Most unstructured data is in textual form from sources such as emails, transcripts, articles and documents. These text files are usually difficult, time-consuming and expensive to analyze and utilize. S&P Global identifies primary sources of textual information that can be parsed and structured for ease of use, bypassing the entire process of sourcing, cleansing and maintaining the data, while enabling metadata tagging and linking to other datasets such as financials and estimates.

The Textual Data Suite includes:

• Machine Readable Transcripts: Sourced from earnings calls of 11,600+ companies.
• SCRIPTS Asia Transcripts: Japanese transcripts from often closed, invite-only financial calls and briefings.
• Textual Data Analytics: Sentiment Scores & Behavioral Metrics: Sentiment and behavioral scores derived from NLP and transcripts.
• Machine Readable Filings: Textual portions of public filings, inclusive of 10K's and 10Q's, and Global Annual Reports broken down into the various sections by company.
• Machine Readable Broker Research: Unlocks the value within equity research reports by cleansing and parsing reports to deliver structured text from partner brokers for Natural Language Processing (NLP) analysis.
• RatingsXpress®: Research: S&P Credit Research proprietary commentary and analysis for global issuers, public finance, and structured finance in a machine readable format.