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Data analytics and statistical modeling

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The value of data is heavily reliant on how it is gathered, processed, stored, analyzed, and interpreted. Bates White has long recognized this and continuously invests in its people and its infrastructure to maintain the highest quality data analytics and statistical modeling capabilities, even as data expand exponentially in both scale and complexity.

We have extensive experience analyzing large and complex data sets and are adept at extracting the most compelling evidence from them. Clients have leveraged our expertise to help secure favorable settlements and substantial damages awards in litigation and to make informed decisions in non-litigation settings, such as fraud detection, risk assessment, and valuations.

We also have extensive experience supporting clients with electronic discovery where, among other things, we have coupled our expertise in database management with our experience in litigation to identify relevant content within parties’ databases and help counsel to make more targeted requests.


  • TWC Product and Technology, LLC. TWC Product and Technology, LLC, engaged Bates White to analyze more than 30 terabytes of data as part of responding to a complaint filed by the People of the State of California, alleging that The Weather Channel (TWC) mobile app misled users by failing to provide transparent details about how TWC used app users’ location data.

  • ResCap Liquidating Trust actions. On behalf of ResCap Liquidating Trust, a Bates White team extrapolated defect rates and assessed damages arising from various originators’ sale of defective mortgage loans to ResCap. To quantify and allocate damages among the various originators, the team developed a statistical sampling protocol that could be used to reliably estimate defect rates and a large-scale loan-performance database of approximately 2 million loans that could be used to reliably assess the relative performance of originators’ loans.
  • Distribution of cable royalty funds. Bates White was retained on behalf of the National Association of Broadcasters to determine the relative value of copyright owners’ content and the appropriate distribution of approximately $900 million in amassed royalties. In reaching their opinion, the US Copyright Royalty Judges relied heavily on the team’s work, which included an algorithm for categorizing the universe of programming that aired on all US broadcast television stations over a four-year period.

See more about the firm's data science experience on the Data Science and Statistics Practice page.

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