All right. We will go ahead and get started. Thanks, everybody, for joining us. I'm Patrick O'Shaughnessy, the Capital Markets Technology Analyst here at Raymond James. And up next, we have Dun & Bradstreet. And on their behalf, we have CFO Bryan Hipsher. Bryan, thanks for joining us. Yeah. Thanks so much, Patrick. We appreciate it. So Bryan, for the benefit of the people in the room who are a little bit less familiar with the story, can you maybe just give a brief overview of Dun & Bradstreet and how it compares today to, let's say, five years ago? Yeah. five years ago, 10 years ago. Dun & Bradstreet, we are a data analytics provider. I think we describe it, Patrick, as both offense and defense. So we support businesses throughout the world on whether they're finance and risk use cases or sales and marketing use cases to really become more efficient and effective from that perspective. And really powered in the middle by our Master Data Management, Entity Resolution, and what we call the D-U-N-S Number, which is, in essence, the Social Security number or fingerprint of 550 million entities throughout the world. And so very deep, very ingrained from that perspective. And I think one of the things that is significantly different, so five years ago, which is shocking, it's been five years, we took the business, actually, private through a transaction and really saw the wonderful aspects of Dun & Bradstreet. But frankly, it had been pretty underinvested in, undermanaged, right, and really was ripe for getting some bureaucracy, getting costs down, and really focusing on innovation and accelerating revenue growth and therefore profitability. So it's been a journey. The business, again, was, I would say, relatively flat from a growth perspective for almost a decade. Again, that's what happens when you have really sticky, really great data sets. You can kind of rest on your laurels. And that's where I was at. So first couple of years, heavy on the transformation side, organizational transformation, Salesforce transformation, a lot initially on moving from 10 terrestrial data centers down to three. Now we're in the more next advanced stage of that, which is moving from those terrestrial data centers into a cloud and cloud-native application stack. This is the question that could go on for the next 15 minutes, so I'm going to cut it off at some point. But the biggest difference has clearly been the accelerated organic revenue growth from flat to now approaching that kind of mid-single digits, the middle point of our guides around 4.6%. Clearly, EBITDA went from somewhere in the $570 million range to now upwards of $900+ million, and clearly continuing to do things like deleverage the business. I mean, we were an LBO, right? And so we were about 9x levered with a preferred equity instrument. And now it's down to 3.8% and continuing that glide path. So it's been a lot of work, been a lot of effort. And so I think we're continuing to see that acceleration of results. Over the next few years, look to continue to improve upon where we've gotten to today. If you were to go back and look at the presentation you guys were talking about during the IPO roadshow, which I recently went back and looked at, how do you think that Dun & Bradstreet's financial and operational performance since the IPO has tracked relative to what you committed to during the IPO? Yeah. I think it's tracked really, really well. When we came out on the IPO, obviously, the transformation wasn't complete at that point, right? But we knew that. But we also knew the markets were in a really good position from that perspective. We knew we had a pretty heavy debt stack that was quite expensive. And we took the opportunity to IPO a portion of the business. And we took out some expensive debt. We refinanced it down. The whole preferred equity was gone. And it also allowed us to actually execute on the Bisnode transaction, which was something that I think really opened up Europe. That was one piece that the international business was really treated more as a data collection kind of methodology. And they had kind of divested of a lot of those assets and created that worldwide network relationship. But there are certain areas, whether it's the UK&I, whether it's certain countries in Asia, but especially DACH regions, Scandi, some of the Southeastern markets, those had a lot of potential from our perspective. And so with some of that excess cash, we were able to acquire that. And it's been a really good payoff from that perspective. In terms of results, I mean, again, we said it. We were kind of back then talking about going from 0-3 to 3-5 to 4-6. The investor day, which was our first follow-up, was in that 5-7 range, right? And so from that side, it's been a progression. And certainly, there's been some things in there that have been you need to do a little work, right, to get down to how the organic engine's been performing. But the nice thing is, a lot of that, all of that's behind us. And you can see now in clean quarters what the business is really doing. And hopefully, you see that in the results. You've spoken to the improved organic revenue growth results that the company's put up. What are maybe the two or three biggest factors driving that improved revenue growth? Yeah. I mean, it is a combination of things, right? So if I said price, right, which has gone from less than 1% of growth to now 2% this year, about 2.5%, you say, yeah, but why? And it's the investments that we've made. I mean, it's interesting. If you look over a 10-year period, right, our CapEx as a percentage of revenue is 5.8%. But the issue was, in those five years before and frankly, the 10 years before that, it was run at 2%, right? There was no innovation. There was no investment into the platform, into the data, into modernizing the solutions that we were delivering. And so from that perspective, by doing those things, by upgrading UIs, by enhancing our API strategy, by taking the D-U-N-S from 300 million to 550 million, by adding millions of UBO records, all of that ends up playing into why our third-party risk and supply chain risk management has been growing double digits, why MDM, which was already a big business, is still growing to high single digits, the finance solutions business, right, still very strong and sticky, but it's getting the price increase that probably deserved back then, right? And then on the international side, we've taken a lot of the products that we had domestically and localized them and delivered them into, whether it's the UK&I, whether it's into India and in some of the other APAC countries. And we've seen that accelerate growth originally up into kind of high singles, little doubles. When we bought Bisnode, right, it was a transformation story in and of itself. So we bought it very inexpensively. But at the same time, we had to take something that was a -1% organic grower. And now it's getting into those kind of low singles into mid singles. And margins have gone from 10%-30%, right? And so what I would say is that it's a combination of initially better cross-sell, better up-sell mechanics, better compensating mechanics around how we pay reps and how we can send reps, better pricing, right? And now you're also starting to see vintages of new products start to take hold. And I think that's reflective in why the Vitality Index is as high as it is. So I think maybe building off of that point, and you talked about capital expenditures as a percentage of revenue being a little bit elevated since the take private. What are some of the biggest areas of spending for Dun & Bradstreet right now? And how much of this spend is kind of structural in nature, like this just what the business requires versus you're still kind of catching up? Yeah. I mean, somebody says maintenance CapEx to me, and it's like jumbo shrimp, right? Because obviously, maintenance, bug fixes, those things, those are OpEx, right? And they flow through. But if you think about kind of how the business was operating before and kind of just steady state, right, not accelerating growth, it was 2%, right? And so clearly, if your reward that you're looking for is to be flat for a decade, right, that's the right level. Now, where we got to and we're up to, I think, 8%, 9%, and it's come down a little bit. But from that perspective, that's why we've ended up blending out to this kind of 5.8% over that time period. Now, I would expect, as we head into 2025, 2026, 2027, we talked about in the midterm that 6%-7% range. So it's not going to go and listen, going from 8%-7% or 8%-6% is predicated on the opportunities in front of us each and every year. And so right now, we're frankly in a little bit of an interesting stage where GenAI opportunities are in front of us, right? We have this great data set. We have this entity resolution and master data management applications. And then we have the ability to build upon that, right? And some of that purchased software, for instance, that we saw last year where [guess] IDS was coming down, it's licenses of some of the we're not going to build $500 million large language models, right? That's not our gig. But using some of that tech and then integrating our data on top of it, Ask Procurement, AI for Hoovers, that's where we're taking from that perspective. When we think about going from roughly 5% to the 6% to the 7% and then continuing to sustain in that range, we don't need to be at 8%. But will we be in that kind of six-ish% over time? That's what we've talked about. Okay. That's helpful. Last piece on that, I'm sorry too. When we talk about the transformation, I think that's an important piece, right? Because one of the things, we hit a lot of transformation. Early on, we were probably, in those first few years, like 80%-90% transformation, right? I mean, I personally, we were doing ERP conversions off of a version of Oracle that had gone out of critical support in 2013. So hand me the ERP conversion baton again, right? I went through this at my prior firm, too. But that's the kind of stuff you got to do that allows the proper foundation to run the company over a longer period of time. So we're doing things, like I mentioned, migrating off of the last kind of three terrestrial data centers with the provider. We're running onto the, we're in a hybrid cloud environment. But the GCPs, the Amazons, the Microsofts, they're the key cloud providers from that side. And so we're going through where we're running right now, almost duplicative between those two. What's important is one's going to fall off. The other one continues on. And we now have stacks that are native cloud and running on cloud environments, which I think, again, are some of the reasons why that CapEx is a little bit more elevated than it will be in the future. And then maybe just turning the CapEx conversation into free cash flow, which has been an area of investor attention, I think because of elevated CapEx and some other factors, free cash flow conversion has been a little bit depressed in recent years. What are your expectations? What can this business model really sustainably do from a free cash flow perspective? Yeah. It's got great natural incremental operating leverage, right? But again, mathematically, if you go from 2% of CapEx up to 6%, 7%, 8%, you have a mathematical differentiation, right? Because CapEx is coming off in period and year, right? And then the amortization is picking up over time. And so we had this conversation, I think, about stock-based comp, right? It's the same thing. In the first year, if you have $3 of stock-based comp, it's only $1 of stock-based comp expense, right? Year two, you give three more. So now you're at two. Once you're at three years and three years of vesting, it's run rated from that perspective. So what we're seeing is that convergence of the CapEx and D&A. So as we're flattening and frankly bringing CapEx down over the next few years, you'll see that D&A pick up, right? But then obviously, the growth, you know what I mean? Profitability is picking up in the EBITDA line, which is very critical because the reason we're investing is because we're expecting the returns and the growth and the acceleration, which we've seen. I mean, I think it's a great example. When you look at this 10-year period from 2014 to 2024 and you say, look, it's 5.8%, right? That's very normal. But the issue is, when you were 2% and the business wasn't growing, the good thing is, now that you're seeing the investment in CapEx go up, you're also seeing that organic growth rate go up. And I think that's indicative of where we're going in the future. You mentioned EBITDA moving higher because of these investments that you're making and the cash that is generating. Much of management's long-term compensation is tied to EBITDA. Why is EBITDA the right metric for your compensation or for investors to really focus on in a somewhat capital-intensive business? Yeah. And I think it's interesting because capital-intensive, I think, is tough because in the short term, with the catch-up of where we're at, I think longer term, it's not, right? It's in that kind of normalized 5%, 6%. But when we think about a couple of things, one, the business was pretty highly levered when we took it over. And so obviously, when we're thinking about from a peer comparison and overall comparison, it takes out the interest side of the equation. And then think about taxes, right? I mean, you're a Notre Dame guy. We love the Irish. We do a great job in Dublin. But Pillar Two, obviously, cost us almost $0.06 of EPS this year because it swung from 15% to 9%. And so as you're going through those types of things, we're thinking about what is kind of the organic growth acceleration? What is the margin flow through from that side? And then we're managing the debt stack down. We're managing the overall, obviously, tax rate as much as we can from that perspective. And so when I think about the incentive compensation structure, I mean, on our side, management incentive comp is organic revenue growth, new sales. There's some on EBITDA. And then there's on EPS. And we have 10% on a risk metric. When we think about the vesting, right, from a stock-based comp perspective, which I think is what you're referring to as the majority, there's a three-year vesting cycle, right? And there's an EBITDA hurdle from that perspective. In the end, my compensation, my earnings, and the majority of our execs, all of our Section 16(b)s and the management team is in stock, right? So really, what we're predicated on is what everybody else in this room is predicated on, which is driving shareholder value. Because again, it's obviously, if you looked at kind of the math of cash comp versus stock-based comp, I mean, we're at like 25th percentile when you're talking about cash comp. And that's the method, right? We want our people motivated by driving shareholder value. And that's why it takes into account the organic revenue growth, right? The EBITDA growth and how we handle OpEx, how we think about cash investment, because all of these things are not just important to investors. They're important to us. And they're important to the long-term sustainability of the business. Got it. That makes sense. So maybe coming back to the business a little bit, you guys have spoken about the value of the D-U-N-S Number quite a bit, particularly in terms of it being a competitive differentiator for Dun & Bradstreet. But I think you kind of touched on this earlier. The company's had the D-U-N-S Number for a long time. And that in and of itself wasn't enough to turn that asset into a revenue growth driver for the company. So what are you guys doing differently leveraging the D-U-N-S Number that hadn't been done historically? Yeah. So I think the D-U-N-S Number, interestingly enough, and the criticality of not just the D-U-N-S, but the data that was attached to it, what it was doing, allowed the business to stay flat in such an underinvested. I mean, most businesses, it was one of the things that attracted me to the role and to the opportunity was like, there were a lot of room for improvement, yet it still stayed where it was at. So really, what it is, is about use cases, right? So the D-U-N-S and the hierarchy and the Entity Resolution sits at the middle from a Master Data Management perspective. So clearly, taking that from 300 million-550 million is big because you've expanded the aperture of the businesses that you're covering throughout the world. Then it's about the different data elements that you're ultimately adding on and the use cases that are driven out of it. Traditionally, we've been great at horizontal use cases, right? Trade credit extension, business-to-business lending, and then on sales acceleration, right? Lead generation and prospecting and propensity to transact, right? What's cool now in one of the great, I think, examples is capital markets, right? So in the end, you'd say, well, the data that goes into the capital markets, hasn't that existed in that same time period, too? And the answer is generally, yes. Right now, things like shipping data, some of the alternative assets have made it that much more interesting. But you got to have some subject matter expertise when you create that product line and when you launch that into from a GTM perspective. So we hired a guy, Bryan Filanowski. He was the former president of Fitch Ratings. Gary Kotovets came in, who was the number two guy in data at Bloomberg and was our CDO. You put them together with our product team. All of a sudden, we landed a top 10 private equity company with this pretty significant deal in the fourth quarter last year. The interesting piece, I think, in there is we're supposed to do a press release with them, right? Then their CEO said, no, right? This is too unique to us, too proprietary. That's a good sign from our perspective. Taking a step back, what do you think investors who aren't very familiar with Dun & Bradstreet don't understand about the company in the way that your biggest, longest-term shareholders do? Yeah. I think, one, what we talked about, what the company was and what it is today are light years apart, right? And you can see it ultimately in the difference in financial results and where we're performing now versus where they perform for 20, 30 years, right? How we're thinking about the data, how we're innovating, how we're investing, the Vitality Index, right? The organic growth acceleration, all those things, right? Are indicators of where it was and where it is now. And so I think that's a big thing for folks to take a look at it and say, this is not your whatever, grandfathers, grandmothers, whatever, Dun & Bradstreet. The second is, I think that when you're looking at all of these metrics, you have to take into account the fact of, while it is a relatively seasoned business, right? In terms of maturity of its investment cycle, it has only been going on for the last three or four years. So when you ask questions like, okay, the perfect info services businesses out there are growing revenue at X, have EBITDA of Y, and free cash flow conversion of this, you got to do things like invest upfront, which is why the free cash flow conversion is a matter of time, right? Because there's a mathematical differential between those two. When I think about things like where the debt stack is, right? There's sensitivity around, hey, it's at 3.8x. I mean, the difference between 3.8x and 3x, right? Is $500 million, right? And it's 6%. It's $30 million of interest expense. And this is a business that's been around for decades and decades and decades, right? And has very deep relationships. And so from that perspective, we can handle, you know what I mean? That much more. But of course, we're looking to get down to that three and frankly could migrate lower from that perspective. So I think it's one of those that as you're picking it up, right? You kind of have to see the transformation and how it's evolved and where we're at and certainly the opportunity of where we're going. And so the folks that have been willing to kind of do a little bit of work and see through some of those early things, that's, I think, the opportunity that's presented because any which way you cut it, right? I think there's a lot of value to be had in where we're trading at today. Maybe just to follow up on the topic of your debt burden at this point, what is the right level of debt for this business in terms of kind of maximizing the debt structure, but also kind of providing comfort to your shareholders? Yeah. Look, I mean, you've seen it. Regardless, we're below 4x. But if there's a day of inflation or there's a day of PPI or CPI print that goes one way or the other, it seems to trade from that side. And so I think the feeling is that as we migrate, and we talked about being around like 3.25, you migrate into that 3-3.25 range. And I think at that point, if you got a mid-single-digit grower, you got the margins at 39%-40% in expanding. Free cash flow is kind of catching up from that tail that we discussed before. And then the only other thing that's out there is buybacks, right? And so that's where you're kind of looking at the balance between those things. But right now, we're focused on investing in the business organically, the dividends maintained at where it's at. And then it's deleveraging through EBITDA expansion, but also gross repayment. M&A, look, we don't want to bury our heads in the sand, right? But the level of quality of that acquisition has to be very high right now for it to be overly interesting from where those other components are at. I'm going to take a pause here and see if there's any questions in the room. All right. I don't see any hands being raised. So I will keep going. All right. You touched on GenAI earlier. I suspect that's been a very popular topic of conversation at this conference this week. What are you guys doing in the GenAI space right now that's really interesting to you? Yeah. I think there's three things. And so what's great is you look at our customer base, right? And I mean, it's everybody and anybody. I mean, the 90+% of the Fortune 500, all the major players that are in that space, whether it's the Microsofts, the Googles, the IBMs, right? From that side. And I think what's interesting is they all have different strategies in terms of how they want to use the GPT versus the watsonx versus the Gemini or the different models. And what all underlies it, though, is the data. And so if I think about the first step from our side, Master Data Management, Entity Resolution, and the overall data that we can provide from a commercial use-based perspective is unparalleled from our perspective. And so I think there's a really unique opportunity. And one of the things that they're seeing is this theory that all the data can just get shoved into these large language models, and it'll all get processed and organized, and the correct answer is going to get spit out is a fallacy. And so what you're seeing is that data needs to be mastered. It needs to be curated. And it needs to be repeatable over time to keep the hallucinations down, to keep the drift from occurring, right? And so that's where I think, as this thing is rapidly evolving, it's one thing on the consumer side, right? But if you're going to make true business and commercial decisions, lending decisions, operational decisions, operational changes, you got to make sure that it's sustainable from that perspective. And so the data underlying it has to be strong. It has to be auditable. It has to be consistent, right? It's got to be trusted. That's where it plays into our wheelhouse really, really well. Then you go into, and we mentioned Ask Procurement. We mentioned AI for Hoovers. The assistants were kind of early on, right? In terms of if you look at the overall kind of landscape, I mean, most of the work out there is being done is customer service, HR. There's a little bit in finance and operations. But take a spot like vendor management and sourcing procurement, huge space, right? Very manual. In large corporations, if you take large software companies, they could have 1,000 people in that area. If you take a large hardware provider, you could talk 3,000, 4,000, right? And you have someone primarily going in and, hey, Googling who's who, right? But financials aren't there. Risk profile is not there. Sustainability is not there. And again, even if you're working inside of a software application like [guess] RA, it still takes a level of filtering and searching through a relatively large data set versus Ask Procurement, which is trained on our models in the background with the support of an LLM. And you're asking it a very simple question. For instance, if I were a pizza manufacturer, right? And I needed all the pepperoni companies in the tri-state area, I can ask that question. Who are the pepperoni manufacturers in the tri-state area? Great. By the way, who are financially stable with a PAYDEX of over 90? Okay, great. Who are ones that have a high sustainability score? Okay. All of a sudden, I took this universe of 1,000 and I shrunk it down. And that's a pretty simple method. But imagine you're hardware or you're making a phone or you're making large-scale industrial equipment. That is now a global question to ask from that perspective. That's the kind of stuff that I think is super powerful and we're really excited about. Got it. Very interesting. I think that's a good spot to end on. So thank you, everybody, for attending. And thank you very much, Bryan. Great. Thanks, Patrick.