Everyone, thanks for joining. Hi, I'm Ashish Sabadra. I cover info services companies at RBC Capital Markets, and I'm excited to host Jigar, CTO of MSCI. MSCI. Sorry, Jigar, thanks for joining. I'll start off with just a strategic overview. I was wondering if you could provide an overview of the technology transformation at MSCI since you've been at MSCI. Well, thank you, Ashish, first of all, for having me here. It's good to see you again. So yes, I'll give you a overview of how technology has evolved over the last several years. So if you think about the vision, it always starts outside in, what do the clients need? What is the business, where is the business headed? But the transformation of the company to get there has to be inside out. So I'll explain the inside-out transformation in four different tiers. So starting with the first one we did four years ago, was our infrastructure modernization. So we have a Hybrid Cloud infrastructure, which is the basic backbone on top of which all of the transformation I'll describe for the company are built on top of. Next was our embracing of the as-a-service model in our strategy that we announced at Investor Day a couple of years ago for Investment Solutions as a Service. The idea of ISaaS was to take all the core services we provide to the investment industry, performance, risk, portfolio construction, indices, all of that stuff. The core IP underneath that, the engines underneath that, the data, the experiences, APIs, all of that to be given to the clients like a service. It helps the clients have a better experience and helps us move faster. So that was the second tier of transformation at MSCI. Third, approximately, there was a one-year gap between each of these four transformations I'm talking about. The third was the launch of MSCI One. So MSCI One realizes the dream of one MSCI that we've been talking about for maybe about a decade. Across asset classes, across product lines, this is more of a client-centric product platform, which actually integrates all of our experiences in one place. It helps clients get a better access to our content. It helps, client coverage in selling and upselling, cross-selling. It helps with servicing, to service the clients and provide product support at a better pace. It also helps with marketing. So there are many elements of, MSCI One, which I'm pretty proud about, and most importantly, it's providing a much better modern client experience end-to-end for all product lines. Now, on top of that, once you have this kind of an integrated platform, we have always been an integrated company, and, through organic and inorganic ways, we have grown, but you need an integrated platform to truly show the vision of that integrated, integrated company. Once we have that, the next layer of transformation that has been going on, that we announced a few weeks ago, around a few months ago, was around Generative AI. Now, in our industry, AI, and probably in every industry, AI has been around for a long time, but the Generative AI is about, you know, the last 12 months, things have heated up with the announcement of new models from OpenAI, then Microsoft and Google and many other companies have been participating in this thing. So we are now focused on that layer of how do we power phenomenal client experiences that create great client value, and in return, create value for our stakeholders. At the same time, how do we use the power of Gen AI to also make the entire company more efficient and our data production, which is the heart of the company? In many ways, data is the lifeblood of the organization. How do we get to scale data from millions of data points to billions of data points at a faster pace through the power of Gen AI? That's great. I think the way you laid those four framework, I think that's really helpful. And what we can do is we can drill down into each one of them. So let's start with the infrastructure layer. On the infrastructure side, you talked about your hybrid cloud strategy. I was wondering if you could drill down further on how that strategy has evolved over the last several years. Yeah. So anything at MSCI starts with the context of the client and the business- Yeah ... even infrastructure, and I'll explain how these things are completely connected. So what are our client needs? Now, some clients want their data in a particular location, like in Japan or in Kingdom of Saudi Arabia or in Singapore, and so on and so forth. Some clients want certain kinds of experiences from us that we are best getting from a platform like Google, and some things we get great from Microsoft. So we have partnerships with Google, with Microsoft, with Snowflake, and we also have our private cloud. Then in terms of our business, the efficiencies we want, the financial governance, the upturn, downturn playbooks we have on a quarter-by-quarter basis to see how things are, how the market is performing in the macroeconomic conditions. Having this flexibility of a hybrid infrastructure helps you migrate workload across public clouds or from public cloud to a private cloud, and also optimize for the kind of workload. So, for example, if you're talking about core engines which create trillions of pricing calculations a year, like risk server, that runs in our private cloud and is very optimized for that, and it's doing great there. On the other hand, for something like MSCI One, we partner with Microsoft to build that platform. We use Power BI and multiple things on Azure to... And the speed at which we launched that was amazing, and this is really fast. And on the other hand, for data acquisition, we use GCP, and it helps us move at a much faster pace in data acquisition. And when it comes to Gen AI, it, you know, these kinds of new capabilities will keep coming in our space, and we don't want to be locked in with only one option. So this is why we have a very hybrid strategy, and it's playing out really well. The extra overhead and complexity we take on in things like security and networking and all the core infrastructure work is there, but it is worth it to provide the client value and the business value of creating great experiences, efficiently, and be able to create value for the company from that. That's great. So you're able to take the best of the breed from both the public cloud providers, but also your on-prem instances, private cloud, and maximize the value. Exactly. A lot of companies have, particularly info services companies, but in general, companies have talked about public cloud rationalization. Looks like you've been pretty strategic about it upfront and balanced that. But I was just wondering if you had some thoughts around the whole public cloud rationalization. How much of the spend goes on public— Like, how much of the compute is on public versus private? Any qualitative color on that front? Yeah. So we don't have some internal principle that this percentage should be on Google, this percentage on Azure, this on private cloud, this should be on Snowflake. We really don't have that. Good. What we have is our North Star is client centricity of experiences- Yes ... and fiscal responsibility for our shareholders, and obviously, creating high-value products at the best possible, with the best possible ROI. So when you put all of that in the blender, it's a complex process. It requires a lot more work, actually, to go through that process than to have a simple strategy that, you know, "We don't believe in the cloud, we're gonna do everything ourselves," or, "Cloud is great, let's put everything in the cloud," or, "We have a partnership with one company, so we're gonna put everything there." Those things are easier to do, but they don't provide the best mix of what we can do for the clients and how we can grow the business better, and also have great eye on the costs associated with all of these things. That's great. And then, oh, you mentioned how MSCI One runs on the Azure platform, where you're able to leverage some of the capabilities like Power BI. You also talked about MSCI One briefly. I was wondering if you can just talk more in detail about what exactly is MSCI One, provide a quick overview. Also, drill down into some of the modules, including the Climate Lab Enterprise or any other modules which have- Sure ... really resonated with customers. Sure. So MSCI has always had the vision of an integrated company through organic and inorganic growth both. And in order to have an integrated company which has... You have to have a great platform. An integrated platform which can provide you opportunities for network effects, for possibilities for upsell and cross-sell, possibilities to create great client experiences across all asset classes, across all product lines we have. That is what MSCI One does for us. It also ends up providing fantastic client experiences, because now you have one place to go if you want to analyze, if you want to use Climate Lab Enterprise or Climate Lab, Company. If you want to get insights, we launched this product, as a fabric called Insights, which is about performance insights, risk insights, index insights. All of those things are now integrated. It doesn't matter whether you need these insights for public assets or private assets. The technology stack is the same. So MSCI One provides that kind of client experience, and the speed at which we are launching the products on top of MSCI One is much higher than ever before. Because you know, think about five years ago, we would have dozens of applications, dozens of distribution mechanisms. Now, mind you, we still want to maintain optionality of distribution mechanisms because it is completely going back to client centricity. If clients want our data through Bloomberg or FactSet or Snowflake or Crux, no problem. It's always going through those channels. But if they want to see a holistic view of all the services they use from MSCI, MSCI One is a great place to do that. The other thing about MSCI One, so the usage has been steadily going up. The whole company is watching this thing very carefully, very closely, and, there is live telemetry coming in, which is of value to everybody in the company. So researchers are looking at what kind of things our clients are doing with this. The marketing folks are looking at the... We have digital marketeers in the company now who are looking at the telemetry data coming in to help us reconfigure MSCI One to, for, per company, to make it... Help us upsell things or cross-sell things, promote new products, and so on and so forth. Client coverage and client servicing is closely watching MSCI One data, and there's a data warehouse behind the scenes which collects all the information of the usage, which tells you maybe there's a prediction for a cancellation coming up, maybe there is an upsell opportunity. Servicing elements of lot more opportunities for self-service because you have one integrated platform that we can add a lot more services to. Search box, more gen AI, Ask MSCI, all of those things. So now we have one place to go to. So this realizes the dream of one MSCI. That's great. And so, as you mentioned, like, the huge opportunity here is ability to upsell, cross-sell, but also, how do we think about from a new win perspective? Is that the fact that this is not all, now all SaaS-based versus maybe prior instances on-prem, how does that help you from a- That's a great question, Ashu. So, the time for deployment gets cut down. Mm-hmm. What used to take months can be done in weeks. What used to take a year can be done in a month or two. So that's one key element of why we're able to move faster. And, in terms of, what's the first part of the question was? Yeah. No, I think it was the new win, and that was where I was getting to, is how quickly have you been able to deploy the products, and what does it take for client onboarding? Yeah, so the client onboarding was actually one win. The other point I was forgetting about was the sales enablement. Yeah. So we have a large sales team, right? And it is... In the past, you would say, like, you know, you're, you're selling ESG in this segment, or, or climate content in that segment. You're in insurance space, you're in that space. What happens when you give access to MSCI One to entire client coverage folks, and we have been training the entire, sales organization on this thing, you get to see the full picture of what MSCI has. So when you go to clients and they ask you about something else, you don't have to create another meeting for that. You just go to that section of MSCI One. You can go to Data Explorer, which is in MSCI One, which you can start searching for that data to see if we have that data. You can go to the Developer Community, which has 500 APIs and use cases around that.... and it's much more easier to explain to the clients the value of various parts of the company, which is all integrated in one place. So it's also a fantastic sales enablement tool, as much as it is a value to the client, for the client experience itself. That's great. Another point that you mentioned is it's accelerating your pace of new product development because now you have a consistent application framework, if I've understood that correctly. That's right. I was wondering if you could talk about anecdotally how it's driven faster new product innovation. Well, that's no, so I'll tell you, so let's take this example, right? So when we announced Investment Solutions as a Service, in, I believe it was March 2021, we announced 4 services. We took our indexes. The first indexes were produced in 1969 when we put the foot on the moon. That's how old these indexes are and how long a legacy we have in this space. And we opened up the index engine so our clients can do institutional indexes and customize it, and see the stress test and the results. And if they like what they're seeing, they can come to us for asking us to put into production. The other service was Climate Lab, and it gives you detailed information about climate data underneath a company, compare it with other companies, and see how they're trending towards net zero, and so on, so forth. The other two services were more horizontal in nature, was the Data Explorer, to explore all the content MSCI has, as well as the Developer Community for access for developers and researchers to get access to all of our APIs and SDKs, and so on, so forth. Now, since then, if you look at the last 12 months, we have over a dozen services announced in the last 12 months because the pace of innovation is much faster. You know, the infrastructure of getting data and instead of flat files or on top of flat files, putting it on Snowflake, and instead of sending PDFs or emails, but along with that, also having Power BI on top of it, interactive dashboards, that infrastructure is ready. So once you do those insights for risk and performance on the portfolio, you know, creating the same thing for indexes or for climate data or for sustainability, and so on, so forth, it's not that much of a challenge. So the speed of innovation has gone up dramatically in the company with these examples that I just shared. That's great. And maybe if I can add one more. So, MSCI recently acquired Burgiss. Prior to that, they had acquired RCA, so your presence in the private market has expanded significantly. As you mentioned, what you're doing is making it holistic across public and private markets. I was wondering if you had any thoughts on how you're bringing all these different assets together, even the recent acquisition, if anything you can share on that front. Yeah, I mean, directionally, I'll share. It's straightforward in terms of one-two big parts. So one is the data. Yes. How do we look at data holistically, and what are the usages with all the, you know, rights in place? Yes ... and all that, obviously? How can we leverage this data for creating products which could be more product, cross-product? And in terms of experiences, you know, Burgiss, RCA come with their own platform. Yeah. They also have to be evolved. But the pace of evolution of those things on MSCI One will be faster again. Yes ... because, you know, so slowly and steadily, a lot of the things across all of these inorganic and organic acquisitions will be migrated towards MSCI One. But we don't have a strategy to just migrate everything over for the sake of technology migration. It is going to be, again, going back to the client need and what are the next set of things clients are asking for? So anything new starts obviously getting built on MSCI One. If there's synergies between something climate and something real estate, we start doing this in a more unified manner. And then, at the right time, we start doing the migration so we can justify why are we doing this thing in the first place. There has to be ROI for any of these kinds of projects we take on. Got you. But we do have a North Star for the company ten years out, where we want to see all of these things. We just don't start rewriting all the code and migrating all the data to get there, but everything new we do is in the guidance of that blueprint we have for the next ten years. That's great. You also mentioned how you're incorporating GenAI into the MSCI One platform. I was wondering just if you could talk about the GenAI strategy. How do you perceive that longer term, and what have you done, what steps have you taken more recently? Yeah, as everybody is talking about, right, it's a very exciting time. You know, I've been in software industry for maybe 30 years, but what has happened in the last 12 months, it kind of accelerates the pace of change in the world. Maybe even more so than when the web came up or when mobile revolution happened, and so on, so forth. So it's, as a developer, it's an exciting time for anybody to be in this space. Now, what are we - what is our strategy there? It again goes back to what are we, what are we doing for the clients and for our business? And then work backward from there in terms of the technology choices we make, the product investments we make, and there's a little bit of that is outside in, and a little bit of that is also bottoms up, tinkering with, experimenting with, doing proof of concepts of all the new technologies, to also inform what is out of the possible. You cannot just go in one direction. You have to start from both ends. So I'll give you some examples of what we're doing. So two examples are given, data production and data qualities. And then I'll talk about how we make the entire company more productive. Every different job function, what can GenAI do for each one of us? And then we will talk about one of my favorite topics, the client experience. The investment industry hasn't seen a bigger change in how investment process gets handled since the computers were becoming ubiquitous, right? So, and then, you know, Excel and this and that came along. So the investment industry is about to go through a pretty big change, and we are going to be at the bleeding edge of that. So what are these client experiences in the core heart of investments? I'll speak briefly about that as well. So in terms of data production and data quality, we are seeing significant gains in our speed and performance, partly with our partnership with Google- Yeah and the Google data acquisition platform we have built. So we are able to acquire data at a much faster pace for things like ESG and climate. That helps us scale faster. In terms of data quality, you can think about, look, we have 300,000 indices, but, you know, this number will be exploding over the next several years as we start getting into more heavily into custom indices. So the quality checks for a custom index, rebalancing every at every period, it becomes very hard. So those kinds of data quality checks are getting faster to implement. So our three areas where we are scaling the company from technology and data perspective, scaling data from millions to billions of data points, scaling portfolios from hundreds of thousands to millions. By portfolio, I include client portfolios and indices, and then scaling experiences. How do we create modern experiences? So we already showed with MSCI One how we are scaling to new kinds of experiences, but with Gen AI, it takes it to another whole other level, with conversational discussions and so on and so forth. Now, I'll briefly touch on the efficiency part, and then I'll talk about client experiences. Now, every function at MSCI is going to see some benefits. If you think about developers and researchers, Copilot helps you write code faster, detect issues in the code, or find bugs and write test cases, and so on, so forth. So we have done a lot of experimentation, and it's showing us a lot of value. But think about a coverage person, salesperson, services person, marketer. Think about folks in accounting and run rate checks and, financial operations. Basically, operations of all kinds across MSCI. Every function has operations layer underneath them, and that operations layer we were in the process of driving operational excellence for, for last several years, and that got a shot in the arm through the power of AI, specifically generative AI. So I think it'll make... And I can get a lot more examples, but we, we won't right now, given the time constraints. But every job function will be seeing new ways of doing their job faster, better, with, with more pleasure probably even, and become more productive. And last but not the least is the exciting space of the client experiences. So going back to the first principles of what do we do for the industry? We help the industry create great portfolios, and these portfolios have $trillions of assets in them, and find performance and risk in these portfolios, and then look at all the data you need to make these three basic things happen. You need climate data, ESG data. You want, you want indexes, you want different products that you hear from the, all the product lines we have. So in that space, the very complicated task of looking at what is your value at risk if you have a portfolio with one million instruments in them and $hundreds of billions of investments in them, or $trillions? And, and there are market events happening every day. News articles are coming out. Now, how do you take all of that fresh data, you take all the, the portfolio information, and then the proprietary models that MSCI is known for, decades and decades of research in risk models and performance models and pricing and all of that? If we can put it all together to give a very simple answer to our clients in the investment insights, to say, "Look," a chief risk officer wakes up and, she sees, "Here are the 10 things you should be watching out for." As opposed to an army of data scientists, an army of, Python engineers putting this together, and it takes days and weeks. We could be cutting that short time pretty short. So that's an example of what we are right now prototyping, talking to clients, doing client consultations, and so on so forth. Another example of this, on the same topic, is what we are internally affectionately calling Ask MSCI, which is basically, if you go to MSCI One, there's a search box, which has been there for a while, and now we are adding next to it this Ask MSCI, which is conversational service, which is getting better and better, over time, which helps you ask investment questions. We are in the process of doing a hackathon soon with Google on discussing how can we build a climate-related model, how can we create an investment-related model that can give even more precise answers? And, so with generative AI, our strategy is to pick and choose the provider, so we have OpenAI and Microsoft partnership, we have Google and their models. But based on the use case, we look at which one is more accurate, which one has better experience, which one has better price point, and which one is faster. And depending on the use case, a support use case is very different than as Chief Risk Officer looking at a report. So depending on the use case, we put in all these parameters and decide which service do we use. So on our infrastructure, we've built this shared AI platform that hundreds of developers for various different... They're working on various different parts, can pick and choose the AI models they need to fulfill their end client need. That's great. So you've essentially kind of abstracted the large language models for developers and, making it easy for them to choose, pick and choose. Right. That's great. And so one of the things you also mentioned, right, like when a risk officer is looking at the parameters are very different. One of the concerns with LLM is the hallucination or not being able to reference back to the source. How are you solving for those? Yeah. So there are dials that you can use, right? So if you are doing something creative, you can use a very liberal dial for that. And when you're doing something for a $100 billion portfolio, where you don't want any creativity, you want precise answer- Yeah ... you dial it towards the more conservative side... and also the other thing about, attribution of where the content came from, we are definitely looking to those RAG approaches to say, "Look at, here are the documents this data was coming from." So none of that will say, "Hey, we don't know anything about this. ChatGPT made that up, so you figure out if it's right or wrong. Yeah. Obviously, that doesn't work in an enterprise use case. Yeah ... in a serious industry like ours. Yes. This is not in the process of building toys for kids or something, right? That's right. So for that, we are going to have a very conservative approach. This is why we are doing such thorough testing of these products and client consultations. We're not jumping into just putting some products out there- Yeah ... without very thorough testing. That said, internally, for client support, for internal efficiency, we are liberally using a lot of these tools that I just described. That's great. That's great. And maybe if I can ask one more question on gen AI. I think, as you mentioned, MSCI fund has been very helpful with the whole cross-sell opportunity. How do you think about gen AI helping bring all these different disparate data assets together and generating insight? How does that also... How do you think about that discovery process and improving the discovery process? I was just wondering if you have any thoughts as we think about over the mid to long term. No, that's a really good question, Ashish, and we talk to a lot of data vendors. And I think this idea, and with certainly these discussions about how do we use gen AI and AI in general to discover more data sets. And it is a constant process. We have a large technology team on data, data technology team and data operations team. They're always doing these kinds of hackathons to try out various different things. That's great. That, that's very helpful. A question that we've been asking a lot of companies presenting at the conference is, if you take your management hat off for a second, what's a Gen AI use case that you think no one is talking about? You know, it's interesting because everybody's talking about Gen AI. Yeah. I'm sure somebody amongst the 7 billion people are talking about something. But in fact, I asked ChatGPT this question- Okay ... because I think it's a little smarter than me in answering these kinds of questions. The answer that came up was, creativity augmentation, and it's not like nobody's talking about it, but it's not really invested a thoroughly investigated area. And what that means is, it's not just the tool to create a new image or a new video, which is out there. But if you're working on a creative project as a team, how do you bring diverse perspectives into the conversation? And how can an AI bot right next to you, or any technology like that, can help you with augmenting your creative thought process? I thought that was pretty intriguing, so I, I thought I'll toss it out there for you to consider. No, that's great. That's absolutely right. I think the intelligence augmenting whatever you're getting is, I think that's where the differentiation could be. In terms of biggest decision, what's the biggest decision that you think you or the rest of the management team would have to make over the next three years? So next three years, it's interesting. Last weekend, actually, I started writing this paper to discuss internally about what's our midterm strategy, and I said, "Why? Why would we talk about midterm strategy," right? People talk about short-term tactics and long-term objectives. Here's my rationale: We have very audacious goals for the company for the next 10 years, and we are very ambitious to go run after that. We are very clear. Quarter after quarter, you folks are the judge for that, but we do a pretty good job. Yeah. Our finance organization and sales, everything runs like a like... It's like clockwork. But what about the midterm, between 1 year to 3 years? We have all these acquisitions coming in, and organic growth with all the new products getting created. So my time is obsessively focused on making sure we don't sacrifice the long term for the short term, and we create this strong game plan. At the same time, we don't mess up on the short term by investing heavily on something which doesn't have the right payoffs. So how do we delicately balance the capital allocation over the next 3 years by not just looking at the numbers, but also looking at the holistic version of an integrated company and client experience? That balancing act is the toughest part, and that we are all obsessed about. That's great. Maybe in closing, what is one thing that you are most excited about for MSCI? I think if you ask me about one thing, like, everything is changing around us. Yeah ... the technology, the investment industry, macroeconomic conditions. The thing that makes me most confident that we will succeed and thrive is our people and our culture, right? We have the culture to keep evolving. We are a good-sized company with a strong brand, stability, and trust our clients have put in us. At the same time, we have the DNA to act like a startup and move really fast, and if you look at the evolution over the last five years, technology has demonstrated that we can move really fast, which is the most important ingredient, to have that culture and the set of people who can do that. So we are ready for anything that comes up next after Gen AI. That's great. That's fantastic. Thanks again. Thank you, Jigar. Thanks, everyone, for joining.