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.

Abstract: A system for generating and inferencing using enterprise knowledge graphs is provided. The system receives first input data related to one or more entities from one or more data sources. The system extracts a first set of data components from the first input data and determines, based upon the extracted data components, a second set of data components. The system identifies one or more relationships between the first set of data components and the second set of data components and generate a knowledge graph comprising a plurality of nodes. A first node of the knowledge graph can represent a first respective data component of the first set of data components and a second node of the knowledge graph can represent a second respective data component of the second set of data components. The first node can be associated with the second node based on an identified relationship between the nodes.

Abstract: Provided herein are methods and systems for identifying a related data values in a plurality of datasets. The method can include extracting data from the plurality of datasets, identifying potential linking categories, and determining a validity of the potential linking categories. One or more linking categories can be selected from the potential linking categories based on the validity, and related data values can be identified between the plurality of datasets based on the selected linking categories. Also provided herein are methods and systems for classifying data values as reconciled or non-reconciled. The method can include identifying a plurality of related data values in a plurality of datasets. For each of the plurality of related data values, a similarity score and confidence score can be determined, and the plurality of related data values can be classified as reconciled or non-reconciled based on the similarity score and/or the confidence score.

Abstract: Provided herein are methods and systems for determining a roll forward amount. The method can include identifying a starting balance, extracting reconciled data values from a database, each reconciled data value having a confidence score that indicates a confidence level that a reconciled data value of a first dataset is the same as a corresponding reconciled data value of a second dataset. The method can include identifying a first subset of the reconciled data values that are a first type and a second subset of the reconciled data values that are a second type, and determining a roll forward amount based on the starting balance, the first subset, and the second subset.

Abstract: Provided herein are systems and methods for decentralized privacy preserving audits comprising receiving by a first local system, from an orchestrator system, instructions to perform a local audit; executing, by the first local system, in response to receiving the instructions to perform the local audit, a first local audit model epoch, wherein executing the first local audit model epoch comprises: analyzing information from one or more data sources from a local data set; receiving first input information from a second local system through a privacy preserving communication framework in response to requesting the first input information; determining whether information from the one or more data sources from the local data set is reconciled based on the first input information; and in accordance with a determination that the information from the one or more data sources from the local data set is not reconciled, executing a second local audit model epoch.

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.

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.

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.

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.

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.