Kpmg LLP

John Hyung Lee

James Johnson Gardner

Timothy J Cerino

Justin Mathew Edwards

Gregory Alexander Vorsanger

Gabriel C Stoenescu

Chenming Xue

Martin Kaestner

Rachel Wagner-kaiser

David Scripka

Steve Rainey

Brian Shea

Matthew Cretcher

Nikhil S Dharap

Rachel A Wagner-Kaiser

Steven Galginaitis

Mitchell Miller

Marc Daniel Allen

Nader Karimi

Jillian Schleicher

Manish U Garg

Rebecca Reitz

Michel Braun

Kallol K Ghosh

Ryan Christopher Soileau

Dylan Kab

David Anthony Scripka

Elliott A Torres

Ricardo Manuel Ramos Dos Santos Neves

The invention relates to computer-implemented systems and methods for identifying and further preventing commercial or contract leakage across multiple different procurement relationships. This may involve ingesting a contract extracting commercial terms, such as price, rates, etc. Invoices may be similarly ingested and commercial terms may be extracted on a line item basis. An embodiment of the present invention may identify various types of commercial leakage, such as rate/price discrepancies, full/partial duplication, unrealized discounts, unrealized rebates, disallowance of charges (travel expenses), etc.

System and method for implementing a commercial leakage platform

The invention relates to a computer implemented system and method for identification of comparables. The method may comprise: receiving input data from a plurality of data sources for a comparable, generating labeled training data for a function classifier by labeling historical search results for comparables, generating probabilistic training data for the primary product and service classifiers, training the primary product and service classifiers using the labeled training data and the probabilistic training data, determining the functions, products, services, and risks of the comparable using the corresponding classifiers, receiving attributes of a tested party, applying a scoring algorithm to calculate a similarity score for the comparable, generating a recommendation to accept the comparable, reject the comparable, or give additional scrutiny to determine acceptability, and automatically providing a written justification for the decision to accept or to reject the comparable.

System and method for identifying comparables

The invention relates to computer-implemented systems and methods for analyzing and standardizing various types of input data such as structured data, semi-structured data, unstructured data, and images and voice. Embodiments of the systems and the methods further provide for generating responses to specific questions based on the standardized input data.

System and method for analysis of structured and unstructured data

The invention relates to computer-implemented systems and methods for analyzing data from a variety of data sources. Embodiments of the systems and the methods further provide for generating responses to specific questions based on the analyzed data, wherein the generating includes: retrieving related documents associated with the analyzed data; determining which information should be reported from which of the retrieved related documents; and providing a response based on the determination and a graph schema associated with the related documents.

System and method for analysis and determination of relationships from a variety of data sources

The invention relates to a computer-implemented system and method for analyzing unstructured data from a plurality of input files, and standardizing the data to a format that can be consumed by downstream systems. The method may comprise the steps of: receiving at least one input file to be analyzed, wherein the at least one input file includes the structured and unstructured data, splitting the at least one input file into a plurality of documents, classifying each page of the plurality of documents as one of structured or unstructured data, parsing the pages of the plurality of documents classified as unstructured data, extracting relevant data from the parsed pages, mapping each of the extracted relevant data to standardized output; and generating canonical data sets based on the standardized outputs.

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Irvine, CA, United States of America

John Hyung Lee