What trends are the latest thematic indices tracking and what’s powering these innovative tools? S&P Dow Jones Indices’ Ari Rajendra and Vidushan Ragukaran discuss how S&P DJI is leveraging AI, machine learning and NLP to innovate and track dynamic industries and emerging trends.
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Jenny Ellice:
With the adoption of new technologies such as AI, we're seeing increased interest in the long-term trends that are shaping industries and economies. Indices are now utilizing innovative technologies such as S&P Global's Kensho to differentiate indices and create a broader set of thematic tools to help meet the diverse demands of today's investors.
Hello, I'm Jenny Ellice, and I'm joined by S&P Dow Jones Indices’ Ari Rajendra and Vid Ragukaran to discuss how they're combining powerful data sets and innovative technologies, including machine learning and natural language processing, in the development of new thematic indices.
So, Ari, Vid, good to have you with us today.
Ari Rajendra, Vidushan Ragukaran:
Thank you.
Jenny Ellice:
So, Ari, I want to go to you first, and what do we mean by thematic and how does that relate to indexing?
Ari Rajendra:
Sure, Jenny. At S&P Dow Jones Indices, we take a comprehensive approach to constructing indices. We create solutions for a diverse range of objectives and practical applications. So this can span across broad value chains, across geographies, market caps, and targeting niche segments of innovation. Over the past decade, we've seen a significant proliferation in assets, but especially in the passive space. And this has partly been fueled by the advancement in technology and data which has made the creation of thematic indices more transparent and efficient. One of the most interesting developments is the use of AI tools, particularly natural language processing, otherwise known as NLP, to identify companies that are associated with a specific theme. At S&P Dow Jones Indices, we have our Global Kensho Index Solutions, which leverages in-house data and enhanced NLP models to parse through global filings in multiple formats to identify themes that are shaping the future tomorrow.
Jenny Ellice:
Well, Ari mentioned S&P DJI's Kensho capabilities there, Vid. So, what or indeed who is Kensho? And how does that fit into indices?
Vidushan Ragukaran:
Good question. So, Kensho is a financial technology company founded in 2013 that specializes in natural language, building advanced machine learning models that ultimately help add structure to unstructured data. And again, in turn, this helps save time from digesting pages and pages of content. The company, which has been recognized on multiple occasions by the World Economic Forum, was acquired by S&P Global back in 2018. Over time, Kensho's toolkit has become integral to S&P Dow Jones Indices in the creation of thematic indices that reflect innovative structural trends. We launched our first index using Kensho back in 2017, initially focusing on U.S.-listed companies and since have launched global indices back in 2023. One of the core benefits of an NLP-driven approach to thematic index creation is the early detection of companies at the first clear signs of commercial product or service involvement related to a given theme.
And so this is especially valuable when we think about dynamic industries, so where there's constant change, major disruptions. And this is where traditional methods, so for example, looking at revenue generation, thinking about traditional frameworks, industry classification such as GICS®, may overlook emerging players. All of that said, of course AI still isn't yet in a place where we can afford to sit back and relax. There is still a human oversight and involvement which is very much necessary in order to maintain best practices and ensure accuracy.
There's been a lot of media and the-world-at-large buzz in terms of excitement around AI tools and its potential. And as you can see on the screen, AI has not been the only beneficiary of technology-driven developments. So, across all industries ranging from solar technology to personalized medicine, regenerative agriculture, you name it, have all witnessed extreme levels of progress over the last decade. I think ultimately what this shows is the importance of an NLP approach and in terms of Kensho, almost that ability to act as our eyes and ears on the ground.
Jenny Ellice:
Well, you have slightly just touched on it, but can we talk a little bit more about indices you've recently launched and why these are particularly interesting?
Vidushan Ragukaran:
Absolutely. So, like we said, the first global index using Kensho that we launched was back in 2023, our S&P Kensho Global Hydrogen Economy Index. Since then, we've added several more to the suite, so things like space, distributed ledger technology, digital health, just to name a few. And more recently, AI enablers, cybersecurity and future defense, all three which have been reflected in dominating headlines in recent times. So, starting with AI, it's obviously continued to gain traction in the workplace context, but also at home. And in our case, our index strictly focuses on enablers of AI technology rather than adopters, which of course now you would hope that would be all of us. And when we think of that ChatGPT was launched, released in November 2022, it'll be interesting to see where we land 5 to 10 years from now. Of course, with the increasing use of technology, the rise of data storage, cybersecurity has also become a feature of everyday life, not only personally, but also the enterprise and national security level. And again, if you think about the advances of technology, you can imagine that we'll only double down from here in terms of the scales of the threats we face as well as the level of protection required.
Speaking about protection, of course defense has been another major talking point in the last several years, and we see this from two different ways. One is the more traditional side, looking at conflict, thinking about defense spending, national security. And of course, the other side, where Kensho really kicks in, is the related breakthroughs in technologies. So, think drones, think robotics, satellite technology. And again, this will only continue into the future and underlines the importance of S&P Dow Jones Indices, whether that's Kensho, AI tools, as well as its human users. That we need to stay ahead of recent developments, future developments, to be able to continue powering indices, thematic or otherwise, to reflect and remain helpful to our users.
Jenny Ellice:
And Ari, of course, this space is constantly evolving. We've seen some really interesting developments in S&P DJI's. Can you tell me a little bit more about this?
Ari Rajendra:
Sure, the evolution of thematic indices has been remarkable, and as Vid pointed out, S&P Dow Jones Indices has played a leading role in driving this innovation. Take the global Kensho index platform. It's a perfect example of how approaches to constructing thematic indices have advanced. If we take ourselves back a couple of decades, constructing thematic indices are likely, the approach is likely using a classification such as GICS, which is a well-established taxonomy still used today. However, as demand for more targeted or niche exposures arose, the construction approaches became more complex. Analysts would comb through annual reports to identify companies, which is time consuming and potentially error prone. Now this is where the global Kensho comes in. By leveraging NLP, it's transformed the process. It allows us to analyze unstructured data in a far more efficient and accurate manner. The platform is truly global.
It is capable of analyzing reports in multiple languages and formats thanks to S&P Market Intelligence’s best-in-class database. In addition to NLP, we have other tools such as revenue data sets that helps improve the level of accuracy. Our focus remains on evolving these capabilities to improve accuracy, efficiency and scalability for our clients.
Jenny Ellice:
Well, it certainly seems that S&P DJI has led this innovation with your use of Kensho capabilities. It's a powerful combination. So, Ari, Vid, great to have you with us today.
Ari Rajendra:
Thank you.
Vidushan Ragukaran:
Thanks.
Jenny Ellice:
And to you, thanks for watching. And to learn more about S&P DJI's indices and the topics discussed today, visit us at the link below. spglobal.com/spdji/thematics
