Leverage a proprietary NLP engine to gain accurate and precise sentiment analysis for earnings transcripts. Analyze summary data such as the document's total sentiment score, event counts by polarity, and totals by sections including Q&A, Prepared Remarks and Overall commentary. Detailed data such as event names in each section, number of events by polarity and related sentiment score is also available.
Uncover detailed information about business events in financial documents that are easily missed by traditional analysis methods. Gain a robust set of company identifiers, event names, their polarity, and type of entities included in the event. Integrate output seamlessly with existing workflows.
Customize the NLP engine for specific needs. Amenity Analytics works closely with clients to analyze, design and build specific signal requirements by combining Amenity’s proprietary NLP models with the text mining Insights Engine to create a robust suite of contextual analytics. Leverage a custom API to transform unstructured data into structured datasets of stock-specific analysis and sentiment tied to business events. Import insights into a variety of tools such as Tableau, Excel and SFDC.
Transform unstructured data into a structured set of themes and overall sentiment scoring that's more powerful and accurate than a sentiment score alone. Using FactSet’s Events & Transcripts data, Amenity Analytics' Thematic Sentiment APIs allow investors to categorize earnings calls and other forms of unstructured financial data into meaningful insights. These APIs apply sentiment analysis and classify clients’ data into dozens of unique events such as margin commentary, employment, and capacity. Further categorization allows users to navigate data by sections such as Q&A, Speakers and Key Drivers.
Amenity Analytics' NLP Platform uses Artificial Intelligence to empower businesses to draw actionable insights from text on a massive scale. With domain expertise in the financial sector and customizable to any strategy or industry, Amenity analyzes regulatory filings, earnings call transcripts, news coverage and research reports or internal documents. Information in text is pinpointed and then delivered in effective formats that are intuitive to use and designed to enhance existing workflows.