Abstract: A management system for cross-network assessment of transactions for provider reputation receives a provider string associated with a provider identification and that includes a provider score. The provider identification is extracted from the provider string. In view of the provider identification, a potential merchant identification code is determined from a set of known merchant identification codes. At least one transaction associated with the potential merchant identification code can be identified by analyzing transaction data stored in a structured data resource associated with the management system. In view of the provider score, a transaction score is assigned to each transaction associated with the potential merchant identification code. The transaction score is stored. Merchant statistics are determined by analyzing the at least one transaction. A report is generated in view of the merchant statistics and the transaction score. The report is provided for display via a graphical user interface.

Abstract: The disclosure facilitates the generation and provision of stop locations based on context data and transaction data associated with a user's account. Context data indicating a location and travel path of a user is collected from a computing device of the user and a plurality of stop locations are identified by a recommendation engine based on the context data. User transaction data associated with the user is received by the recommendation engine. User preference data is determined by the recommendation engine based on the transaction data. The recommendation engine provides a recommendation of at least one stop location based on the user preference data, whereby the user is enabled to select a stop location based on the recommendation. Generating recommendations based on the user's transaction data and context data provides reliable recommendations to the user and enhances the efficiency of the user's stops while traveling.

Abstract: A method for identifying spending trends at multi-category merchants includes storing historical transaction data for a plurality of transaction accounts, each transaction account having account attributes associated therewith. Spending amounts are received for a plurality of spend categories for a consumer group having set account attributes. Stored transactional data is identified for those transaction accounts having the same account attributes as the consumer group; then the spending amounts are extrapolated onto the stored transactional data to estimate categorical spending by the related transaction accounts across each of the spend categories, based on the overall transaction amounts and extrapolation of the spending amounts, over a plurality of periods of time. Spending trends are then identified based on changes in the estimated categorical spending over time, enabling trends to be identified on a department-level basis for multi-category merchants where such spending data is unavailable.

Abstract: A method for providing merchant offers to customer mobile devices. In some embodiments, an offer engine determines, on a periodic basis for each of a plurality of merchants, a proximity-sensitivity score that indicates a likelihood that potential offers from the merchants would be accepted by customers. The process includes the offer engine receiving, from a mobile device of a customer, an indication of a customer's current location, then receiving customer transaction data in substantially real time and adjusting the proximity-sensitivity scores of the merchants based on the customer transaction data. The offer engine then automatically selects at least two offers from a plurality of potential offers based on the adjusted proximity-sensitivity scores for the customer, and transmits, to the mobile device associated with the customer, data associated with the at least two selected offers for display on a display screen of the customer's mobile device.

Abstract: The disclosure facilitates the generation and provision of stop locations based on context data and transaction data associated with a user's account. Context data indicating a location and travel path of a user is collected from a computing device of the user and a plurality of stop locations are identified by a recommendation engine based on the context data. User transaction data associated with the user is received by the recommendation engine. User preference data is determined by the recommendation engine based on the transaction data. The recommendation engine provides a recommendation of at least one stop location based on the user preference data, whereby the user is enabled to select a stop location based on the recommendation. Generating recommendations based on the user's transaction data and context data provides reliable recommendations to the user and enhances the efficiency of the user's stops while traveling.

Abstract: Provided are a system and method for linking cardholders with communication service subscribers. In one example, a method includes generating anonymized cardholder information representing a group of cardholders that reside within a predetermined geographic location, receiving anonymized communication service subscriber information representing a group of communication service subscribers that reside within the predetermined geographic location, and linking the anonymized cardholder information to the anonymized communication service subscriber information based on the predetermined geographic location.

Abstract: Embodiments of the disclosure enable a system to generate transaction data associated with one or more financial transactions. The system analyzes location data associated with a first user account to determine a user footprint, analyzes first transaction data associated with the first user account to identify one or more first members associated with the user footprint, identifies one or more second members associated with the user footprint to generate a merchant list, analyzes second transaction data associated with one or more second user accounts to generate one or more parameters associated with the merchant list, and uses the parameters to generate third transaction data for use in generating a user profile associated with the first user account. Aspects of the disclosure provide for generating and/or modifying a user profile based on one or more cash-based financial transactions in an efficient and user-friendly manner.

Abstract: Provided are a system and method for linking cardholders with communication service subscribers.

Abstract: A method includes tracking a location of a motor vehicle that has been registered with a vehicle communication system. Promotional offer information is received. The promotional offer information indicates a promotional offer identified based on a current location of the motor vehicle. The promotional offer information is pushed via the vehicle communication system to an information output device installed in the motor vehicle.

Abstract: Payment card account transaction data sets and mobile device travel profiles are compared with each other to detect matches in terms of times and locations of use and/or presence. Such an analysis may link a mobile device to a transaction account. Residence location data relevant to the owner of the mobile device may be appended to the transaction data to facilitate improved location based analyses.

Abstract: Systems and methods are provided for evaluating a service provider based on transaction data for the service provider. One exemplary method includes accessing transaction data for a payment account of a target service provider, where the transaction data represents multiple transactions from the payment account and the transactions involve multiple merchants; assigning the target service provider to a group of other service providers, selected from multiple groups of other service providers, based on the transaction data for the payment account of the target service provider; associating a rating for the selected group with the target service provider; and transmitting the rating.

Abstract: Systems and methods are provided for rating merchants in different industries, based on transaction data for the merchants and relative to multiple other merchants within same industries as the merchants to be rated. A merchant to be rated is initially identified (e.g., from a request, etc.), along with an industry with which the merchant is associated. Transaction data for the merchant is then accessed from a payment network. The transaction data includes data relating to both payment transactions and chargeback transactions to the merchant over a time interval. Next, a score for the merchant is generated based on at least a number of the chargeback transactions to the merchant during the time interval, and on transaction data for multiple other merchants within the same industry as the merchant. The resulting score is then associated with a risk rating for the merchant, thereby providing an indicator of the merchant's reliability.

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: Systems, methods, means, computer program code and computerized processes include receiving a first set of de-identified transaction data from a first transaction data source, receiving a second set of de-identified transaction data from a second transaction data source, filtering the first and second sets of de-identified transaction data to identify transactions associated with at least a first entity and to create first and second filtered data sets, removing data associated with an identifier field for each of the transactions in the first filtered data set to created a de-identified first data set, removing data associated with an identifier field for each of the transactions in the second filtered data set to create a de-identified second data set, and processing the first and second de-identified data sets using a probabilistic engine to establish a linkage between data in each data set.

Abstract: Methods and systems facilitate strategic installation of charging ports for charging electric vehicles. Transaction information associated with financial transactions executed using payment cards is analyzed to determine identification (ID) proxies for consumers, charging locations, and reference locations. Predictors are used to determine outputs that facilitate strategic installation of charging ports.

Abstract: Systems, methods, means, computer program code and computerized processes include receiving a first set of de-identified transaction data from a first transaction data source, receiving a second set of de-identified transaction data from a second transaction data source, filtering the first and second sets of de-identified transaction data to identify transactions associated with at least a first entity and to create first and second filtered data sets, removing data associated with an identifier field for each of the transactions in the first filtered data set to created a de-identified first data set, removing data associated with an identifier field for each of the transactions in the second filtered data set to create a de-identified second data set, and processing the first and second de-identified data sets using a probabilistic engine to establish a linkage between data in each data set.

Abstract: A method includes receiving, from a user, a request for seating at an event. The method further includes fulfilling the request for seating, based at least in part on spending habit information for the user, where the spending habit information is derived from data indicative of payment card account transactions by the user.

Abstract: A method includes receiving a data set that represents payment card transactions of a set of cardholders during a current time period. The method further includes filtering the set of cardholders based on one or more spending characteristics exhibited by the set of cardholders and indicated by the payment card transactions during the current time period, to produce a subset of the cardholders. Still further, the method includes filtering the subset of cardholders based on one or more spending characteristics of the subset of cardholders during a historical time period that ended substantially prior to an ending point of the current time period, to produce an audience set of the cardholders. Promotional contact information relating to previous contacts with cardholders, and/or non-transactional account information (e.g., credit limits), may also be used in defining the audience set instead of twice filtering the set of cardholders based on spending habits.

Abstract: Systems, methods, means, computer program code and computerized processes include receiving a first set of de-identified transaction data from a first transaction data source, receiving a second set of de-identified transaction data from a second transaction data source, filtering the first and second sets of de-identified transaction data to identify transactions associated with at least a first entity and to create first and second filtered data sets, removing data associated with an identifier field for each of the transactions in the first filtered data set to created a de-identified first data set, removing data associated with an identifier field for each of the transactions in the second filtered data set to create a de-identified second data set, and processing the first and second de-identified data sets using a probabilistic engine to establish a linkage between data in each data set.

Abstract: A method includes receiving a first data set and a second data set. The first data set may include anonymized transaction data that represents purchase transactions made by customers of a merchant. The second data set may include anonymized transaction data that represents purchase transactions made by cardholders in a payment network. The method further includes filtering the second data set to remove therefrom data relating to cardholders who are not customers of the merchant, and processing the first data set and the filtered second data set using a probabilistic engine to establish linkages between data in the first data set and data in the filtered second data set. The method may also include performing a predictive analysis based on one or more independent variables from the second data set and with a dependent variable represented in the first data set.