Mastercard International Incorporated

Walter Francis Lo Faro

Christopher John Merz

Ravi Santosh Arvapally

Matthew Scott Morice

Peng Yang

Anita Christine Galliani

Adam Kenneth Hosp

Gary Randall Horn

Amy Christine Milam

Thakur B Kondasani

Pauline Ow

Matthew Richard Stocke

Gautam Uppalapati

Stephen P Hendrix

Stephan J Klaus

Lorrie M Littlefield

Steve Oshry

Robert T Grothe, Jr

Robert Thomas Grothe

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.

Systems and methods for generating recommendations using a corpus of data

A computer system including a processor, in communication with a database, programmed to identify a plurality of billers from the database, including biller information, and receive a payee file including payee information identifying a payee which issued a bill to a payor. The processor determines an approximate match score for each of the billers in a first set of billers of the plurality of billers by comparing payee information to biller information and identifies a candidate list of billers from the first set of billers having an approximate match score indicating a likelihood of matching the payee information. The processor adjusts the candidate list of billers by altering the match score of at least one candidate biller by comparing a payee account number of the payee information to an account mask associated with the candidate biller and generates an output file of candidate biller information from the adjusted candidate list.

Systems and methods for improving error tolerance in processing an input file

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.

Systems and methods for associating related merchants

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. The method also includes electronically storing the transaction information within the database, generating a profile of the stored transaction information for the cardholder, the profile including a type, a recency and a frequency of transactions initiated by the cardholder using the payment card and the at least one subdivision, grouping the cardholder into a single cluster with other cardholders registered within the payment card network based on the profile of the cardholder and the other cardholders, and outputting marketing information based on the cluster.

Method and system for predicting future cardholder behavior

Systems and methods are provided for evaluating aggregate merchant sets, which are often generated by a payment network. One exemplary method includes accessing, by a computing device, a monitor score and a volatility score for an aggregate merchant set representative of multiple merchants having at least one disparate parameter in a transaction data structure, fuzzy sets for the monitor score and the volatility score comprising linguistic values, and inference rules that use the linguistic values in logical operations. The method also generally includes determining degrees of membership of the monitor score and volatility score to the associated fuzzy sets and generating an evaluation index based on the inference rules and the degrees of membership to the fuzzy sets, thereby providing an indication of a propriety of the aggregation of said multiple merchants.

Systems and methods for use in evaluating aggregate merchant sets

A computer system for recommending merchants to a candidate cardholder is provided. The computer system includes a memory device in communication with a processor. The processor is programmed to receive transaction information for a plurality of cardholders from a payment network. The transaction information includes data relating to purchases made by the cardholders at a plurality of merchants, the purchases satisfying a first criteria. The processor receives candidate cardholder preference information for at least one of the merchants input by the candidate cardholder, determines a merchant rank for each merchant based on the received transaction information and the candidate cardholder preference information, determines a neutral merchant rank for each merchant based on the received transaction information and neutral cardholder preferences of the plurality of cardholders, and determines a merchant score for each of the plurality of merchants by comparing the merchant rank to the neutral merchant rank.

Systems and methods for recommending merchants

Systems and methods are provided for use in distributing code testing tasks among multiple testers, and incentivizing testing with rewards. One exemplary method includes testing, by a computing device, a code set, where the testing is performed by a tester associated with a profile, and receiving, by the computing device, peer tester feedback based on the testing of the code set, where the peer tester feedback is associated with at least one peer tester profile. The method also includes receiving, by the computing device, a developer decision based on the testing of the code set and/or the peer tester feedback, and rewarding, by the computing device, the profile of the tester and/or the at least one peer tester profile when the developer decision agrees with the testing of the code set and/or the tester feedback associated with the at least one peer tester profile.

Systems and methods for use in distributed and incentivized code testing

Determining whether two merchant location database entries are describing the same merchant location. A subject merchant location database entry and comparison candidate merchant location database entries include a DBA name field, a street address field, and one or more additional descriptive fields descriptive of one or more predetermined characteristics of the respective merchant location. The subject merchant location database entry is compared to a set populated with candidate merchant location database entries, candidates having a predetermined minimum textural similarity with the subject merchant location database entry on the basis of each entry's DBA name field or street address field. The subject merchant location database entry is compared with each of the candidate database entries on the basis of the one or more additional descriptive fields, and a logistic regression is performed using the results of the comparing, in order to calculate a probability that the database entries refer to the same merchant location.

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Chesterfield, MO, United States of America

Walter Francis Lo Faro