MSCI Inc. (MSCI) Earnings Call Transcript & Summary

Good morning, everyone. Hi, I'm Ashish Sabadra, and thanks for joining us. We are excited to host Jigar Thakkar, the CTO of MSCI, with us today.

Jigar, you joined MSCI in 2018, nearly after 20 years at Microsoft. How do you see the investment landscape and the client needs evolve since then?

Thank you, Ashish. Thank you for having me here, and thank you to all the investors who have joined to hear our story of reimagining MSCI. 2018 is when I joined here, moved from West Coast to East Coast, moved to New York City. Has been a pretty big transition. And as I reflect back on those years, I mean, you think about the industry landscape that has changed, or the world landscape that has changed, right? We have gone through a pandemic, we have part that's still going through it. Wars are happening. Socioeconomic revolutions have gone on across the several years of -- for various different reasons that popped up around the globe. The climate agenda has become extremely prevalent across the world, which has had big implications to the investment industry. And along the way, the amount of data has just exploded by probably orders of magnitude for the investors. So that is the kind of complexity our clients are living with. They are also -- there is a strong need for transparency. We talked about climate as an example. They really, the investors want to get a lot more transparency into things like ESG Ratings and climate details, the companies' disclosures on climate and so on and so forth. There's a lot of need for personalization and customization. We build some of the world's best indexes, as you know. But there is a lot of need for personalization and customization based on values for wealth and other reasons, right? So those are the areas where the complexity, the scale is increasing in a big way for the clients. There are margin pressures and efficiencies -- efficiently needs to deal with. So I would say, in general, the world for our clients have gotten a lot more complex, and there's a strong need for them to scale, and that is where we come in to help.

That's very, very helpful color, Jigar. And so how is -- like as you talked about how the landscape is changing, but how is MSCI responding to the clients' need in this changing landscape? And in particular, what is MSCI's ISaaS, or Investment Solutions as a Service, strategy all about? And if you could also highlight what are the key services within those?

Sure, sure. So I talked about -- I spoke about -- I'll speak about ISaaS, Investment Solutions as a Service. And before that, I'll mention something about the scale challenges our clients are having, right? So if you think about the 3 areas technology is helping MSCI scale and to help scale client needs are around -- starting with data. We have a huge amount of data we ingest, and that data is going to scale from, in some areas, of 100x to 1,000x over the next few years. So we'll talk about that when we talk about a data acquisition strategy later in the talk. Then you think about scaling the portfolios themselves, the whole -- the idea of all the investments, $100 trillion of public assets alone, and about the same amount in the private assets. So the portfolios, the indices, those have to scale from a few hundred thousand indices we create today to millions of indices when we get into personalization. And the third area that we are focusing very heavily on is scaling the client experience. So it's about scaling the experience that -- of the products clients see, and we'll talk about many different services we have launched on ISaaS, including MSCI ONE and so on and so forth. But it's also the client experience doing business with us, right? So how do we do the sales and servicing and how to do contracting and how do we do invoicing all the things included. So we are reimagining the entire client experience plans have with MSCI. Now going to ISaaS. We announced the Investment Solution as a Service around a couple of years ago, and we launched 4 services with it. But since then, we have launched around a dozen services, and all of it has come together with MSCI ONE. Now the idea is about on an open architecture, and MSCI has always been open architecture since a few -- a couple of decades, at least. And the Investment Solutions as a Service, imagine the cloud architecture, right? First came the platform or infrastructure service, then platform as a service and software as a service. And the idea was -- for the cloud was to let the various industries outsource or give away the plumbing work for managing your compute and storage and networking gear so you can focus on your day job, or finding alpha in our case, for our industry, right? Similarly, for our clients, the amount of complexity they're dealing with has exploded over the few years. So the idea of ISaaS, Investment Solutions as a Service, is to help them say, "Look, these are the things that MSCI can help you with so you can focus on finding alpha for your clients, finding efficiencies for your clients." And when we announced Investment Solutions as a Service, we announced 4 products, 4 services, were the Climate Lab, the Index Builder, the Developer Community and the Data Explorer. And the idea behind all 4 of them was opening up our engines. So to give you an example, right? In 1969, when the moon landing happened with Neil Armstrong, that is the time when our first set of indexes were launched. The first index from Capital International was launched back then. So now with Index Builder, we give you a capability to customize index, do stress testing and so on and so forth. Similarly for ESG and climate, the product we have launched with the ISaaS announcement was about showing you complete transparency of all the data points underneath the issue rating on climate and so on and so forth. With the Data Explorer, we exposed all of our data. And so for clients who are licensed, or not licensed it yet, they can browse all of our content in one place. You can see sample data sets. And on the delivery community, similarly, we expose our hundreds of APIs, all out there with documentation. And for all these things, you don't even need -- you need a license to use it, obviously, but for exploring what APIs we have, what data sets we have, you can just go and take a look at it yourself. So that was, in a nutshell, the broader announcement of Investment Solution as a Service, and we announced that in 2021. And in the last 2 years since that, I'm really proud to say that we have launched around a dozen services. And to bring it all home together, the idea of Investment Solutions as a Service makes as a strategy is now resulting in MSCI ONE as a product, which is an association of that strategy. You see all of that coming together. And now we know that this is not just a long-term strategy, it's actually an application platform, content platform for premium content experiences all in one place. And that's what you see in MSCI ONE.

Jigar, that's great. So you mentioned MSCI ONE a couple of times here, and thanks for providing that overview of what MSCI ONE is. But I was wondering if you could give us a glimpse of the products, like give us a quick demo and what the key capabilities are.

Happy to do that, Ashish. Thank you so much for asking. So yes, this -- hope you can see my screen. This is MSCI ONE. And we started going a little prototype with a couple of developers, a designer, a program manager with a very small team 2 years ago. And the idea was testing out -- I started testing out all the applications we have in the company, and we wanted to reimagine the experience for our clients. And when I say applications, it's about all of our content, right, whether it's the factor models or there's risk models and so on and so forth, our indices, all of that content is delivered through some channel. Now the idea was to think about our contribution to the investment industry from the very first principle. So what do we do for -- there's a very complex workflow system in the industry, front to back. And what portions of the workflow does MSCI contribute to? We completely reimagined our role about how do we present that in a new interface? So that's when MSCI came out of that discussion. So what you see here on the home screen, you can highlight what is new. So when clients log in, you get to see that we might have launched Climate Lab Experience or MSCI Insights that we announced a few months ago. And on the left side, the left navigation bar, you see all the key services that MSCI provides. So starting with insights, and I'll do every one of them, but I'll give you a quick overview of what all we have on MSCI ONE, then we'll flip through various areas of the product. So MSCI insights, it's about -- going through the complexity of our investment managers and owners deal with and providing them key insights. So the idea is you have millions of data points around performance and risk, climate, ESG, fundamental data for all your assets, whether it's a building, it's -- or it's an equity or an index. And we want to provide you with the risk insights, performance insights, climate insights, ESG insights across all these spaces. So that's what insights section is all about. On the design section, you will see how you can build. You eventually will start seeing how do you create a portfolio or how do you create a -- customize an index, a client-designed indices in the case of Index Builder, how can you see your models and how to use those models in your world. And the Developer Community and Data Explorer that I talked about. So let me show you some examples. So here, you see this morning, I created a custom index using Index Builder. And essentially, I took the MSCI USA 100 Index and actually removed 13 sectors to see how would that index perform. And you can see that, in this particular example, the -- what has stressed test for several years, the customized index has better performance and it has better ESG characteristics and so on and so forth, and it may not have. So the idea here is instead of having 1 or 2 or 3 great ideas and try to do a hypothesis on that, we want to enable rapid prototyping for our clients so they are able to see their dozens of ideas or hundreds of ideas and put them into motion to see which will perform better. So you don't really have to think too hard about which hypothesis works. If you can experiment at a fast pace, you should be able to have several ideas that you can run through within a week or a month. Now if you think about these kinds of indices, you could have -- the clients would have dozens or hundreds of these industries. We create close to 300,000 indices, produce them every single day. Now here's a list of indices. And let's say you want to see the metrics. So you -- then you start drilling in. So this page gives you a quick overview of all your key metrics. Then you could drill into performance, ESG and climate characteristics, for example. Now this whole platform is built very quickly because we -- what we have done is pull the data out of the hardcore brains of MSCI, which is Risk Server, for example, the common platform underneath Barra systems. All of those data points, we bring it out, we put it into Snowflake and we put an analytics tool like Power BI on top of it. There are many -- those clients can use Looker or Power BI or Tableau and so on and so forth. And we are able to generate these insights at a very fast pace because we are focusing on what we are good at, which is producing these insights and not worrying about how to do charting and modeling for all these things. Here is an example of the performance chart for this particular customer that we just created. If you compare it with the [ SAL ] factors and compare with the benchmark and so on and so forth. Here, you see the risk summary and then what is the value at risk and -- for your portfolio? Or for example, in the middle part on the bottom side, you see the stress test results. What would happen with the financial crisis that happened? And what -- how would this portfolio behave in that model? What happened during COVID? So these are -- if you have these kinds of stress you want to put on your portfolio, it tells you how your portfolio would have reacted in these kinds of situations, and that helps you manage your risks. Getting into more of performance insights. Here is an example of equity factor performance that tells you what are your top factors? And how does your portfolio perform over time. What are the bottom factors and top factors? And which are the biggest contributors to your performance? And so on and so forth. And that's another example of the factor attribution, to see clearly what -- how much of your investment return is coming from your strategies versus it's coming from other explainable factors. Moving on, I'll show you the examples of our climate products that we announced and launched over the last couple of years. Now here is the climate company product, which gives you here an example of Apple, right? It shows you it's aligned with 1.3 degrees centigrade, it's 1.5 degrees aligned. And it helps you manage your in-house emissions and look at the targets, net zero goals these companies have. And you can look at, in the case of Apple, in which areas do they have sufficient disclosures? Which area they don't have disclosures? You can drill in, for example. And if you have -- it will provide you with details of Scope 1, Scope 2 and Scope 3 emissions for this company. Similarly, you look at Starbucks. And here, you see it's aligned towards 2 degrees centigrade change. And you may want to compare this, our clients want to compare. Clients could be investors or they could be corporates themselves, and they want to compare a company with their competitors. And before that, I'll show you the overview what the report looks like, right? So this is their ESG report and various different factors around environment, social and governance. So here, you provide a lot more details. So just the rating is not enough for the investors or the corporates, they want to look into the details. Sometimes, they want to see that so that they can improve the ratings. Or sometimes, investors want to look at this ingredient data to come up with their own portfolio strategies to see, maybe it's not just the rating I care about, it's about the underlying constituents of the rating, around 4,000 data points in the rating. They want to use those data points to help construct a portfolio they want, or portfolio strategy. And here is how you can compare a company with its competitors, and across all vectors of environment, social and governance. So this provides you with just a taste of how many different ways you can actually get more transparency data that our clients really need. Now by the way, you are looking at the product right now, these are the -- open architecture means that you can take our applications or just take our APIs or even directly get the data. So if you're a quant audience or a developer, you don't need to ever use these applications. You can go to use Python, use our APIs and get access to all of our data in a place you want. Here's a quick overview of our reports. So we create thousands and thousands, millions of reports every quarter for our clients for various different needs. And they're all now placed -- they're all in one place now. So here, you can go and get access to your index reports and ESG reports. Here is an example of index metrics. This is a 14-page document for a particular index. Or you can look at the ESG company reports. Freeport is an example here. You can get their ratings report, our controversies report and so on and so forth. So we're also working on the search experience, where you can actually just search through what you're looking for from our entire ecosystem of our content across all product lines. So whether you're searching for an index, a controversy report or you're looking for factors for a particular portfolio, you can just search through all of that content, and it comes to you in one unified experience. So here's an example of 114-page report that you can go through. Again, there are portfolio managers who want to look at these PDFs or a dashboard. They want to look at the whole rating report. Or the same data is available through APIs and through our data distribution as well. And we'll talk about the data distribution strategy as well. So this is more details about how we democratize our data. We want our clients to be able to see all of our data in one place. And whether they have licensed this content or not, they should be able to go and search for all the content we have available for them to try out. And many times, over the -- a few years ago, we would be getting thousands of calls a year on -- or thousands of calls a month sometimes, on data queries. Do you have this kind of data? Or do you have those data sets on ESG, climate or not? We don't have those queries at that point -- at this point anymore. We can just point our clients to the Data Explorer, and they can themselves search for any data they want. So here is an example of ESG Rating. Search for ESG, and ESG Ratings product shows up. But that's a whole big product, and it's -- we provide you with the product overview, you go to data sets, you see dozens of data sets. And we can download a few rows of data sets without having to license anything. So it gives you an opportunity to see whether this data set is valuable for your investment needs or not. And if you feel like this is something, is -- you would like to use in your investments, then you can request a license and we will follow up with you and enable that to happen in one place. Very similarly to exposing all of our data. Here is our Developer Community, and this is going to evolve very quickly in -- at the moment, you see all of our APIs. So developers can come and look at our 500-plus APIs we have across all our product lines and open up one of them and see the details, what are the things provided in ESG, data APIs. You can get ratings, you can get carbon and fossil fuel, you can get sustainable impact solutions. So this is an example of -- if you want to use Climate Lab, you can do that. You want to use our ESG Ratings report, you can see the report and read it. Or you can use our APIs and extract all the data you want so that you can actually blend that with your data you collect and create portfolio strategies based on that or use it in any which way you want. So here's an example of developers and quant audience can actually look at the APIs, interested APIs, and look at the return value you get. So it helps you get started without -- so all the documentation you need on how to get going on MSCI using APIs for developers is right all in one place. And we also have a lot of code samples we provide, so you can get started, get going very quickly. So next step, I want to share a little bit about the factor models that we announced a few weeks ago, where they're available for -- on Snowflake. This was an often-asked need from clients. They wanted to take our models and share it out on Snowflake or any other model. So we have data distribution model where we can share models wherever our clients want them. In this example, I will show you the Snowflake integration. You see this U.S. equity factor models. And with one click, the single sign-on, you can get into Snowflake. And then suddenly, you have the full power of Snowflake, where you can open up a database, you can create like a SQL-like query. And you can do joints, you can actually export this data back into your Snowflake warehouse from ours and get pretty easy access to all the data. So this is the entire flow I want to show you about how are we completely reimagining the client experience. To start with -- you can start with the MSCI ONE and go into various different applications, or you can get to all the APIs directly, or you can even jump into Snowflake to get access to the data we have shared out with you. So this is why we believe in a completely open architecture. We really don't believe in a locked-up system because our client needs are extremely complex, they have their own very unique workflows, and we want them to be able to plug in MSCI where they need it as opposed to have to redefine their architecture to fit with MSCI's strategy. So that was -- in summary, this is a full view of MSCI ONE. I hope you get the picture of how all of MSCI is coming to one place. It actually helps you view all of our offerings in a unified experience, get access to all of our data, content, APIs. And actually, imagine how it also would make it easier for us to sell the product and service the product when every client coverage person, every servicing person, salesperson in the organization, has access to pretty much the whole real estate of our suite of content and APIs and data in one place. So the whole company is now getting ramped up and getting trained on MSCI ONE so we will all be proficient in doing the demo, turning it to the clients. And you don't have to be -- you can be a specialist in one area as a salesperson or a researcher or a developer of the company, but the barrier to checking out other areas is completely gone. The idea that we are floating in the company is that we want to be able to dogfood, this is a very standard software term, that you try out everything yourself before you give something to the clients. Investment world is a complex world, the products and the contents are very complex, but that does not mean that the platform that delivers all this content needs to be complex. That has to be extremely easy to use. So we have really designed MSCI ONE with ease of use in mind. We really want our clients to see this reimagined MSCI, reimagined MSCI experience. And we really want our clients to love every experience they have with MSCI, whether it's with data directly with the content, the APIs, or the applications that we are building, to actually the search and the notifications and more proactive services. And we want this platform to help the investors, our clients, see that we are providing more premium content experiences than what they were used to before. So over the last few years, as we built up our infrastructure strategy, we focused a lot on culture and recruiting talent, dozens and dozens of engineers from the technology in the data world, and creating these shared practices around design, around experience. We took the company from -- more from a product-centric view to more of a client-centric view, where we still have product lines, we still have product line reporting to the financial summaries every quarter, but the client experience is horizontal, it cuts across all product lines. And MSCI ONE is our way to show you that this -- everything is coming together, and this is very much built with clients in mind and client centricity outside-in. And then we start pulling in APIs, the data from across the different product lines. It has been a lot of work over those earlier years laying this foundation of infrastructure, the engineering organization, design, program management. And -- but all has come together now. And what you see, Ashish, if you've watched the trajectory of our services over the last -- since 2018, the speed of innovation has dramatically increased. The cost of the next feature to add, the cost of the next content distribution, the cost of the next insight or the API to be treated is incrementally a lot lower now than it was 4 years ago when we did not have this common platform that every product team could use. So I hope that gives you a good overview of what MSCI ONE is all about.

Thanks, Jigar. This was very exciting to see this product. And it seems like the entire force, right, all the key offerings of MSCI truly come together. It's also -- I think it's a huge reflection on your technology organization, where we think, across the board, we've seen technology organization being shifted from being more of a cost center to a revenue generation. And I think this is -- this seems like a great example of that. We did -- we do have one question from an investor, and I think you might have addressed a part of it. But I would -- the question is -- or the first, the comment is love the demo. And then the question is, who are the earliest users of Index Builder? Is it existing customers? Are the products skewed to newer customer types like wealth manager, insurance, et cetera?

That's a very good question, and thank you for the compliments. I'm sure my -- the technology team, the product team will be very happy to hear that. We have taken a lot of pride in building this new experience. Regarding Index Builder, I think it's a little bit of both. And if you think about the earlier point I made about customization, right, and personalization. So it is both institutional investors who need their own custom indices, which has been in that business for a while now. As well as when you think about the wealth segment, that's also an area where we're looking at because there are slightly different needs there. So I would say the usage is -- and the interest has been from both sides. Now the area we are looking at scaling. There's a lot of work to be done to scale -- to go from thousands of indices to millions of indices someday. And to some extent, we have 2 opposite ends of the spectrum we are working on with what you see is Index Builder now. On the one end, you have the lot more sophistication, a lot more complexity needed. So there are quants who want to work with our research organization to focus on some custom methodology and have a very complicated and sophisticated customization need. And for that, you will need STKs, Python, Jupyter Notebooks. Your STK comes with all the data of the APIs, and our researchers can help you with the changes in the methodology you want to create. So that's one end of the spectrum. The other end of the spectrum, you can imagine, the wealth space is something a lot simpler, where your client comes and says, "Based on my personal values, I don't want to invest in this part of the industries or this part of the world." Or, "I want to" -- you have different values where you stand related to climate or fossil fuel products and so on and so forth, either way. And we provide you with those -- we need to provide a way to make those things a lot more simple and a lot more intuitive from an experience -- user experience perspective. So there are 2 different ends of the spectrum that we are working on scaling towards both ends. And you see Index Builder somewhere in the middle at that point.

That's great, Jigar. And as you said, right, the intuitive UI makes it easy for even the most sophisticated users to use it, well, as well as more, as you said, even naive users as well. We'll continue to take questions from investors. So investors, if you have any questions, feel free to add those. But in the meantime, in the interest of time, switching gears and talking about your cloud strategy. So you obviously talked about Snowflake during the demo. You have signed partnership with both Microsoft Azure as well as Google GCP. The Google GCP was the recent one. You also have your on-prem -- your own data centers. So can you just talk about how do you expect -- or how do you anticipate your cloud strategy to evolve, particularly the hybrid multi-cloud strategy?

Great. Great, Ashish. And I think it's -- the infrastructure strategy is extremely crucial for any industry, and especially -- and with the kind of complexity we deal with. So I'll start out by saying that what do you optimize for, right? We optimize for the client experience. And that includes multiple things, whether they want our data to be in a particular country, we got to work on that. If they want us to deliver things at a fast pace, so the speed of innovation is a factor. Location, data locality is a factor. Fiscal responsibility is an important factor, too, that you want to make sure that you -- what you're spending on the cloud or in our own data centers or through distribution like Snowflake, that there is good ROI for the firm because we want to be helping our clients with keeping costs under control, right? So think about speed of innovation, costs and fiscal responsibility. And the choice of different technology is also very critical. And this is -- the strategy we have has evolved over time, and it will continuously evolve. What I will tell you today may be different from what we will see in the next 3 to 4 years. And I'll give you some rationale behind the way we are, the status quo of where we are right now. So we look at -- we did a partnership with Microsoft in 2021. It is a pretty broad partnership. We use Azure for are serving needs, all of ISaaS and MSCI ONE, ESG works on Azure. We have a deep partnership with them for the Power platform, for Microsoft Teams, all of those things. And that has done really well for us, and it's been great. Now you think about the offline need for data collection. I was talking to you about the scaling of data elements. In some areas, we are scaling our data needs from 10x to 100x to even 1,000x. Think about the spatial data we need, right? The spatial data that we need in the context of climate, in climate assets and private company -- infrastructure of buildings and so on and so forth. So in those areas, we did this strategic alliance with Google for using their data pipeline. So we did a lot of proof of concepts with Google, and we really liked the way they have neatly integrated AI, ML, NLP, all of that with the big query and Vertex AI and all of those technologies, Talkia and so on and so forth. So the data acquisition platform has been reimagined for us to scale 100x, or 1,000x and up. And for that, we feel like we have a very good mix of partnership now with Microsoft for ISaaS and Power BI and all of those things. But with Google for the data acquisition and to learn from someone who has built the data products at scale like Maps or YouTube or Search and Ads and so on and so forth. So that is our current strategy with Microsoft and Google. And snowflake has a very important role to play because it's simple. Our clients want -- some of our content are -- slowly and steadily, every product lines content is being requested. You'll see a lot more content going through Snowflake. And for us, we really don't debate client needs, we will really just meet them, right? They want us to put the data in Snowflake, then that's where we put our content for setting it up. So that's why it's a multipart -- it's a pretty complex hybrid strategy, and it creates a lot of -- the engineering and technology complexity goes up a lot. Security, networking, shared services. You have to learn how to manage your data centers. We have data centers in [ Geneva ] and Nevada. You have to manage those data centers. You have to learn to run on Google platform, you learn how to run on the Azure platform. And then you need to have secure access across all of these platforms and our own data centers. And you need to be able to have data access and API access across all of these things. But that complexity, we have done a lot of analysis on this last year, that this complexity that the technology organization has to incur is well worth it for the benefits of creating a balance of the best-in-class technologies to use from the various cloud providers for very fast pace of innovation and scaling, and for being -- for having the best approach to cost management of this massive infrastructure spend that any company has, including ourselves. As we scale, we have to spend a lot more on compute and storage and networking, all of those things. So this flexibility comes at a cost, but the ROI is great to provide us what we need across the board for our great client experience.

That's great, Jigar. So essentially, you are able to take best of the breed, best of the capabilities from all the vendors while optimizing your spend. So win-win all ways. I know you touched upon Snowflake. You obviously talked about the API and your Data Explorer as well. So I just wanted to bring all of that together, and wondering if you could talk about your content distribution strategy. And what role, or how important a role technology is playing on the distribution front as well.

Great. Great. So for years, our strategy of content distribution has been pretty much open architecture. We have dozens of partners we distribute our content with. Whether as Bloomberg, FactSet, [ Trax ], so on and so forth. We partnered with JPMorgan, we've partnered with Goldman. We have a lot of partners. [ CRD ], another example of big partnership for distributing our content. So we always have that open mindset with the industry. So a lot of key players in the industry are our partners, and we distribute our content through various different channels, and that will never stop. So what we changed in the last 4 years though, is also developed the highest fidelity last-mile delivery of our content directly through MSCI's distribution channel. And the reason to do that is to ensure the freshest content with highest quality, can be distributed directly to the clients who want to use and come to us directly. And now various clients have various needs, some of them had using some of our partners, and they want to see the data come to -- all of their data come to them from that particular partner. So that's completely fine. And some clients are coming to us saying, "We want to directly get your data as fast as possible." So imagine our indexes. We can -- we distribute those through file stores from like 20 years ago, FTP, SFTP. But now we also have distribution through Snowflake. We also have the Data Explorer which helps to browse all of our data. So essentially, our data distribution strategy is now, you go through our partners, you come to us directly, you can browse the data through Data Explorer. You can even see the Explorer in MSCI ONE. And you can get all the data through available APIs. You can go through our Developer Community, use the APIs and get the data directly. We are also working on a software development kit which brings it all together for you. So you can write code in Python, Jupyter Notebooks, all open standards. Everybody knows how to do this. So the quant audience can actually -- bringing it all together, make it even easier for our clients to get access to our content with Python, STK. And whether you want to use an optimizer, you want to use our performance attribution, or you're going to use our -- customize some indices, you can do all of those things and get direct access to our content through this direct channel, direct distribution from us. And there are some benefits for the clients with this model and with -- and collect benefits from MSCI as well. So if you come directly to MSCI, first of all, our clients don't need to pay the fees to other partners for the content that they can get from us directly. And from MSCI perspective, we can actually have a more direct influence on the end-to-end experience because now we have telemetry. What are you searching for? What did you find on our site? What did you not find with us? Like it helps us build products or reach out to the clients. It creates leads for the client coverage or it gives signals to product team and client coverage team teams on what are the things clients are really interested in? When COVID happens or the Russia-Ukraine crisis happens, the clients come to us for different content and different data sets. And those are the signals we can get directly form the platform, of how much usage is going on. So there are a lot of benefits of having a world-class, end-to-end, proprietary-owned distribution system. At the same time, we are not actually going to stop distributing through any of our partners. That will continue. So we are having -- trying to have our cake and eat it, too, essentially.

No, that's great, Jigar. And I think most importantly, right, what you're doing is you're meeting your customer where they are, lowering their barrier to adoption, making it easier for them to adopt. And I'm sure with having that ability to do it even through APIs and STKs. And it's just potentially bringing in -- is that even bringing in like a new set of customers who historically may not have been customers of the MSCI?

Exactly. I think it helps you go to a much wider audience. Other point to remember is that there are high-touch and high-cost models and there is low-touch, low-cost models. And we're trying to bring in technology to help you relatively high touch in terms of experience quality, but still low cost because these things are done at scale. So high-touch doesn't necessarily mean that you have a human handholding you through everything, but it's about telling you -- giving you a full experience on what you were looking for, but more in a self-service manner. To your earlier point about data technology going from cost center to being more of creating new revenues and now new approaches for the business. That's -- it was a really interesting point you made because I've only seen this at -- it depends on the industry you're talking about, right? In industries like investments or retail or health care, technology was seen as an enabler or something that can help you. But in the technology world, technology is the product. So there is no distinction between the two. And I would say investment world is a little bit of a hybrid, right? Because the core work investments is your -- are your content investments, the content model, risk and performance models, portfolio constructions are key. But then where does a line -- there is -- it's a pretty blurry line because you quickly bleed into technology as you want to do customization, personalization. You want to scale the number of indices. You want to get transparency on all the data. Suddenly -- and you want applications. And certainly, you're talking about the technology solutions, which itself becomes kind of a product.

Yes. No, Jigar, that's great. This is very, very helpful. Maybe switching gears a bit. Obviously, a lot of hype around the ChatGPT release or from OpenAI and the integration with Microsoft. You obviously also have a partnership with Microsoft and Microsoft Azure. I was just wondering what are your views on generative AI? Microsoft AI-GPT partnership, but also Google Bard. What do you -- how do you see these technologies being used at MSCI?

Yes, it's a great question. And I think there's a lot of hype, noise. At the same time, some people are massively underestimating what's going on as well, right? So we have to cut through the clutter and not go on either end of the spectrum that, oh, we are all dead, AI is going to take over the world. Or on the other end of the spectrum, the, yes, this is stuff who knows when this will actually be of high impact for us. So our approach to this, yes, we have been using AI, NLP and machine learning for a very long time. But with the avalanche of innovation going on around ChatGPT and OpenAI and Bard and other -- Google announced services as well, it's a really healthy competition amongst 2 of the cloud providers, Google and Microsoft. And we have partnerships with both. We have access to Bard and we have access to Google AI services that they announced last week, and we have access to OpenAI and ChatGPT through Microsoft as well. And to us, going back to client centricity, we are focusing on what are our client needs, right? On the one hand, we can help answer their questions faster. We get thousands of queries on our ESG products, thousands and thousands for climate. And all of those client queries can be answered at a much faster pace if you had artificial intelligence which can go over your documents in a secure manner, which only can be accessed on our domain, in our -- on either one, Azure or GCP. So we can answer those queries very quickly. Another example is data collection. A huge part of MSCI is relying on the data we collect, right? It's really critical that we scale that data. Now we use -- already use a lot of AI for collecting this data and scaling to thousands of new companies, new countries, new asset classes in both public and private side. And AI and the language -- large language models are coming up from all over, from multiple companies, is going to help us collect that data at a much faster pace. So think about we had to find a needle in a haystack. I find -- if you have a bug and -- or if you want to do a query of the millions of data points we collect, it's very difficult to find that data whether from a technology perspective, there's an error, or from answering your question perspective when a client is asking that crush. So apart from the classic approaches to collecting and finding and correcting that data, AI will also help us in that area. As another example of how we can be leveraging AI. And then going back into the most fundamental thing the industry does, right? Portfolio construction, performance analysis, risk analysis. You have to reimagine what can AI do in that world as well. So we have about a dozen projects going on, proof of concepts. Our technology organization is very excited. A lot of people are doing a lot of different experiments, hackathons, to try things out, see what works best for our clients in terms of what can we provide as a solution. Some things can show pretty early success, some things are a lot more complicated thing. You also have to balance the need for precision and recall because you know the issue of hallucination with ChatGPT. And now they're working on that, I'm sure they'll fix it. You'll remember this technology is very early and it's early on, and it's actually evolving at a very fast pace. So whatever shortcomings you see in generative AI today, and there are a lot of critics, and they're right. But these things will be getting fixed at a fast pace as well. So we are betting on neither side. We are just factually valuing the current sort of technologies we have across from both providers. And we're looking at internal and external use cases. For internal use cases, your bar can be different because we are using this as an assistant, right? Something like a copilot that is helping you do what you're doing. But you can always double check it. But if you're going to put something on an external-facing product, then we have to be assuring multiple lines, right? 99.9% is not enough for our clients. It has to be extremely highly accurate. So the bar of putting AI in an external-facing product is going to be much higher, and we will be very thoughtful and careful about when do we do that. But be rest assured that, as you have seen the evolution of technology at MSCI over the last few years, going from basically out of infrastructure and a platform creation, shared service engineering, ISaaS coming on top of that, MSCI ONE coming on top of that. Now we have this cohesive platform where it can become a hotbed of all of this innovation. So whether ChatGPT comes or the next set of innovations from technology, we have one place where we can do data acquisition, data distribution, APIs, applications. And in that one place, we'll be introducing and prototyping all of these new technologies at a very fast pace. And we are very excited about it. We are very optimistic about it. But we are very fully aware of all the pitfalls it has. We have seen some egregious examples of wrong answers, of cooked up answers. So you have to be extremely careful not to give out elite investors, highly sophisticated investors, some silly answer because the chatbot told you so, right? So you have to be leveraging the best technologies, at the same time, be very careful about not letting a single one of those errors flow out to the clients. Otherwise, they will lose trust in AI or in our systems, which obviously, we don't want to do that. But just to summarize. We do have access to Bard and OpenAI, ChatGPT, all of it. And we are going to -- and again, it's not an either/or. We can pick and choose. We have half a dozen to a dozen different use cases internally in the company, and we can pick and choose, cherrypick what -- which piece of tech, which API that we want to use in a very granular manner for the particular business team we have.

That's a great, Jigar. And I think for me, the key takeaway was, obviously, you've seen the pace of innovation at the company has accelerated. And now, as you said, like all the infrastructure is in place, it's relatively easy for you to experiment with new technology. And I wouldn't be surprised that we would have one of these generative AI models on top of MSCI ONE. And really now, not only do you have the power of all these data and technology coming together, but ability to make it even easier for customers to benefit from it. So that's very exciting. Maybe just in summary, I was wondering if you could give your closing thoughts on the role of technology at MSCI, but just overall investment industry in general.

Yes. Thanks, Ashish. So just to summarize, our landscape has changed a lot over the last few years, and it's going to keep changing at a faster pace. The rate of change is just increasing in the world, which is reflecting in our industry. And the complexities in our industries and in our industry is growing at a fast pace for our clients. And to address these needs, what we are focused on with technology and data at MSCI is helping scale MSCI. How do we scale MSCI to help the clients scale their own needs? This data scaling -- these scaling needs are in data. How do we acquire and process this good data? It's about portfolios. And by portfolio, I mean indices, I mean, data underneath that. How do we scale that from a few thousands to hundreds of thousands to millions of indices and in millions of portfolios with a lot more complex instruments and in a lot more companies, a lot more countries around the globe. So the scaling needs are there. And the last one is around scaling the client experience. It is the right time for us, and we have started reimagining the client experience at MSCI. That has to be powered by -- completely by technology, modern technology. And you see the example that this is not, like I said, just a long-term strategy. We showed you the demo to say that it's actually happening now. And the pace of innovation is increasing pretty rapidly over the last couple of years. It took a couple of years to lay the foundation. As soon as we announced ISaaS, we launched a lot of new services. And MSCI ONE is here now, so there's a quick and easy distribution approach. So the client experience is the holy grail that we are after to make sure that when clients come and interact with any of our content, our APIs, our application, that they really love this experience. And whether it's about using our content or doing business with us, asking us for licensing a custom index, or asking for buying some more licensing, more content and data and ESG and climate data from us. So all the touch points clients have with our products and services, or our people, right? Our research folks, our client coverage, our product folks, we want to take that experience to the next level. And that is the work we are doing both internally, reimagining how do we do all of our systems, as well as how do we really imagine the external systems that is sought today through MSCI ONE. So yes, it's been an exciting time for the team, and we're all pumped up about where we will be in the next couple of years.

That's great. Jigar, thanks again for giving us this opportunity. This was very exciting, and we are really excited about what's next to come with MSCI ONE and your cloud strategy. So thank you very much. Really appreciate it.

My pleasure. Thank you, Ashish.