Abstract: A method for detecting fraudulent transactions includes generation of a graph including a plurality of nodes and a plurality edges between the plurality of nodes based on historical transaction data of a plurality of historical transactions. The plurality of nodes include a set of merchant nodes and a set of consumer nodes. A set of static features and a plurality of dynamic features are determined based on the historical transaction data and the generated graph, respectively. A neural network is trained based on the set of static features and the plurality of dynamic features for detection of transaction fraud. The neural network is used to detect a first transaction as one of a fraudulent transaction or a legitimate transaction based on first transaction data of the first transaction.

Abstract: A system and computer-implemented method includes the operations of transmitting a cold reset signal to a multiple-funding source payment card and receiving a first answer-to-reset message therefrom. The first answer-to-reset message includes governing rules for performing a single-swipe transaction. The operation also includes receiving payment account details for a first payment account in accordance with the governing rules. A first PIN associated with the first payment account is input by a cardholder and a first payment authorization request message for approval of the single-swipe transaction is transmitted. Upon receipt of a payment declined response message, a warm reset signal is transmitted to the payment card. A second answer-to-reset message is received including payment account details for a second payment account.

Abstract: A method for audience recommendation using node similarity in combined contextual graph embeddings can include receiving a merchant identifier of a merchant and generating one or more merchant tags describing merchant data corresponding to the merchant. A set of audience embeddings can be generated from a set of audience auxiliary data using an audience taxonomy and a set of merchant embeddings can be generated from the merchant data relating to the merchant using the one or more merchant tags. The set of audience embeddings and the set of merchant embeddings are used to produce a heterogenous information network of combined audience data and merchant data, which is then analyzed to identify relationships between each audience and the merchant. A score for one or more audiences can be determined based on the relationships between the one or more audiences and the merchant.

Abstract: A method for determining the validity of a computational model using a blockchain and zero knowledge principles includes: storing, in a memory of a first computing system, a computational model; receiving, by a receiver of the first computing system, a blockchain data value from one block of a plurality of blocks comprising a blockchain, wherein the blockchain data value includes a data set; receiving, by the receiver of the first computing system, an expected accuracy value; applying, by a processor of the first computing system, the data set to the computational model to generate a result value; and determining, by the processor of the first computing system, a validity measurement for the computational model based on a comparison of the generated result value and the expected accuracy value.

Abstract: Embodiments provide methods and systems for merchant data cleansing in payment network. Method performed by server system includes accessing electronic payment transaction records from transaction database. Each electronic payment transaction record includes merchant data fields. Method includes determining set of electronic payment transaction records with ambiguous merchant data fields having matching probability scores less than predetermined threshold value computed by probabilistic matching model and identifying at least one issue for non-matching of each of set of electronic payment transaction records. Method includes determining data model based on at least one issue of each of set of electronic payment transaction records. Data model is one of: phone-to-city model, payment aggregator model, and merchant name normalization model.

Abstract: The invention relates to methods and systems for reducing user interventions necessary for authentication of electronic payment transactions. In an embodiment the invention comprises (i) receiving from a POS terminal a payment transaction request, and information identifying a first payment card for implementing the payment transaction request, (ii) receiving from a wireless access point, information corresponding to a set of payment cards enrolled with a mobile payment wallet implemented on said mobile communication device, (iii) determining whether received information corresponding to the first payment card matches received information corresponding to any payment card within the set of payment cards enrolled with the mobile payment wallet, and (iv) implementing the requested payment transaction based on the first payment card.

Abstract: A method for audience recommendation using node similarity in combined contextual graph embeddings can include receiving a merchant identifier of a merchant and generating one or more merchant tags describing merchant data corresponding to the merchant. A set of audience embeddings can be generated from a set of audience auxiliary data using an audience taxonomy and a set of merchant embeddings can be generated from the merchant data relating to the merchant using the one or more merchant tags. The set of audience embeddings and the set of merchant embeddings are used to produce a heterogenous information network of combined audience data and merchant data, which is then analyzed to identify relationships between each audience and the merchant. A score for one or more audiences can be determined based on the relationships between the one or more audiences and the merchant.

Abstract: Embodiments provide electronic methods and systems for facilitating payment authorization for payment transactions initiated from an on-board device of an autonomous vehicle. The method performed by a server system includes receiving payment transaction request initiated from on-board device positioned in autonomous vehicle. The method further includes accessing authentication parameters received from on-board device, wherein authentication parameters include multisensory data captured using sensors positioned in autonomous vehicle, and generating authentication features based on authentication parameters and neural network models. The neural network models are trained based on historical multisensory data of one or more autonomous vehicles.

Abstract: A method for facilitating entity resolution is provided. A server generates a graph based on a first dataset comprising a first entity and a second dataset comprising a plurality of entities. Each node in the generated graph corresponds to the first entity or one of the plurality of entities. The server generates a plurality of embeddings for the plurality of nodes in the generated graph. Each of the plurality of embeddings represents an entity as a point in a d-dimensional embedding space. The server identifies a set of nearest neighbors for the first entity based on the plurality of embeddings. The server determines a similarity metric for each of the identified nearest neighbor with respect to the first entity. The server associates the first entity with a second entity of the second dataset that corresponds to a nearest neighbor in the set of nearest neighbors.

Abstract: A method for detecting fraudulent transactions includes generation of a graph including a plurality of nodes and a plurality edges between the plurality of nodes based on historical transaction data of a plurality of historical transactions. The plurality of nodes include a set of merchant nodes and a set of consumer nodes. A set of static features and a plurality of dynamic features are determined based on the historical transaction data and the generated graph, respectively. A neural network is trained based on the set of static features and the plurality of dynamic features for detection of transaction fraud. The neural network is used to detect a first transaction as one of a fraudulent transaction or a legitimate transaction based on first transaction data of the first transaction.

Abstract: A method for verified data storage via blockchain includes: storing a blockchain comprised of a plurality of blocks, each comprised of a block header and a plurality of transaction values, the block header including a timestamp; receiving a transaction notification including an entity identifier and data values; validating the data values based on a validation notification received from a verifying entity; generating a new block header comprised of a current timestamp, a block reference value, and a transaction reference value, the block reference value being generated via hashing of the block header included in a most recent block based on the timestamp, and the transaction reference value being generated via hashing of new transaction values including the data values; generating a new block comprised of the generated new block header and the new transaction values; and transmitting the new block to a node associated with the blockchain.

Abstract: A payment network server for processing a cashless payment transaction via a point-of-sale (POS) terminal associated with a merchant server is described.

Abstract: A method for secure usage of a gift card via blockchain includes: storing a blockchain including a specific data value related to a gift card that includes a gift card number and a first recipient address; receiving a transfer request including the gift card number, a first digital signature, and a device identifier; verifying the first recipient address based on the first digital signature; generating a new data value comprising the gift card number, the device identifier, and a second recipient address; transmitting the generated new data value to a node associated with the blockchain; receiving a redemption request from a second computing system including the gift card number, a second digital signature, and a submitted device identifier; verifying the second recipient address and submit device identifier based on the second digital signature and the device identifier, respectively; and transmitting a result of the verification to the second computing system.

Abstract: The present disclosure generally relates to an electronic system, a computerized method, and a non-transitory computer-readable storage medium for advertisement pricing. The system comprises a host server configured for performing steps of the method comprising: generating an electronic map representation of a geographical area; demarcating the electronic map representation into a plurality of demarcated regions; retrieving, from a transaction database, transaction data associated with merchant transactions in the plurality of demarcated regions; receiving, from a telecommunications service provider, mobile traffic data for generating consumer traffic data indicative of consumer traffic activity in the plurality of demarcated regions; and performing an advertisement pricing process to determine advertisement prices for each demarcated region based on at least the transaction data and consumer traffic data.

Abstract: A method for redemption of an electronic voucher via blockchain includes: storing transaction data for a proposed payment transaction comprising a transaction amount; receiving an electronic voucher and a blockchain transaction identifier from a computing device, the voucher including payment credentials associated with a transaction account; receiving blockchain data associated with a blockchain including a transaction data value corresponding to the blockchain transaction identifier including a redemption amount; validating eligibility of the electronic voucher based on a comparison of the transaction data value to the stored transaction data; updating the stored transaction data based on the transaction data value, including updating the transaction amount based on the redemption amount; and transmitting the updated transaction data and the payment credentials included in the electronic voucher to a third party system.

Abstract: A system and computer-implemented method includes the operations of transmitting a cold reset signal to a multiple-funding source payment card and receiving a first answer-to-reset message therefrom. The first answer-to-reset message includes governing rules for performing a single-swipe transaction. The operation also includes receiving payment account details for a first payment account in accordance with the governing rules. A first PIN associated with the first payment account is input by a cardholder and a first payment authorization request message for approval of the single-swipe transaction is transmitted. Upon receipt of a payment declined response message, a warm reset signal is transmitted to the payment card. A second answer-to-reset message is received including payment account details for a second payment account.

Abstract: A system and computer-implemented method includes the operations of transmitting a cold reset signal to a multiple-funding source payment card and receiving a first answer-to-reset message therefrom. The first answer-to-reset message includes governing rules for performing a single-swipe transaction. The operation also includes receiving payment account details for a first payment account in accordance with the governing rules. A first PIN associated with the first payment account is input by a cardholder and a first payment authorization request message for approval of the single-swipe transaction is transmitted. Upon receipt of a payment declined response message, a warm reset signal is transmitted to the payment card. A second answer-to-reset message is received including payment account details for a second payment account.

Abstract: A system and computer-implemented method includes the operations of transmitting a cold reset signal to a multiple-funding source payment card and receiving a first answer-to-reset message therefrom. The first answer-to-reset message includes governing rules for performing a single-swipe transaction. The operation also includes receiving payment account details for a first payment account in accordance with the governing rules. A first PIN associated with the first payment account is input by a cardholder and a first payment authorization request message for approval of the single-swipe transaction is transmitted. Upon receipt of a payment declined response message, a warm reset signal is transmitted to the payment card. A second answer-to-reset message is received including payment account details for a second payment account.

Abstract: A payment network server for processing a cashless payment transaction via a point-of-sale (POS) terminal associated with a merchant server is described.

Abstract: The invention relates to methods and systems for reducing user interventions necessary for authentication of electronic payment transactions. In an embodiment the invention comprises (i) receiving from a POS terminal a payment transaction request, and information identifying a first payment card for implementing the payment transaction request, (ii) receiving from a wireless access point, information corresponding to a set of payment cards enrolled with a mobile payment wallet implemented on said mobile communication device, (iii) determining whether received information corresponding to the first payment card matches received information corresponding to any payment card within the set of payment cards enrolled with the mobile payment wallet, and (iv) implementing the requested payment transaction based on the first payment card.