May 2021 | Issue 234
Opinion ESG
The lack of standardised ESG data creates opportunities for data-driven investors
Fatima Hadj
Chairwoman, structured finance advisory board Principles for Responsible Investment
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Investors can gain an edge by using technology to help parse ESG data
Regulation and technology are disrupting most industries and asset management is no exception. Indeed, the technologies that will transform the investment process in the next few years are the same ones impacting other sectors: blockchain (which we will cover in another column), big data, artificial intelligence (AI) and machine learning.
Big data refers to any large volume of data, structured or unstructured, easily quantified or not. It’s not just the amount of data that is important — it’s how it can be analysed and used. That’s where artificial intelligence and machine learning are playing a role. With increased data volumes, advanced algorithms and improvements in computing power and storage, AI makes it possible for machines to find new patterns in data.
In asset management, the exponential growth in information — especially the explosion of non-financial data — is fuelling investment decisions but also creating confusion. There is a proliferation of third-party providers and vendors, yet investors have been highlighting the lack of standardised data as a barrier to the proper assessment of company performance on environmental, social and governance criteria.
However, standardisation alone won’t solve challenges faced by the investment industry because of the growing universe of varied, multi-dimensional information that is becoming available. This data is complex, in part, because it is collected from social media, internet web traffic and other new sources. Much of it, such as carbon footprint and gender diversity data, did not exist a few years ago — and many new streams will emerge as a consequence of future regulation.
Rapid innovation brings opportunities
Luckily for asset managers, the pace of innovation in data technology is faster than ever, and the evolution of AI and machine learning allows them to analyse new unstructured data. This kind of technology is already being used in many industries, but in finance few investors have incorporated the latest tools into their investment process — which means there is an opportunity for early movers to use nuanced and unconventional data to gain an information advantage.
New data technology brings at least three advantages: the ability to capture a massive amount of data; the ability to process that data rapidly; and the ability to analyse it to find new correlations and trends. We will see an increasing gap between modern investors adopting this technology and traditionalists without the tools to capture and analyse information.
Forward-thinking investment managers could potentially create an information edge in their trading that would put them ahead of their peers and allow them to profit from an ‘information arbitrage’ between their expanded models and those of investment managers following more traditional analytic techniques.
New tools can assess non-standard data
Data-driven investors will have the tools to digest and assess ESG criteria for potential investments, as well as learning from and adapting to constantly changing data.
Nevertheless, technology won’t replace human judgement. The most obvious reason is that technologies are developed by human beings and the ability to adapt them still relies on human expertise. Moreover, in areas such as risk assessment, the qualitative review is as important as the quantitative results — and human innovations can’t be coded and predicted using automation. We are not yet able to predict the future.
Co-authored by Murray Birt, senior ESG strategist, DWS
Principles for Responsible Investments is a UN-linked campaigning organisation committed to keeping market participants posted on the key milestones, industry actions and ESG tools that can help transition portfolios to net zero carbon.
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Global credit funds & CLO's
May 2021 | Issue 234
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