William Blair 46th Annual Growth Stock Conference

Hi, everyone. Good afternoon. Why don't we go ahead and get started? My name is Jeff Schmidt. I cover wealth management in capital market stocks here at William Blair. I'd like to introduce SS&C Technology, leading provider of enterprise software and outsourcing solutions for the financial services industry. We're very happy to have them here again this year. And, you know, with us, we have the CFO, Brian Schell. so thank you he's here to discuss the business and as usual please go to williamblair.com for a full list of disclosures so I will turn it over to

Brian oh that's a good start thanks Jeff and again thanks for a terrific conference and the quality of investors we're we're meeting with so far and so we love coming back every year and thank all of you for joining today brief highlight of what I'm gonna do today I'm just gonna cover SS&C real quick in case some of you are maybe not as familiar with SS&C provide an overview really dig right into AI at the end of the day right it's not an extra topic it's really kind of part of part and parcel of what we do and the story and what investors want to understand as respect to SS&C and then I'll just jump to our financial performance and some of the guidance that we put out there and And so with that, we'll just start with the, oh, I'm going to need the clicker. Thank you. With the Safe Harbor, I won't spend much time on this, but it's there, again, to be part of the presentations. Jeff kind of highlighted here is kind of a bit of our, you know, kind of high-level description about SS&C, as far as kind of where we sit in providing the mission-critical systems, financial services, and healthcare industry. and you'll hear more and more about this as we go through but it's important to kind of easy to come back to but specifically you know SS&C why do we own what we own what do we do what we do is is that we believe there's a value in the breadth and depth of the services that we offer across the board right the services include the transaction process and the accounting the operations supporting everything that that I'll call it in broad asset managers primarily do the reporting the compliance the analytics and those asset managers including you know the asset you know the the hedge fund industry banks insurance companies private markets wealth management and then we do have technology where our provider to the healthcare industry as well for a small sliver of the organization again that technology solution that we provide is IS PRIMARILY AROUND EITHER THE ONPLAM OR CLOUD SOFTWARE AS A SERVICE, THE ACTUAL SOFTWARE ITSELF, OUTSOURCING OF OPERATIONS AS WE MENTIONED EARLIER, AS WELL AS AI, AGENIC AI, AND KIND OF THAT WORKFLOW ORCHESTRATION, INCLUDING USE OF RPA AND OVERALL OPERATIONAL EXECUTION. AS WE LOOK AT THE REVENUE BY BUSINESS, HERE'S A, LIKE I SAID, HIGH-LEVEL perspective right so three of our business units cover 75 percent of the business right so you have globe op you have kids and you have the wealth and each of those roughly represent about 25 each uh and so as these three business units go as well consolidated um as s and c goes a couple of the remaining 25 is covered by a couple of horizontals in the form of of intelligent automation analytics, which is where we have the RPA and the AI and the agents that we've been deploying, as well as interlinks, which many of you are familiar with, providing a lot of the transaction support services and secure data sites, data rooms. And then the remaining roughly 5% now actually close to 4% is our healthcare kind of medical and claims processing group, and providing analytics to those users as well let's just jump right into you know AI and we've had this conversation with some of the one-on-ones earlier today about you know is it is AI is it disrupting our industry 100% it is right that's when we bring it up front what are we doing what does it look like how is it involved SS&C and how are we thinking about it and when we think about disruption the use in this word is that disruption you know is is is definitely meaning change at the end of the day, right? There are some organizations that will not survive as much and will be significantly impacted in the future. Others who it's either a tailwind or a headwind. And for those that we think it's more of a headwind to it, it's those that we think are convenience software as a service and something that's very vulnerable that could be easily replicated versus we think which is less disrupted, but certainly is impacted. we think as a positive can utilize those changes is we've categorized selves in more of that the system of record and how we think about where SS&C sits with its primary services with the proprietary data, the regulatory requirements, and everything that we have, we think AI strengthens the offering that we have. Because if you think about what we do versus what AI can enable, there's four assets or qualities that we bring and we call it to the AI cycle. And the first is that domain expertise across financial services and healthcare services. There's that accounting logic, that regulatory interpretation, that exception handling that just comes with time and knowledge that is just not easily replicated or sitting outside some system about how does this work, that you can just kind of make up. You have to have the same consistent answer every single time you process the transaction. And that's where the domain experience and expertise and real IP in the broadest sense comes into play. The other is we call it the stewardship of the client operational data. And here's where we have the continuity of all the data, the information, I mean there's 55 trillion dollars of assets of client assets that sit on an SS&C software solution service our SS&C tech and knowing this how it works this is very difficult to replicate this knowledge at the end of the day the embedded system is record I kind of referenced this right up front right I mean the production systems the you know the execution where the work is executed and and where does it go from there and what is needed. And that integration with custody systems, integration to the regulators and the reporting is critical overall to operational efficiency and processing overall to meet various compliance standards as well as not just the regulators, but also to the clients of the clients that we serve most importantly. And then the last part, which we think is one of the most compelling parts, certainly working with our clients, is that we take this perspective of being client zero. A lot of this work and these systems and everything start out inside of SS&C's four walls, is that we test it, we utilize it, we deploy it on ourselves, within our operations, to achieve the efficiencies and achieve the outcomes that we essentially will eventually, and that we have sell to our clients, both either embedded within the software or as part of the overall operations. So real operational, practical knowledge of how it works, what to use in the loop, where does it make sense, the controls, and what works and what doesn't. So we think these are our, I'll call it, the assets that we bring to the cycle and why, at the end of the day, we feel positive and feel that the AI elements and what we can do is really more of a tailwind for us. And we're excited about what it can do for us going forward and our growth rates, both top line and bottom line. Again, a little bit of a backdrop of leading up to this and why do we have these capabilities. A lot of the acquisition work, and this is a summary of some of the larger acquisitions that we've done, really you see how it expands our network and what we've done of our services, our capability, our distribution, our client base. You can see we've added analytics, trust services. You see the Blue Prism Automation, which was really found served as a foundation with originally as RPA, moving that to be more AI forward, it really gave us a really jumpstart overall to incorporate within our own operations. And then the most recent acquisition with Callstone, which also gives us a foothold into tokenization. They already have clients already utilizing tokenization in its operations, again, nascent, but actually live and actually working right now. If we want to take a closer look at the agentic AI elements and a little bit of the timeline and how we've evolved Blue Prism with the RPA, because this is pretty fundamental to our AI strategy going forward, is you can see the timeline that we have here and what we've done. This is, you know, we acquired the business three years ago, closer to four I guess now, and you can see how that we've made a lot of strategic changes starting last year with what we've done around the business and how we've continued to evolve it from just I'll call it a pure RPA play to beginning to make those agents smarter starting to leverage AI and being able to do more with the agents and being able to connect different processes that it couldn't before and as we've we recently launched and we've added a lot of talent along the way that was more focused on this AI forward look and utilization of the tools that and when we get to the end of the day and we see the positive called revenue or commercial outcome the revenue mix within you know this business unit and within blue prison more specifically is we are going to see larger contracts and work that's being done and it won't necessarily be you know seat based type of licensing be more outcome base and usage you know similar to what you might expect and so like I said we're very hopeful we're in the early stages of it and as we have more to report we certainly will but we do expect larger dollar contracts to start as the commercial outcome of what we're doing here as we look at our overall approach now these next couple slides are a bit dense and I don't expect to I'm gonna hit every point so I would encourage you to to download the slides and you can kind of see some of the other metrics that we're looking at but some things we need to continue to reinforce with with our investors to understand that this isn't just a you know we're just put AI on the PowerPoint slide and said we're an AI company is that you know we are used to and this is what we do is fundamentally is we spend a lot of money on R&D every year and more and more money is being deployed utilizing AI across the board in some of the examples of where we put it in we put some statistics there in that second chart of the multiplier of looking at how much less time of those developers who started to start using some of these tools reduction in cycle time in reduction of how much time we get a new release to the market and you know kind of some of the return numbers that we've calculated internally and what this looks like we talked about the work HQ launch which again is an overall orchestration layer that can be applicable kind of horizontally primarily financial services firms with clients using our existing software connecting the ai agents connecting rpa connecting digital workers and the course you know services and software that they're already utilizing and they don't have to rip out their existing systems and again a lot of these systems you know the the expression you've probably heard it from others it's it's not necessarily greenfield for ai it's brownfield because ai doesn't work as well um working with apis at the end of the day right and agents do uh and so leveraging that technology under leveraging that understanding and how everything needs to flow to get to a specific outcome from the client data we think gives us a really good advantage and understanding um and a tool that a lot of people are going to want and we're testing it internally like i said and we have several clients that we're working with right now in a advanced stages again nothing to report yet but we're very excited about like i said the prospects overall we already have a lot of infrastructure internally to support this with you know multiple llms deployed you know on-prem globally so that it's everything is still within our four four walls we call ai gateway uh to help support that governance structure uh given that we our clients are almost all regulated uh some more so than others in different geographies and so that governance that auditability understanding the flow and changes is very important and making sure there's no data leakage or external uh so control of that data and use of AI has been very important from day one. So I want to mention, again, this is also, I mentioned, a dense slide. You can take a closer look at this, but what we want to do is lay out with the six different business units that we do have is these are specific examples and capabilities that we're rolling out right now, that we actually are utilizing, right, within our global business, Trade break reconciliation, which takes out a significant amount of time and resources across the millions and millions of trades that are done on a daily business by our clients. You look at the invoice processing across the board. You have fraud detection and AML. You have AI product-driven capabilities embedded within products within the WIT business that a lot of the clients, particularly that small to medium-sized RRAs, are demanding. or make it so that you have those tools where they can deploy it on their own for some of the more sophisticated organizations. And Interlinks has been embedded as a native part of the software and their latest deal center release. So you see a lot of AI-enabled services that are being deployed right now within different businesses, some on the revenue side and some on the expense-saving side to create efficiency, increase accuracy, quicker time to deliver so we're pretty excited overall about you know where this goes with that I will turn to an overview of our financials and we'll do this quickly you know the high-level metrics here with the adjusted revenues again just looking at first quarter up almost nine percent on revenues was about five percent organic growth rate the strength of the 88 was driven by some acquisitions and a positive fx impact you can see that more drop to the bottom line with EBITDA growth of 10 percent operating you know cash flow from operations up another 10 percent and you can see margin expansion of EBITDA about 40 basis points and we guided roughly high level for the year to about 50 so this right in line with where our expectations were and you can see the eps increase of 14 percent lower 14 percent uh for the quarter uh more broadly um as we look at the um the the margins over time i mentioned the 50 basis point uh or excuse me 40 basis points for the quarter but 50 more broadly is you know we have a you know pretty pretty high margin business model uh it's pretty consistent you know we've delivered you know 180 basis points over the last two years so fluctuating between 40 to 60 bps again that's balancing driving incremental productivity and efficiency um and incremental cash flows to our shareholders but also with a discipline of redeploying some of that earnings or you know that that that that that efficiency into um our structure to allow for uh longer term revenue growth rate as well So we've tried to make sure there's a reinvestment, and so that we're reinvesting for the long-term growth of the business and long-term health of the business, as well as delivering incremental efficiency and margin expansion to our shareholders. We think it's important to deliver both over time. I think that's translated to higher earnings over time, right? So you have the higher revenue, you have increasing EBITDA margins, you've got the benefit of a lower expense structure from lower debt as well as rate reductions over this time frame. We've been working really hard on our tax rate to continue to help deliver incremental earnings. And then, of course, you know, the benefit of share buyback continues to help contribute to that EPS, you know, growth rate trend over time. 14.3 percent on a three-year CAGR using our midpoint guide for 26. One of the core elements that we look at from other metrics has been just basically AUA. This has been a real nice driver for our primarily our global business. I think during the last call we talked about this metric and the growth that we've seen over the last several years and a lot of firms that compete with us you know don't even have this amount in total let alone the growth that we've seen in these uh years so solid consistent growth continues to help drive his underlying metric uh for the health of the business and what we do and also speaks to the um to our servicing capability to the largest of clients primarily the hedge funds private markets and private credit private equity and we serve the the most sophisticated of these firms across the globe and we continue to benefit from their success i mentioned earlier about r d as an important metric and on an earlier slide we talked about you know the reinvestment and what we do is you know we've invested 3.2 billion dollars in r d since 21 right so that's a very important part of continuing to try and drive that long-term revenue growth rate um so we we measure it we want to be thoughtful we're looking for an appropriate roi on it and again we think it leads to better long-term results um as far as revenue growth and earnings over time and we think that again that leads to ultimately cash flow which is what you know we can redeploy back to our shareholders so you've seen the growth rate over time we've got a little chart on top of it to kind of look out the cash conversion which is basically the net income report and the cash flow from operations continuing to exceed conversion above 100 percent and what this does we think can lead us to what we believe is an appropriate and shareholder friendly capital allocation program this is just a snapshot of q1 but our priority has traditionally been high quality m&a transactions that we believe can create shareholder value uh you can see the company has has a history of doing that um and you know absent that we've said very clearly particularly given where the stock is trading right now we will prioritize share repurchase i'm not sure much else can say that other than what this chart does and so i would expect to see this chart um you know throughout the year um obviously the dividends been set the the the debt payment that you see here was a mandatory debt payment uh and everything else was share repurchase activity and we would expect to continue to see that and have uh that benefit uh over time um turning to guidance a little bit of longer term and what we did this goes back to a couple years ago from our investor meeting is we set the medium term guidance organic growth as a key metric and we've given a range of four to eight percent as our core growth rate and then we'd expect to try and do more as we are active in opportunistic m&a activities and i think we've demonstrated that over the last year or two with respect to some of the recent acquisitions have really done a nice job of adding um call it one to three percentage points on the top line you can see that 48 uh organic revenue growth rate uh you'll see the 24 through the 26 estimate we've been squarely you know in the middle of that 6.148 uh 5.3 is the current um midpoint in the guidance uh and you can see the different levers and and and methods that we use to achieve that with the products uh with cross-sells price increases have been a relatively small component of that but still there across the organization and then the other one that's um that we're seeing you know i think uh benefits of uh is improving the uh the customer retention and certainly measure that very closely at the uh at each business unit level um as far as the m a and what makes a good m a or what makes it attractive obviously we want that high level you know shareholder value accretion but what are some of the characteristics we look for and a good M&A transaction for us is we want that revenue growth rate of that candidate to be revenue growth rate accretive ability to leverage the existing client base in either services or geography and look we want to see profitable growth at the end of the day right we want we don't want to buy a startup or no earnings growth business so those are important things that as part of the target which makes it very attractive to us and of course we've always tried to deploy price discipline as far as what we're willing to pay for our transaction to make sure there's not a too much of a evaluation gap in our expectations as far as a quarterly guide goes again this is out there for the second quarter we put out an organic growth rate midpoint of 5.6 percent a little bit higher than obviously than what we got it to for at least for the full year you'll see that eps growth rate excuse me eps number at the midpoint of $1.67, which is a 12% growth rate. For the full year, I'll just flash that up as well, is an organic growth rate midpoint of 5.3%, which is up from 5.1 from the beginning of the year, and then EPS midpoint of 6.90, which is about a 12% growth rate, which is kind of what we said as far as the growth rate. We've seen that 12 to 14%, depending on which metrics you're looking at and that's where we're leaning right now as well as the continued healthy cash flow from operations which again is a key metric from us so I think that takes me to the end so we have roughly five minutes do

you want to turn over to you or yeah I would say that we are the the approach

that we're taking is a we don't need to be bleeding edge certainly and I'll say that for the couple right right is is that we're putting it in the hands of our most savvy uh both developers as well as those with them for example like when the finance organization that are not like how do i turn on the computer type of not that we have any of those those people but basically who may have already been using it on their own i'll call it the power users already so we've already seen that efficiency uh built in but it's been we're trying to be very measured in it before we, you know, everybody has a clawed license, for example, type of thing. So we're monitoring token usage, trying to measure ROI right away as far as it's taking, you know, two days to do this and needs to take, you know, three months type of those types of being able to put these enhancements in place. So we are, I would say right now, those productivity gains were rolling back into I'll call it the business and being getting more efficiency and productivity uh to where we see right now right so there's three paths I think that very high level around AI is that you can see the that path of that technology use and you don't have to hire incremental resources to support more client growth or you're delivering things a little bit more quickly. The second path, which you've seen a lot of announcements in a 5, 10, 20% reduction of headcount because I don't need as many people or I'm going to deploy AI. And that third path, which we're starting to see more of is on the revenue delivery. Is it enhancing your revenue sales as a result of utilization of AI? So I would say we're still, given the 6.7-ish billion of revenues, it's hard to show a huge impact right away on it but we're starting to see signs of it for sure so what we do is for the so the LLM know but for the so so we don't use the in a way I want to answer yes so so so we're exploring different right so we do bring some on-prem when we're actually putting our data in and exploring that right so we put it within our AI framework so that any of the enhancements and the learnings and everything is does the revisions stays within so that's not shared back out okay and so we do monitor the token usage if we are going external if we're using it say to build code say I'm gonna use an opus model that's the frontier model a frontier model and I'm gonna have to pay for some of that upfront that's a we've found a pretty good investment so learning to use which of the models are great for the brains and which are good for just the muscle so to speak that can still do things that the average person can't and so we're looking for that blend and finding the right blend around those costs so but but keeping that data and that learns particular we're doing internally is is what we're doing for the the actual data more running that through is on-prem well to the extent that we can yes as far as learning so so if it's generating like for example a Python code to be able to do this we take that code plop it in and I don't to keep tapping the opus model because i now have what i want to do but would it help me create so i don't have to keep doing it it becomes it becomes an r d tool in and of itself all right thank you brian yeah thanks