Patents by Inventor Lori Marie HALLMARK

Lori Marie HALLMARK has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20230004590
    Abstract: Systems and methods for adjudicating AI-augmented automated analysis of documents in order to quickly and efficiently make various adjudications based on the documents are provided, including adjudications as to whether the documents represent underlying data that meets one or more predefined or dynamically-determined criteria. Criteria for adjudication may include commercial-substance criteria, related-party-transaction criteria, and/or collectability criteria. A system may receive a plurality of documents and generate a plurality of feature vectors by applying natural language processing techniques. The system may apply one or more classification models to the plurality of feature vectors to generate output data classifying each of the feature vectors. The system may identify, for each feature vector, a subset of closest matching prior feature vectors.
    Type: Application
    Filed: June 30, 2022
    Publication date: January 5, 2023
    Applicant: PricewaterhouseCoopers LLP
    Inventors: Chung-Sheng LI, Winnie CHENG, Mark John FLAVELL, Lori Marie HALLMARK, Nancy Alayne LIZOTTE, Kevin Ma LEONG
  • Publication number: 20230004888
    Abstract: A system for generating risk assessments based on a data representing a plurality of statements and data representing corroborating evidence is provided. The system receives data representing a plurality of statements and data representing corroborating evidence. The system applies one or more integrity analysis models to the first data and the second data in order to generate an assessment of a risk that one or more of the plurality of statements represents a material misstatement. A system for generating an assessment of faithfulness of data is provided. The system compared data representing a statement to data representing corroborating evidence, and generates a similarity metric representing their similarity. Based on the similarity metric, the system generates an output representing an assessment of faithfulness of the first data set.
    Type: Application
    Filed: June 30, 2022
    Publication date: January 5, 2023
    Applicant: PricewaterhouseCoopers LLP
    Inventors: Chung-Sheng LI, Winnie CHENG, Mark John FLAVELL, Lori Marie HALLMARK, Nancy Alayne LIZOTTE, Kevin Ma LEONG
  • Publication number: 20230005075
    Abstract: Systems and methods for determining whether an electronic document constitutes vouching evidence is provided. The system may receive ERP item data and generate hypothesis data based thereon, and may receive electronic document data and extract ERP information therefrom. The system may then apply one or more models to compare the hypothesis data to the extracted ERP information to determine whether the electronic document constitutes vouching evidence for the ERP item. Systems and methods for verifying an assertion against a source document are provided. The system may receive first data indicating an unverified assertion and second data comprising a plurality of source documents. The system may apply one or more extraction models to extract a set of key data from the plurality of source documents and may apply one or more matching models to compare the first data to the set of key data to determine whether vouching criteria are met.
    Type: Application
    Filed: June 30, 2022
    Publication date: January 5, 2023
    Applicant: PricewaterhouseCoopers LLP
    Inventors: Chung-Sheng LI, Winnie CHENG, Mark John FLAVELL, Lori Marie HALLMARK, Nancy Alayne LIZOTTE, Kevin Ma LEONG, Di ZHU, Kevin Michael O'ROURKE, Eun Kyung KWON, Vandit NARULA, Weichao CHEN, Maria Jesus Perez RAMIREZ
  • Publication number: 20230004845
    Abstract: Systems and methods for providing explainability for processing data through multiple layers are provided. An input layer is configured to receive an evidence data set comprising a plurality of evidence items, apply evidence processing models to the evidence data set to generate evidence understanding data, and generate input-layer explainability data, wherein the input-layer explainability data represents information about the processing of the evidence data set by the input layer. A presentation layer is configured to receive data (the evidence understanding data and/or data generated based on the evidence understanding data), apply one or more presentation generation models to the received data to generate presentation data, and generate presentation-layer explainability data for presentation to the user, wherein the presentation-layer explainability data represents information about the processing of the received data set by the presentation layer.
    Type: Application
    Filed: June 30, 2022
    Publication date: January 5, 2023
    Applicant: PricewaterhouseCoopers LLP
    Inventors: Chung-Sheng LI, Winnie CHENG, Mark John FLAVELL, Lori Marie HALLMARK, Nancy Alayne LIZOTTE, Kevin Ma LEONG, Kevin Michael O'ROURKE, Robert Michael HILL, Timothy DELILLE, Maria Jesus Perez RAMIREZ, Thomas Vincent GIACOMUCCI
  • Publication number: 20230004604
    Abstract: Systems and methods for automated document processing for use in AI-augmented auditing platforms are provided. A system for determining the composition of document bundles extracts substantive content information and metadata information from a document bundle and generates, based on the extracted information regarding a composition of the document bundle. A system for validating signatures in documents extracts data representing a spatial location for respective signatures and generates a confidence level for respective signatures, and determines, based on location and confidence level, whether signature criteria are met. A system for extracting information from documents applies a set of data conversion processing steps to a plurality received documents to generate structured data, and then applies a set of knowledge-based modeling processing steps to the structured data to generating output data extracted from the plurality of electronic documents.
    Type: Application
    Filed: June 30, 2022
    Publication date: January 5, 2023
    Applicant: PricewaterhouseCoopers LLP
    Inventors: Chung-Sheng LI, Winnie CHENG, Mark John FLAVELL, Lori Marie HALLMARK, Nancy Alayne LIZOTTE, Anand Srinivasa RAO, Kevin Ma LEONG, Di ZHU, Timothy DELILLE, Maria Jesus Perez RAMIREZ, Yuan WAN, Ratna Raj SINGH, Vishakha BANSAL, Shaz HODA, Amitoj SINGH, Siddhesh Shivaji ZANJ