Patents by Inventor Ramakrishnan Ponniah

Ramakrishnan Ponniah 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: 11475456
    Abstract: A system for predicting a non-fraud dispute using an artificial intelligence (AI) based communications system is disclosed. The system may comprise a data access interface to receive instructions historical transaction and disputes data from at least one data source associated with an account issuer. The data access interface may also receive incoming transaction data associated with a transaction from at least one data source associated with an account holder.
    Type: Grant
    Filed: October 22, 2018
    Date of Patent: October 18, 2022
    Assignee: ACCENTURE GLOBAL SOLUTIOS LIMITED
    Inventors: Ramakrishnan Ponniah, Rehan Guha, G. B. Balasundaram, Vijay Mahalingam, Freeda Kanickairaj
  • Patent number: 11151573
    Abstract: A device may receive first information relating to a first set of transactions and a first set of chargebacks associated with the first set of transactions; process the first information to generate a processed data set; train a model to perform classification of the first set of chargebacks, where the model is to receive, as input, information relating to transactions and at least one chargeback, and where the model is to output information identifying a classification of the at least one chargeback; receive second information identifying a second set of transactions and a second set of chargebacks associated with the second set of transactions, where the second information is received from multiple, different sources; determine a classification of the second set of chargebacks using the model and based on the second information; and perform an action based on the classification of the second set of chargebacks.
    Type: Grant
    Filed: November 30, 2017
    Date of Patent: October 19, 2021
    Assignee: Accenture Global Solutions Limited
    Inventors: Ramakrishnan Ponniah, Pramod Nair, Ankit Suneja, Rajeev D. Nair
  • Publication number: 20200034842
    Abstract: A system for predicting a non-fraud dispute using an artificial intelligence (AI) based communications system is disclosed. The system may comprise a data access interface to receive instructions historical transaction and disputes data from at least one data source associated with an account issuer. The data access interface may also receive incoming transaction data associated with a transaction from at least one data source associated with an account holder.
    Type: Application
    Filed: October 22, 2018
    Publication date: January 30, 2020
    Applicant: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Ramakrishnan PONNIAH, Rehan Guha, G.B. Balasundaram, Vijay Mahalingam, Freeda Kanickairaj
  • Publication number: 20190164159
    Abstract: A device may receive first information relating to a first set of transactions and a first set of chargebacks associated with the first set of transactions; process the first information to generate a processed data set; train a model to perform classification of the first set of chargebacks, where the model is to receive, as input, information relating to transactions and at least one chargeback, and where the model is to output information identifying a classification of the at least one chargeback; receive second information identifying a second set of transactions and a second set of chargebacks associated with the second set of transactions, where the second information is received from multiple, different sources; determine a classification of the second set of chargebacks using the model and based on the second information; and perform an action based on the classification of the second set of chargebacks.
    Type: Application
    Filed: November 30, 2017
    Publication date: May 30, 2019
    Inventors: Ramakrishnan Ponniah, Pramod Nair, Ankit Suneja, Rajeev D. Nair