Abstract: A method for identifying a high growth business from combined data sets comprising: storing, a plurality of data elements configured to store at least a merchant identifier, acceptance flag, transaction date, and transaction amount; receiving, a merchant growth request command including at least a specific merchant identifier associated with a specific merchant; executing, a query on the transaction database to identify a subset of transaction messages; determining, a transaction volume over time for the specific merchant based on at least the transaction amount and transaction date; identifying, social media data associated with the specific merchant, and a growth index for the specific merchant based on at least the transaction volume over time determined for the specific merchant and the measure of social media presence over time based on the associated dates.

Abstract: A method for generating a model for indexing neighborhood growth includes: storing transaction messages, each including a geographic location and transaction data, where the geographic location is in one of a plurality of geographic areas; receiving demographic characteristic data including property value data associated with each geographic area; identifying transaction groups for each geographic area including transaction messages where the geographic location is included in the respective associated geographic area; identifying purchase behaviors for each of the plurality of geographic areas based on the transaction data stored in the transaction messages included in associated transaction group; and generating an indexing model configured to calculate an index value for a geographic area indicative of growth or decline of the geographic area based on the purchase behaviors and property value data associated with the respective geographic area for each of the plurality of geographic areas.

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 are provided for compiling total amounts spent through payment accounts. One exemplary method includes accessing transaction data associated with a payment account for transactions known to a first payment service provider, and identifying, at a computing device, a first amount spent through the payment account based on the accessed transaction data. The method also includes determining, at the computing device, a second amount spent through the payment account for transactions not known to the first payment service provider, based on at least one predefined factor relating to the transactions known to the first payment service provider. The method then includes aggregating the first amount spent through the payment account and the second amount spent through the payment account.

Abstract: Systems and methods are provided for identifying traits of abnormal data. One exemplary method includes accessing transaction data as associated with at least one merchant, where the transaction data includes multiple transactions. The exemplary method further including detecting abnormal transactions from the multiple transactions based on at least one parameter of the transactions, identifying, at a computing device, at least one trait associated with at least a portion of the abnormal transactions, but not associated with a typical consumer associated with the at least one merchant, and reporting the at least one trait to the at least one merchant.

Abstract: A method for identifying business service recommendations includes: storing merchant profiles, each profile including data related to a merchant including a merchant identifier and transaction for a plurality of payment transactions; receiving, a data file including a plurality of merchant entries, each entry including data related to a merchant including a merchant identifier and firmographics; identifying a specific merchant entry where the merchant identifier corresponds to a merchant identifier in a specific merchant profile; calculating transaction scores for the specific merchant entry based on the transaction data in the specific merchant profile; identifying a related merchant entry where the firmographics correspond to the firmographics in the specific merchant entry and where the merchant identifier is not included in a merchant profile; and identifying one or more business service recommendations for the merchant related to the related merchant entry based on transaction scores and firmographics in

Abstract: A method for estimating a consumer geolocation using filtered transaction data includes: storing transaction data entries, each including an account identifier, merchant identifier, and merchant category code; storing filtering rules, each including one or more merchant category codes; receiving a location request including a specific account identifier and specific filtering rule; identifying a subset of transaction data entries including the specific account identifier; filtering the subset of transaction data entries to remove transaction data entries where the merchant category code does not correspond to one of the merchant category codes included in the specific filtering rule; identifying a geographic location for each transaction data entry in the subset based on the respective included merchant identifier; estimating a geographic location based on the geographic location identified for each transaction data entry in the filtered subset; and electronically transmitting the estimated geographic locatio

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 computer-implemented method for recommending items for future purchase by a consumer based on the consumer's historical actions is provided. The method is implemented using an adaptive recommendation (“AR”) computer device in communication with a memory. The method includes receiving from a recommender server computing device at least one preference vector, storing the at least one preference vector, receiving at least one consumer action including a time aspect, from a candidate consumer, and determining at least one personalized vector based on the at least one preference vector, the at least one consumer action, and the time aspect associated with each of the at least one consumer action. The at least one personalized vector represents at least one future purchase that the candidate consumer will likely conduct. The method also includes displaying at least one recommendation to the candidate consumer based on the at least one personalized vector.

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 determine the line of business for a corporate payment account.

Abstract: A method for identifying business service recommendations includes: storing merchant profiles, each profile including data related to a merchant including a merchant identifier and transaction for a plurality of payment transactions; receiving, a data file including a plurality of merchant entries, each entry including data related to a merchant including a merchant identifier and firmographics; identifying a specific merchant entry where the merchant identifier corresponds to a merchant identifier in a specific merchant profile; calculating transaction scores for the specific merchant entry based on the transaction data in the specific merchant profile; identifying a related merchant entry where the firmographics correspond to the firmographics in the specific merchant entry and where the merchant identifier is not included in a merchant profile; and identifying one or more business service recommendations for the merchant related to the related merchant entry based on transaction scores and firmographics in

Abstract: A method for identifying consumer purchase probability includes: storing transaction data entries, each entry including a transaction time, a consumer identifier, and a first product identifier or second product identifier; receiving transaction data for a specific consumer's transaction including a purchase time and the first product identifier; identifying a present time; calculating a ratio of consumers that have purchased the first and second products to consumers that have only purchased the first product; calculating, for consumer that have purchased both products, an average time interval based on a difference in the transaction time for purchase of the first product and transaction time for purchase of the second product; calculating a recency time based on time between the present time and the purchase time; and calculating a probability that the specific consumer will purchase the second product based on the calculated ratio of consumers, average time interval, and recency time.

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 system for correlating customer payment card purchases and contemporaneous weather conditions. The system comprises a first data storage device containing payment card transaction data and a second data storage device comprising historic weather data. A processor is provided and configured to identify correlations between payment card transactions and weather conditions contemporaneous to the transactions or otherwise associated therewith.

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 generating a micro-neighborhood of consumers includes: storing a plurality of account profiles, each profile including data related to a consumer including account data, a micro-neighborhood location identifier, and a plurality of transaction data entries, each entry being related to a payment transaction involving the related consumer and including transaction data; scoring each account profile stored in the account database by application of a scoring model to the transaction data included in one or more transaction data entries included in the respective account profile; and identifying a plurality of account profile groupings, each grouping including a subset of the plurality of account profiles identified based on the score for and micro-neighborhood location identifier included in each account profile included in the subset, wherein the subset of the plurality of account profiles included in each account profile grouping includes at least a predetermined number of account profiles.

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 linked payment accounts includes storing an account profiles related to payment accounts and storing transaction data for a plurality of payment transactions, each involving a payment account, a merchant, and each conducted at a specific time and/or date. Transaction pairs are identified for two transactions conducted within a predetermined period of time and involving the same merchant, but two different accounts. Sets of transaction pairs are then identified, with each set including at least transaction pairs that include the same two accounts. Those two accounts are then identified as linked payment accounts. A network of accounts may be identified based on payment accounts and their links to other accounts. Within the network, influencer accounts may be identified from accounts that conduct transactions with a merchant before others in the network, and follower accounts may be identified from accounts that follow influencers in transaction at merchants.

Abstract: A method for identifying agency entitlements includes: storing a plurality of transaction data entries, each entry including data related to a payment transaction including a specific account identifier associated with a payment account involved in the transaction and transaction data; storing a plurality of account profiles, each profile including data related to a payment account including an account identifier associated with the account and account data; identifying entitlement rules, wherein each o entitlement rule is associated with an agency entitlement and is configured to identify recipients of the entitlement; applying, to account profiles, the entitlement rules to (i) the account identifier and/or account data included in the respective profile, and/or (ii) the transaction data included in transaction data entries associated with the respective account profile, to identify an agency entitlement associated with the account; and updating account profiles to include the identified entitlement associat