Mastercard International Incorporated

Christopher John Merz

Joshua A Allbright

Felix Johannes Flory

Peng Yang

Adam Kenneth Hosp

Walter Francis Lo Faro

Julia Sharon Gosset

Amudhan Venkatesan

Brian John Piel

Mark Wiesman

Ravi Santosh Arvapally

Johan Gerber

Ranjita Shankar Iyer

Matthew Scott Morice

Thomas McGeehan

Stephen P Hendrix

Matthew Richard Stocke

Walter Lo Faro

Robert Albert Ederle

Douglas Van Horn

Robert T Grothe, Jr

Simon R Hunt

Oran Cummins

Stephen Elder

Derek Humphreys

Stephen Toner

Andrea Rizzini

Dennis A Gamiello

Andres Gonzalez

Chengxi Li

Warda Zahid Khan

Melanie Gersten

Brian Piel

Mark B Wiesman

Rachael Vahle Cordero

Janet Smith

Walter F Lo Faro

Matthew Wickman

A system including a greeting card, a scannable code positioned on a surface of the greeting card, and a computer device comprising at least one memory and at least one processor in communication with the memory. The at least one memory storing instructions causing the at least one processor to electronically create a profile data file associated with the participant and a beneficiary designated by the participant. The profile data file configured to receive and store message data and configuration data, the configuration data including at least an account identifier for linking transferred funds to the profile data file.

Systems and methods for integrating digital operations with a physical greeting card

An inverse recommender system for detecting out-of-pattern payment transactions includes a memory device and a processor programmed to receive transaction data. The transaction data corresponds to historical payment transactions between account holders and merchants. The processor is programmed to generate a merchant correspondence matrix including the merchants and counters indicating the number of historical payment transactions between merchant pairs of the merchants and the account holders. The processor is programmed to store the merchant correspondence matrix in a memory device linking the merchant pairs to each account holder. The processor receives additional transaction data associated with a new payment transaction between an account holder and a merchant, and to generate an inverse recommender score for the new payment transaction based on the account holder's historical payment transaction data. The account holder's historical payment transaction data includes historical payment transaction data associated with the merchants visited by the account holder.

Systems and methods for detecting out-of-pattern transactions

A method and system for detecting fraudulent network events in a payment card network by incorporating breach velocities into fraud scoring models are provided. A potential compromise event is detected, and payment cards that transacted at a compromised entity associated with the potential compromise event are identified. Subsequent transaction activity for the payment cards is reviewed, and a data structure for the payment cards are generated. The data structure sorts subsequent transaction activity into fraud score range stripes. The data structure is parsed over a plurality of time periods, and at least one cumulative metric is calculated for each of the time periods in each fraud score range stripe. A plurality of ratio striping values are determined, and a set of feature inputs is generated using the ratio striping values. The feature inputs are applied to a scoring model used to score future real-time transactions initiated using the payment cards.

Systems and methods for incorporating breach velocities into fraud scoring models

A computer-implemented method for determining a level of confidence that a payment transaction is not fraudulent is provided. The method is implemented using an assurance exchange (AE) computer device in communication with a memory. The method includes receiving authentication data associated with a candidate payment transaction being conducted by a cardholder via a website associated with a merchant from the merchant, storing the authentication data, receiving an authorization request message for the candidate payment transaction from a payment processor, retrieving the authentication data for the candidate payment transaction based on the authorization request message, and calculating an assurance level score based on the authentication data and the authorization request message. The assurance level score represents a level of confidence that the candidate payment transaction is not fraudulent. The method also includes transmitting the authorization request message including the assurance level score to an issuer processor.

System and methods for enhanced approval of a payment transaction

A computer-implemented method for authenticating an online user includes steps including receiving, from a requestor server in communication with a merchant website, an authentication request message including authentication data collected from a user computing device during an online interaction with the merchant website. The steps also include extracting the authentication data from the authentication request message, and applying a risk-based authentication (RBA) engine to the authentication data to obtain RBA result data including a reason code that includes no more than three bytes of data. The steps further include causing the reason code to be embedded in an authorization request message generated during the online interaction and routed to a decisioning server via a payment network. The authorization request message is formatted according to a set of proprietary communications standards promulgated by the payment network for exchange of data between institutions that are members of the payment network.

Systems and methods for authenticating online users and providing graphic visualizations of an authentication process

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

An authentication platform for authenticating an online user is provided. The authentication platform includes a memory device including an authentication profile and at least one processor coupled to the memory device. The at least one processor is programmed to receive an authentication request message for a transaction. The authentication request message includes authentication data. The at least one processor is also programmed to extract the authentication data from the authentication request message and determine if the ACS is available to process the transaction. If the ACS is unavailable, the at least one processor is further programmed to generate, based at least in part on the extracted authentication data, risk-based authentication (RBA) result data including a risk score and transmit an authentication response message based on the RBA result data.

Systems and methods for authenticating online users

A method and system for detecting fraudulent network events in a payment card network are provided. A plurality of scored payment card transaction authorization requests is received, originating from a plurality of merchants, and data structures for each of a plurality of merchant groups are generated. Each data structure sorts the scored authorization requests into fraud score range stripes. The data structures are parsed over a plurality of time periods, and at least one cumulative metric is calculated for each merchant group for each of the time periods in each fraud score range stripe. A plurality of ratio striping values is determined for each merchant group, and a set of feature inputs is generated using the ratio striping values. A second fraud detection model is applied to the scored authorization requests. Parameters of the second fraud detection model are configured to change based on the generated set of feature inputs.

Systems and methods for improved detection of network fraud events

A common point of purchase (CPP) system for identifying a common point of purchases involved in fraudulent or unauthorized payment transactions is provided. The CPP system includes a common point of purchase (CPP) computing device that is configured to receive transaction data and build a table in a database, the table including recording pairing merchant and account identifiers. The CPP computing device is also configured to receive a list of flagged account identifiers and compare the list to the table. The CPP computing device is further configured to compute a metric and build a merchant profile for each merchant, for display at a client system.

Systems and methods for identifying fraudulent common point of purchases

A system for identifying complete account identifiers from partial account identifiers is provided. The system includes an account identification computing device including at least one processor and a memory device in communication with the at least one processor. The processor is configured to receive transaction data including unique merchant identifiers, build a merchant table using the transaction data, and receive a list including partial account identifiers. The processor is further configured to determine, for each unique merchant identifier, a number of candidate account identifiers and calculate at least one metric based on the number of candidate account identifiers. The processor is further configured to identify a source unique merchant identifier and match at least one candidate account identifier to a complete account identifier by matching one of the partial account identifiers to the at least one candidate account identifier.

Systems and methods for identifying full account numbers from partial account numbers

A computer-implemented method for authenticating an online user with an access control server (ACS) is provided. The method includes receiving, at a risk-based authentication enabled (RBA-enabled) directory server, an authentication request message including authentication data, extracting, using the RBA-enabled directory server, the authentication data from the authentication request message, transmitting the extracted authentication data to an RBA engine, generating, using the RBA engine, based at least in part on the extracted authentication data, RBA result data including a risk score, a risk analysis, and at least one reason code, transmitting the RBA result data to the RBA-enabled directory server, embedding, using the RBA-enabled directory server, the RBA result data into the authentication request message to generate an enhanced authentication request message, and transmitting the enhanced authentication request message to the ACS to enable the ACS to make an authentication decision based on the RBA result data.

Systems and methods for authenticating online users with an access control server

A computing system for detecting a pattern of fraudulent network events in a payment card network is configured to continuously receive a plurality of scored transaction authorization requests each including a respective account number and a respective fraud score. The computing system is also configured to sort the scored transaction authorization requests into account ranges based the account number, and sort the transaction authorization requests within each of the account ranges into a fraud score range stripes based on the corresponding fraud score. The computing system is further configured to calculate, for the scored transaction authorization requests within each fraud score range stripe, a ratio of a cumulative metric for a shorter time period over a longer time period, and detect, in near real-time, a fraud event associated with one of the account ranges based on the ratio for one of the fraud score range stripes within the account range.

Systems and methods for early detection of network fraud events

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. The computer system determines a merchant rank for each merchant based on the received transaction information and the candidate cardholder preference information, and determines a neutral merchant rank for each merchant based on the received transaction information and neutral cardholder preferences of the plurality of cardholders. The computer system also determines a merchant score for each of the plurality of merchants by comparing the merchant rank to the neutral merchant rank.

System, method, and non-transitory computer-readable storage media for recommending merchants

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Wildwood, MO, United States of America

Christopher John Merz