ESG REPORTING
The Importance of ESG Reporting
Investors’ appetite has progressed far beyond just increasing profits. In recent years, societal impact influencing a company's competitive edge and business reputation has emerged as an important consideration for evaluating investment opportunities. Top management is expected (and soon, in the US, will be required by the SEC) to report on a variety of Environmental, Social, and Governance (ESG) metrics. These ESG characteristics, i.e. diversity and sustainability, climate change and environmental risk factors, help investors decide how to deploy their capital according to their sustainable investments’ criteria. Additionally, companies also tie compensation metrics to ESG goals, making accurate ESG reporting even more important. Below is a breakdown ESG metrics by category according to Equillar research.
Market players, such as investment banks, private equity firms, lenders, banks among others, use corporate sustainability reporting to inform a wide range of decisions. Investors want a direct access to ESG data so they can evaluate it to their own standards. This, in turn, has put forth the need for more standardized ESG data. However, traditional data collection techniques, aren't always the best option. They can be costly, manually intense and time-consuming.
An Existing ESG Framework
Disclosure standards and frameworks, including those provided by the Sustainability Accounting Standards Board (SASB) and Global Reporting Initiative (GRI), are at the center of the ESG ecosystem.
Framework: a set of principles and guidance for how a report is structured.
Standards: specific, replicable and detailed requirements for what should be reported for each industry.
Information producers and information users are interested in the disclosure of comparable, consistent, and reliable ESG information. Using this information, industry participants can build tools, analytics, and resources for the capital markets.
ESG Data Collection & Reporting
ESG reporting will necessitate the analysis of complicated metrics derived from unstructured data sources that, in some circumstances, have yet to be identified. These reports must be simple to share and update in real time with fresh data; they need to contain customized ESG metrics suitable for a specific type of investment being evaluated. Thus, a flexible, yet powerful tool capable of sourcing and connecting diverse pieces of unstructured data into a coherent whole is absolutely necessary for any investor seeking an information edge over its peers.
Corporate Governance Assessment - ESG Scorecards
Advanced tools can be applied to automating a large volume of what could otherwise be manual data processing. For example, time spent analyzing the diversity scorecard data elements, such as gender, age, race of company boards and senior management can be cut by on average 80% with the help of AI and Machine Learning tools.
Video Robotic Process Automation
Most lenders and investment management firms develop proprietary ESG Scorecards. The process of populating the scorecard is often manual and time-consuming. As ESG is becoming a mainstream reporting requirement, the challenge of reporting both standard and custom metrics needs to be solved. Data science and video robotic process automation tools will provide a viable solution.