AI is a great source of insights to drive more informed decisions about investments and in particular to spot ESG risks in the market.
The first big benefit of using AI within an ESG analysis dwells on the Sustainability Report analysis that can be automated using AI and text recognition.
But the biggest advantages of AI stands in the possibility to overcome the lack of ESG data. Indeed, AI can be used in analyzing the market to understand how a company is behaving compared to what it disclosed about itself and to discover why data are possibly missing.
The main challenge is to manage such a huge volume of data: extracting, categorizing and summarizing relevant information from unstructured data.
Here are a few examples of the places from where these information are retrieved:
- Mainstream News
- Vertical News
- Social media
- Forums and product reviews
- Financial and non Financial statements
- Corporate Websites/CRM/ e-commerce Call center data
A news-driven ESG analysis allows investors to be always up to date. It’s a very dynamic approach where news about any company’s impact on Environment, Social and Governance issues is collected every day, helping stakeholders to shape a very accurate portrait of the company they are likely to invest in.
This very summarized advantages in using AI within ESG research, is exactly what Finscience is aiming to build with its proprietary automated ESG solution. Thanks to a proprietary algorithm and a transparent use of AI, Finscience retrieves about 1.5 Million web pages every day from 35.000 different domains.
Unlike the multi-source approach, and thanks to the NLP latest technologies, it is possible to determine which specific events have determined a variation in the risk signal. Transparency is a key aspect in the sustainability analysis and in the risk management for investments.
The ESG framework
In order to better address the different ESG areas and granularity we have built a proprietary ESG Framework. This is a set of rules and procedures aimed at guiding the processes of collection, aggregation and representation of all information related to the world of ESG. The subdivision of the classic pillars of the ESG (Environmental, Social and Governance) responds to all the critical areas of sustainability, with the aim of enclosing in one place, all the information available and necessary for an ESG analysis can be complete and easy to understand.
A materiality map is then used for the score association to the single layer based on the sector the company is involved.
FinScience ESG monitoring & risk alerting and reporting
FinScience clients get access to a monitoring dashboard, report or CSV where they keep track of daily ESG news and risk alerts (high negative sentiment events)
- for Financial institutions related to the companies they have under coverage or in their portfolio;
- and for Corporates and their peers.
For analysis and reporting purposes, FinScience also offers quarterly reports by merging news and proprietary data with internal information (website analysis, sustainability report, membership).