Patents by Inventor Sumraat Singh

Sumraat Singh 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).

  • Patent number: 10943196
    Abstract: Data from multiple sources may be gathered continuously to perform reconciliation operations. The data items in a first data set may be matched with those in the second data set using a data matching technique. Based on the matching, a confidence score indicative of an extent of match between the data items in the data sets may be generated. Based on the confidence score and predefined thresholds, it may be ascertained if the data items are reconciled. The non-reconciled items in at least one of the first data set and the second data set may be classified in a classification category, based on an artificial intelligence based technique, the classification category being indicative of an explanation of a non-reconciled data item being non-reconcilable. When the data item is not reconciled and classified, the data item is identified as an open item for further analysis.
    Type: Grant
    Filed: July 9, 2018
    Date of Patent: March 9, 2021
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Chung-Sheng Li, Emmanuel Munguia Tapia, Jingyun Fan, Priyankar Bhowal, Mohammad Ghorbani, Abhishek Gunjan, David Clune, Sumraat Singh, Samar Alam
  • Patent number: 10795752
    Abstract: In an example, data, such as, a journal entry in a ledger, to be validated and associated supporting documents may be extracted. Further, an entity, indicative of a feature of the data may be extracted. Based on the extracted entity, one or more probable values for a field of the data may be determined. A probability score may be associated each of the probable values of the field. At least one of the probable values of the field may be compared with an actual value of the field of the data. Based on comparison, a notification indicative of a potential error in the data may generated. The data and historical data associated with the data may be processed, based on at least one of predefined rules and a machine learning technique, to detect an anomaly in the data, the anomaly being related to a contextual information associated with the data.
    Type: Grant
    Filed: June 7, 2018
    Date of Patent: October 6, 2020
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Chung-Sheng Li, Emmanuel Munguia Tapia, Mohammad Ghorbani, Jingyun Fan, Priyankar Bhowal, David Clune, Sumraat Singh
  • Publication number: 20200012980
    Abstract: Data from multiple sources may be gathered continuously to perform reconciliation operations. The data items in a first data set may be matched with those in the second data set using a data matching technique. Based on the matching, a confidence score indicative of an extent of match between the data items in the data sets may be generated. Based on the confidence score and predefined thresholds, it may be ascertained if the data items are reconciled. The non-reconciled items in at least one of the first data set and the second data set may be classified in a classification category, based on an artificial intelligence based technique, the classification category being indicative of an explanation of a non-reconciled data item being non-reconcilable. When the data item is not reconciled and classified, the data item is identified as an open item for further analysis.
    Type: Application
    Filed: July 9, 2018
    Publication date: January 9, 2020
    Inventors: Chung-Sheng LI, Emmanuel MUNGUIA TAPIA, Jingyun FAN, Priyankar BHOWAL, Mohammad GHORBANI, Abhishek GUNJAN, David CLUNE, Sumraat SINGH, Samar ALAM
  • Publication number: 20190377624
    Abstract: In an example, data, such as, a journal entry in a ledger, to be validated and associated supporting documents may be extracted. Further, an entity, indicative of a feature of the data may be extracted. Based on the extracted entity, one or more probable values for a field of the data may be determined. A probability score may be associated each of the probable values of the field. At least one of the probable values of the field may be compared with an actual value of the field of the data. Based on comparison, a notification indicative of a potential error in the data may generated. The data and historical data associated with the data may be processed, based on at least one of predefined rules and a machine learning technique, to detect an anomaly in the data, the anomaly being related to a contextual information associated with the data.
    Type: Application
    Filed: June 7, 2018
    Publication date: December 12, 2019
    Applicant: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Chung-Sheng LI, Emmanuel Munguia Tapia, Mohammad Ghorbani, Jingyun Fan, Priyankar Bhowal, David Clune, Sumraat Singh