Time
1 month
Location
USA
Sector
FinTech
Description
Our client faced the formidable task of managing an extensive dataset consisting of corporate earnings conference call transcripts in XML format. Each transcript contained multiple sessions, making the need for topic extraction and analysis crucial.
Solution
To address this challenge, our team devised a bespoke LDA (Latent Dirichlet Allocation) model, tailor-made to accommodate the client’s dataset. Leveraging this model, we analyzed thousands of documents and developed a system capable of pinpointing topics within earnings calls. We further streamlined this system with a user-friendly interface, designed to enhance navigation and provide clear visualizations of topics and statistics.
Results
The outcome of our efforts was a fully automated system that seamlessly identified topics across a massive volume of earnings call records. This system revolutionized our client’s analysis process by significantly reducing manual analytical work and enhancing overall efficiency.