Brendan Bradley - ESG Investing For Dummies

Millennials, those youngsters born between 1981 and 1996, are part of the generation entering their prime earning years. Numerous surveys have indicated that the vast majority of high net worth (HNW) millennials consider a company’s ESG track record before investing, or alternatively they want to tailor their investments to their personal values. This reflects a need for their money to not just earn a decent return but to contribute to the social good and how it impacts society and the planet at large.

Why is that important? Millennials are a large demographic, representing about 25 percent of the world’s population and a greater percentage of the workforce now and into the future. Moreover, this group is due to inherit a large amount of wealth as their parents, the baby boomers, pass on their considerable nest eggs. Furthermore, surveys have suggested that wealth management firms typically lose more than 70 percent of assets when they are transferred from one generation to the next. Subsequently, asset managers that offer millennials ESG investment options will be well positioned to attract new assets as well as retain beneficiary millennial clients.

So, millennials will require more active involvement in their investments, as they need to feel they are controlling their own destiny, and consequently they will have more activist tendencies. They are interested in ensuring that their financial return is linked to positive, or at least not unduly negative, environmental and social impact. In summary, while ESG investing will be used to create a competitive advantage, asset managers have to adopt socially responsible practices to continue gaining business in the investment industry.

As the significance of the ESG market has grown, the financial industry has evolved the definitions of which ESG factors are relevant and how they can be applied to the performance of a company. Using this more informed data from companies, combined with enhanced ESG research and analytics capabilities, the industry is producing more systematic, quantitative, impartial, and financially applicable approaches to highlight the core ESG factors.

In turn, this has generated more research that advocates a better understanding of ESG investing and resultant data points to feed the new AI approaches to filter unstructured data through Natural Language Processing (NLP) and Machine Learning (ML) to drive predictive analytics (find more information on this later in this chapter). There are tens of thousands of company issuers and hundreds of thousands of equity and fixed-income securities — combined with an increasing array of ESG ratings and metrics — to be considered when identifying the risks and opportunities within a portfolio.

ESG ratings are used to evaluate how far companies have integrated and applied ESG factors into the management of their business, and these evaluations are then used as part of the investment process when deciding what securities to buy. Different industry providers have developed different approaches to how they score ratings for their solutions, but they all need to fundamentally consider the following issues:

Identify the most material ESG risks and opportunities that a company and its industry are facing. (I cover materiality earlier in this chapter.)

Quantify how exposed a company is to those key risks and opportunities.

Determine how well a company is managing the key risks and opportunities.

Conclude what the overall picture for a company is and how it compares to similar companies within its sector or geographical region.

This allows an objective consideration of any negative externalities that companies in an industry may face, and highlights potential, unforeseen costs apparent in the mid to long term. Equally, understanding negative externalities should help emphasize ESG factors that present opportunities for companies in the mid to long term. This section highlights the metrics around ESG and hones in on some of the “good, bad, and ugly” issues relating to how data is applied. Chapter 14has even more information on ratings and metrics.

ESG ratings are still evolving. Keep in mind that they rely on limited and sometimes misleading disclosures by companies, which themselves are learning the ropes as to how they should report their ESG exposure. So, as with traditional securities analysis, the analysis of any data can be subjective because the selection and weighting of data points is qualitative. Historically, investors have questioned the inherent bias that has been displayed by ratings agencies or the recommendations of securities analysts, and ESG ratings will face similar scrutiny as they develop further. ESG data providers generally develop their own sourcing, research, and scoring methodologies.

Therefore, individual ESG ratings aren’t comparable across providers, due to a lack of standardization of the objective criteria required. As a result, the rating for a single company can vary widely across different providers. Moreover, there are differences in how providers obtain and purchase raw data that’s released by the company or publicly disclosed. Data providers also use statistical models to generate approximations for unreported data. These models are based on norms and tendencies from comparable companies and established benchmarks. As such, investors are integrating convictions from the data provider into their investment procedures.

To be fair to the data providers, some of the differences in methodology are also due to the different priorities of their customers — the asset managers and asset owners that subscribe to their services — who have different investment objectives. This exacerbates the difficulties in standardizing an approach.

ESG data providers perform a significant part of the investment procedure by collecting and assessing information about companies’ ESG practices and scoring them appropriately. The expansion of these ratings systems has helped to encourage the growth of ESG investing by providing asset owners and managers with an alternative to managing such widespread due diligence themselves. There are more than 100 ESG data providers, which include well-known suppliers such as Bloomberg, FTSE, MSCI, Sustainalytics, Refinitiv, and Vigeo Eiris, as well as focused data providers such as S&P’s Trucost (providing carbon and “brown revenue” data) and ISS (corporate governance, climate, and responsible investing solutions). Investors increasingly view material ESG factors as being essential drivers of a company’s capacity to produce sustainable long-term performance. In turn, ESG data is growing in importance for investors’ ability to assign capital effectively.

Despite the significant contributions that data providers have achieved in evolving ESG investing, asset owners and managers should understand the intrinsic limitations of this data, as much as the challenges of relying on any one data provider.