Here are 5 examples of how corporations and investors can use Amenity's NLP to systematically understand how ESG factors in the news drive company performance, with an unbiased dataset built around transparency and granularity.

By
Amenity Analytics
|
July 23, 2020

5 Use Cases for NLP in ESG

Technology
5 Use Cases for NLP in ESG

Environmental, Social, and Governance (ESG) factors are increasingly relevant in investing, operational, and purchasing decisions. Amenity's natural language processing (NLP)systematically evaluates and quantifies the materiality of ESG in the news with an unbiased dataset built around transparency. Investors can use Amenity's NLP to understand how ESG events drive company performance, drilling down to the specific sentences that our NLP tags as material— well ahead of when this information is furnished in a company's reported information or is revealed by the market. Amenity delivers these insights via dashboards or APIs integrated into internal systems, with the option for customization.

Credit Rating Agency

Amenity created a custom ESG-NLP Model to parse text for research purposes, using client press releases to identify when ESG events are cited as material credit drivers. The model captures client-specific ESG taxonomy, including a broad range of qualitative considerations. These considerations relate to the sustainability of an organization and to its broader impact on society relative to its business practices, investments, and activities. Examples include conversation around a company’s carbon footprint and the accountability of a company’s management or a nation’s government. The enriched research content helps to facilitate conversations with regulators.

Sell Side Bank

Amenity worked with a research team on a custom ESG-NLP Model to analyze 10 years of content that had previously not been examined using a sustainability framework. In single- and multi-entity research, our model extracted material ESG conversations related to themes like Human Capital and Corporate Transparency. Through this proprietary data set,the research team were able to find meaningful evidence of a positive relationship between institutions’ ESG profiles and monetary returns.

Media Company

Working with the Impact Advertising team at a leading media company, Amenity created an ESG tracker on news for their key accounts, allowing the team to track the sentiment around clients before and after impact campaigns. The ESG tracker empowered their sales force to react quickly to emerging ESG risks faced by their accounts, create targeted pitches to accounts with negative sentiment, and validate their campaigns by systematically tracking news.

Sustainability Investor 1

A sustainability investor approached Amenity because they worried about missing important ESG information in news — information that wasn’t being captured in company disclosures or by survey-based data providers. The investor leveraged Amenity’s off-the-shelf ESG analytics to track their portfolio, learning in real-time when material ESG conversations were taking place in the news sources that mattered to them. Previously the investor would comb through all news that contained a set of ESG terms and mentions of their portfolio companies. Now, Amenity points them to the riskiest articles every day, helping to target their research.

Sustainability Investor 2

A savvy investor with a sustainability mandate asked Amenity for next-generation ESG datasets. The investor had been consuming data from several other providers, but wondered what insights were being overlooked. Working with Amenity, the investor was able to backtest our Deception signal, a proxy for management transparency created by looking at clarity in Q&A on Earnings Calls. The results showed outsized returns for companies with consistently low deception (high clarity). Amenity is now working to create similar datasets for further testing.

This communication does not represent investment advice. Transcript text provided by S&P Global Market Intelligence.

Copyright ©2020 Amenity Analytics. 

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