Abstract: 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.

Abstract: 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.

Abstract: A system, method, and computer-readable storage medium configured to maintain account continuity when payment account numbers change.

Abstract: 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.

Abstract: 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

Abstract: 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.

Abstract: 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.

Abstract: A method for identifying members based on purchase behavior analysis includes: storing a plurality of point of sale data entries, each including a point of sale identifier and a geographic location of the point of sale identifier; storing transaction data entries, each including data related to a payment transaction including at least a point of sale identifier, an industry type, a time and/or date, and a consumer identifier; receiving a data request related to a target geographic area; identifying at least one point of sale identifier associated with a geographic location located within the target geographic area; identifying at least one transaction data entry associated with the identified at least one point of sale identifier; classifying the at least one identified transaction data entry into at least one consumer transaction set; calculating a member estimation score for each consumer transaction set.

Abstract: 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.

Abstract: 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.

Abstract: A method for measuring the effectiveness of an advertisement includes: storing, in a database, a plurality of consumer data entries, each being associated with a consumer and wherein each includes at least a plurality of characteristics and activity data; identifying a subset of the plurality of characteristics; encrypting, by a processor the subset of characteristics for each consumer data entry using a one-way encryption; transmitting, by a transmitter, the one-way encryption; receiving, by a receiver, advertising data entries, each being associated with a consumer and wherein each includes at least the encrypted subset of characteristics and a segment indicator; identifying a subset of consumer data entries that correspond to the advertising data entries based on the encrypted subset of characteristics; and analyzing the activity data for each consumer data entry in the subset to measure the effectiveness of an advertisement based on the corresponding segment indicators.

Abstract: 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