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StarMine Text Mining Credit Risk Model

An overview of StarMine Text Mining Credit Risk Model 

StarMine Text Mining Credit Risk Model (TMCR) assesses the risk in publically traded companies by systematically evaluating the language in Reuters News, StreetEvents conference call transcripts, corporate filings (10-K, 10-Q, and 8-K), and select broker research reports to predict which firms are likely to come under financial distress and which are likely to thrive. It is a percentile ranking (1-100) of stocks, with 100 corresponding to the healthiest companies.

At the core of StarMine TMCR is a classic “bag of words” text mining algorithm. A bag of words text mining algorithm breaks a document into its constituent words and phrases and establishes relationships between the frequencies of these words and phrases and a known training variable, such as observed defaults.

Key Facts 

  • Geographical coverage
  • History
    From 1998
  • Data format
    User Interface
    Zip Archive
  • Delivery mechanism
    Deployed/Onsite Servers
  • Data frequency

Features & Benefits

What you get with StarMine Text Mining Credit Risk Model 

  • TMCR identifies key language from multiple text sources to turn raw textual data into credit scores.
  • TMCR model each document source independently and then combine to create an overall probability of default.
  • TMCR applies sophisticated text mining algorithms to identify language that is predictive of credit risk.

How it works

 Accessing the dataset

This dataset can be used by the following products. Talk to us to learn more about different packages and offerings.

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