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: A method for identifying relationships between time series variables includes: storing a plurality of transaction data entries, each including a transaction time and transaction data; receiving a data request including a time period, time interval, a requestor time series variable, and a data value for each interval during the period; calculating for each of a plurality of processor time series variables, a data value for each interval during the period, the data values based on the transaction data and transaction times included in the transaction data entries; identifying a related processor time series variable based on a correspondence between the data value for each interval during the period for the variable and the data value for each interval during the period for the requestor time series variable; and transmitting the identified at least one related processor time series variable and the respective data values for each interval during the period.

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: Systems and methods for linking or matching data of disparate datasets and then performing business related data analysis. Consumer-related data of two or more disparate datasets are linked in a privacy-friendly manner, and then analyzed to provide business information and/or consumer information to clients. The linking and analysis is performed in a manner to protect personally identifiable information (PII) of the consumers. In an embodiment, a processor receives a plurality of disparate anonymized datasets originating from a plurality of different data sources, formats the de-identified data to provide a plurality of formatted anonymized datasets, and links the data entries of the de-identified individuals by matching at least date data, time data, and location data. The processor then analyzes the activity data of the linked data entries, and generates a report based on the analysis.

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 spending behaviors in a geographic area includes: storing, in a database, a plurality of geographic centroids, each corresponding to a centroid of a predefined geographic area; receiving a plurality of financial transactions involving each consumer of a plurality of consumers; identifying a geographic location of each transaction; calculating, for each consumer, a purchase centroid of the transactions involving the consumer based on a centroid of the location of each of the transactions involving the consumer; analyzing, for each consumer, spending behaviors based on the consumer's transactions; associating the analyzed spending behavior for each consumer with the corresponding purchase centroid; associating the analyzed spending behaviors for each purchase centroid with a predetermined number of geographic centroids based on the distance from the purchase centroid to each of the geographic centroids; and aggregating, each of the spending behaviors associated with each geographic cent

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 analyzing advertising effectiveness includes storing entity information including activity and characteristic information associated with a plurality of entities; generating a plurality of microsegments, each microsegment including a subset of the plurality of entities based on the associated characteristic information; generating a test audience including a plurality of first microsegments including entities exposed to an advertisement for a period of time and a control audience including a plurality of second microsegments including entities not deliberately exposed to the advertisement; analyzing the activity information for the test audience and the control audience to determine spending behaviors for the associated entities during the period of time; comparing the spending behaviors determined for the test and control audiences to determine the effectiveness of the advertisement; and reporting the effectiveness of the advertisement.

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