11 May 2021

Deciphering the ESG data deluge

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First an FX trader and later the global head of ESG at Northern Trust, Mamadou-Abou Sarr has first-hand experience of quantitative finance and ESG investing. He believes his new investment firm holds the answer to bringing both approaches together

Environmental Finance spoke with him to see how quantitative approaches can help process the deluge of ESG data.

Environmental Finance: Which ESG data market developments inspired you to set up VSQM?

Mamadou-Abou Sarr, President, V-Square Quantitative Management: In 2020, 74% of the funds in the Morningstar Database were rebranded ESG funds. In addition, you have around 12 million data points across 450 metrics when it comes to ESG data. There is a plethora of data providers and index providers that are building more and more ESG metrics. As such, it is complex for an asset owner or an asset manager to decipher that universe and make investment decisions.

I wanted to build an investment firm that has the power to understand qualitative data but also has the ESG expertise to decipher, harmonise and standardise data. And, on the back of it, make better informed investment decisions.

I have a fundamental belief that profit maximisation, long-termism and sustainable investing can work hand-in-hand. V-Square was built on that premise. And so, we built a specialised sustainable investment firm with a focus on research and portfolio implementation.

EF: How can quantitative finance be applied to deciphering and organising complex ESG datasets?

Mamadou-Abou SarrMS: In the post-2000 era, algorithm and high-frequency trading was the poster child of quantitative finance. The reality is that the algorithmic approach of trading is just one application of quantitative finance. In fact, quantitative finance is a means to an end. It helps us link investment to the financial theory that markets are efficient on average and risk premia can be explained by a set of factors.

The approach we use at V-Square to implement portfolios and apply research is quantitative in nature. Given amount of the ESG data out there, we wanted to use quantitative skills to understand and clean this data and then apply it portfolios in way that delivers better risk-adjusted returns.

We have two tools that achieve this. Firstly, we built a data warehouse called ESGCentral™. It allows us to have access to more than 1000 ESG data points and narrow them down to comparable metrics. This allows us to compare scores from MSCI, Sustainalytics and other providers in a simplified user-friendly interface.
Secondly, we have our reporting capabilities. What doesn't get measured and reported doesn't get addressed. The ability to report will also address the issue of greenwashing or greenwishing.

EF: Are you utilising AI to organise and collate the data?

MS: AI is one way to do it. I think AI will have a strong application going forward in the ESG world, especially when it comes to unstructured data. A lot of data in the ESG space tends to be disclosure information taken from corporate social responsibility (CSR) reports. These often come in different forms, shapes and languages. AI allows us to get the data from different sources, put them in a certain format and then apply them to a score or any type of methodology.

In addition, we have an open architecture platform. It is probably the highest cost we have at V-Square. We thought that the best way to understand the field was to acquire datasets, clean and compare them and assess their materiality. It took along a long time for us access all the data points and build ESGCentral™, but it has turned out to be a very handy and powerful tool for us and our clients.

EF: How can better harmonisation of standards and reporting help with understanding datasets?

MS: We've seen attempts by Sustainability Accounting Standards Board (SASB) and others to create standardised reporting frameworks and I commend this. Standardisation simplifies the metrics and enables us to compare stocks using the same baseline. If you have multiple systems and frameworks, it is extremely hard to organise them and understand which one is more relevant. The TCFD framework has demonstrated that the more these entities work together the easier it is for asset owners and asset managers to make investment decisions.

EF: Do you think the integration of material sustainability factors needs to be intentional to achieve targeted impacts?

MS: Intentionality is the starting point of everything. ESG managers have not always been intentional in their design of portfolios or methodologies. Many have used ESG as a marketing tool or as a way to make ex-post claims. In this scenario you could still end up with a good ESG score because you hold the right stocks but, if it's not intentional and it's not part of your investment process or ESG policy, you are unlikely to sustain and remain truly ESG relevant.

V-Square was built with intentionality. We merged our quantitative skillset with our ESG expertise and, in fact, the first policy we wrote was our ESG policy. That says it all. It is very difficult for an old firm to claim that they started with ESG in mind but that is exactly what we did at V-Square.

Sponsored by

Contact: V-Square Quantitative Management LLC
Social media handles:
Twitter: @VSQUANT @mamadouabousarr

Phone: +1312-872-7281
Email: info@vsqm.com

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