ESG 2.0 – a solution to slow moving ESG scores

Julia Asri Meigh, Head of ESG and Macro Research (New York)

Neudata Intelligence
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With 90% of today’s data created in the last two years, opportunities to leverage vast amounts of unstructured data sources are growing at an exponential rate. The proliferation of AI and big data is transforming the ESG industry – providing investors with a greater supply of more timely information and the ability to develop more sophisticated investing strategies. Alternative data is the driving force behind ESG 2.0.


The problem
Company ESG scores are commonly updated every 3-12 months. These scores are often based on self-reported information which the issuer is required to disclose on an annual basis. In short, outdated datasets can lag behind the speed and timeliness of important information that influences investment decisions.

The solution
The development of alt data has resolved many of the issues of timeliness in slow moving ESG scores – giving the investment community a greater supply of high frequency ESG datasets. In particular, using AI and machine learning to aggregate relevant sustainability information from unstructured data sources now provides more timely ESG risk signals.
At Neudata, we work with a number of high frequency providers of ESG information. Outlined at the end of this report are a few of our data partners that provide ESG data at a daily frequency or higher.

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