A global research and consulting firm was looking for ways to automate part of their process for monitoring a wide range of signals about thousands of companies on behalf of their clients. This process, which includes ESG assessments, opportunity identification, risk management, and competitive intelligence, traditionally required a large team of analysts to manually read English language news stories about the companies. The consulting firm was looking for a way to identify more relevant signals and free up analysts' time for higher value tasks.

To achieve these objectives, the consulting firm worked with Dcipher Analytics to deploy customized text analytics workflows that collected millions of news articles about the companies of interest in many different languages from all over the world. 

AI was used to identify predefined signals about the companies and to automatically summarize the corresponding events. By using unique zero-shot learning techniques, signals could be identified without the need for large volumes of annotated training data, saving a lot of time that would otherwise have been required to train models for text classification. 

The results were delivered daily via email as an auto-generated Excel report with all the relevant information.

The use of Dcipher Analytics' automated text analytics workflows allowed the consulting firm to identify more relevant signals than previously possible. Additionally, the automation of this process freed up the time of analysts, allowing them to focus on higher value tasks. Overall, the deployment of Dcipher Analytics' workflows helped the consulting firm to more efficiently and effectively monitor signals about the companies of interest.