Founded in 2012, California-based firm OWL ESG seeks to help clients see the most accurate and up-to-date data with transparent and unbiased insights to help them make decisions based on ESG practices important to them.
The ESG market is growing at a remarkable pace, and the ESG data segment is one of the biggest drivers of this growth. With more companies looking to do their bit to make operations more sustainable, as well as to make their social and governance strategies more equitable, the demand for ESG offerings – particularly data – is growing with increasing vigour.
One such company in the ESG data sector is OWL ESG. In a recent interview with FinTech Global, OWL ESG CEO Benjamin Webster provided some key insights into the company and what the company is looking to achieve in the sector.
The firm’s tagline states that OWL is transforming how ESG data is gathered, analysed, researched and applied. How does the company accomplish this task?
Webster explains, “It is important to note that, for the most part, consumers of ESG data and analytics are dependent on third-party providers to not only give them ESG data, but also provide interpretations or insights from that data. Many of these firms are in the business of telling others what they think that data means, moreso than necessarily prioritizing data quality. We see it differently. Our clients trust us because they know that data quality is our first concern, and then they can trust all the analytics on top of it.”
Despite this effort, with the industry attracting more attention, investors, regulators, and other stakeholders have responded with increased scrutiny as problems with such ESG ratings have become more apparent – especially with increased worry around greenwashing.
Webster remarked, “There’s been a lot of research into the subjectivity of ESG ratings. In just the last few years, with all this new attention on how investors are responding to sustainability expectations, this concerted effort to understand how subjective the ratings really are and how they drive investment decisions, is driving a new level of regulatory scrutiny. This is especially true around transparency into what is driving those ratings, like the underlying data and the ratings weightings and biases.
“To deal with those problems, we’re seeing more and more institutional investors, as well as consultants and ESG advisors, verifying ESG data from their broad providers and scrutinising it much more closely.”
According to Webster, ESG market participants are gathering data themselves, but not all of this is proving to be fruitful. Recent studies from Forrester and Gartner found that nearly one-third of analysts at investment management firms spend 40% of their time gathering and verifying data. This costs firms on average $15 million a year, and bad data can triple that loss.
To tie it back to how OWL accomplishes the task in its tagline, Webster states, “Traditionally, analysts and those involved in the aforementioned work – and I specifically mean those undertaking highly manual time-consuming tasks – have been stuck in a system where they are copying, pasting, and verifying one metric at a time, click after click. To address this, we [OWL] built AI that gathers huge amounts of ESG data. We free our clients teams from this laborious process so they can focus on more valuable work, and we do it with accuracy and speed that people alone can’t match.”
He further explained, “For the last three-plus years, we’ve been building ESG-focused AI language technology that allows us to gather data from sustainability reports and other company documentation disclosures. Our tech can now gather this data fast, at the speed of technology we like to say, and with remarkable accuracy.
“We’ve been able to cut our research time down to gather data by more than 90%, saving us a significant amount of time and money to conduct our ESG research. That solves the first problem the market faced, around accuracy concerns and inefficient, expensive data gathering processes. So what we’re doing now is addressing the market’s need for tools to nimbly pivot and leverage the freshest data for analytics.
“For example, we’re providing those AI-driven tools through a software package that allows just about anyone who is diving into company disclosures and manually trying to research and gather data to do that way more quickly and efficiently, way more cost-effectively, and without taking up valuable analyst time and with a lot higher quality output.”
OWL’s clientele
In line with the rapid expansion of the broader ESG industry, new customer bases are developing, and the clientele and their needs are diverse.
According to Webster, the company works with a wide variety of institutional clients across the world such as asset managers and owners, management consultants, insurance companies, FinTechs, ESG advisory firms and more. More recently, the firm has an uptick in stewardship and engagement teams and sustainability teams.
Beyond this, OWL is increasingly working alongside management consultants and ESG advisory shops that can help corporate issuers prioritise and execute on the sustainability goals of corporate issuers. Many of the teams above with whom the company has been working are moving towards increased ESG research, whether gathering data themselves or verifying data from their existing ESG data providers, but they realise the data they are getting has some quality issues.
Webster explained, “So the problems we’re really solving is helping with the data quality by providing high quality data, but also helping these groups to conduct their ESG research much more efficiently in less time and for less cost.”
Higher quality data
In a sector that is adjusting to the rapid pace of growth, OWL holds itself as a high-standard provider of ESG data– something which helps the company to stand out.
Webster emphasised OWL originally set itself apart as a contrast to the subjectivity present in ESG ratings today. But the market shift away from scores and toward the actual data exposed further ESG data shortcomings.
Webster explained that, as many of these stakeholders started to ‘look under the hood,’ for further insight into what was behind the ratings they were using, they realised that the data itself had significant problems. One of the key issues here was lack of freshness, with ESG data providers on average gathering data every 21-30 months.
Webster continued, “One of the drivers of low levels of accuracy is the fact that companies tend to report their ESG metrics yearly. If you wait two years to gather that data, then the data you are using is time-decayed, stale, and inaccurate.”
What sets OWL apart here, Webster underlines, is that OWL’s data is always the freshest on the market – which also helps to keep it accurate, above 97 percent accurate in backtesting, which is ‘the gold standard’ in the industry.
Another core tenet of OWL’s is transparency, “You are often given the data without knowing data provenance. Where did that data come from? Is it a recent or old data point? Is it modelled?” said Webster. The firm also provides the source of each data point so that its clients can quickly and easily verify data accuracy.
As the market adjusts to changing demands, the possibility increases that other ESG data providers will focus more on timely, accurate data. On this, Webster has little doubt. However, he sees a clear difference between OWL and its competitors.
“They’re [the competitors] going to catch up. But I don’t think they’re ever going to move in the direction we are, where we’re trying to empower our clients to be their own experts – I think that’s a good way of looking at it.”
ESG data idiosyncracies
Rapid growth in the ESG data market has been fueled by increasing demand; similarly, there is increasing demand for standardized products and consistent data, and vendors are beginning to coalesce around this need. As regulatory requirements provide an additional foundation, certain segments of the data market are beginning to stabilize, especially in terms of corporate disclosure.
Still, ESG is a broad topic, and there are as many applications as there are consumers of the data. As different investors and funds balance their respective values and ESG priorities with the consistent pursuit of financial returns, coverage of more raw data points at a greater range of companies provides investors the flexibility to pursue investments in line with their respective fund’s values. For example, some investors are focused on small cap companies.
Webster outlined this point by stating that every consumer of ESG data has their own bespoke needs. “I won’t name names BUT we just got off another call with a stewardship team that invests in stewardship of investment shops and large data providers just don’t cover these companies at this level of detail.”
“We also find that consumers of ESG data want data points that the major providers don’t necessarily provide. The limited ability for ESG data consumers, in terms of coverage, and I mean companies and data points, to get everything they want, I think that is a key problem in the market,” explained Webster.
The tools that OWL offers, Webster states, will empower these customers to find that information, both the data point and the companies that they care about, much more quickly.
Another key issue Webster highlighted is that ESG data providers have very restrictive use rights. “Oftentimes, the data they provide is for internal research purposes only. So, what happens is an investment management firm could maybe start to make investment decisions, but they can’t, for example, construct an index and launch an index-driven ETF.
“I think a lot of institutional investors are trying to find out how can they get more use rights and have fewer restrictions so they can more effectively do their jobs and satisfy their stakeholders – this is something they are struggling with.”
Finally, many institutional investors have multiple agreements with a singular data provider. “What we mean by that is one team may licence XYZ data providers data over here, another team may licence it, and then you may have five or six teams that have contracts with a data provider. So it’s very, very expensive and contracting can be difficult,” Webster detailed.
Because of the additional costs and inefficiencies of this approach, Webster believes a lot of institutional investors are trying to centralise their provisioning – meaning they’re trying to have a single contract. Then, from there, the data comes in from one pipe and they can distribute that out to the rest of the firm, making it simpler for the entire organization to access to the same information.
Future plans
Going forward, OWL is looking towards solidifying its technology as part of its overall offering – with the company’s next aim to turn its data gathering technology outward.
Webster remarked, “The OWL ESG Deep Research App [the new technology] is currently opening up to beta testing from users who are a good fit for its capabilities. We plan to launch the full application in December.
“The Deep Research App is designed for ESG researchers to gather their own data and generate their own analytics all powered by AI. We’ve already got a number of prominent asset management shops and corporate and management consultants who have signed up for that beta.”
OWL’s CEO concluded by stating that ultimately, the firm’s goal is to empower such organisations to conduct their research more efficiently and cost-effectively.
He defined it, “We really do want to transform how the industry gathers research and analyses ESG data that that software application is what’s going to do.”.
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