Insights

At Aneuvia, we believe in democratizing financial wellness and investment advice for the betterment of companies, communities and individuals. Here we share our insights, point of view and advice on global impact investing, corporate diversity and inclusion, new financial market trends, impact investment funds and more. 

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Bridging the Gap Between “hard” and “soft” ESG Data
Posted by Janelle Metzger

A recent survey completed by the Chartered Financial Analysts (CFA) Institute found that “valuation approaches lack consistency, and investment professionals report various ways of incorporating ESG into equity analysis.” 

It’s no secret that investors struggle with assessing the impact of their ESG investments as a result of unverified, opaque, and incompatible measurement frameworks. Many businesses have acknowledged and even embraced the U.N. General Assembly’s Sustainable Development Goals (SDGs) and often include their version of reporting in an annual Corporate Sustainability Report or company disclosure. However, not all ESG factors are created equally. So how can investors weigh ESG data to make informed and socially conscious investments?  

Understanding the differences between “soft” and “hard” data.

The CFA’s report goes on to give a distinct classification between “soft” and “hard” ESG data. Hard ESG data is available in the traditional format, is easily quantifiable, and can be readily plugged into valuation models. On the other hand, soft data is qualitative and challenging to capture in the investment decision-making process.  

At Aneuvia, we compensate for the inevitable task of working with potentially critical hard and soft ESG data points by taking quantitative and qualitative approaches to ESG integration.  

From a quantitative standpoint, we rely on Bloomberg’s proprietary scores built on the foundation of a business’s ESG disclosures. In addition to collecting data from corporate filings and Carbon Disclosure Project disclosures, Bloomberg also conducts an ESG survey which is derived from a quantitative model that minimizes noise, size bias, and disclosure gaps.  

ESGHardandSoftDataFrom a qualitative standpoint, we procure data from Sustainalytics, which calculates an overall percentile rank assigned to a business based on its ESG total score relative to its industry competitors. We also draw insights from S&P Global’s SAM, which evaluates companies on sustainability criteria within ESG factors.  

Continued ESG success will hinge heavily on better data, transparency, governance, and accountability. By setting up a global ESG data measurement framework, investors can measure, monitor, and manage the impact generated by their portfolio.  

Understanding the ESG Data Value Chain
Posted by Janelle Metzger

Environmental, Social and Governance (ESG) metrics are not part of mandatory financial reporting, however, investors are increasingly applying these factors to their analysis in order to identify material risks and growth opportunities. As part of the ESG data value chain, the following three factors are key for investors: 

  • Negative screening refers to the exclusion of companies and certain sectors based on ethical, social, environmental, or religious factors. Most commonly, exclusionary strategies avoid investments in companies that are fully or partially involved in gambling, alcohol, child labor, human rights violations, tobacco, and other related factors. 
  • Positive screening involves the inclusion of companies due to the social or environmental benefits of their products, brand value, leadership team, or processes. Investors place a ‘premium’ on these ‘best in class’ businesses which ultimately increases their value. 
  • Shareholder engagement and proxy voting leverage shareholder rights to drive progressive change in investee company behavior. They can often be drivers of success, transparency, and accountability, resulting from a demand for better ESG-related disclosures and effective social and environmental impact.

In our latest report, ESG Data, Impact Criteria and Measurement, we map out the ESG data flow from companies to investors - from collection, processing, and assessment to usage.  

ESGDataValueChain

Benchmarking, data ubiquity, and quality are acknowledged as barriers to ESG analysis. In fact, a recent survey completed by the Chartered Financial Analysts (CFA) Institute found that “78% of practitioners surveyed believe there is a need for improved standards around ESG products to mitigate greenwashing… greenwashing means conveying a false impression or providing misleading information or a misleading narrative about how a company and its products are environmentally sound or positive in an ESG context.”  

Without a source of truth or rubric of success, investors are left having to independently assess ESG disclosures, despite disparities in data availability, timeliness, quality, methodology, or even ESG definitions. The self-reporting nature brings the credibility of ESG data into question.  

We are optimistic that cohesive, methodical reporting and transparency are on the horizon. Armed with a standardized data framework, investors will be able to make smart, informed, and socially responsible financial decisions - the holy grail of ESG.

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