Patents by Inventor Hayden Jeune

Hayden Jeune 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: 20230377053
    Abstract: Described embodiments relate to determining a candidate financial record associated with a transaction between a first accounting entity and a second entity, and determining, using a numerical representation generation model, a numerical representation of the candidate financial record, the numerical representation generation model having been trained on a corpus generated from historical transaction records. The method further comprises providing, to a transaction attribute prediction model, the numerical representation of the candidate financial record, the transaction attribute prediction model having been trained using a dataset of previously reconciled financial records, each associated with a respective first transaction attribute; and determining, by the transaction attribute prediction model, at least one first transaction attribute associated with the candidate financial record.
    Type: Application
    Filed: June 16, 2022
    Publication date: November 23, 2023
    Inventors: Delia Rusu, Hayden Jeune, Rebecca Dridan, Soon-Ee Cheah, Brett Calcott, Zhimin Wang, Quentin-Gabriel Thurier, Fubiao Qin, Niklas Patrick Pechan
  • Publication number: 20230123072
    Abstract: Described embodiments relate to determining a candidate financial record associated with a transaction between a first accounting entity and a second entity, and determining, using a numerical representation generation model, a numerical representation of the candidate financial record, the numerical representation generation model having been trained on a corpus generated from historical transaction records. The method further comprises providing, to a transaction attribute prediction model, the numerical representation of the candidate financial record, the transaction attribute prediction model having been trained using a dataset of previously reconciled financial records, each associated with a respective first transaction attribute; and determining, by the transaction attribute prediction model, at least one first transaction attribute associated with the candidate financial record.
    Type: Application
    Filed: December 20, 2022
    Publication date: April 20, 2023
    Inventors: Delia Rusu, Hayden Jeune, Rebecca Dridan, Soon-Ee Cheah, Brett Calcott, Zhimin Wang, Quentin-Gabriel Thurier, Fubiao Qin, Niklas Patrick Pechan
  • Patent number: 11610271
    Abstract: Described embodiments relate to determining a candidate financial record associated with a transaction between a first accounting entity and a second entity, and determining, using a numerical representation generation model, a numerical representation of the candidate financial record, the numerical representation generation model having been trained on a corpus generated from historical transaction records. The method further comprises providing, to a transaction attribute prediction model, the numerical representation of the candidate financial record, the transaction attribute prediction model having been trained using a dataset of previously reconciled financial records, each associated with a respective first transaction attribute; and determining, by the transaction attribute prediction model, at least one first transaction attribute associated with the candidate financial record.
    Type: Grant
    Filed: May 20, 2022
    Date of Patent: March 21, 2023
    Inventors: Delia Rusu, Hayden Jeune, Rebecca Dridan, Soon-Ee Cheah, Brett Calcott, Zhimin Wang, Quentin-Gabriel Thurier, Fubiao Qin, Niklas Patrick Pechan
  • Publication number: 20220351302
    Abstract: Described embodiments relate to determining a candidate financial record associated with a transaction between a first accounting entity and a second entity, and determining, using a numerical representation generation model, a numerical representation of the candidate financial record, the numerical representation generation model having been trained on a corpus generated from historical transaction records. The method further comprises providing, to a transaction attribute prediction model, the numerical representation of the candidate financial record, the transaction attribute prediction model having been trained using a dataset of previously reconciled financial records, each associated with a respective first transaction attribute; and determining, by the transaction attribute prediction model, at least one first transaction attribute associated with the candidate financial record.
    Type: Application
    Filed: June 16, 2022
    Publication date: November 3, 2022
    Inventors: Delia Rusu, Hayden Jeune, Rebecca Dridan, Soon-Ee Cheah, Brett Calcott, Zhimin Wang, Quentin-Gabriel Thurier, Fubiao Qin, Niklas Patrick Pechan
  • Publication number: 20220198581
    Abstract: Described embodiments relate to determining a candidate financial record associated with a transaction between a first accounting entity and a second entity, and determining, using a numerical representation generation model, a numerical representation of the candidate financial record, the numerical representation generation model having been trained on a corpus generated from historical transaction records. The method further comprises providing, to a transaction attribute prediction model, the numerical representation of the candidate financial record, the transaction attribute prediction model having been trained using a dataset of previously reconciled financial records, each associated with a respective first transaction attribute; and determining, by the transaction attribute prediction model, at least one first transaction attribute associated with the candidate financial record.
    Type: Application
    Filed: March 11, 2022
    Publication date: June 23, 2022
    Inventors: Delia Rusu, Hayden Jeune, Rebecca Dridan, Soon-Ee Cheah, Brett Calcott, Zhimin Wang, Quentin-Gabriel Thurier, Fubiao Qin, Niklas Patrick Pechan