FactSet Research Systems Inc. (FDS) Earnings Call Transcript & Summary

All right. Good morning again. Thank you for being here. For those of you who just walked in, again, I'm Manav Patnaik, I'm Barclays' business and information services analyst. And we're pleased to have back with us again, Linda Huber representing FactSet. So Linda, thank you for being here. I know you've been doing this conference under many different roles for many years. So thank you for your support. Linda, maybe just to start off. When people hear FactSet, I mean, the first simple thing they say is, oh, the desktop company, right? But you guys are obviously much more than that. It's been a process of diversification over the years. So maybe if you can just set the stage for the audience in terms of the different buckets and mix of your business, I guess, the way you would describe it today.

Yes. And thank you very much for having us back from FactSet. If you awarded frequent flyer miles for this conference, Manav, I think I would get some. So thank you. Yes, FactSet is much more than a desktop information provider right now. We work with a variety of clients in the financial services and other spaces. 50% of our business is actually on the buy side right now and about 20% in the deal makers or sell-side part of the business. Wealth is a little bit smaller than that, but not too much. And then we have a business called Partners, which are the companies that both provide information to us and who are also our customers. So the investment thesis for FactSet right now is we are really the best positioned data and analytics provider for the financial services industry. Now why do we say that? We sit on top of 40 years of connected, well organized and concorded data, which other companies do not have. And in fact, many of them depend on us to supply that data for them as a service. So that data is ready to go right now for AI. So if you believe that data is the new oil and AI is the wave of the future, FactSet is really the best situating company to take advantage of that situation right now. So we're pretty excited about the future. Last week, we had our FACTSET FOCUS conference in Miami with hundreds of clients, and we demoed a few new things, and I'll talk about those in a minute. But Manav is asking the questions. So back to you.

Yes. Well, maybe just one other mix breakout. You gave us the mix by your end markets, but how about by your products as I'm referring to CTS and data and those kinds of things.

Yes. So we're reorganizing toward firm type as we had said. So the CTS business is now really a horizontal in terms of data solutions. And in there, we have the CUSIP business, which we bought back in 2021, financed that in 2022, got our investment-grade ratings back at that time. And just by way of note, we don't break out CUSIP anymore, but it's revenue growth and its margins. Both of them have well exceeded our expectations. So that's an acquisition that I think could be characterized as a home run, and we love having the CUSIP team with FactSet. So it's been great.

Got it. Okay. I want to touch on the customer type, I guess, breakout you gave. But first, maybe to your point on 40 years of concorded well-organized data, et cetera, and the hot topic of the year around GenAI basically. How do you, at FactSet, think about the opportunity GenAI provides both from a cost side because you're in charge of that and then revenue as well?

Sure. So we're going to the revenue side first. I don't think it's a big shock that for the entire industry, this has been a bit of a tough year and the revenue line has not been what we would have hoped. I think you may have seen prints from our competitors recently that have pointed that out. So in the near term, we're focusing on generating annual subscription volume, ASV, from AI, and we're looking to do what's useful to our clients. So we've been in development with a number of our closest clients in the development of what's called FactSet Mercury, which is our overall AI tool. That has gone great. And as we said, we demoed some of the things that we have last week. So first job is to be outward-facing and to drive ASV in a way that works for our clients. We're not sitting around in a skunkworks trying to develop it on our own. We're doing what makes sense for the clients. In terms of efficiencies, those may start showing up in '25. We've got really 3 things that we're looking at. The first would be there that with some of the new products, our engineers can be more efficient in their coding. Even some of our most difficult to persuade engineers have said that they've seen pretty good productivity enhancements from having the next line of code suggested by AI. Of course, your goal is to write better code, not just more code, but it does seem to be helpful and it's relatively new. So we'll say more when we do FY '25 guidance in September about that. The second thing would be on our help desk. A lot of the inquiries are about FactSet codes. If we can automate that, we can release some of those people from help desk work and have them do other things, which would be great. And then we also have the assist tools, which are helpful to our own teams in terms of enhancing their efficiencies. So we see some good opportunities there just now looking at what those cost savings might be in terms of productivity. So we'll have more to say about that in September.

Got it. And so obviously, the cost savings the way you described it could be significant. But how should we think about not numbers because you said you'll tell us more later, but just the philosophy around whether you let that drop through or how much you choose to reinvest?

Yes. I think we've been -- we've made great progress on our margin line. This has kind of been our quest over the last few years. So we've guided to 36.5% adjusted operating margin at the midpoint this year, depending on what happens with the technology budget spend and the uptake from our clients on usage of cloud because of GenAI, we may come in at those heavier numbers or we may do a bit better. We'll have to see. I think we'd like the incremental improvement in our margin, and we had talked about 50 to 75 basis points of improvement. With AI, we may pace that a little bit as we get to where we need to go with AI. But we have set out medium-term targets to get to a margin which we've gotten to a year earlier than expected. So we're very pleased with the progress. But right now, we want to get back to that strong top line growth. That's job 1 right now.

Got it. And just considering that you mentioned it was a challenging environment. The top line growth is a little bit muted. What tools are in your belt in terms of keeping that margin where it is or even expanding it like you are every year so far?

Well, we think about the 4 major cost buckets. So in terms of the sizes in descending order, the people costs are the highest for FactSet. And I think we've done a pretty good job. We're 68% offshore right now, which feels pretty good about right. We are shifting some higher-value work over to some other offshore locations, which will help us. We're looking to keep headcount a little bit flatter and the comp line will go up as we provide salary increases and respond to inflationary pressures for our employees. But we want to keep that headcount number under pretty close control. Real estate, we've reduced our real estate footprint from 1.7 million square feet to 1.1 million square feet. So we've reduced it by about 1/3, which has been really good. I think we were early movers on that. And I think we've about optimized that at this point. And then lastly, third-party data. We've held our cost there to about $100 million. It's pretty amazing in an inflationary environment but we have some pretty good negotiators who've done a really good job for us there. So that takes us to the tech budget, which is the second -- actually, it's second biggest expenditure bucket. I have said those out of order. Sorry about that. So that one has been growing in the high teens. And a lot of that is preparation for AI. We've got 3 fast-growing components there. One is amortization as we've automated time tracking. So we're tracking that, I think, quite effectively, but the amortization line has grown. Second is the cloud budget. And if you're looking to host more for AI, the cloud budget will go up, and this is something that success will add to increased costs in our cloud budget. But we have tools to manage cloud usage. So I think we're doing pretty well there. And the last one is third-party software. And we have to be a little bit more cautious about how much third-party software we let the company, the employees of the company buy. So those are the 3 big drivers of the tech budget, and we're working on it very closely with Kate Stepp, who's our Head of Technology. But again, focus is to make the best use of AI right now. Outward focus comes first, internal efficiencies will follow that.

Got it. And the 68% that's offshore that you talked about, like is that the area that you could reduce if GenAI works in your favor from a cost side or not necessarily?

One thing that I forgot to mention, we have about half of our employees collecting content. It's a very expensive thing to do. And as we move forward, if we could further automate that content collection, I think we could see some further margin improvement there. Now that's going to be a multiyear journey of exploration as to what we can do in terms of that function. And of course, many of those people are quite highly trained and could do other things for us. So I think as we look to automate content collection, that's a big potential lift for us, but not quite sure what the extent of that will be quite yet.

Got it. And I think we've heard this from other companies, but to your point on success means higher costs in the cloud. So is that just -- is that purely because of the cost of running GenAI on the cloud? or is that a broader comment?

I think it's a broader comment. We have 6 million portfolios on our system, most of them in the cloud, and we want that. It creates great stickiness with our clients, and it allows them to do many things with and -- in terms of analytics on those portfolios. So it's an important component of our client retention, which is very high, around 95%. So we want to keep that, but we have to balance that with the cloud costs. And I think everyone's aware. The cloud providers are doing pretty well right now. The chip providers are doing pretty well. So we have to be thoughtful about how we're managing those costs.

Got it. Well, that's a good segue into you mentioned you're focusing on revenue enhancing products using GenAI. You've had a few releases of PR at least out there. I don't know if you want to refer to a couple of them and just help us appreciate in the context of this usage-based cost going up, how do you price these new products?

Yes. So that's something we're working on right now, but we have some directional ideas. So maybe the coolest new thing we demonstrated last week at FOCUS was the portfolio commentary summary product. So if you have a portfolio and you have that up on FactSet, if you want to write a summation of how that portfolio is done over a quarter or a year, generally, it might take a well-trained PM or at least one of our colleagues who is pretty smart and went to Stanford as an undergrad, so I've got to think he does a good job at this, 25 minutes to write a piece of commentary. Now if you have your portfolio on FactSet, you apply our AI tools, 1 minute. So there were auditable gaps from the audience last week in terms of what this product is able to do. It's really pretty cool, pretty gee-whiz. So the idea is real tools that will help real people doing their jobs now reducing the work that takes more time, but could be done or could be assisted by a machine. So the way that's working now is you can look at -- you can do this for 5 of your portfolios in a day. If you want to do more than that, you're going to see the helpful button that will allow you to subscribe to this service. So we're going to price for that. The pricing amount is not fully aligned and determined yet, but it's a great product for everybody to take a look at. And I think it has that wow factor, which will really be great for everyone to see. The second one we have is transcript summary. You may have seen this already. It's out there. So say, for example, you're looking at UBS had a print this morning, strong print, so good for them. If you want to make better use of your time and rather than listen to the whole Q&A, the transcript summary has an AI feature, which will take the top -- we'll consolidate the top 5 points from the management Q&A and put it right up there for you. So rather than wait for the whole transcript, you can just look at those top 5 points and see what they are. The other thing you can do is with natural language, not a drop-down prompt, natural language, if you want to say operating expense comments and just type that in, the assist will come back to you with everything that UBS said this morning on its operating expense metrics, and it'll just put that right up there for you. And again, natural language query. It's not a drop-down menu, and you can see that instantly. Now that, we think, is going to be a feature of what we already provide to our FactSet users. So you should be able -- if you subscribe to FactSet, you should be able to see that right now. And then last one, particularly popular with my family of junior bankers, the junior banker workflow tool that allows for quick preparation of charts. So you can either type in a natural language, what you want in terms of the chart. We're working toward being able to query the machine verbally about what kind of a chart would you like and it will create the chart for you. Now we've heard from junior bankers saves 5 to 10 hours a week. I'm not sure if that's absolutely the correct metric, but this is really a game changer for junior bankers who need those charts. Also, this tool can assist in pitch book preparation. Now that will be a premium add-on for what we're charging. But the 3 of these are pretty cool tools that are available right now. This is not vaporware we have this right now. And if anybody would like to see demos of these things, we can arrange that. So pretty good response from our clients last week on each of these things. And again, looking to help clients with their workflows, where they are, we haven't just developed these as gee-whiz tools ourselves. So encourage everyone to take a look at those products.

Got it. And just from your standpoint, like do you see the competition doing the same things or how differentiated do you feel like these offerings are? Because it sounds like that, for example, the transcript summary, there's a few different areas that you can get the same thing. The portfolio one sounds a little bit unique, but I'm not sure where the commentary is coming from. So just how do you think about that?

I think the portfolio commentary is unique from what we've seen so far. But again, you have to sit on top of 40 years of FactSet data to be able to bring in trends and things like that. So we think we have a unique advantage there. Transcript summary is available through other providers, but those are drop-down menus. The ability to query in natural language and to ask it about any specific question that you want is really pretty helpful. For example, when we're trying to track our competitors' performance in the analytics business space, for example, we can just ask the transcript, it says, talk about what they said about the analytics business. And you can do that comparison, Ali does it herself. And that is really helpful if you're looking for a specific area of comparison across transcripts.

And then maybe just a broader question around competition. The industry is challenged. Everyone's -- all the reports are showing they are feeling the pain. Have you seen competitors change their behavior at all? Any dynamics of any particular competitors you would call out?

I think everybody is on the same path toward trying to maximize use of AI, but they don't have our 40 years of data to service the foundation for that effort. So I think as a technology company, I think we really have the ringside seat there, I think we really are in the best position for that, maybe you'd call it the pole position. We see other competitors buying some things, but we're very thoughtful about what we're buying right now in terms of acquisitions because some nichey business models can be replaced by AI in a couple of years. So we're being really thoughtful. We like this CUSIP business that we purchased because it's a global standards business and we can look to step out in CUSIP identifiers to go to private equity and syndicated loans, which are areas that we're looking at. An interesting fun fact is with interest rates as high as they are, if you buy a certificate of deposit in the U.S. and lots of people have been doing that, you have a specific CUSIP identifier for each CD. So the explosion in people investing in CDs has been very helpful to the CUSIP business. It's kind of a funny indicator, but it's been one that you might not immediately think of. And that business is 85% subscription, as we've talked about before, 15% new issuance. But you might think less -- fewer IPOs, fewer bond deals but offset by a lot of CD issuance, which is helpful to us.

Got it. The topic of when the consolidation always pops up more when the industry is challenged. You mentioned a few deals here and there. But -- and that makes sense, but it never seems to happen at a pace fast enough that you would think it should, given the long list of vendors. Why do you think that is the case? And do you have a pipeline like are you trying to go after this in the consolidation theme?