Sustainable investing is no longer a niche subject but has in recent years increasingly been discussed as a regular item on the financial agenda. A growing number of investors are looking to harmonize their investments with their values and have a real positive impact, fueling the need for credible quantitative approaches in both sustainable investing as well as impact measurement. In this article, we research the transformations in quantitative sustainable finance methods by categorizing those changes, clarifying why they are necessary, and describing their directions.
The Rise of Sustainable Investing
Sustainable Investing — ESG (Environmental, Social, and Governance) The adoption of sustainable investing is accelerating faster every day. In 2020, sustainable investing assets expanded to $35.3 trillion worldwide — a rise of 15% as per the Global Sustainable Investment Alliance (GSIA) from its previous value in on end-2018. In this one-pager, you will find how there is an increased appetite for more sophisticated and advanced tools to evaluate the impact of investments in a way that goes beyond traditional financial metrics.
Quantitative Approaches in Sustainable Investing
1. ESG Scoring and Rating Systems
ESG scoring is one of the most common quantitative tools used in sustainable investing. Many different providers, such as MSCI and Sustainalytics or the ESG rankings of S&P Global, have developed elaborate methods to evaluate companies based on their environmental, social & governance performance. These scores usually sum up several data points in each of a variety of categories, and the whole shebang gets passed through multiple weighted algorithms to generate one final number.
ESG scores also have weaknesses, despite being a useful starting point. Ratings may vary greatly between providers as their methodologies can differ considerably. Moreover, the use of self-reported data and a continuous struggle to quantify qualitative factors leads to many biases and inaccuracies.
2. Carbon Footprint Analysis
An increasingly important performance measure is the carbon footprint because it has been put into focus by investors as they try to assess climate change. This method is based on the greenhouse gas emissions of a company’s operations, supply chain, and products. Developed by investors to assess climate-related risks and opportunities in investment portfolios.
Improved satellite imagery, artificial intelligence (AI), and big data analytics are making carbon footprints measurable with greater accuracy at much higher resolution or ‘granularity.’ One of these AI-powered platforms is Cervest, helping the asset-level investor assess physical climate risks.
3. Impact Measurement and Management (IMM)
In order to calculate the impact an investment has on society and the environment, IMM frameworks exist. The Impact Management Project (IMP) has created a five-dimensional framework for measuring impact: What, Who, How Much, Contribution, and Risk.
In the case of IMM, quantitative techniques commonly involve defining precise deliverables in line with KPIs and SDGs (Sustainable Development Goals) set by the United Nations. A clean energy investment might measure megawatt-hours of renewable energy produced and tons of CO2 emissions abated, for example.
4. Natural Language Processing (NLP) for ESG Analysis
While sustainability-related data is exploding, enabling natural language processing (NLP) techniques is a crucial tool for handling and interpreting unstructured text records from corporate reports, news articles, or social media. However, these algorithms can recognize ESG-related themes, sentiments, and controversies that are likely to elude traditional ESG ratings.
TruValue Labs (now part of FacSet) for instance leverages NLP to better understand the qualitative detail with millions of points daily, allowing real-time ESG insights that can supplement or challenge company-reported data.
Challenges and Future Directions
While there has been some good work done, many challenges remain in the development of rigorous quantitative approaches to sustainable investing.
Data Quality and Standardization: Without question, one of the major challenges remains the absence of delineated consistent quality ESG data. Organizations such as the Sustainability Accounting Standards Board (SASB), and Task Force on Climate-related Financial Disclosures (TCFD) have set out to make standards more robust but their mainstream adoption would be a process in itself.
Materiality – Identifying what ESG factors are financially material to different industries and companies is hard. Using the SASB Materiality Map as a starting point is strategic but there are many other factors to consider and novel research still needs to be done on how ESG drivers translate into monetary results.
Only Publicly Marketed Impact Attribution: Public market social impact is less easily captured, as the direct reflection of investment also remains relatively difficult to measure. This type of detailed attribution results in more meaningful information for measuring the effectiveness of specific marketing investments and is an important direction for future research.
Incorporating Alternative Data: With the growth in new types of data such as satellite imagery, and IoT sensors integrating these disparate streams into consistent ESG and impact assessments presents key opportunities and pitfalls.
AI & Machine Learning: The use of clunky AI and machine learning algorithms for sustainable investing is beginning to take shape, but it still has a long way to go. They can help reveal more complex patterns and relationships from ESG data that human analysts might not identify.
Conclusion
These are not the end of quantitative sustainable investing and impact measurement by any means, but neither is it an easy lift. With better data quality, more advanced methodologies in place, and the continuous advancement of new technologies, sustainability criteria will be assessed with even greater precision on all levels.
Investors should stay on top of these rapidly evolving quantitative tools. Of course, the full complexity of environmental performance cannot be captured by any one approach above and beyond careful examination from a qualitative point of view; however, combining multiple quantitative methods could result in offering complementary views on risks as well as opportunities related to sustainable investing.
Integration of quantitative sustainability metrics with conventional financial analysis is expected to follow fairly soon as the discipline consolidates. The new system will be more sustainable, resilient, and ready to live up to the challenges in this 21st-century world.