Patents by Inventor Joshua A. Allbright

Joshua A. Allbright 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: 20200211021
    Abstract: A computing system for detecting fraudulent payment card network events includes a ratio striping engine that receives scored payment card transaction authorization requests and generates data structures for a plurality of account ranges. Each data structure sorts the transaction authorization requests within the associated account range over a plurality of fraud score range stripes. The data structures are parsed over time periods that extend back from a common starting point. For each data structure and time period, at least one cumulative metric is calculated from the transaction authorization requests in each fraud score range stripe. For each data structure, ratio striping values are determined between values of the at least one metric in a fraud score range stripe over two of the time periods. A fraud event associated with at least one of the account ranges is detected based on the ratio striping values for the corresponding data structure.
    Type: Application
    Filed: December 28, 2018
    Publication date: July 2, 2020
    Inventors: Joshua A. Allbright, Christopher John Merz
  • Publication number: 20200211022
    Abstract: A method and system for detecting fraudulent network events in a payment card network by incorporating breach velocities into fraud scoring models are provided. A potential compromise event is detected, and payment cards that transacted at a compromised entity associated with the potential compromise event are identified. Subsequent transaction activity for the payment cards is reviewed, and a data structure for the payment cards are generated. The data structure sorts subsequent transaction activity into fraud score range stripes. The data structure is parsed over a plurality of time periods, and at least one cumulative metric is calculated for each of the time periods in each fraud score range stripe. A plurality of ratio striping values are determined, and a set of feature inputs is generated using the ratio striping values. The feature inputs are applied to a scoring model used to score future real-time transactions initiated using the payment cards.
    Type: Application
    Filed: December 28, 2018
    Publication date: July 2, 2020
    Inventors: Joshua A. Allbright, Amudhan Venkatesan, Felix Johannes Flory, Christopher John Merz
  • Publication number: 20200211019
    Abstract: A method and system for detecting fraudulent network events in a payment card network are provided. A plurality of scored payment card transaction authorization requests are received, originating from a plurality of merchants, and at least one data structure is generated. The data structure sorts the scored authorization requests into fraud score range stripes. The data structure is parsed over a plurality of time periods, and at least one cumulative metric is calculated for each of the time periods in each fraud score range stripe. A plurality of ratio striping values is determined, and a set of feature inputs is generated using the ratio striping values. A second fraud detection model is applied to the scored authorization requests. Parameters of the second fraud detection model are configured to change based on the generated set of feature inputs.
    Type: Application
    Filed: December 28, 2018
    Publication date: July 2, 2020
    Inventors: Joshua A. Allbright, Christopher John Merz
  • Publication number: 20200211020
    Abstract: A method and system for detecting fraudulent network events in a payment card network are provided. A plurality of scored payment card transaction authorization requests are received, originating from a plurality of merchants, and data structures for each of a plurality of merchant groups are generated. Each data structure sorts the scored authorization requests into fraud score range stripes. The data structures are parsed over a plurality of time periods, and at least one cumulative metric is calculated for each merchant group for each of the time periods in each fraud score range stripe. A plurality of ratio striping values is determined for each merchant group, and a set of feature inputs is generated using the ratio striping values. A second fraud detection model is applied to the scored authorization requests. Parameters of the second fraud detection model are configured to change based on the generated set of feature inputs.
    Type: Application
    Filed: December 28, 2018
    Publication date: July 2, 2020
    Inventors: Joshua A. Allbright, Christopher John Merz
  • Patent number: 10346376
    Abstract: A database management (DM) computing device for reducing an amount of data stored within an enhanced database while ensuring that data remaining within the enhanced database is able to satisfy a plurality of user queries is described. The DM computing device is in communication with the enhanced database and a secondary storage database. The DM computing device is configured to receive a log data file identifying a number of times each data field in the enhanced database has been queried, rank the data fields based on the number of times each data field has been queried, and identify least-queried data fields from the ranked data fields, wherein the least-queried data fields are defined by rules in a memory. The DM computing device is also configured to store in the secondary storage database the least-queried data fields from the enhanced database, and remove from the enhanced database the least-queried data fields.
    Type: Grant
    Filed: November 2, 2016
    Date of Patent: July 9, 2019
    Assignee: MASTERCARD INTERNATIONAL INCORPORATED
    Inventors: Srinivas Kosaraju, Hima Bindu Nagisetty, Jeffery David Hiatt, Joshua A. Allbright
  • Publication number: 20190188722
    Abstract: A common point of purchase (CPP) system for identifying a common point of purchases involved in fraudulent or unauthorized payment transactions is provided. The CPP system includes a common point of purchase (CPP) computing device that is configured to receive transaction data, store the transaction data in a database, and perform a look up within the database. The CPP computing device is also configured to build a merchant table, receive a card list, and compare a plurality of flagged account identifiers in the card list to account identifiers in the merchant table. The CPP computing device is further configured to retrieve a unique merchant identifier and/or a merchant name identifier associated with the merchant table account identifiers matched with the flagged account identifiers, aggregate the unique merchant identifier using the merchant name identifier, and determine a first number of the flagged account identifiers associated with the merchant name identifier.
    Type: Application
    Filed: December 15, 2017
    Publication date: June 20, 2019
    Inventors: Joshua A. Allbright, Christopher John Merz
  • Publication number: 20190188716
    Abstract: The methods described herein are configured to obtain a first record pattern associated with the unidentified entity and select a second record pattern associated with an entity identifier of a known entity. Based on the first record pattern matching the second record pattern, the entity identifier of the known entity is associated to the unidentified entity to indicate that the unidentified entity and the known entity are the same. Determining the entity identifier of the unidentified entity enables the linking of separate identifier systems of data structures to facilitate communication and/or interaction between the data structures.
    Type: Application
    Filed: December 20, 2017
    Publication date: June 20, 2019
    Inventors: Christopher John Merz, Joshua A. Allbright, Adam Kenneth Hosp
  • Publication number: 20190147448
    Abstract: An analytics computing system for analyzing payment transaction data to identify merchants having a recurring payment program is provided. The analytics computing system is configured to receive first payment transaction data for a plurality of transactions associated with a merchant, generate an actual transaction amount distribution, compare the actual transaction amount distribution to a stored model distribution, compare an angle distance to a predefined threshold value, and identify whether the merchant is a merchant performing recurring payment transactions. The analytics computing system is also configured to store that the merchant is a recurring payment merchant and alert an analyst that the merchant is a recurring payment merchant by transmitting an alert message to a user computing device in communication with the analytics computing device.
    Type: Application
    Filed: November 15, 2017
    Publication date: May 16, 2019
    Inventors: Joshua A. Allbright, Christopher John Merz
  • Publication number: 20190130403
    Abstract: An inverse recommender system for detecting out-of-pattern payment transactions includes a memory device and a processor programmed to receive transaction data. The transaction data corresponds to historical payment transactions between account holders and merchants. The processor is programmed to generate a merchant correspondence matrix including the merchants and counters indicating the number of historical payment transactions between merchant pairs of the merchants and the account holders. The processor is programmed to store the merchant correspondence matrix in a memory device linking the merchant pairs to each account holder. The processor receives additional transaction data associated with a new payment transaction between an account holder and a merchant, and to generate an inverse recommender score for the new payment transaction based on the account holder's historical payment transaction data.
    Type: Application
    Filed: October 26, 2017
    Publication date: May 2, 2019
    Inventors: Christopher John Merz, Joshua A. Allbright, Peng Yang
  • Publication number: 20190130404
    Abstract: A compromise detection computing device is configured to receive transaction data associated with a set of transactions performed at a plurality of merchants, each transaction conducted using a payment device, identify a first merchant, and generate a list of every payment device that was used to conduct a transaction at the first merchant. The compromise detection computing device is further configured to monitor subsequent transaction activity associated with each payment device on the list, and generate a fraud proxy score for each payment device based upon the activity. The compromise detection computing device is further configured to access fraud report records associated with any payment device on the list, generate an implication score for the first merchant based upon the fraud proxy score and the fraud report records, and, when the first implication score meets a first criteria, automatically transmit an alert message to a receiving party.
    Type: Application
    Filed: October 26, 2017
    Publication date: May 2, 2019
    Inventors: Christopher John Merz, Joshua A. Allbright
  • Patent number: 10120921
    Abstract: A system, method, and computer-readable storage medium configured to facilitate the parallel transfer of Structured Query Language (SQL) data to a software framework.
    Type: Grant
    Filed: October 20, 2015
    Date of Patent: November 6, 2018
    Assignee: Mastercard International Incorporated
    Inventor: Joshua A. Allbright
  • Publication number: 20180174170
    Abstract: Systems and methods are provided for modeling transaction data associated with merchant category codes (MCCs) assigned to merchants. An example method includes accessing a transaction data structure having transaction data for a plurality of merchants, and accessing a merchant data structure including multiple merchants and a category descriptor for each of the multiple merchants. The method also includes combining data in the transaction data structure and the merchant data structure based on a merchant identifier for a merchant common thereto, and assigning a label to the common merchant based on at least one category descriptor for the common merchant in the merchant data structure. Further, the method includes generating a model for a MCC assigned to the common merchant, based on transaction data for the common merchant and the assigned label, whereby the model can be used to verify assignment of the MCC to other merchants.
    Type: Application
    Filed: December 16, 2016
    Publication date: June 21, 2018
    Inventors: Walter F. Lo Faro, Joshua A. Allbright
  • Publication number: 20180121473
    Abstract: A database management (DM) computing device for reducing an amount of data stored within an enhanced database while ensuring that data remaining within the enhanced database is able to satisfy a plurality of user queries is described. The DM computing device is in communication with the enhanced database and a secondary storage database. The DM computing device is configured to receive a log data file identifying a number of times each data field in the enhanced database has been queried, rank the data fields based on the number of times each data field has been queried, and identify least-queried data fields from the ranked data fields, wherein the least-queried data fields are defined by rules in a memory. The DM computing device is also configured to store in the secondary storage database the least-queried data fields from the enhanced database, and remove from the enhanced database the least-queried data fields.
    Type: Application
    Filed: November 2, 2016
    Publication date: May 3, 2018
    Inventors: Srinivas Kosaraju, Hima Bindu Nagisetty, Jeffery David Hiatt, Joshua A. Allbright
  • Publication number: 20170109420
    Abstract: A system, method, and computer-readable storage medium configured to facilitate the parallel transfer of Structured Query Language (SQL) data to a software framework.
    Type: Application
    Filed: October 20, 2015
    Publication date: April 20, 2017
    Inventor: Joshua A. Allbright