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How will the landscape for ESG tech & data analytics solutions evolve?

Natalie Runyon  Director / ESG content & Advisory Services / Thomson Reuters Institute

· 6 minute read

Natalie Runyon  Director / ESG content & Advisory Services / Thomson Reuters Institute

· 6 minute read

How can companies' ESG initiatives get a boost from available technology and data analytics solutions that could help in areas of transparency and risk mitigation?

The ecosystem of technology and data analytics solutions around environmental, social & governance (ESG) activities is vast and fragmented, yet new developing areas in this landscape continue to emerge.

Before any organization begins the procurement process of what solutions a company may need for its ESG strategy and tools, there are critical elements that first need to be worked through, in order to ensure the best solutions are evaluated and fit for purpose, and that valuable resources are not wasted.

Defining ESG for a specific organization

There are several aspects to the challenge of defining ESG for a specific organization. The first step is to figure out what elements, climate risks, health and safety, and governance structure, of the multitude of possible frameworks best apply to a particular company within a specific sector. Also, it’s necessary to understand what parts from these frameworks could have a materially financial impact on the organization’s operations. For public companies, it is important to go one step further to ascertain each factor’s influence on the company’s overall creditworthiness as assessed by external rating agencies.

“The definitional problem exists within the companies, the rating agencies that seek to judge them, and certainly within the models and the processes of investors who are looking to compare and contrast companies’ ESG risks and opportunities and investment worthiness,” says Andrew Archer, Head of ESG Advisory at European shareholder intelligence advisory firm Investor Update.

Ensure data quality with standard processes, controls & governance — Good data that provides transparency and accountability is critical to any ESG initiative. The challenge, however, is that sources of ESG data can sit across multiple corporate functions in siloed information systems. The richness — yet isolated nature — of that data leads to complexity that complicates information integrity around definition because the data often comes from different sources and is housed on different platforms.

Make it comparable with industry peers — One of the ongoing complaints about ESG from a variety of corporate investors is that a lack of standardization makes it difficult to analyze a point-by-point comparison for investment opportunities. This in turn makes it challenging to determine whether a company within a particular industry is doing a more effective job at reducing ESG risks relative to its competitors.

The data analytics solution

ESG technology and data analytics solutions can be valuable in solving for the ability to extract ESG data from multiple information systems into a common platform and to create the kind of comparative basis for assessing and judging companies that operate in multiple jurisdictions with many business lines across different geographical markets.

Despite the multilayered, convoluted requirements and landscape, ESG is graduating toward the highest common denominator, not the lowest at least from an access-to-capital-markets perspective. And this is a key difference when compared to past financial regulatory and compliance-related endeavors, explains Archer.

Yet, problems in this process remain. The current internal enterprise technology systems and processes being used to collect, analyze, and communicate ESG information are inadequate and need a review, tweaking, or an overhaul. The technology companies claiming to solve a piece of the complexity problem across the ESG landscape remain fragmented, although the technology capability exists.

Below are several examples of technology solutions that taking on some aspect of the ESG data complexity problem.

Follow the capital — Companies too often do not know how to judge their own performance or how to understand where best practices really exists, especially around their ESG information and strategy. As a way to cut through the noise, some solutions can provide transparency into where ESG-related capital is flowing to see how it is being allocated by investors across a specific sector or a set of peers.

For example, a company can see exactly how much capital is being allocated by investors to its competitors or peers through Investor Update’s platform, Archer says. Those companies attracting the most capital from specialist ESG investors are also the ones that demonstrate best-practice ESG disclosure, and it is those behaviors that should be emulated, he adds.

Improve transparency by industry — The corporate legal function plays an important role in a specific company’s ESG strategy and direction. Indeed, the legal team provides advice and contributes to the company’s overall ESG objectives through its internal activities and use of outside legal counsel.

As part of this legal supply chain, the general counsel selects law firms based on fees and skills, now with an ESG lever being factored into the selection process with increased frequency. Law firms are not known for their transparency on ESG, however, due mostly to the difficulty in collecting and comparing information across firms, according to Yannick Hausmann, a former Group General Counsel and co-founder of impactvise.

To increase transparency for the legal industry as a whole, Hausmann and Adrian Peyer, a former in-house counsel executives and current company secretary, created impactvise, a platform that includes a database of publicly available ESG information on more than 1,000 law firms across the globe. The platform also gives users the ability to compare data by geography and peers, using the World Economic Forum’s framework.

By focusing on the legal industry, the platform lets both general counsel and law firms understand where they rank within their peer group on key ESG factors. In addition, it also includes scoring related to “skills of the future” specifically for lawyers, tracks how law firms treat employees and care for employee well-being, and, by using a media sentiment analysis, ensures ESG is more than a branding exercise for the firm. Also, from law firms’ governance perspective, impactvise scores how the firm navigates conflicts of interest and client acceptance policy, according to Hausmann and Peyer.

Mitigate ESG risk — Another area evolving in the ESG data landscape is identifying ESG risk and predicting such risk in the future. For example, a partnership among Kona AI, the Massachusetts Institute of Technology (MIT), and several law firms established Integrity Distributed, a not-for-profit shared technology platform that allows organizations all over the world to contribute their ESG and corruption intelligence as a mechanism to train algorithms to better detect patterns of fraud and corruption in their respective industries. The goal of the collaborative project is to predict improper or corrupt payments with up to 90% statistical accuracy.

The divergence of systems and platforms continues to come market without standardization in mind, but that is improving as the various definitions and frameworks converge. Only time will tell how fast or slow the process of merging occurs, yet the willingness and necessity to create a positive impact will set the pace for change around ESG data analytics going forward.

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