Using tech to take on the ESG data challenge

Those who try to consume data in an 'analog world' face an impossible challenge, says Northern Trust's head of Investment Data Science

Using tech to take on the ESG data challenge

Record-high inflation levels continue to grab headlines across the world, and much ink has been spilled over the mismatch between the supply of goods in general and consumer demand for those goods. In the world of ESG investing, a similar mismatch is taking place.

As investors increasingly look to make a difference while they make a profit with their portfolios, the demand for ESG investment is surging. But aside from the lack of a consistent set of standards, the growth of ESG investing is being stifled by some fundamental challenges.

“There are a few large questions that are challenging the effective use of ESG data for decision-making purposes,” says Paul Fahey, head of Investment Data Science at Northern Trust. “I think one of those is the availability of data, and related to that would be the availability of consistent and complete data from various providers in the marketplace.”

According to Fahey, using comparable ESG data from different providers reveals different answers to the same questions. That inconsistency poses a problem as accusations of greenwashing are already rampant across the responsible investing space.

To mitigate that problem, he says asset managers are relying on multiple data sets to inform their investment decisions. In one survey Northern Trust conducted, 63% of managers said they use five to seven data sets; he suspects if the survey were to be repeated, that number will probably be larger, mainly due to the increased use of ESG data sets.

“That points to another challenge, which is the ability to make sense and draw signals out of multiple large data sets,” Fahey says. “It's not just about the vendor data around ESG scores. It's a combination of multiple data sources – portfolios’ reference data, market data, and so on – all coming together.”

All of that is compounded when firms operate in what Fahey calls an “analog world,” where data lives in and is transmitted through a pastiche of vehicles including Excel spreadsheets, Word documents, and email. That difficulty, which applies to investment data beyond that relating to ESG, is one of several reasons why Northern Trust invested in a company called Equity Data Science, a platform that digitizes the whole process of pulling data together so that users can extract meaningful information from it.

Fahey notes that while certain specific types of data might be available across many or all providers, some providers stand head and shoulders above all others in specific aspects of ESG – by drilling down to more granular levels of climate data, for example, or having better data on governance or social factors. Still, he argues, that doesn’t mean asset managers would necessarily want to have just one or two strong data providers driving their investment strategies.

“If you don’t consume multiple data sets, you’re going to get an incomplete picture. You have to be in a position where you have the tools and technology to consume large datasets, and consume multiple datasets, as well as be able to bring it together into a single view that can be interrogated by managers and investors,” Fahey says. “If I were being polite, I’d say doing that in an analog world is difficult; if I were being direct, I’d say it’s impossible.”

According to Fahey, asset managers must start with a single platform – whether it’s driven by robotics, machine learning, or some other tool – that can effectively consume ESG data. From there, they have to cleanse the data using AI – not simply artificial intelligence, but augmented intelligence.

“You have the human and the machine working in tandem, to deliver a better result,” he says. “You’re letting the machine focus on the things that it can do significantly more effectively and efficiently than a human being, and then the human being applies his ability to get information and insights from the data.”

What’s crucial aside from processing enormous amounts of data, Fahey says, is being able to do so with a quick turnaround time. In the absence of a uniform framework for identifying and categorizing ESG investments, investors and regulators alike are putting pressure on asset owners and managers to be more transparent.

“As long as they are driven, the questions that are coming from both the regulators and the investors require complete responses, no doubt,” Fahey says. “Those responses need to be readily available, and getting back in a week or two weeks with an answer is just not going to be acceptable.”