Abstract: A computer-based method for identifying a user computing device used in a fraudulent transaction is provided. The method includes receiving device data associated with the user computing device during a first payment transaction initiated from the user computing device, wherein the device data is capable of uniquely identifying the user computing device. The method further includes storing the device data within the at least one memory device, and receiving an indication that the first payment transaction initiated from the user computing device was fraudulent. The method further includes assigning a risk factor to the user computing device, and transmitting the risk factor to a merchant, wherein the merchant uses the risk factor to determine whether to process a resale transaction initiated from the user computing device wherein the resale transaction is associated with a resale of goods acquired in association with the first payment transaction.

Abstract: An auto-enrollment billing updater (AEBU) computing device for enrolling enrollees in an automatic updating program is provided.

Abstract: Computing systems and methods for detecting account range fraud attacks in a payment card network are described herein. An attack detection and response (ADR) computing device detects a fraud attack in which a set of primary account numbers (PANs) that share a common bank identification number (BIN) are subject to potential fraud, retrieves transaction records associated with transactions initiated during the fraud attack, and, for each transaction, determines an issuer response that indicates whether the transaction was authorized or declined. The ADR computing device also extracts, for each authorized transaction, the PAN from the transaction record, identifies a respective issuer of the payment card associated with each extracted PAN, and transmits a fraud attack alert to each identified issuer, the fraud attack alert identifying the fraud attack, a time period associated therewith, and the PANs associated with the authorized transactions, causing the issuer to record the PANs as compromised.

Abstract: A system for building a data table of travel-related data and using the data table to reduce false declines when processing payment transactions is provided. The system includes a travel identifier (TI) computing device configured to receive transaction data that includes travel-related data and cardholder identifiers, the transaction data associated with transactions initiated by a cardholder, identify the travel-related data for the cardholder, and build a data table for storing one or more records within an itinerary data source using the travel-related data. The TI computing device is also configured to receive current transaction data for a current transaction initiated by the cardholder including a current transaction location and a current transaction date. The TI computing device is further configured to authenticate the current transaction data by electronically matching the current transaction location and the current transaction data to the data table stored in the itinerary data source.

Abstract: A computer-implemented method for isolating transaction records having deficient standard data elements. The method may include: acquiring a first transaction record corresponding to a transactional entity, the first transaction record including a set of standard data fields in a first state; acquiring a second transaction record corresponding to the transactional entity, the second transaction record including the set of standard data fields in a second state; analyzing the first state and the second state to identify a deficiency of the standard data fields of one or both of the first transaction record and the second transaction record, the deficiency corresponding to a misclassification of an installment payment transaction of the transactional entity; and storing a record of the misclassification, the record identifying one or both of the first transaction record and the second transaction record.

Abstract: A computing system for validating repeating data is described. The computing system includes at least one computing device including at least one processor communicatively coupled to a database. The at least one processor is programmed to receive a first instance of data, the first instance of data including first repeating data elements, and store, in the database, the first repeating data elements. The at least one processor is also programmed to receive a second instance of data, the second instance of data including second repeating data elements, determine the second instance of data includes the second repeating data elements, and compare the second repeating data elements to the first repeating data elements. The at least one processor is further programmed to determine the second repeating data elements are inconsistent with the first repeating data elements and transmit a signal associated with the second repeating data elements.

Abstract: Described are systems and methods for transferring a token between mobile computing devices. A token transfer processing computing device includes a memory device for storing data and a processor in communication with the memory device. The processor is programmed to receive a token transfer message. The token transfer message includes a current device identifier associated with a current mobile device having an original token associated therewith for initiating secure payments using the current mobile device, and a new device identifier associated with a new mobile device replacing the current mobile device. The processor is further programmed to perform a lookup in a device-to-token mapping table to identify the original token associated with the current mobile device. The processor further generates an updated token associated with the payment account and transmits a token transfer response to the new mobile device. The token transfer response includes the updated token.

Abstract: A computer-implemented method for enhancing authorization of prepaid payment cards is provided. The method is implemented using an interchange network and an authorization computing device in communication with a memory.

Abstract: Systems for identifying multiple merchant category codes associated with a merchant include a database and a server. The database has a merchant table with several merchant records, which have unique merchant identifiers associated with distinct merchants and one or more active merchant category codes associated with the merchant identifiers. The server receives a clearing transaction message, which includes payment account data associated with an issuer. A transaction merchant identifier in the message is detected by the server. The server retrieves a merchant record that corresponds to the transaction merchant identifier. The server determines whether the merchant record includes several merchant category codes, and if it does, adds an indicator within a first data element and the active merchant category codes within a second data element of the clearing transaction message. The server then transmits the clearing transaction message to the issuer associated with the payment account data.

Abstract: A fair price estimator system has a memory device and a processor programmed to receive historical transaction data including historical payment transactions between account holders and merchants. The transaction data includes a merchant name, category code (MCC), and location associated with each of the payment transactions. The processor generates a first subset of data based on predetermined transaction parameters and stores the first subset in the memory device. The processor receives, from a consumer, a first input value including one or more of a merchant name and/or an MCC that are included in the first subset of data, and a second input value including a location identifier. The processor generates a second subset of data from the first subset based on the input values. The processor then determines one or more transaction value properties of the second subset of data and presents to the consumer the one or more transaction value properties.

Abstract: Described herein is a data optimization computer system for optimizing transaction authorization request messages directed to an authorizing party. The computer system includes a historical transaction database, a merchant database, and a data optimization computing device. The historical transaction database stores a plurality of historical transaction records. The merchant database stores a first merchant registered with the optimization computer system. The data optimization computing device may analyze at least a subset of the historical transaction records to generate a set of optimization rules. The set of optimization rules identifies optimal values for an optimized transaction authorization request message. The optimized transaction authorization request message may be associated with an improved likelihood of resulting in a positive request outcome.

Abstract: A computer-implemented method for enhancing authorization of prepaid payment cards is provided. The method is implemented using an authorization computing device in communication with a memory. The method includes storing a plurality of transaction histories associated with a plurality of prepaid payment cards, receiving an authorization request for a payment transaction between a cardholder and an originating merchant initiated using a prepaid payment card, determining a transaction history associated with the prepaid payment card based on the plurality of transaction histories, calculating a prepaid risk score for the payment transaction based on the authorization request and the determined transaction history, and transmitting the prepaid risk score to the originating merchant.

Abstract: A capacity analysis computing device for determining a restaurant capacity level is provided. The capacity analysis computing device is configured to store historical transaction data for a restaurant for a period of time, and analyze the historical transaction data to identify a maximum restaurant capacity for the restaurant over the period of time. The capacity analysis computing device is also configured to receive, from a user computing, a selected time interval for which a current capacity level is to be determined. The capacity analysis computing device is further configured to identify a similar historical time interval to the selected time interval, and determine a historical capacity level for the restaurant during the similar historical time interval. The capacity analysis computing device is further configured to assign the historical capacity level as the current capacity level for the restaurant, and display the current capacity level on the user computing device.

Abstract: An insight data computing system for generating a pre-chargeback record for a payment transaction between a customer and a merchant is provided. The payment transaction is authorized over a payment processing network based on transaction data submitted over the payment processing network. The transaction data is stored by the payment processing network in a historical transaction database. The insight data computing system includes an insight data interface computing device programmed to (i) receive, via an insight communication channel other than the payment processing network, an insight data message including insight data and transaction link data, (ii) store the insight data in an insight database, (iii) link the insight data to the transaction data by matching the transaction link data in the insight data to the transaction data in the historical transaction database, and (iv) generate the pre-chargeback record including the transaction data and the linked insight data.

Abstract: A dispute scoring computing device for generating chargeback dispute scores is provided. The dispute scoring computing device extracts historical transaction data and account profile data for a plurality of transactions associated with an account, and generates a chargeback dispute prediction model for the account based on the extracted data. The dispute scoring computing device further receives a candidate chargeback for a transaction initiated with a merchant using the account, extracts transaction data from the candidate chargeback, and determines, using the generated chargeback dispute prediction model, a chargeback dispute score indicating a likelihood that the candidate chargeback, if disputed by the merchant, would result favorably for the merchant.

Abstract: A computing network system including a historical authorization database, a lost and stolen card (LSC) database, an account data breach (ADB) database, and a compromised identification (CI) computing device is provided. The CI computing device retrieves a set of historical account identifiers associated with historical transactions of a candidate merchant from the historical authorization database. The CI computing device compares the historical account identifier to lost and/or stolen (LS) account data stored by the LSC database and breach data stored by the ADB database. The CI computing device generates a compromised account message when a historical account identifier has a matching account identifier within the LS account data and/or the breach data. The compromised account message includes the matching account identifier and an associated reason code indicating a cause of compromise. The CI computing device transmits the compromised account message to the candidate merchant for review and analysis.

Abstract: An auto-enrollment billing updater (AEBU) computing device for enrolling enrollees in an automatic updating program is provided.

Abstract: A chargeback analytics computing device for generating chargeback analytics associated with service chargebacks is provided. The chargeback analytics computing device is configured to retrieve transaction data for a merchant, the transaction data associated with transactions initiated at the merchant, and extract chargeback data from the transaction data, the chargeback data associated with chargeback transactions. The chargeback analytics computing device also parses the chargeback data to identify a chargeback reason code associated with each chargeback transaction. Based upon the chargeback reason codes, the chargeback analytics computing device isolates a fraud-related portion and a non-fraud-related portion of the chargeback data, and extracts a service subset of the non-fraud-related portion associated with service chargeback transactions, wherein a service chargeback transaction is initiated by a cardholder having an unsatisfactory experience with the merchant.

Abstract: A computer-implemented method for identifying errors in transaction messages associated with payment transactions. The method includes a step of receiving a transaction message associated with a financial transaction, whereby the financial transaction originates from a merchant and is processed by an acquirer. The transaction message comprises a plurality of data element fields, with at least one of the data element fields being a merchant identification field used to identify the merchant originating the financial transaction. An additional step includes performing an error-identification routine on the transaction message, with the error-identification routine including analyzing a merchant identification (ID) data element populated in the merchant identification field to determine if the merchant ID data element is not uniquely associated with the merchant.

Abstract: Systems and methods for verifying the current status of a payment card are provided that may efficiently aggregate and distribute non-visible information regarding a recovered payment card. More particularly, the systems and computer-implemented methods of the present invention permit the efficient aggregation of the non-visible payment account data associated with a payment card and the distribution of such data to investigators in possession of the card. Such systems and methods for verifying a payment card typically involve: (a) aggregating payment account data associated with the payment card in an aggregated data storage site; (b) obtaining visible verification data associated with the payment card from an investigator; (c) verifying the visible verification data associated with the payment card; (d) retrieving the payment account data from the aggregated data storage site; and (e) submitting the payment account data to the investigator.