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Helping Investors Overcome ESG Data Hurdles

Hendrik Bartel | TruValue Labs

September 08,2017

Without timely and transparent ESG data asset managers and owners can’t invest effectively. We’re on a mission to change that.

Investment professionals are used to analyzing fundamental value with a set of hard numbers, required by law and audited by an independent firm. Straightforward factors such as stock price, profit margins and overhead are relatively easy to track and evaluate. But in recent years, company valuation is increasingly dictated by emerging factors that go beyond financial statistics: environmental, social and governance, also known as ESG. ESG covers a swath of issues. For instance, how many women sit on your corporate board? Does your supply chain use only fair trade goods? Are your office buildings carbon-neutral? These factors go beyond dollars and cents, but are becoming increasingly vital to success. "Investors see a pivotal role for nonfinancial information in investment decision-making," Ernst & Young reported in 20171. "As investors come to see non-financial information as increasingly material, they reveal still higher expectations for it being timely, comparable and verifiable."

There’s a cascade of evidence2 in support of investment strategies that consider ESG, and asset owners and investors of all stripes are asking for these strategies to be put to work on their behalf.

But most investors agree that data hurdles are a serious problem to integration of ESG strategies. The hurdles include bias, timeliness, transparency and comparability.

The Bias Issue

First, ESG data released by companies—"inside-out" data, tends to have a natural bias towards the positive. At TruValue Labs we gather data from tens of thousands of sources for an "outside-in" perspective.

"For the most part, the sustainability information that is disclosed by corporations today is not useful for investors or other decision-makers," said Michael Bloomberg in Bloomberg, LP's 2015 impact and sustainability report. If a company gets to choose what they disclose and how they disclose it, how is an analyst supposed to compare that with another company’s information in a meaningful way? Like anything else, if the data isn't clean the analysis won’t be as helpful as it could be.

That's why TruValue Labs and State Street have partnered with the Sustainability Accounting Standards Board (SASB) to promote relevant, financially material standards. SASB’s review3 of current corporate reporting practices found the most common form of sustainability disclosure is in fact just generic boilerplate language! That information, while it sounds nice, doesn’t help develop thorough and data-backed investment strategies.

ESG data released by companies—"inside-out" data—tends to have a natural bias towards the positive.

Timeliness, Transparency, Comparability

We support SASB's effort to use a consistent framework to highlight which ESG issues are financially material for each industry. It's clearly the way forward and will help investors improve the world and responsibly manage risks. But that doesn't mean SASB's important work is a magic bullet for the three other ESG data hurdles mentioned above.

Timely data can be hard to find—companies often publish reporting on an annual basis, and ESG ratings firms rely on that underlying data. As the financial services industry moves closer and closer to real-time data, it is imperative that ESG information be updated just as fast.

Transparent data describes an issue with the "black box" of ratings firms—it's not clear what raw data was considered by its analysts, or which controversies or positive events resulted in a rating or score. After all, if you don't know what data went into the analysis, how can you trust that the analysis is complete and un-biased?

Comparability is a challenge intertwined with transparency. Different ratings firms have different methodologies, and within a firm, the case for each company is based on substantially different available data types, and is filtered through an analyst’s human bias. Apples to oranges comparisons just hinder real analysis in the longrun.

Solving these problems is the reason TruValue Labs was founded.   We address these challenges with the outside-in approach that provides investors with a multitude of perspectives.  We call the approach "ESG2.0."

There's an uncountable wealth of data on companies available on the internet, which is constantly updated, transparent in that each item's publisher and perspective can be reported, and comparable once it’s normalized using one of the most important technological advances of the 21st century to date, artificial intelligence. Our goal is to take that information and process it as fast as possible so the end reports are up-do-date and provide comparable evaluations.

AI Solving the Puzzle with ESG Big Data

Since the solution to these hurdles is often described as "Artificial Intelligence," I'd like to make the case that this technology we call "AI" should refer to "Augmented Intelligence" instead.

Big data can mean dumb data because there’s such a large volume that it’s humanly impossible to grasp it all. Augmented Intelligence addresses many challenges human ESG analysts currently face in measuring a company’s environmental, social, and governance performance:

The mass of "big data" represented in articles and analysis on the internet is too big to consider simultaneously — or in a timely fashion

·Analyst ratings are subjective; computers apply criteria uniformly and objectively

·Company-reported data is out of date and hard to compare

·The amount of information to review is overwhelming, AI is almost infinitely scalable and nearly real-time.

We aim to solve these issues by continuously gathering up far-flung news, and converting it to scores for company performance in common ESG categories. This enables analysts to easily drill down to the source documents to understand the news and events that are driving score changes.

At the end of the day our augmented intelligence allows human ESG analysts to do the higher value work, rather than the grunt work of monitoring news streams and searching for company information on Google. Offloading that to a computer just makes business sense. When it comes to ESG data hurdles, we've got to work smarter, not just harder, to overcome them.  That’s ESG2.0.

1. Ernst and Young, Is your nonfinancial performance revealing the true value of your business to investors?, www.ey.com/Publication/vwLUAssets/EY_-_Nonfinancial_performance_may_influence_investors/$FILE/ey-nonfinancial-performance-may-influence-investors.pdf. Accessed 8 Sept. 2017.

2. Caroom, E. (2017, April 25). 10 studies that show how and why ESG investing works. Retrieved September 08, 2017, from https://blog.insight360.io/10-studies-that-show-how-and-why-esg-investing-works-35bf6c1b5a12

3. The State of Disclosure. (n.d.). Retrieved September 8, 2017, from http://library.sasb.org/wp-content/uploads/2016/11/StateofDisclosure-Report-113016v2.pdf

CORP-3218

Topics: ESG , Data Analysis


Hendrik Bartel | TruValue Labs

Hendrik Bartel is the CEO and Co-Founder of TruValue Labs, the leader in timely ESG platforms. With an engineering background, Hendrik is still drawn by the siren call of technical development work. He can often be found mingling with developers in the engineering section of TruValue Labs offices, enthusiastically discussing solutions.