Palantir Technologies Inc.

Tom O'Brien

Peter Maag

Maciej Albin

Sarun Peter Tosirisuk

Phil Cross

Greg DeArment

Carl Freeland

Matthew Lynch

Phillip Worton-Cross

Alexis Daboville

Christopher Stokes

Saad Abdali

Naytri Shroff

Peter Tosirisuk

Suran Peter Tosirisuk

Various systems and methods are provided that allow reviewers to review and potentially flag processed communication data in order to spot potential malfeasance or illegal activity. Certain systems and methods includes modules for removing duplicate data from the communication data files, generating thread data for email data files, generating lexicon tag data for the data files, removing blacklisted data that meets blacklisted criteria, or generating group association data.

Communication data processing architecture

In various embodiments, systems, methods, and techniques are disclosed for generating a collection of clusters of related data from a seed to assist in detection of financial malfeasance. Seeds may be generated based on seed generation strategies or rules. Clusters may be generated by, for example, retrieving a seed, adding the seed to a first cluster, retrieving a clustering strategy or rules, and adding related data (such as trades, emails or chat messages) and/or data entities to the cluster based on the clustering strategy. Various cluster scores may be generated based on attributes of data in a given cluster, and the clusters may be displayed and ranked based on their scores. Various embodiments may enable an analyst to review clusters of trades, emails and/or chat messages that are the most likely to reveal financial malfeasance.

Systems and user interfaces for dynamic and interactive investigation based on automatic malfeasance clustering of related data in various data structures

Embodiments of the present disclosure relate to a data analysis system configured to implement cross-application coordination between a chart creation tool and a data analysis workspace, in order to create one or more charts from customized sets of data points, synchronize chart manipulations between charts, and drill down into the metadata of data points in the created charts. The user uses the data analysis workspace to select, remove, or cherry-pick data items to be used to create a chart, which may be transmitted from the workspace to the chart creation tool as data points. In addition, the user may select the data points in the chart to retrieve one or more identifiers to be transmitted back to the workspace, where they are used to identify the data items associated with the data points, and retrieve the full metadata of the data items.

System and method of generating data points from one or more data stores of data items for chart creation and manipulation

Clustering data based on indications of financial malfeasance

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New York, NY, United States of America

Tom O'Brien