How much can you save clients by knowing weeks earlier of emerging issues?

The city of Selma, Alabama experienced a credit rating drop by S&P Global Ratings in 2018.

Download this case study and learn:

  • How Bitvore knew there was trouble months before Selma's credit rating was downgraded by S&P Global Ratings.
  • The reported indicators leading up to the rating change that Bitvore captured and weighed.
  • How municipal and economic precision news using AI and machine learning algorithms drive predictive analytics. 

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    Discover our approach to making predictions using massive amounts of precision news data

Bitvore AI surveils all U.S. muni obligors and provides early warnings on material changes.

Sifting through an overabundance of news and other unstructured data sources in real-time is a huge challenge. In this case study:

  • Learn how you can use our AI platform to monitor and analyze hundreds of thousands of articles a day
  • Learn how to simplify the research process from 10 hours down to as little as 10 minutes 
  • Learn how our research reveals trends and educated predictions 
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MEET SOME OF OUR CUSTOMERS

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optum grey
charles grey
suntrust grey
blackrock grey
bam grey
ubs grey
s&p grey

By harnessing the power of data collection, Natural Language Processing (NLP) and other AI techniques, our customers can glean insights into emerging issues with municipal obligors (and associated muni bonds at the CUSIP level).

We are often asked for examples of how we use
precision news data to predict material changes when we explain how our customers use our data.

In this case study, we outline 15 weeks of warning headlines leading up to Selma's credit downgrade. Revealing trends included:

  • Layoffs
  • Declining Revenue 
  • Economic Outlook
  • And More...
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Make better decisions, faster

Making sense of massive amounts of unstructured data from news and other sources is complicated. Our approach to sifting, cleansing and organizing all of that data helps our customers make business decisions simpler.