Enhancing ESG measurements leveraging alternative data
Social Bonds : A significant financing opportunity amid the pandemic
Introduction
Data helps businesses improve their decision- making through accurate and faster analytical models. This, in turn, improves risk management, driving performance to new heights. It is no secret that data can be used to quantify metrics in several areas or categories within a business, including the most basic ones (such as revenue or customer satisfaction) and the most complex ones ESG metrics).
In this whitepaper, we discuss and analyse the evolution and importance of ESG for businesses. We also propose an alternative, more robust, approach to measure the metrics, implementing different artificial intelligence (AI) programmes and natural language processing (NLP). Additionally, we present a case study from China and highlight how this can be practical, fruitful, and advantageous for other countries and businesses around the world.
Defining ESG – Evolution and importance
The ultimate goal of these metrics is to measure all non-financial risks and opportunities inherent in a company’s daily activities. Additionally, ESG resembles a framework for assessing the impact of a company’s operations within these three areas (environment, social and governance). ESG was not considered essential for companies when it originated, but it became a ‘nice-to-have’ metric when the first socially responsible investing attitudes emerged in the 1960s and 1970s. During these years, companies equated excellence and good performance with financial and monetary results, ignoring secondary consequences detrimental to society and the environment.
The push for ESG nowadays is driven by the fact that investors seek companies that not only focus on monetary results, but also are socially responsible and sustainable. These three pillars constitute an effective mechanism to ascertain how truly companies are committed to these areas and their ability to integrate them in their strategic decision-making. Firms are prioritising ESG, as it has been proved to increase resiliency, reduce risks and attract and retain not only clients but also investors in the long run.
How can alternative data help analysts quantify ESG aspects?
Technological advances have revolutionised the way we leverage data in various areas, including ESG. The emergence of advanced AI programmes has enabled data transformation beyond ESG, allowing companies to understand their ESG performance in a more robust way. New qualitative approaches use NLP to identify ESG themes from sources outside ESG reports, such as news and social media.
By creating these themes, companies can leverage data analytics to gains perceptions about their performance from different areas such as whether or not they have a strong governance, how much they support their communities, how committed they are to sustainable finance, how customer focused is their approach, and other categories that can give a wider analysis on how to achieve their ESG objectives.
Alternative data through AI and NLP allows to close this gap via a two-step process. This process was presented by the Data Bricks platform in 2020 in a blog called ‘A Data-driven Approach to Environmental, Social and Governance.
Conclusion
In conclusion, every company should provide the same weightage to ESG as financials and accounting. ESG works as a tool for one principal objective – a company’s sustainability over time. Companies should leverage AI and NLP to build an alternative and more-data-driven approach in order to calculate their ESG score.
How can Acuity Knowledge Partners help?
By deploying a team of data scientists and data engineers, Acuity can help clients use alternative data to better understand ESG performance of different areas within their company. The data engineers can build a framework and a data-driven ESG score so that companies do not solely act upon their own perception of their ESG performance, but also take into consideration external opinions, making the process more transparent and robust.
After the framework creation, data scientists can gather and analyse data to integrate actionable insights into a presentation to help clients identify their strengths and weaknesses. Acuity also provides support in identifying and monitoring emerging ESG trends and unearthing potential risks and opportunities using alternative data sources including news, social media and traditional ESG reports. Given Acuity’s expertise and experience in this space, clients will have access to more robust data and be better equipped to make data-driven decisions and gain a competitive edge.
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