Updated Investverte Data Is Now Integrated Into CSRHub’s Ratings
Investverte aims to combine the best modelling practice and pragmatic approaches to ensure a high quality and robust results through in-house Advanced AI and Machine learning tools. By analyzing a both conventional and unconventional data, the company seeks to continuously improve its practices and outputs.
We work with several machine learning/deep learning based data sets. They all have low correlations with both CSRHub’s scores, the scores of the “major” ESG rating sources, and with each other! InvestVerte is comfortable with being “different” because it has shown that its ratings can generate positive investment returns.
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To make AI generate robust data, Investverte adds strong controls and checking. It also layers human input onto the output of its learning models. This generates feedback that continuously improves the model and its connection to what matters to investors. (CSRHub uses similar Big Data-driven feedback to improve its connection the consensus view of a wide range of stakeholders.)
Perhaps because of its focus on investor needs, Investverte’s “ratings” have never had a high correlation with CSRHub’s outside-in, stakeholder-perception driven scores. Its rating also do not have a high correlation with those of “major” ESG investment data sets or with those of other AI-driven system.
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Investverte recently decided to revise and further strengthen its approach. In particular it sought to use deep learning to help fill in missing data.
We have long seen missing data as one of the ESG data area’s biggest weaknesses. Many of the data sets we work with are 80% empty at the indicator level. When they try to generate scores off these “empty” indicators, they generate consistency issues that are hard to manage.
Fortunately, our big data aggregation system is able to integrate a disparate signal such as the one Investverte generates and use it to fill in and strengthen our overall ratings. Adding new voices—especially ones with a unique perspective—is what CSRHub’s system is built to do.
About CSRHub
CSRHub provides decisive ESG data to reduce risk, improve ESG reporting, strengthen brand and manage stakeholders, using authoritative sustainability metrics and data harmonized from key investor sources (i.e., MSCI, ISS, S&P Global), and hundreds of other ESG experts.
CSRHub provides ESG ratings, benchmarking tools, and data feeds that support:
- Benchmarking to improve ratings
- Supply chain and vendor assessment
- Regulatory readiness
- Investment and risk analysis
- Academic and research applications
If you are interested in using CSRHub data for research, reporting, or analytics, please contact us or explore our tools and data offerings on our website.
About Investverte
Machine learning–based, InvestVerte provides ESG scores, benchmarking, and portfolio arbitrage. Advances in technology continue to expand and enhance the world of ESG and sustainability data. ESG integration goes hand in hand with best investment practices, and keeping a long-term goal in view is important — especially given the several challenges and barriers along the way. Learn more: https://www.investverte.com/
Bahar Gidwani is CTO and Co-founder of CSRHub. He has built and run large technology-based businesses for many years. Bahar holds a CFA, worked on Wall Street with Kidder, Peabody, and with McKinsey & Co. Bahar has consulted to a number of major companies and currently serves on the board of several software and Web companies. He has an MBA from Harvard Business School and an undergraduate degree in physics and astronomy. He plays bridge, races sailboats, and is based in New York City.