Abstract: A method and system for recommending a merchant are provided. The method includes receiving financial transaction data documenting financial transactions between a plurality of account holders and a plurality of merchants and generating a merchant correspondence matrix that includes the plurality of merchants and a plurality of indicators of interactions associated with pairs of the plurality of merchants. The plurality of indicators of interactions tallying financial transactions conducted by the plurality of account holders at both of the merchants in a pair of the plurality of merchants. The method further includes receiving a query for a recommendation of a merchant from an account holder and generating a ranked list of merchants based on a recommender algorithm. The recommender algorithm inferring user preferences from attributes of the plurality of merchants that were visited by the cardholder.

Abstract: Systems and methods for use in identifying one or more aggregate merchants are provided. An exemplary method includes compiling, by a computing device, a merchant data structure based on a region where the merchant data structure includes multiple merchants and, for each of the multiple merchants, a Doing Business As (DBA) name and at least one merchant metric. The exemplary method further includes aggregating, by the computing device, ones of the multiple merchants in the merchant data structure based on at least one rule including a Doing Business As (DBA) name and/or at least one Merchant Category Code (MCC). The method also includes sorting, by the computing device, the aggregate merchants in the merchant data structure based on at least one merchant metric, and then publishing the sorted aggregate merchants to a user.

Abstract: Systems and methods are provided for processing messages from users, via interactive interfaces, requesting support relating to features of applications available to the users. In connection therewith, the systems and methods normalize and score the user messages, and use the scores, in combination with scores for historical messages or scores for crowdsourced messages, to identify appropriate response messages for transmittal to the users. In various aspects, the crowdsourced solutions can be voted by both users and domain experts, and also verified by the domain experts. If a solution is verified it will be flagged and it can be included into a reference solution database as a standard response. However, when the scores assigned to the messages do not produce suitable results, a request for additional information relating to the issue described by the user is transmitted via the interactive interface.

Abstract: A computer-implemented method for associating a merchant with an aggregate merchant uses a computing device having a processor and a memory. The method includes identifying an association rule for the aggregate merchant, including one or more antecedents. Each antecedent includes a model value for the antecedent associated with the aggregate merchant. The method also includes identifying one or more merchant data values associated with the merchant. Each of the one or more merchant data values correspond to one of the one or more antecedents. The method further includes applying the association rule to the one or more merchant data values by comparing the model value for each antecedent with a merchant data value associated with the corresponding antecedent, thereby generating a confidence score for the merchant. The confidence score represents a likelihood the merchant is associated with the aggregate merchant. The method also includes outputting the confidence score.

Abstract: A method of monitoring cashless transaction data includes extracting transaction history data for a merchant within a first predetermined time period from a transaction data storage. A plurality of forecast models that forecast transaction patterns for the merchant over the first predetermined time period are provided, each forecast model of the first plurality having a different forecast period. The forecast models may be constructed according to a Holt-Winters time-series forecast. The forecast model which most accurately forecasts periodic fluctuations in the transaction history data is selected, and a first forecast of transactions for the merchant for a first forecast period outside the first predetermined time period is provided. A score comparing the forecast with actual data for the first forecast period is further provided. An alert is generated when the score exceeds a predetermined threshold. Also disclosed are a computer and recording medium to carry out the method.

Abstract: A computer-based method for managing a profile for a cardholder is provided. The cardholder having an account associated with a payment card. The method includes electronically receiving, at the computer, transaction information for a cardholder for transactions with at least a first business entity and a second business entity, the transaction information including data representing each transaction initiated by the cardholder using the payment card and at least one subdivision within the first business entity, the transaction information further including data representing each transaction initiated by the cardholder using the payment card and the second business entity.