Case Study

A financial services group uses Aicadium’s data extraction model to enable topic modeling and sentiment analysis


A financial services group wanted to develop an automated platform to monitor ESG-related news articles to detect emerging trends and understand which topics are gaining importance over time.


The group uses a Aicadium’s AI-powered media sentiment engine that monitors ESG-related news articles and extracts relevant trending topics from news feeds for different industries. Deployed on Azure cloud, the engine recognises which topics are being discussed, then filters and rates them with a sentiment score.


The ML engine generates a significant increase in user click through rates (CTR) by tailoring fast personalised offerings unique to each customer, through real-time serving of recommendations (sub-30ms) for a seamless user experience. Deployed in weeks, not months, impact on business priorities has happened quickly.

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