Mastercard International Incorporated

Arun Elangovan

Michael Lester Zhao

Jeremy Michael Pastore

Edward M Lee

Michael Cardamone

Andrey Birukov

Rajesh Chopra

Juan Carlos Gonzalez

Systems and methods are provided for implementing an interactive loyalty reward program for transactions conducted at transaction terminals, for instance, consumer purchase transactions conducted at a point-of-sale terminal. The system includes a server configured to monitor and identify qualifying transactions under the reward program. The server also coordinates operation of consumer-facing devices accessible to the consumer at the point-of-sale. The consumer-facing devices include an interactive value generator (IVG), which is configured to provide a game-like experience to consumers and interactively generates unspecified reward values for qualifying transactions. A loyalty reward application executing on the transaction terminal is also provided to guide consumer interaction with the IVG and communicate the generated reward values to the server. The server is further configured to calculate loyalty reward amounts for respective transactions based on the generated reward values and prescribed terms of corresponding loyalty reward programs.

Interactive loyalty reward system and method

A system, method, and computer-readable storage medium configured to verify minimum age of accountholders, to enable age restrictions on purchases.

Age verification through mobile wallet method and apparatus

A method for communicating an index of service performance based on gratuity value includes: storing transaction messages, each including a merchant identifier associated with a merchant involved in the related payment transaction, a transaction amount, and addendum data; receiving a data request including a specific merchant identifier; identifying a subset of transaction messages that includes the specific merchant identifier; identifying a tip amount for each transaction message in the by (i) extracting the tip amount from the addendum date, or (ii) calculating the tip amount based on the transaction amount stored respective transaction message and a transaction amount stored in a matching clearing record; calculating an average gratuity index for a merchant associated with the specific merchant identifier as an average of the identified tip amounts; and transmitting the calculated average gratuity index in response to the data request.

Method and system for determining merchant gratuity values

A system and method is disclosed for the real-time active surveillance of disease. The system generates an outbreak detection model by analyzing the spending records of individuals who are known to be infected to identify purchases and purchase patterns that correlate to infection in the population with a disease. Based on the identified purchases, the system generates probabilistic identification criteria and merges the criteria to simulation models of infection spread by geography to generate a geospatial outbreak detection model. The system applies the generated model to spending records, in real time, to identify and monitor disease spread in the population. The system can also generate alerts if the likelihood that an individual is infected, or one or more individuals in a set or population is infected exceeds a threshold. Actions are taken at remote devices, such as mobile phones, computers and POS terminals in certain embodiments.

System and method for conducting real time active surveillance of disease outbreak

A system and method is disclosed for determining an optimized sequence of visits by a consumer to a plurality of merchant locations irrespective of travel distance. The system is configured to receive, from the consumer, errand data including start time and start and finish location and a plurality of merchant locations to visit. The system also generates one or more models for predicting visit durations the merchant locations as a function of time using transaction data and location data associated with a plurality of consumers that previously visited the merchant locations. Based on the generated models, and current and historical travel/traffic information and the errand data, the system generates an optimized sequence of visits for the consumer.

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Astoria, NY, United States of America

Arun Elangovan