy misstep. Were already running pretty high prior to the shutdown as the Fed juggles threats to its dual mandate from higher tariffs and flying blind only heightens that risk. There are a few private sector alternatives that help inform the state of the labor market, but these are really best looked at as a supplement to, rather than a replacement of the official jobs report.
Justin Begley (01:30):
Private estimates of payrolls for September suggest that hiring was tepid like we expected it to be as employers remain firmly planted in their no hire, no fire mindset. ISM purchasing manager surveys for September agree, and the ISM manufacturing index remained in contraction territory in September, suggesting continued weakness in the factory sector. The employment index improved slightly, but contracted for the eighth consecutive month in the services sector. The ISM survey implies that the industry neither grew nor contracted in September, and the Services Employment Index has contracted for four straight months, adding further evidence to the rapid cool down in the labor market. Many among the unemployed and underemployed are seeing job postings being pulled down and are waiting weeks or, and or even months to hear back from potential employers. As a result, consumer's perceptions of the labor market are deteriorating the conference board's labor market differential, which is the difference between the share of consumers reporting that jobs are plentiful versus hard to get fell in September to its lowest since February, 2021 when the economy was in its early stages of recovery from the pandemic recession. Confidence, therefore is relatively weak and is at its lowest since April.
Emmaline Aliff (02:51):
Thank you, Justin. So today what we wanted to you know, talk about with everyone is, you know, the idea of how how much information is out there. And whenever we go into our conversations with you know, our, our, you know, customers we oftentimes are asked like, what are the most important things to look at, what's relevant? And, and these things can change over time. And so what I wanted to do was to, you know, bring in the advisors to to have that conversation with everyone. So today I have joining me, Jesse Hardin, Tom O'Neill, and Maria Urtubey. One of our team members had and a personal emergency is unable to join us, but Dave is with us in our thoughts. So welcome team to the latest installation of of Market Pulse podcast. Hi,
Jesse Hardin (03:46):
Emily. Hey, Emily. Hi. Good to see you again. Good to see. I think I did this one solo last time, so it's good to have you as on again,
Emmaline Aliff (03:53):
We're there for you, Joseph. Agreed. And that was you know, that one was quite that was quite enjoyable. I think it was very timely with respect to you know, the discussion you had with Stephanie around you know, things that are happening from a, a, a government relations standpoint. So appreciate that. So maybe we'll just, you know, kick it right off in, into you know, what are the things that you look at. You know, let's start with you. Yeah, you know, if you think, if you're thinking about recommending at an economic level any metrics to be able to to track monitor, maybe mention some of the ones that you think are most interesting and relevant and why.
Jesse Hardin (04:30):
Sure. I love economic metrics. I think that probably sounds weird to say. It sounds weird to hear, but , I think it seems like economic metrics really have a, a place now in, in judging where the, just where the overall economy is. I, I tend to find that some of the metrics that we see, we, we see a lot of higher level metrics. The how many jobs grew where are prices going. We see a lot of those high level metrics. And I think where I like to go is maybe taking a step, a step down. So I wanna see some of that data that, that underlies that, that overall headline number. Couple of the, the data points that I'm, I'm looking at, I'm looking right now. When, when we think of the labor market, I'm thinking of jobs grown certainly looking month to month at the number of jobs grown, but we're looking at revisions.
Jesse Hardin (05:24):
So the number of of jobs that get revised either upwards or downwards, that can be a, a good indication of what's the overall health in the job market. I also look at a three month moving average of jobs. So not really just looking from point to point, but looking at that three month average, we typically want to see maybe about 150,000 jobs grown a year. So that's a good barometer to, to figure out really where, for example, the health of the job market is a lot of focus on prices as well. Looking at CPI the consumer price index, the overall price index kind of gives you a good indication of, of where things, where prices are. However, I'm also looking, again, that le that next level of, of of layer deep. I'm looking at things like consumer core core prices.
Jesse Hardin (06:15):
So core goods, prices, where is that number going? That's a good indication of where consumers, when they go to the grocery store and they have to make, you know, their, their grocery store you know, a dollar last, that's, that's really showing like, where, where is the pain? You know, where's that pain growing? And so I think getting that, that layer deeper, looking at some of those metrics, especially as it relates to the labor market, there's been a lot of discussion about that now. So so go in that layer deeper really to see where that you know, where that that measure or where those measures tell us the, the market's going.
Emmaline Aliff (06:52):
That's great. So it sounds like you're, you're hitting on a number of the key components around spend labor markets you know, you know, additional things. You know, it could be imports, exports you know, what, what's, you know, what's been occurring in the overall market in, you know, I guess if we're, you know, kind of pivoting you know, Tom and Maria, what, what would you potentially add to some of the things that Jeff, Jesse was describing?
Maria Urtubey (07:18):
I'm going to step in, and Jesse, you mentioned you love economic metrics. I love math and statistics, likewise. And I always look at this from the perspective of the food groups, right? Like, how can I pick a favor when there's a series of, of component, like if we were to focus, for example, on a credit score we know that it's not just paying or not as agreed which is extremely important within the score, but of course, how utilized or how much are you overextending the use of your credit? Are you seeking for more credit? How long have you had experience? And of course, what type of experience? And similarly when I was debating about the macro and how this drills down into the specific questions we get from our customers, I'm looking at things such as hard metrics such as DDP, which give us the global perspective, but also the low local insight of the health of the economy.
Maria Urtubey (08:14):
And of course, given two thirds of the GDP comes from consumer spending we've been hearing it's been resonating, and I know Dave commented this in, in previous discussions, how the low and the middle incomes have been, of course, pulling back. And we see that with a pessimistic view from the soft data in the consumer sentiment surveys, right? That spending is coming mostly from the high end of the income bracket, that case shape of the economy, the one that is doing better compared to the lower end. And not just that, when we look at wealth trends, for example, we at the globe, at the overall US level, we're seeing that the six 73% of the wealth and coming mostly from investment, not deposit component, but investment is held by 10% of the households in the us. And if we were to now narrow it down to an age bracket, if we look at the Gen Zers that have access to credits such as those between 18 and 28, that's even more I would say surprising. It's 5% hold 63 of that young population wealth. So again, having that information readily available, being able to have very verify insight, right, to drive those decision is critical. And these are some of the questions and comments and highlights that we are hearing from our customers directly.
Tom O'Neill (09:40):
Yeah, Maria, I, I was, I started to get nervous when you, when you were talking about the components of credit scores as food groups, and I was, I was worried you were gonna start giving some food examples, and I was gonna start, you know, working up an appetite anytime we start pivoting to credit scores. So thank you for not going too deep down that, that path , you know, I can now talk credit performance without without having food in mind. But I, I love this topic because it's, it actually, it's very, very relevant right now, not only in terms of the environment that we find ourselves in, but what we at Equifax are actually doing right now. And some of the exciting stuff that we're, we're putting out, because the examples that Jesse and Maria both put out are, are terrific examples.
Tom O'Neill (10:30):
There are historically, you know, several of the go-to metrics that, that we go, that we use and, and their go-to for a reason. You know, Jesse's mentioning, you know, the, you know, CPI and prices along with the, the labor market and jobs and incomes Maria's talking about credit performance and GDP and consumer spending, and all of these are fantastic metrics that give us insights into what's happening with, with consumers. But yeah, here's where I'll pivot from what they were, what, what they were talking about in that each one of those is an individual dimension of those consumer finances. You know, jobs, obviously that's, that's your income. That's, that's critically important, but it's a facet of your, your financial picture, so to speak. Your spending obviously very important, but it's a single facet of, of your of your overall financial life, your wealth, your assets, your financial durability, your credit history.
Tom O'Neill (11:40):
All all of these things are different components of what makes up the bigger picture. And that's where I'm going with this, is that when, when you ask, you know, what is our go-to metric, I'm gonna throw out one that is, you know, just, just coming out hot off the press and what we're calling the market pulse index, which is something that Equifax has developed that brings in all of these components. Again, Maria, going to your food groups. Yeah. We know that credit is comprised of, of different components, different ingredients, so to speak. Same thing with the market pulse index, but instead of saying, you know, we're defining a consumer by their credit score or by their income level or by their assets total, it's a combination of all of those things, you know, plus other dimensions and, and bringing this in together to a holistic view of that, of, of that population.
Tom O'Neill (12:35):
And what that provides for us, what that enables us to do is, is really see how different populations are impacted by economic conditions that we otherwise wouldn't necessarily be able to, to see. We've seen, for instance, with credit scores that if we look at aggregate and we say, what's the average credit score, whether it's, you know, one credit score or the other, we see that over, over time, that average changes little if at all. But what's happening underneath is extreme. We see that, you know, a lot of people are going up, you know, some populations, you know, Maria, again, Maria mentioned the K curve. Some populations are doing great. They're seeing their wealth takeoff, they're, they're paying down debts. They're, they're ma you know, they're improving their credit performance, their credit scores are going up, and obviously others on the other side of the K are struggling. Those are going down. The average is staying the same, but what's happening underneath paints a very different picture. That's where I'm excited about, you know, this more holistic view, being able to gain insights that's looking at a single dimension, you know, might not be able to do by itself.
Emmaline Aliff (13:48):
Yeah. Tell me when, when, oh, go ahead, Jesse.
Jesse Hardin (13:51):
Yeah, I was I was just gonna comment real quick, Tom, I, I think that's where I'm most excited as well about market pulse index. When you think about, we even sought out the first of the year when we started talking about the, the hard economic data, and then the soft economic data. The idea of, you see hard data is telling us one thing, and then soft economic data, which is like your, your consumer sentiment. It's almost like consumers were saying one thing, and then the data, the hard data, like the CPIs and the spend and the GDP, that's all saying another. And it's almost like you need that metric that can take both of those and tell you, this is the pulse. Like this is what's really happening. When you, when you take all of the different facets of either a consumer or a business and kind of put 'em together to say, this is the direction that, you know, largely we're seeing you know, in the, in the economy, it just, it seems like that's a, a fitting a fitting metric for for what we're trying to look for.
Tom O'Neill (14:45):
Exactly. Yeah.
Maria Urtubey (14:47):
Like catching up of the hard data to the consumer sentiment aspect of soft data.
Tom O'Neill (14:52):
Right? Yeah. And I, I remember that even being a direct question that we were at, like, the question was always, you know, when economists are looking at these aggregates, you know totals, C-P-I-G-D-P stuff, that's, that's happening at a very high level. And we see consumer sentiments, you know, going in an opposite direction. Is it because the aggregates somehow don't match up with what's hap, you know, what's truly happening at the, the consumer level, or is there a lag? And I, I think that having this sort of this index, the market pulse index saying, here's what's going on with different populations, gives us the answer to that, we could say yes in some cases, even if the, the total numbers are looking good, there are populations that are really struggling and, and others that are doing well. And also we can, we can also make the, in environments of even some of the populations that are doing well at a particular point in time, they see where things are going, and, and so yeah, it very much is a lagging yeah. Indicator. So a lot of insights that we would have to either infer or miss altogether. Yeah. Otherwise,
Emmaline Aliff (16:08):
So with all the things that we've talked about with the different metrics that we've been incorporating does the market pulse index include some of that, or what, like what are, what are some of the key things for why it is potentially relevant specifically right now?
Tom O'Neill (16:26):
Yeah, so I'm, I'm, yeah. After having just made a big deal about Maria's food group's analogy, , I'm gonna, I'm gonna keep playing with that one because I think it's so good. There are, there are components that we, you know, we can sort of visualize, you know, making up the market pulse index, things like credit, things like, you know, affluence, things like income, things like debt levels and, and capacity. And those, those are truly inputs, you know into the market pulse index. But even within those categories, you know, we know that there's a lot of interaction between those. And so the, the approach that we took to develop this accounted for the fact that these aren't, these aren't stove piped dimensions, these aren't things that happen in a vacuum, and we just sort of add one plus two plus three to come up with an answer.
Tom O'Neill (17:23):
We know that as one changes, it has an impact on the others and so forth. And so we, we took an approach that's account that captures that, that interaction. And then on top of that, we also knew that there's a real life context to, to what we're trying to measure. I'll take one of those components assets, for example we could look at two different populations that have on average $50,000 in assets. That has very different, meaning that 50,000 in assets has very different meaning if you are a young population coming right out of school and starting into their careers and their financial lives as opposed to $50,000 in assets for a older population that's a couple years from retirement, that that has very different context, very different meaning. And so we wanted to capture that as we were pulling this together. So, so, yes, a a lot of these ingredients, so to speak, these different food groups coming together to create, you know, one dish.
Emmaline Aliff (18:30):
Yeah. So my understanding, you know, with all of those things, you, you, you talked about, you know, consumer debt, you know, I guess when we think about credit trends in general debt is important, delinquency utilization credit score as a whole, and then you just brought in a different picture there with respect to you know, some form of wealth and asset type of you know, you know, basis as well. So when, when we think about that, like, is this meant to to create more understanding at an individual level or more of an aggregate level? 'cause We're talking about economic metrics now.
Tom O'Neill (19:04):
Yeah, no, this, this is definitely the latter. This is definitely meant to, to provide, to provide insights at an aggregate level. This, this really, it, it's developed to be used at an aggregate level, and even just from a practical standpoint, it's meant to be applied that way because that's where you start to get the real meaning. We all know that each individual circumstance is different. That even if we have a full picture from a data standpoint on an individual, we're gonna miss some of the, the nuances of, of that individual's circumstance. But when we pull that up to a fuller population and we start looking at this, you know, the different dimensions across fuller populations, we're not missing out on that. We're not, you know, we're, we're basically bringing ourselves up beyond the nuances of, you know, Tom O'Neill's individual situation. So, short answer is yes, it is. This is definitely designed to provide insights into populations, either populations in comparison with each other, or focusing in on a specific population over time, and see how that's, they've been impacted by conditions over that time period.
Emmaline Aliff (20:29):
That was a short answer. Very interesting that,
Tom O'Neill (20:31):
Yeah, that was my short answer. Imagine if I had given you the long answer. Mm-Hmm .
Emmaline Aliff (20:35):
Yeah. What, what I, what I particularly like about some of the things you've been describing and the rest of the team has been adding on here is that it's bringing in a lot of the key components that that are necessary to understand for the market. And in particular, you know, we, we think about things like credit score, credit score, migration, movements that have occurred. There's been a lot of major pivots and shifts over the last few years. Like we know over the since 2020, you know, the subprime population as a proportion has shrunk, for example, but the delinquencies have been on the rise. And so what, what I find interesting just based on some of the things that we've been talking about, is the ability to capture within and between those various metrics, whether like are we seeing any al almost competing effects, like where someone's credit score could be going up?
Emmaline Aliff (21:25):
Like is that, is that going up, but add a detriment to some of the, you know, other components that they have, like what wealth and asset picture, for example. So thinking about like, the way we've described this and how we're looking to, you know, explore this, what, what, what are some some things that'll help us understand maybe, you know, Jesse, you can, you know, tie into some of that as well, that, like, what are, what are areas that we think we could understand by leveraging something that's a little more you know, you know, capturing the, the, the different varying behaviors of financial profiles?
Jesse Hardin (21:58):
Yeah. You know, I, I mean, one, one comes to mind right now and just the situation we find ourselves in with the government shutdown, a lot of data that the government uses specifically the Federal Reserve uses to make decisions that data is kind of put on hold. And so it's interesting to see a holistic, you know, data source that can provide some semblance of idea about where the economy is. Frankly, in a situation where we're not gonna get updated data, or we may not get updated data just depending upon the direction that the, you know, that the government goes. And so I think having a data source, again, like a, a holistic data source, looking at a multifaceted approach to to an aggregated consumer, I think it really provides that, that picture that we, you know, we may not see, or we may not get completely in, in a situation like we find ourselves in,
Emmaline Aliff (22:55):
We very often will talk about inflation and interest rates amongst our team. And I think the, you know, because we, we know that interest rates is one of the biggest things that impact you know, whether or not originations will occur or, you know, you know, various, you know, capacities like savings and things like that. Even, even with respect to yield curves, like interest rates are such a driving force of that. And oftentimes interest rates are meant to understand behavior around inflation. And, and one of the things that that I found particularly interesting is how the shape of our function with respect to the things we track on our market pulse index has been related to in, you know, inflation in general. You know, maybe you guys can talk about the, you know, I guess that, that aspect and, you know, you know, Tom, I know you, you have familiarity, but if anyone else would like to chime in there, I think it's, I think it's a very interesting behavioral representation that economic metrics are being captured at the, at, you know, at a more of an individual level that we can boil up to then.
Maria Urtubey (23:58):
Yeah, I, I would say, or I would as I was listening to the details Tom provided on Market Pulse index is the, the component or the in a way the visibility into the affordability of, of the, our lenders, our customers customers, right? And that discrepancy that we observe between the top part of the K and the bottom part of the K shape economy. We've been when we look, for example at housing, we've been seeing that that disparity or that growth in the medium housing price versus the median income how it's spreading even further, you know, since 1985, specifically the last 40 years, and how this can provide some, shed some light into where it's occurring. For example, if we are looking at, at specific segments where that ratio is, is more noticeable than the, you know, 5.6 times that we're currently observers versus the three over three times ratio. And going back to what Tom also highlighted the wealth disparity, having this other component or, or visibility into the consumer will shed some light into our customers plans for growth and also for making products that are affordable to others as well.
Jesse Hardin (25:24):
Yeah. Emily, I think, you know, when you asked the question spec specifically too about inflation, knowing how much inflation had an impact on consumers and, and businesses alike, but especially thinking of the K and the K shape, one of the things I've been really excited about with Market Pulse Index as well is, is being able to look at market pulse index in different different cuts. So geography, like what does the market Pulse index look at, look like, maybe by a state level, you know, we've seen differences. Some some recessionary trends are, are are shaping up differently by state. So so that could be an interesting aspect, even looking from an incomes perspective. Like what, what do different incomes exhibit when you, you know, when you see something like market pulse index and then you know, as well, just credit tiers diff looking at different credit tiers. So I, I'm really excited about that aspect as well, being able to see not just overall aggregate amounts, but then those aggregate amounts by different cuts of, of the population.
Tom O'Neill (26:30):
Yeah, and, and I, I like the fact that you, you used CPI you inflation as as an example to draw that out, because it's such an obvious one to say, oh, we've been in, you know, this, this past four years of an inflationary environment, and inflation is an eroding factor on, on consumer finances. So it's been a really bad period that we've been in for the last four years, right? And we could look at metrics and say, yeah, it's obviously had a negative impact on a lot of different areas of, of, of financial behavior, but it gets back to what we were talking about before. That's, it's, it's a single aspect, even something as, as heavy and pervasive as inflation. It's one aspect of the financial conditions out there. What else was going on when, when inflation was, was ratcheting up, and it was the only thing we were hearing about in the headlines.
Tom O'Neill (27:31):
Incomes were going up, the stock market was going up, housing prices were going up, equity was being built. All of these things, like when we look at, at measures like the market pulse index, sure, we could see that inflation and the, you know, rising card balances and the rising personal expenditures as a result of, of rising prices, those were having a negative effect. But on the flip side, incomes were having an effect, you know, rising wealth in the stock market was having an effect, but not for everybody . And, and that's where a lot of the stuff that we talked about before, we would have to infer that we'd have to sort of piece that story together. Here we're seeing it laid out for us. We know that all of these things are happening at once, and it's a different scale for one population as it is for another.
Tom O'Neill (28:30):
We talk about the scale, or we talk about the, the K shape, and we've had to sort of pick different metrics in the past to illustrate how, how that's happening for different populations. Here we have it laid out and saying, this population, gen Z, for example, that doesn't have, you know, the history of building up a stock portfolio or having a house gain in value in building up equity. They're, they're coming through this period very differently than the Gen X or the boomers, you know, are going through, you know, this period where they, those populations that have had time to build those things up. So yeah, very exciting to, to see how this could be applied to different things.
Emmaline Aliff (29:18):
Yeah, that's, that's, that's great. I think you know, maybe I'll ask each of you to to do a closing you know, thought here. I think you know, some of the things we, we've, of course, in our roles, we do take a very heavy focus as it relates to you know, financial metrics, specifically when thinking about something like the market pulse index being like a financial safety, financial freedom type of metric. There, there's other things, of course, beyond this that will help measure an understanding of an economic or socioeconomic scenario of things like health, like life expectancies, education with years of schooling, standard of living, you know, some of the things you talked about just now where, like national income per capita, for example versus just the, the average 'cause things can get distorted. So looking at things from a distributional level is something that I'm, I'm keenly personally interested in and especially seeing some of these things as they, as they tie out. So maybe each of you can offer you know, very brief you know, you know, closing thoughts in terms of some of the things we've been talking about today.
Jesse Hardin (30:23):
I'll, I'll take a stab. I'll, I'll be, I'll be brief. I would say that when I talk to customers and our, and our customers specifically, I talk to them a lot about whatever data you're using. You know, if it's internal data, if it's external data, if it's a third party data source looking at the frequency of that data, so making sure that it's updated so that you're seeing that current snapshot. And then you know, making sure that if you are only looking at one type, you know, one, maybe one component of data branch out, you know, look at other data sources. I think it's in the credit world, we think of, there's credit data, there's scores, there's alternative data. There's so many different data sources, there's internal data. Just using that breadth you know, of, of different data assets, I think really can you know, can, can move the needle more than just that very that very small specific use. So again, using the data that you have available and and then learning from from, you know, past experience. We've seen some of these ups and downs. We saw a pandemic, we saw post pandemic, we saw the type of economy that we had. So a lot of, a lot of history and a lot of knowledge there to, to tap into.
Maria Urtubey (31:43):
I, I would add, going back to the, the data component that Jess is referring to ensuring, because it can be overwhelming, the number of sources and some of you might be able to handle and have practices in place, and that feed that constant frequency is, is there and available to turn that data into insight and to drive decisions and updates to strategies. In some instances, given its overwhelming, something like the market pulse index might be the way to get that global perspective versus and, and those local component differences. Tom referred to the student loan population, right? Differences such as something as evident as my off population or of me student loan population that is present. And how does it differ compared to those that do not to those that are delinquent, given I have this new visibility into their profile. Again, maybe simplifying that feed, but having access on with verified accurate information that can give you the, provide you that insight, reliable insight. Yeah,
Tom O'Neill (32:55):
And I think, you know, to, for me, after spending this entire podcast, you know, talking about the market pulse index and the holistic side, I'm going to, I'm going to reverse and, and then say, okay, but once you have that strategy that, that Maria just laid out, that's that, that understanding of how conditions are impacting different populations and how I, as a lender, you know, take advantage of that, that's where it then drills back to those individual, you know, behavioral components. Like, all right, I understand what's happening to the Gen Z student loan holders, for example. How do I craft my strategies, my actions to, to take advantage of that understanding? How do I craft my messaging to that population? How do I develop my risk strategies, you know, given that you know what I understand about that population, and that's where those individual components really shine and come through. That's where I can use the credit scores and, and the other types of, you know, wealth and asset type information to develop those, those onboarding and, and and growth strategies in relation to my risk strategies. So it's, it's a, it's a very nice, you know, mesh and, and interplay between, you know, the very, you know, holistic view and the individual components that at the end of the day is what's going to make a, a difference in the business. That's
Emmaline Aliff (34:28):
Great. Thank you all for being here today. Much thanks to Tom, Maria and Jesse, and our thoughts. Go out to Dave again and he'll be joining us again next month. So with that I will, you know, of course you will be back for additional updates and sharing more information on this and tune in to our market Pulse later this month to hear more about you know, the Market Pulse Index as well as you know, you know, various things that we're anticipating from a upcoming holiday perspective. So as a reminder, your feedback is important to us and critical to conversations like the one we had today. If you have questions or suggestions for future podcasts, please reach out to us at Risk advisors@equifax.com.