Pwc Product Sales LLC

Anand Srinivasa Rao

Chung-Sheng Li

Joseph David Voyles

Winnie Cheng

Bo Li

Yifeng Wang

Samuel Pierce Burns

Scott Likens

Yuan Wan

Nancy Alayne Lizotte

Kevin Ma Leong

Mark John Flavell

Shaz Hoda

Ratna Raj Singh

Vishakha Bansal

Lori Marie Hallmark

Amitoj Singh

Zhen Qi

Mansi Arora

Ali Rusta-sallehy

Luisa Breidt

Jeffrey Kevin Dicker

Kazi Islam

Di Zhu

Matthew Lawrence Messina

Timothy Delille

Siddhesh Shivaji Zanj

Maria Jesus Perez Ramirez

An entity trust index relating to an entity may indicate a trustworthiness level of the entity. To generate an entity trust index, entity information may be received from one or more information sources. Using the entity information and one or more machine learning models, a performance index, an innovation index, and a sustainability index for the entity may be generated. The entity trust index may be generated based on the performance index, the innovation index, and the sustainability index. One or more actions for the entity that will modify the entity trust index may then be determined.

Systems and methods for measuring trust

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.

AI-augmented auditing platform including techniques for automated document processing

System and methods for generating synthetic data according to a plurality of options are provided. According to a first option, synthetic data is generated based on an indication of one or more target distributions. According to a second option, a one or more target distributions are determined based on a sample data set, and synthetic data is generated based on the determined target distribution(s). According to a third option, a temporary synthetic data set is generated based on an indication of one or more target distributions, matches between the temporary synthetic data set and a sample data set are then identified, and a synthetic data set is then generated based on the identified matches. A system may automatically determine which option to leverage based on whether a user provides a sample data set, one or more target distributions, or both.

Systems and methods for generating synthetic data

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Boston, MA, United States of America

Anand Srinivasa Rao