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ESG and the Evolution of the Research Process

By Jennifer Djaferis  |  December 6, 2018

Machine learning is shaking up the world of finance. What was once the preserve of technology firms, the financial industry is starting to embrace such advancements in technology, changing the global market landscape forever.

This shift has coincided with another mega trend that we are currently witnessing across finance; the rapidly increasing demand for environmental, social, and governance (ESG) data and products. As more and more corporate sustainability information flows into the market (and as its material value is better understood), machine learning and big data are enabling a new, quantitative approach to ESG. It is opening a new dimension of security analysis, and a new dimension of investing. 

A silent corporate revolution has been re-shaping global markets over the past decade in response to changing framework conditions. Driven by regulatory changes, shifting consumer behaviour, natural resource constraints, and social inequalities, corporations everywhere are striving to move from industrial-era approaches towards cleaner, technology-driven, and socially inclusive business models. The growth of corporate sustainability movements, such as the UN Global Compact and the UN Guiding Principles on Human Rights over the past two decades illustrate this worldwide trend. 

Increase in the Number of Investors Joining the Principles of Responsible Investment

PRI Signatory trends

Era of Transparency

The materiality of sustainability big data being recognized across global markets is nothing short of a data revolution. Transparency itself is becoming a key instrument of change in shifting unprecedented levels of capital towards those companies which consider the interests of all stakeholders. Consider the example of Dr. Bronwyn King, the founder of Tobacco Free Portfolios, who was galvanized to act when she discovered her pension fund was investing in the same cigarette companies that were killing her cancer patients. Over many years of successful lobbying, she has persuaded over 35 Australian superannuation funds that control nearly half the total funds under management to shun tobacco.

Leveraging Technology as a Solution

Coinciding with the emergence of ESG data as a global trend is the ability—through artificial intelligence—to make sense of it on a massive scale. As ESG disclosure becomes an established norm for publicly listed companies, the real value lies in the increasingly sophisticated tools required to analyze increasing volumes of sustainability data.

Quantitative strategies analyze an amount of data that is too vast for any one human mind to grasp, and they are fast replacing and complementing discretionary investment approaches. Today, cutting edge algorithms and machine learning are quickly becoming an investor’s tools of choice, providing the ability to extract financially material information quickly and effortlessly.

By leveraging machine learning, we are able to take an unbiased quantitative approach to the data collection and mapping process. AI compliments the emergence of ESG data as it acts as a sophisticated tool that is required to make sense of data on a vast scale. Further, information which was once disparate, is now understood and applicable with a blossoming variety of solutions.

As it becomes more of a challenge for the human brain to process the growing amount of data available, machine learning will continue to play a key role in complimenting traditional methods in research and investing. 

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Jennifer Djaferis

Director of Client Services, Arabesque

Jennifer is a Director of Client Services for the United States and is based in Boston, Massachusetts. She is responsible for the execution of sales, marketing and business development initiatives for the region.  Jennifer joins Arabesque with significant experience working with institutional clients in North America in both an electronic trading and franchise sales capacities at Goldman Sachs & Co.

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