Tackling the data challenge in ESG investing
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The growing popularity of ESG investing
Investors worldwide are keen to put their investments to greater benefits, which explains the surge in environmental, social, and governance (ESG) investments, in addition to those in exchange-traded funds (ETFs) and sectoral categories such as technology and banking.
Investors’ interest in ESG funds is due to the growing awareness about environmental, social, and corporate governance issues – this offers them the opportunity to be a part of initiatives around ecological protection, social welfare, and good governance.
ESG assets saw significant expansion in Q4, 2021, relative to Q3 with ESG funds following a similar increasing trend. Stocks of companies classified as ESG investments rated highly for their sustainability efforts have shown considerable appreciation. Various benchmarks such as MSCI ESG Leaders Index have also shown increased gains in the past one year.
ESG stocks are hot, but there are complexities
The lack of data transparency, inadequate availability, inconsistency, and data costs pose significant challenges in ESG investing.
ESG data – ESG ratings and disclosures – helps investors decide how they should invest in sustainability initiatives. However, there are some challenges that need to be addressed, which are:
Although ESG investing offers a lot of potential benefits for investors and enterprises, there are a few initial hurdles to overcome for widespread adoption. To address these challenges, it is necessary to look at relevant technology interventions, stakeholder-specific solutions, and regulatory frameworks.
An overview of the stakeholders in ESG investing
Data needs and challenges are dependent on the type of stakeholders.
Given the diverse needs of the various stakeholders in the ESG investing space, it is unwise to follow a one-size-fits-all approach while designing data solutions.
Following are the key stakeholders whose data needs merit consideration during solution design:
Technology has a key role to play
Technologies such as blockchain, artificial intelligence (AI), the internet of things (IoT), and natural language processing (NLP) can address the challenges pertaining to ESG data and enable the availability of data in near real time.
While blockchain solutions can bring transparency, accuracy, availability, and consistency to ESG data, applying AI to unstructured data will improve the reliability of ESG reporting. AI-driven sentiment analysis could address many of the shortcomings in ESG measurement. Financial firms can use AI to analyze a broad range of categories of underlying data in order to understand the risk of exposure to specific ESG factors. For example, Sensefolio tracks and assess over 30,000 companies on their ESG initiatives with the help of NLP techniques and ML algorithms.
NLP can analyze unstructured information such as articles, categorize items, and extract positive and negative sentiments to produce an array of ESG metrics.
IoT and drone technology will drive better monitoring of ESG assets and aid in collection and reporting of ESG metrics with far more accuracy – this will help in smart monitoring of various parameters such as carbon footprint.
Regulations will help
The Sustainable Finance Disclosure Regulation (SFDR) is a European regulation that aims to improve transparency in the market for sustainable investment products.
The SFDR will prevent greenwashing and lend transparency to the sustainability claims made by financial market participants.
This regulation lays down harmonized rules for financial market participants and financial advisors with regard to the following:
Additionally, the SEC has introduced new rules to enhance and standardize climate-related disclosures for investors. The UK has introduced climate-related financial disclosure requirements that will be part of the annual reports of publicly quoted companies and large private companies.
Firms that offer innovative solutions around ESG reporting and analytics will certainly have an edge over their competitors.
ESG investing is sure to gather steam in the coming decade, which is why it is crucial to bring consistency in data collection and reporting globally. Technology interventions, regulations, and stakeholder-specific solutions are the three focus areas that this transformation will be wrapped around.
It is imperative for countries and firms across the globe to collaboratively define a common ESG framework and use technology to address the data challenges in ESG investing.