Now more than ever, investors have priorities beyond just profit and earnings potential alone. As sustainability and social changes continue to be at the forefront of decision-making for many, ESG strategies, such as environmental, social, and governance, will keep gaining momentum in the coming years. With a record amount of inflows to ESG funds in 2021 and a 42% growth rate between 2018 and 2020, this investment strategy is here to stay.
As ESG investing strategies become more popular, there is a growing need among financial professionals for tools and quality data to make informed investments decisions based on ESG insights. Since most information in the financial services industry is qualitative rather than quantitative, sentiment analysis can help asset managers quickly gain insights on the latest developments and make investment decisions accordingly.
Challenges to ESG investing
Despite its growing popularity and record-breaking 2021, some challenges remain in the space. For finance professionals, ESG-related data and information are not universal or easily accessible, which can be a barrier to implementing the strategy. Plus, what qualifies as an ESG factor often varies between countries or regions.
While becoming more normalized in the finance world, ESG investing is still not the primary strategy utilized by most investors. There is a common misconception that investments made on ESG criteria will mean sacrificing potential returns, though this hasn't proven true. As of November of 2021, the MSCI World ESG Leaders' index had risen 22% year-to-date, compared to the World Index's 15% growth.
Additionally, given that performance is a significant indicator for investment professionals, it is often difficult to concretely measure ESG factors and their progress within a specific company. Thus, it can be challenging for firms that utilize an ESG-focused strategy to show clients the positive impacts of their investment. With this, many have critiqued current ESG investing practices, noting that the focus has been too narrow on the easily measurable and comparable topics rather than the complex subjects that have a more long-term and systemic impact.
The Importance of Data for Sentiment Analysis
Most companies aren't fully transparent about their social or environmental initiatives and the measurable impact of such strategies. This ambiguity poses a challenge for investment firms as they are flooded with information and left to sort out what is material and what isn't. Add to this the constant flow of news stories and quarterly filings by companies, and it becomes impossible for one person to process all the information themselves.
Through artificial intelligence (AI) and natural language processing (NLP), financial services firms can quickly sift through all the noise in the data to identify only the essential points and make informed decisions using ESG criteria. Investors need to make quick but informed decisions to prosper and stay competitive, and it's easy to let a vital item slip through the cracks without using helpful tools like AI.
Like other finance industry sectors, news sentiment plays a significant role in ESG investing and forecasting future price movements. Sentiment analysis is helpful for investors who need to stay up-to-date on all emerging news stories and require actionable data to make decisions. AI can help identify relevant news stories, determine the slant, and forecast potential stock movements based on text analysis that uncovers sentiment.
Significance of Sentiment Analysis for ESG Investing
As ESG investing becomes more prevalent in the industry, the flow of information and relevant news articles in the space will only increase in magnitude. This volume of data makes sentiment analysis invaluable, as it enables automated analysis and reveals the most essential and relevant pieces. Investors can use sentiment classification to extract insights and make informed investment decisions quickly.
Analyzing Data
One of the main challenges investors face when utilizing an ESG strategy is the lack of standardized data and the barriers to accessing relevant data sets. Plus, given the qualitative and subjective nature of many ESG factors, it can be difficult for finance professionals to effectively and efficiently analyze all the data available and gather meaningful insights.
AI and sentiment analysis tools can help process large amounts of data related to ESG factors and analyze news and announcements from specific companies that meet the ESG screening criteria. Investors can benefit from sentiment analysis by reducing the hands-on time required to read through each news story while still obtaining transparent and comparable data on ESG factors to stay competitive and relevant in today's industry.
Sentiment Scores
When using sentiment analysis to assess a company and its ESG factors, investors can easily see the news sentiment or tone among stakeholders from millions of available data pieces worldwide, including social media posts, news stories, press releases, interviews, etc. Sentiment analysis can analyze each of these pieces and determine the consensus emotion or tone.
The algorithm can determine whether the piece is positive, negative or neutral, to which degree, and the pattern of such sentiments by scoring the text data. This capability is extremely helpful in sustainable investing and can give a quantitative value to unstructured data like news stories and analyst opinions. Firms can compare companies, perform due diligence and forecast future stock movements. Overall, sentiment analysis helps investors find lucrative investment opportunities based on ESG criteria.
ESG Signals
To make informed and meaningful ESG investments, finance professionals need a way to identify markers within companies to measure against their ESG criteria and invest accordingly. With most of the data and information in the field unstructured and subjective, it is often challenging to create standardized or universal signals to qualify companies.
With AI and sentiment analysis, firms can more easily turn news stories, reports, and filings into quantitative data and signals that can be analyzed and compared across companies and industries. With a lack of readily available data in the field, investors can have an upper edge over competitors when using AI to capture the news sentiment on a company, determine how they measure up to ESG criteria and make informed investment decisions.
Using No-Code AI To Analyze News Sentiment for Better ESG Insights
Looking ahead, ESG factors will become even more of a priority among investors over the coming decade. Now seen as a requirement for most asset managers to stay competitive, firms need a quick and easy way to implement sentiment analysis into their operations and support their ESG strategy. Through AI, they can extract insights, identify investment opportunities, and stay competitively related to ESG.
Through the use of no-code AI solutions, investors don't need to hire a data specialist or software engineer to reap the benefits of sentiment analysis in their firm. Like the solution offered by Accern, no-code AI can help determine the news sentiment around recent developments or announcements and let investors quickly sift through the piles of data available to make informed investment decisions. To see how your ESG strategy could benefit from sentiment analysis, contact Accern for a free demo today.
