- ESG Data for Wealth Management
- Sustainability Opportunities
- Collecting ESG Data
- Cleaning ESG Data
- Multiple Data Sources
- Fintech ESG Use Case
Craig: I’m very happy to introduce our next guest on the program. It is Elena Philipova, Director of sustainable finance for Refinitiv which is part of the London Stock Exchange Group. Hello Elena. Welcome to the program.
Elena: Hello and thank you for having me.
Craig: It’s wonderful for you to be here. Where are you calling in from?
Elena: I’m joining today from Switzerland.
Craig: Wonderful. So nice to speak to you in Switzerland. I’m in lovely New Jersey in the US. So power of technology brings us together. So let’s kick things off. We’re talking about ESG and ESG data as on this podcast. So can you give us a 30-second elevator pitch for the sustainable finance group at Refinitiv?
Elena: I’m happy to so it’s Refinitiv we been providing ESG data to the global financial community for close to 20 years now. So we’re we’ve definitely been pioneers in the sustainable finance industry. And the primary purpose that’s we are solving for and servicing the industry wheat is translating sustainability data, which is not necessarily financially fit or fit for purpose to be used by financial professionals in its raw form and transforming it into actionable and investor ready data sets that can inform and enhance investment and financing decisions made by our clients.
ESG Data for Wealth Management
Craig: Excellent, thank you for that. So diving into ESG data, maybe I think would help the audience if you kind of give an overview of ESG data around the specific on the ESG data related to wealth management.
Elena: Yes to date is a term that’s been around for more than 20 years now. And it’s not necessarily a new data set. It exists for decades. Previously, it used to be defined as sustainable, responsible investments data or SRI data. But what is what this included in ESG has evolved over time and it’s changing very much very rapidly, primarily because of two main reasons. One is definitions standards around the world are evolving in terms of what ESG data for investors and and wealth in particular users needs to look like. So that it’s relevant material actionable, so that it’s less noisy, so to speak. ESG data, currently is some views is a noisy data set. And to reduce that noise. It’s really important to to drive towards global consistent definitions and standards. So that’s one of the drivers and another driver is regulation. We’ve seen the role of regulators in this space escalating and accelerating very rapidly in recent years around the world. And this force, or what we call a push factor is pushing integration and incorporation of ESG factors in no investment financing decisions. As such, finance professionals require data to be able to firstly diagnose their portfolios, product strategies, exposure to sustainability related risks, but equally to sustainability related opportunities. And secondly, build strategies that allow them to execute on different objectives that they have or that their customers have asked for. And measure monitor progress against those objectives. So data really underpins the full value chain. And what is ESG data has evolved in recent years to a lot more clear data set of sustainability related teams KPIs and metrics that companies, financial firms, and anyone else that uses the data is required to start measuring and reporting against.
Craig: I thought that was interesting you called the use of the term push factor.
Elena: Yes, what we’ve seen in the market is very interesting dynamics until few years ago. It’s the pool factor that has led to the state of the industry. And what I mean by a pool factor its market led initiative. It’s it’s the investors that have been demanding from companies to receive ESG data. But in in this has been going on for quite some time and we’ve been seeing incremental improvements year after year. But the the speed with which the industry has adopted and understood sustainability has not been sufficient. Therefore regulators I think, have realized that they have a really important and urgent role to play in creating that push factor that accelerates adoption of sustainability and ESG data across the financial industry. are also players in the financial industry. So the combination of the two is what we believe creates a new norm in capital markets, which is here today.
Craig: You also mentioned sustainability related opportunities. Can you give me an example of a sustainability related opportunity that wealth management firms or fintechs could be open to?
Elena: I think the the easiest and the most obvious example is related to climate change and the decarbonization of the economy and the race to lead Zero. What’s what that means is that there will be no industry there will be no single company that doesn’t get impacted by this transformation. Many will emerge as leaders, those that innovate and create the technologies of the future that so for, for the climate challenges across their industry, and the companies that choose to see on the sideline and watch and kind of continue it’s the business as usual note, face, never increasing risk of being left behind. Because I think that it is no longer a debate of beef and why the conversation is about.
Elena: Just one more comment, the opportunities that that I’m referencing are also not only kind of financial opportunities and innovation, life opportunities to support the the transformations that are happening and are going to continue to happen across the global economy. But it’s even more fundamental in terms of in terms of just sustaining economic growth and job creation. I think there’s been quite a lot of literature and examples that prove sustainability transition is and will continue to be one of the major sources of economic growth and job creation, whether it’s at a country level or at the sectoral level, in a company level. There are numerous examples out there that speak volumes about that.
Collecting ESG Data
Craig: Let’s talk more about ESG data, specifically, and around the process of gathering it and accessing it. So what makes it ESG difficult ESG data so difficult to collect and access?
Elena: That’s a great question. And interestingly enough in our conversations with wealth managers, suite advisors, and other customers that we serve is really issue data. One of the key reasons of kind of reluctance to roll out more broadly sustainability across the portfolio’s and products of our customers is, is the challenges around ESG data. So ESG data very frequently is quoted is the reason number one for reluctance and slowing down adoption. And from my perspective, I think that this is human nature going full speed. Human nature is such that is reluctant, reluctant to change. And we also like to procrastinate so we’d look for reasons and excuses to be lazy to push back on change. And data used in data has been used as one of those reasons most frequently, because the data set is quite different. It’s not a typical data set that the financial industry is used to deal with. It’s patchy. It has gaps it has holes in the data. Unlike financial data, for example, which is mandatory and all companies have to report on a consistent frequency within a consistent template following the same accounting rules. This is not the case with ESG data. ESG data up until very recently, has been reported by companies on a voluntary basis.
Elena: Numeric most of the time, and even if it’s numeric, it’s not in units that the financial industry is used to deal with. It’s not it’s usually not in money, or in percentages. Most of the time is in tonnes, for example, greenhouse gas emissions in tonnes or energy in megawatt hours or injuries per 100 employees and so on. So, the type of data is a different data set. And that makes it for some users scary to face and do it but on the contrary, over all of those years that we’ve been servicing the financial industry and and different wealth managers. We’ve seen numerous examples of users building very successful investment strategies, enhancing conventional products to overlay them with sustainability considerations, whether that’s overlaying them with an overall ESG score, or with some of the more granular components like intensity ratios, or even bought independence. There are a number of very widely used ESG metrics within the wealth management firms to screen on and provide solutions that respond to requirements of the retail investors end users. And if you think about it, I mean, all of us. It’s quite natural that we want to preserve our environment. It’s quite natural that we we want to see people being treated fairly, and that there are fundamental human rights being respected by institutions encoded in our pension funds or institutions that we invest our wealth into most of the time. It is lack of knowledge that leads to a lot of the capital being allocated into organizations that retail investors would not be happy to to find out they are financing so it’s about knowledge. And that’s what data provides data provides knowledge and knowledge leads to accountability. And this is what is really required for capital markets to be able to serve is society.
Cleaning ESG Data
Craig: So talking about the datasets, the ESG data set, how different it is a patchy it is the gaps, the holes you mentioned. And you also mentioned it’s a noisy data set. How does Refinitiv go about cleaning the data to turn it into a better a data set that that can be used in wealth management.
Elena: And this has been exactly what we’ve been doing for all these years. It’s about taking a non financial data set that tends to be very much narrative. So it’s unstructured data or vast majority of it and transforming it into investment great data set. Let me maybe start by explaining what it from our perspective and based on great data set is. This is a data set that is firstly reliable and trusted. Secondly, it’s numeric, its quantitative. It is consistent, comparable, and it’s auditable, it’s transparent. So the way we do that is by Well firstly mobilizing a very significant team of experts and specialists that are trained on reading through hundreds those hundreds of pages that are usually included in sustainability reports and extracting the data in a consistent comparable way. So we’ve provided so we’ve broken all of the ESG questions into components into simple questions where the chance of subjectivity and not comparability of the data is minimum. And the analysts follow very specific guidelines when they find when they look for answers to those questions. So for example, if a company is publishing its its climate related strategy and talks about different processes in it and and how they plan to achieve the decarbonization strategy and let’s say the company has committed to net zero by 2030. We break it into Does the company have a policy as not great. Is there a process? Yes, no. Is there a target yes, no, how much is the target by what tear so you break up the text into very clear data points and KPIs, which, if answered by different analysts, they will answer it the same way. And we preserve the connection between the way that the company has reported the data and metrics that are captured in our system. So everything is fully transparent, leveraging click through technology, and it is very similar to how our fundamental data is also presented our products to our clients. It is the same technology that powers that transparency from the aggregation and the overall scores back to the underlying inputs and matrix and back to the actual source documents that we use to collecting the data. To give you just a few numbers, our operations team these are our ESG specialists consists of more than 700 analysts, and we process data on 12,000 global organizations. It’s a very labor intensive and time consuming process to do that transformation of ESG reports and texts into investor ready and actionable yesterday.
Craig: Yes, 700 analysts processing data on 12,000 organizations is quite a huge lift, not something that any many other companies could be able to handle.
Elena: You do need a lot of specialized experience and expertise to do that as well. The training cycle of our analysts it’s a lot longer than a typical training cycle to collect any other data set, because again, the concepts the topics that are covered under ESG data are so wide ranging, and you do need to be familiar with them to be able to synthesize and extract meaningful data out of the reports. tend to specialize on industries because sustainability teams tend to be more relevant and material to certain sectors over others. So for example, climate change is certainly more relevant to oil and gas and transportation companies then maybe financial institutions. Although we shouldn’t undermine the importance of financial institutions through their indirect impact on climate investments. They are accountable under their scope three emissions, also for the emissions put in the atmosphere by the companies that they invest in.
Multiple Data Sources
Craig: How many data sources does Refinitiv aggregate in your data sets?
Elena: So we capture ESG data from roughly about two dozen publicly available information sources. And maybe it’s important to mention the reason to rely on public data only and that is to be able to provide an investment grade data set that’s trusted and reliable. It is important to make sure that we take only credible data and from our experience if companies are reluctant to publish data in the public domain, usually its data quality tends to be a lot lower. So about 20 or so sources are used in capturing ESG data, but those are specifically to the self reported ESG data points. So whether that’s the annual reports or 10 case of companies, different integrated report sustainability reports or GRI reports the proxy statement. Then there are different committee charters code of conduct. Documents, corporate governance reports by Lowe’s and constitution. mean a lot of the kind of sustainability information is embedded in the DNA of companies. So our analysts really need to go deep into the into the organization that they process data for, to be able to extract the data. And in addition to that, we source data from a number of external to the company sources, like for example, more being contributions or companies that are on the HRC index. So there are some additional sources that we also process data from, and this gives a view that we like to describe this inside out view so it allows users of the data to understand what companies put out about themselves. But our users would like to normally complement that with an outside in view as well. So it says the perception about companies and our companies walking the talk, how are they viewed from the communities and societies where they operate? So we also sort of source ESG controversies from global editorials including Reuters but not limited. And through partnerships, we also assess sentiment from social media. So that’s allows clients to really do something like a balanced scorecard and evaluate our company’s walk in the park.
Craig: So when you consolidating data from multiple sources, now these about 20 public sources you mentioned, they each could use different methodologies. And those methodologies require some estimates, maybe even some guesstimate, as to certain things because you’re going to then you’re trying to organize data, which is not standardized. And oftentimes, that data could have errors or or a range of accuracy then you’re compiling multiple data sources that have different ranges of accuracy, different estimates. How do you what do you do with your methodology to ensure that these errors don’t multiply as you put them together?
Elena: So there are two parts to your question. The first is around kind of compare ensuring the comparability of the data because there is no one accounting standard there is no one way to calculate and aggregate these data that companies can rely on for publishing it. There are different standards, different definitions some companies will provide the ratios in very inconsistent and not comparable way. So part of a part of what we add to on top of the data is ensuring that layer of standardization, but this is not very unique to only ESG data. It’s the same similar concepts to even Company Financials. There are different gaps in the accounting standards IFRS US GAAP and so on. And even within our financial data, we have what’s called SLS reported layer of the data. And some clients like to see the data in its raw form because it allows them to go deep into the unique nuances of individual companies. But equally we offer a standardized layer which allows users to have that comparable view across a portfolio of companies across different sectors, geographies, and even asset classes. So we use CI we do the same approach we would capture the data as reported by the companies we very diligently collect the units definitions and so on. And then our technology our solution that we failed to capture the data aggregates and creates a standardized layer. So unit some are converted to the same same unit same ratios. We also apply consistent accounting standards and definitions. So for example on GHG emissions, some companies may classify type of emission as scope two emissions. And for other companies, it may be scope three emissions, we apply the GHG Protocol definitions and we make reclassify the data to ensure that it’s fully compare comparable within this standardized layer of ESG data. So kind of this is the first side about comparability. The second part of your question, and very rightfully so is about data quality. And there’s been even rising concerns in the industry around greenwashing, and can use today to be used with confidence to inform investment decisions and strategies. And are those strategies true to what they are? Meant to assess and deliver. So data quality is quite important in this space. And it again goes back to the fact that there are no mandatory and widely agreed standards on how the data should be published. What we do it for infinity is because we’ve been pioneers in this space, and we’ve been working with ESG data for for such a long time. We have a lot of history and historical data. And historical data is is a very valuable source of insights and information. So we use leveraging technology, we extract knowledge from the historical data that we apply to all new data that we capture. And we run hundreds of checks on the data that says comparability consistency, that assess correlated metrics that assess variance in data that’s been captured for each industry. So for numeric metrics, we know we didn’t want range any data points to be and this is quite useful to capture outliers and capture errors in company’s own reports. And we unfortunately still see those company may say that the data reported is in 1000s. But actually, we see it’s missing three zeros. So what we do in those cases is we put the company on hold. We believe it’s really important
Elena: From an ESG perspective, because the data is not market. It’s it’s not like other datasets real time. It doesn’t get refreshed every minute, every hour every day even. So it’s important to ensure its accuracy. And we put the data on hold, we contact the companies, we rectify the problem. Many times companies say there was a mistake in our report. And they immediately make a correction. We then put the right number in the system and that’s what’s used to calculate the ESG scores of companies. And this is really important because these two scores are informed by by all the data in a data set in a peer group, their relative to peer group and if you have one significant outlier, it can significantly impact the score of everyone else. And that can trigger a lot of investment activities that are that are not desired. So we’ve been putting a lot of emphasis when designing our tools to ensure that date is double, triple and quadruple, quadruple qualified, quality controlled. before it’s published upon.
Fintech ESG Use Case
Craig: Elena, we are running out of time but I wanted to squeeze in one more question, which I think will be helpful for our audience. Could you give us a quick and just the next two minutes an example of a use case where a FinTech or wealth management firm would be able to use your data and maybe one of the FinTech side because you’ve got many, many partnerships with fintechs that use your ESG data.
Elena: Happy to and that’s indeed what we’ve seen happening in recent years is a lot of fintechs are entering the sustainable finance landscape. Because there are endless opportunities. It’s a field that’s hungry for innovation, and thus it makes it really attractive working takes however, as I described, creating a consistent and reach enough ESG data set to be used to build those innovative solutions. So for different sustainability use cases and challenges. There needs to be a very strong partner and that’s what the perfect the past been viewed by many fintechs that come to us and want to work to create those solutions, or for the financial industry of the future to enable more accelerated adoption of sustainability into core investments and product design workflows and solutions. So we’ve we’ve done quite a number of those partnerships in recent months. And years. And we believe that they’re very important enabler for adoption of sustainability globally at the pace that’s needed. In terms of wealth management firms, the use case there is we work with quite a large number of some of the largest wealth managers, and they use our data to present it to their advisors because the advisors are being asked by the end users customers around sustainability considerations more and more frequently. And having access to the data allows the advisors to have the right conversations with their customers, to provide them with the right advice that aligns with their personal beliefs and expectations that go beyond just pure financial performance. But also touch on sustainability, desires and needs. So it empowers them to to have again knowledge and provide this the right solutions at the hands of their customers.
Craig: Elena, that was an excellent answer and just in time, key please let the audience know because we’re now done. Can you give the audience where they can find out more information about Refinitiv sustainable finance?
Elena: We publish quite a lot of information on refinitiv.com under ESG data, I would also encourage you to follow our refinitiv perspectives there is a option to select ESGs team and then you’ll receive a lot of top leadership reports and blogs that we publish on the topic. And these are the main places to start with and happy to provide any additional support if needed.
Craig: Fantastic. Thanks so much for being on the program.
Elena: Thank you for having me, Craig, have a good day.