Michelle Dunstan: Hello. Welcome to Janus Henderson’s Global Perspectives podcast. I’m Michelle Dunstan, the Chief Responsibility Officer at Janus Henderson, and I’m delighted to be joined today by Antony Marsden, our Global Head of Responsible Investment and Governance, and Cat Ziac Boyd, our Global Head of Responsibility, Strategy and Operations.

We’re going to talk to you today about what is responsibility. Responsibility, ESG, sustainability, there is an alphabet soup of language out there referring to the same thing and a lot of people get confused. Cat, you’ve recently published an article on this very thing. Maybe you could spend a minute and talk to us about what exactly do we mean by responsibility or ESG?

Catherine Boyd: Right. Thanks, Michelle. So, when we think about ESG or responsibility, there are so many acronyms out there and a lot of synonyms and a lot of confusion of course. So, what is ESG? It’s environmental, social and governance. When we think about these topics, there’s so many key issues under each of those pillars. So, on the environmental side, we’re thinking about everything from carbon emissions and also pollution. We’re thinking about waste management practices, things that could be affecting companies around the world.

On the social side of things, we’re thinking about labour practices, issues like modern slavery or human rights. How are your products affecting consumers? Those consumer protection considerations, too. And then finally, under the governance umbrella, we think about things like board diversity, but also board structure, board composition. Do you have mostly independent directors? We also think about things like pay practices and other governance practices.

And so, in the market, we talk about ESG, we talk about each of these key issues. It’s also oftentimes synonymous with the notion of corporate responsibility, or sometimes people talk about sustainability. And of course, in our world, we think about responsible investing. So, I’d love to hear from you, your perspective on responsible investing and how do we define that at Janus Henderson.

Dunstan: Yes, that’s a really good question. So, when we think about responsible investing and responsibility, we take a three-pronged approach to it. The first is actually our own corporate responsibility. If we are out there asking our portfolio companies to do things better or do things differently, our own corporate practices need to reflect what we expect of those companies.

The second is what we call responsible investing, or ESG integration. Where there’s a financially material, environmental, social or governance consideration, we should be treating it the same way we do any other financially material consideration, which is incorporating it at each appropriate stage of our investment management process. This is the core of what we do. About 85% of all our portfolios integrate ESG. We think it makes us better investors. A more thorough examination of risk and return helps us deliver financial results to our clients.

Then our last pillar is what we call our Brighter Future funds. These are portfolios for clients who want to go above and beyond investing just for risk and return, so they all have ESG objectives alongside those financial objectives. So let me touch a little bit more on ESG integration because this is at the heart of who we are as Janus Henderson.

Like I said, that more thorough evaluation, that different lens of evaluating risk and return really helps us produce differentiated, actionable investing insights. When we talk about it, we think about ESG integration in a thoughtful, practical, research-driven and forward-looking manner. It’s not about exclusions or values-based investing. It’s about understanding each of the considerations that you just outlined, Cat, and what is the implication on the future of that company? How is it going to impact cash flows? How is it going to impact cost of capital? How is it going to impact valuation? All of those things are critical for investors to make the best decisions they can for our clients.

So, let me give you a quick example. Let’s think about a company that has a factory that emits lots of carbon. Well, is carbon being taxed in the jurisdictions in which this company operates today? If it is, I as a portfolio manager and analyst should be taking that into account when I’m valuing the company. Even if it’s not being taxed today, are there going to be future taxes or is regulation going to come in that’s going to cause this company to have to spend money to install scrubbers? Again, that’s a financially material consequence for that company.

Well, what if there are no regulations but a competitor has developed a new lower carbon alternative? Is your company going to lose market share? Again, financially material. And what about those third and fourth order considerations? Younger people in particular are making value-based considerations or decisions on where they want to work. Is your company going to be able to attract talent that’s going to enable them to keep costs low, or innovate if they’re now getting bottom of the barrel talent?

All of these things are rolled into our investment decision. It’s not about invest, don’t invest. It’s about understanding those nuances that enable us to better understand the future path of a company and make a better or enhanced financial decision. In most cases, that is a clearer understanding of the bull and bear case. In some cases, it could impact the way we think about target prices, or the way we think about position sizes. And, in very rare instances, it might say, wow, the market is really missing something, I want to avoid this company. But it is always based on that research and that engagement.

Antony, your team is really heavily involved in this. They spend a lot of time coordinating, supporting and participating in research and engagements with our investment teams in order to better understand those companies. Maybe you could provide us with a few examples that really help bring this to light.

Antony Marsden: Sure. Thanks, Michelle. As Michelle said, ESG integration is a core responsibility of the investment teams they lead. I lead a team of eight analysts and we partner with the investment teams on all aspects of ESG integration. That includes research, engagement and voting, wherever we can add value to those teams. I like to think of it as a support and challenge philosophy. We support teams by helping them with their own research, engagement, proxy voting analysis.

That could include, for example, doing a deep dive of a particular company to get a much wider view on the stakeholders and what they’re thinking of that company. Thinking about the customers, the employees, that company’s impact on the environment, that can help round out and perhaps provide some additional analysis, which can help portfolio managers or analysts.

We also have the challenge side of what we do, which is to think a little bit outside the box. So, to bring a bit more of a stakeholder lens to the conversation, thinking about forward ESG risks and opportunities that maybe the average investment analyst hasn’t quite thought about. Something that can potentially be very useful in terms of warning them against potential road bumps ahead or potential opportunities that they hadn’t really grasped yet.

Dunstan: Great. You mentioned a lot of research and engagement, and a lot of that is driven by fundamental analysis. A lot of fundamental analysis is grounded in data. Cat, you’ve been dealing a lot with data and as do a lot of other asset managers. What have we found? What are we doing with the data?

Boyd: Yes. So, I like to say all roads lead to ESG data. And of course, the way our team is structured, we of course have the traditional stewardship functions that engage with companies, partner with our investment teams to integrate fundamental ESG-related research into their investment processes. But we know we’re an extremely data heavy business, regardless of ESG. From an ESG data perspective, there’s a few ways we look at this.

First and foremost, we know that data is important to understand these risks and opportunities facing the companies we’re investing in. More and more companies are reporting data. So, whether they’re doing that in an elective way or following best practice frameworks that are out there in the market, or increasingly following regulations that mandate this kind of reporting, we’re seeing more and more data come to investors.

Now, data is good. More data is better. But if it’s not structured, then it’s useless. And so, the way we’ve approached it, even in just the last year, is starting to take a very methodical approach to how we’re taking in this ESG data and structuring it and presenting it to our investment teams in a decision useful way. So, in the last year, we released a proprietary ESG data tool that we call ESG Explore.

Now, this tool leverages a mix of third-party ESG data, which we know has pros and cons in terms of, we like some of their estimation models. We like some of their web scraping practices. We find issues with some of these practices of course, too. We’ve also married this with some of our proprietary data. So, when our teams talk to companies and conduct those engagements, we’re collecting information about those engagements and those companies, and we surface that data in a system like ESG Explore as well.

Now, behind the scenes of [ESG] Explore, it’s not just a pretty user interface that gives data to our investment teams in a decision useful way. But, behind the scenes, we have a data taxonomy that we’ve developed to structure the data in a consistent way and probably longer-term layer in other data providers. So, we use a handful of third-party data providers. We know more providers are coming to the market and we know more data is coming to the market through these regulations. So, we’ve built this system in a way to futureproof it and make sure that we’re able to take in new data sources going forward, and ideally make the system better and better for our investment teams to enable, hopefully, better investment decision making.

In fact, on ESG data and ESG Explore, which is a system that our investment teams use daily, I’d love to turn it to you, Antony, and hear a little bit more about some practical examples of cases where you’ve used this platform with our investment teams and how have they integrated into their investment decision-making.

Marsden: Sure, Cat. So, when we sit down with investment teams, and we do this on a regular basis, we’ll often look through the portfolio and we’ll take a look at companies that maybe aren’t rated as well as we’d like. And then also if they’re trending downwards, and so trying to understand why that might be. We have access to this external research, but we do our own work. And so, this can often be a way of determining what our future engagement targets are going to be.

And a recent example, an environmental and industrial services company, which we were surprised both at its low rating and that it was forecast to deteriorate. And so, we arranged an engagement with that company’s management team, and we went through the issues in a lot of depth. And, as a result of that engagement, we were both able to impress upon the management some of our concerns. But also, we were able to get comfort that actually we don’t think things are as bad as the external rating firm was saying and actually gave us comfort in the investment case.

Boyd: Great. And tell me a little bit more about some of these thematic engagements that you’re conducting with companies. What do those look like?

Marsden: Sure. So, we try as far as possible to ground the work we do on thematics with what the investment teams are most interested in and what’s most topical. So, three examples that come to mind. Most recently, we’re doing a lot of work on responsible artificial intelligence. We’re doing research and engagement, looking into responsible AI practices. Both at the largest tech companies, the so-called hyperscalers, and how they’re managing both the social risks, the environmental risks, and also the governance risks.

We’ve also done quite a lot of work looking at data centre companies and, in particular, the environmental footprint in terms of energy use and water consumption. A big topic for us most recently has been health and nutrition, looking into the impact of GLP-1 drugs, and growing concern over the health impact of ultra-processed foods. We’ve engaged with a whole range of companies with exposure to changing consumer food preferences, including food producers, supermarkets, catering companies, and restaurants.

And perhaps a final example, listed private equity firms and ESG integration. We’ve done a bit of engagement with three of the largest listed private equity companies just to really understand what their approach was to ESG integration. And what we were quite interested in was, this isn’t just about them meeting demands of clients. They’re increasingly seeing a huge amount of value that they can add to their own portfolio companies through better ESG integration. So, for example, issues such as better governance, better cybersecurity practices, human capital management, share ownership, not just amongst the management team but amongst the employee base as a whole, and improvements to climate policies and practices.

And, increasingly, they’re seeing this as a way of making sure that these companies are going to be fit to relist onto a stock market and will attract a wide shareholder base.

Boyd: Fascinating topics and extremely topical I think, or timely, too. On responsible AI, that’s one that jumps out to me as one that’s extremely popular right now. Everyone’s talking about AI, but maybe not responsible AI. We just recently had an event where we were talking about the research we’re doing on responsible AI. What does that mean? How are we thinking about our investment processes? Michelle, can you share more about how we think about responsible AI?

Dunstan: Yes. No, it’s a super topical issue right at the moment and one of the things that we talked about was AI is everything, everywhere, all at once, right at the moment. It is the buzzword for everything and the next big thing. And AI does open up a world of opportunities. And what we’re talking about here is Gen AI. So generative AI, the capability of generating or creating new and original content based on digesting large datasets and predicting what comes next.

So, we’re not talking about artificial general intelligence that may have human consciousness. We’re talking about the technology that we actually have today, and it’s advancing extremely rapidly. It is opening up a world of opportunity. Whether it is speeding up the pace of drug development or making more tailored drugs. Whether it is enabling autonomous driving. Whether it’s being used in manufacturing, in healthcare, or in education to tailor processes. The world of opportunity is endless.

But with that great opportunity comes great responsibility. So, we need to ensure how we use it and it’s being used for good rather than for evil. So, we talked a little bit about the layers of AI and how we think about the development of AI in investing. We focused a little bit on the greenness of AI. A lot of forecasts predict a tripling of power consumption from AI by the year 2030 and a corresponding tripling of carbon emissions from AI, largely from the data centres and the hyperscalers.

All of that is predicated on extrapolating today’s power intensity and the carbon intensity of that power today. Based on historical investing, we actually think there’s a lot of efficiencies in the system that are going to be had over the next little while that’s going to enable us to bend that curve. And just like we heard the internet will drive coal, or the cloud will drive coal, that there are opportunities to make AI more efficient that it will not be the environmental impact that a lot of people think it is.

We also talked about the social side, both the opportunities, but a lot of the risks. Antony, maybe you could talk a little bit about those and also the world of regulation and how we think about our role as responsible investors in it.

Marsden: Sure, Michelle. On the social risk side of things, the way I think about it is, you can’t just think about the negative side of AI. And there are certainly concerns and risks about all kinds of aspects of AI, particularly the most recent large language models and issues such as so-called hallucinations, or just plain errors or bias being another massive topic here.

You have to balance this out by thinking also about the opportunities, and there are huge opportunities of AI technology to do good and have a positive impact on humankind. So, from my perspective, there isn’t some one-dimensional form of ESG analysis that can simply bolt on responsible AI to this. It’s far more complex, and it requires a much deeper and more thoughtful approach. You can’t just score companies, I think, for responsible AI in any sensible way because of this incredible complexity around the opportunities and also the risks.

Dunstan: Yes, absolutely. And will regulation be sufficient in the next few years to address this?

Marsden: Trying to keep track of AI regulation is a daily task. If you think about this at the country level, there are numerous new regulations, new best practices coming out almost on a weekly basis, it seems. At the country level, it’s still mostly voluntary, but with some exceptions, such as China where they have put in place quite significantly tough AI regulation. But we’ll see I think in 2025, 2026 a lot more country level regulation.

And of course, we have the EU AI Act, which will mean many of those EU countries will obviously have quite stringent rules themselves. And even in the US where there isn’t an overall regulation at the federal level, we’re starting to see state level rules appear, for example in New York, around AI bias and recruiting.

So, I think it’s hard to see exactly the future direction in terms of whether it will be enough because there’s all kinds of moving parts here. But if I was giving some advice to someone starting out in their career right now, I think you could do a lot worse than advise them to go into AI regulation.

Dunstan: Well, that means, though, that there is an onus on the companies themselves to have good governance practices, ensure that they have processes in place to assess their models, but also remediation processes. If something goes wrong, how do they address it? And that is one of the things that we are focused on, looking at how these companies are actually behaving. Do they have good governance in place? Do they have processes in place to address issues or errors that arise? Are they thinking proactively about how they’re using their AI?

So, it is incumbent on the companies and us as responsible investors to actually police this, as regulation is unlikely to be completely effective over the coming years. Look for a series of reports coming up from this AI event that we’ll be publishing over the course of the next few months.

So, thank you very much for listening to this Janus Henderson’s Global Perspectives. Hope this gave you a bit of insight into how we approach responsibility and responsible investing. Thank you.