Mastercard International Incorporated

Todd Christian Lowenberg

Curtis Villars

Rohit Chauhan

Serge Bernard

Andrew S Reiskind

Gary Randall Horn

Kimberly Ann Martin

Thomas Joseph Sellner

Richard Thomas Flynn

Raegen Ann-Marie Lang

Cristobel Kay Von Walstrom

Peter Julian Ramon Antonio R Flor

Ana Paula Martinez Prada Peyser

Jason Alexander Korosec

Bruce William Mac Nair

JoAnn C Stonier

Michael Lester Zhao

Nikhil Malgatti

Kimberly Ann Purcell

Bruce William MacNair

Dhruv Akhauri

Nigel Noyes

Harry Chen

Shweta Jain Chaudhury

Jason Alexander Kiorosec

Adam Michael Granoff

A method for fraud modeling based on shared computing device usage includes: storing transaction data entries, each including a transaction date and/or time, account identifier, and device identifier associated with a computing device; receiving a transaction message for a payment transaction, the transaction message including a specific device identifier, primary account number, and additional transaction data; identifying transaction data entries where the included device identifier corresponds to the specific device identifier; determining a fraud risk rating based on a number of unique account identifiers included in the identified transaction data entries over a predetermined period of time; and transmitting the transaction message and the determined fraud risk rating to a financial institution associated with the primary account number.

Method and system for identification of shared devices for fraud modeling

A method for double anonymization of data includes: receiving, by a first computing system, a plurality of first data sets, each including a set identifier and personally identifiable information; anonymizing, by the first computing system, each of the first data sets, by hashing the set identifier included in each first data set to obtain a hashed identifier and deidentifying the personally identifiable information; transmitting, by the first computing system, the plurality of anonymized first data sets to a second computing system, wherein the second computing system is distinct and separate from the first computing system; anonymizing, by the second computing system, each of the anonymized first data sets, by hashing the hashed identifier to obtain a double-hashed identifier; and storing, in the second computing system or a third separate and distinct computing system, the plurality of double anonymized first data.

Method and system for double anonymization of data

A method for linking de-identified data identifiers to traceable data identifiers in compliance with applicable data privacy rules and regulations includes: receiving a plurality of first data identifiers from a first computing system; applying a one-way hashing algorithm and salt to the first data identifiers to generate second data identifiers; storing an association between each of the first data identifiers and the respective second data identifier; receiving one or more specific second data identifiers from a second computing system; identifying, for each of the one or more specific second data identifiers, the associated first data identifier; and transmitting each identified associated first data identifier to the first computing system.

Method and system for securing personally identifiable information

A network operator intermediates a cashless transaction by sending a payment device issuer an outbound clearing data file enriched with cleansed merchant data. Issuers that choose to participate in the merchant data cleansing service will be provided with the cleansed, and optionally augmented, merchant information. Providing this data to the issuer could be used to help reduce costs associated with 'do not recognize' calls by cardholders, disputed charges, and charge-backs. With cleansed data provided in the clearing record, a device holder would be given access to this cleansed information about the merchant where a transaction took place through their statement. The present disclosure also provides for augmenting the clearing record data to include merchant-specific add-on and/or aggregate data not presently included in the transaction clearing record, yet useful to the issuer both in form and content.

Merchant data cleansing in clearing record

A method for real-time measurement of campaign effectiveness includes: storing device profiles, each including a hashed device identifier, geographic location, and transaction entries including a transaction date and transaction data; receiving a data request including a start date, end date, merchant identifier, a plurality of device identifiers, and, for each device identifier, a category identifier of a set of category identifiers; generating a hashed identifier for each of the device identifiers; identifying, a device profile for each hashed device identifier; calculating purchase behaviors for each category based on transaction data in transaction data entries that include a transaction date between the start date and end date that are included in each identified device profile that is associated with the respective category and includes a geographic location corresponding to the merchant identifier; and transmitting at least one of: the calculated purchase behaviors and one or more metrics based thereon.

Method and system for real-time measurement of campaign effectiveness

A method for determining an economic impact of a candidate event includes receiving an event type identifier representing an event type of a candidate event to occur, and building a reference data store including historical transaction data records of payment transactions occurring in reference geographic areas associated with a reference event having the event type identifier. The method also includes generating a reference model from the historical transaction data records the models a reference number of active accounts and active merchants within a reference geographic area during a period of time associated with the reference event occurring in the geographic area. The method further includes determining a predicted number of active accounts and active merchants within the target geographic area using the reference model, and determining a predicted consumer spend using a predicted spend model. The method also includes generating an economic impact report including the consumer spend.

Systems and methods for determining economic impact of an event within a geographic area

A method for generating microsegments includes retrieving a first set of information including activities attributable to a first plurality of entities and first entity identifiers; retrieving a second set of information including characteristics attributable to the first plurality of entities and second entity identifiers; combining the first and second sets of information using the first and second entity identifiers to obtain a combined set of information, the combined set of information not including personally identifiable information; generating a plurality of microsegments based on selected activities and/or characteristics criteria from the combined set of information; receiving a third set of information including characteristics attributable to a second plurality of entities; and matching characteristics in respective microsegments to characteristics of entities in the second plurality of entities to identify an audience of entities that have a propensity to carry out certain activities based on the selected activities and/or characteristics.

Protecting privacy in audience creation

A method for combining disparate data sets using dynamic de-identifiers includes: receiving a first data set from a first external entity, the data set including first data entries including attribute values, and wherein the first data set does not include any personally identifiable information; receiving a second data set from a second external entity, the data set including second data entries including attribute values, and wherein the second data set does not include any personally identifiable information; identifying a dynamic de-identifier (DDID) for each first data entry and second data entry; matching each second data entry to a first data entry based on a correspondence between the associated attribute values; identifying insights for at least one first data entry based on at least the attribute values included in the corresponding matched second data entry; and transmitting at least the identified insights to the first external entity.

Method and system for dynamic de-identification of data sets

A method for maintaining consumer privacy in behavioral scoring includes a first computing system and a second computing system. The first computing system disguises consumer characteristics and maps disguised consumer characteristics to unencrypted account identifiers, and then transmits the data to the second computing system. The second computing system encrypts the account identifiers upon receipt, and maps the encrypted account identifiers to anonymous transaction data. The second computing system uses the transaction data to calculate consumer behavioral scores, and then generates a scoring algorithm that uses disguised consumer characteristics to calculate consumer behavior scores based on the calculated consumer behavioral scores and corresponding disguised consumer characteristics. The generated algorithm is then returned to the first computing system, with the second computing system not receiving any unencrypted account identifiers, any undisguised consumer characteristics, or any personally identifiable information.

Method and system for maintaining privacy in scoring of consumer spending behavior

Growing community of inventors

Redding, CT, United States of America

Todd Christian Lowenberg