April 25, 2022
RavenPack’s ESG Controversy Scoring framework is based on real-time detections of events across 40,000+ news sources in 13 different languages.
Forming a comprehensive view of a company’s sustainability profile is a genuine challenge. Sustainability data mostly comes in unstructured formats that are difficult to consume systematically, which makes the relevant sustainability signals often go unnoticed by practitioners. As investors are increasingly relying on data-driven processes to achieve scale and efficiency across ESG applications, addressing the data challenge has become the foundational step in any long-standing ESG strategy.
RavenPack’s ESG Controversy Scoring framework is based on real-time detections of events across 40,000+ news sources in 13 different languages. It follows an event-based approach that can help assess the extent of a firm’s ESG controversy exposure through time by monitoring real-time news coverage.
The approach is based on RavenPack’s event detection capabilities, making the process fully transparent down to the news article. In comparison, packaged ratings from major rating agencies rely on relatively opaque analyst views that are much slower to react to novel news events.
RavenPack’s full event taxonomy is extremely granular and contains nearly 7,400 events, grouped into topics, groups, types, subtypes, and categories, which allows us to achieve high specificity in the measure of controversies. We have identified 171 events from our event taxonomy that represent ESG-related controversies of various degrees.
Download the whitepaper for details on our model, and case studies that highlight its advantages in terms of transparency and timeliness.
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RavenPack’s ESG Controversy Scoring Framework is based on real-time detections of events across 40,000+ news sources in 13 different languages. It follows an event-based approach that can help assess the extent of a firm’s ESG controversy exposure through time by monitoring real-time news coverage.