Abstract: A payment management system and method of managing a payment network includes generating a payment token based on a bank account of a user (e.g., a buyer), receiving a dynamic code through a network for a transaction, and validating a request for payment of the transaction using an installment plan based on funds from the bank account. The validating the request for payment of the transaction is performed based on operations which include authenticating the payment token and verifying the dynamic code. In addition, the method includes generating a decision signal indicating a decision for the request when the request for payment is validated and transmitting the decision signal to a merchant system to authorize or decline completion of the transaction.

Abstract: A method for maintaining a consistent blockchain ledger for storing commitments across multiple separate blockchains includes: storing a blockchain comprised of a plurality of blocks, each block including at least a block header and one or more blockchain data values; receiving a base commitment from a first node, where the first node is included in a first blockchain network; generating a first new block including at least a first block header and the received base commitment; storing the first new block in the blockchain; receiving a state commitment from an additional node included in each of at least two additional blockchain networks; generating an additional new block including at least an additional block header and each received state commitment; and storing the additional new block in the blockchain.

Abstract: A method for reducing file size of a blockchain through hash truncation includes: receiving a plurality of blockchain transactions; generating a first Merkle root of a first Merkle tree comprised of a first hash of each of the plurality of blockchain transactions; generating a second Merkle root of a second Merkle tree comprised of a second hash of each of the plurality of blockchain transactions, where the second hash is a truncation of the first hash for the respective blockchain transaction; generating a new block comprised of a block header and the first hash of each of the plurality of blockchain transactions, the block header including at least a timestamp, the first Merkle root, the second Merkle root, and a block reference value associated with a prior block in a blockchain; and transmitting the generated new block to a plurality of additional nodes in the blockchain network.

Abstract: A secure and flexible pipeline management solution includes determining, based at least on an order in which files are received, a precedence for defining variables, and when a file has multiple definitions for a variable, the order of appearance of the definitions defines precedence. A configuration file is generated with controlling definitions, which are based on the precedences, and a continuous integration continuous delivery (CI/CD) pipeline is executed dependent upon the configuration file. Multiple inheritances and string interpolation are supported. An advantageous result is a significantly simplified CI/CD pipeline that is secure, flexible, and is agnostic to the target environment. Thus, adding a new environment may not require the conventional (burdensome) task of adding further logical dependencies into the pipeline itself. The disclosed solution thus enhances efficiency and reduces errors when maintaining code bases.

Abstract: A method for generating cryptograms in a webservice environment includes: receiving, in a first environment of a computing system, a credential request transmitted by an external computing device using a secure communication protocol, the credential request including a transaction identifier and account identifier; transmitting, by the first environment, a data request to a second environment of the computing system, the data request including the account identifier; receiving, by the first environment, an account profile and session key from the second environment; transmitting, by the first environment, a cryptogram request to a third environment of the computing system, the cryptogram request including the account profile and session key; receiving, by the first environment, a cryptogram from the third environment generated using the account profile and session key; and transmitting, by the first environment, the cryptogram and transaction identifier to the external computing device via the secure communic

Abstract: A token management computing system for provisioning a payment token to a token storage device for a payment transaction is provided. The token management computing system includes a user computing device in communication with the token storage device and a token management server that includes at least one processor communicatively coupled to a memory device. The at least one processor is programmed to (i) receive, from the user computing device, a token request for a payment token, the request including a payment account number (PAN) selected from a digital wallet stored on the user computing device, and at least one token control, (ii) store token information including the PAN and the at least one token control, (iii) generate a single-use payment token, (iv) transmit the token to the user computing device, and (v) instruct the user computing device to transfer the token to the token storage device.

Abstract: An integrated circuit is disclosed. The integrated circuit comprises: a processing region configured to run one instruction from a plurality of instructions; a first temperature measuring region configured to measure a first temperature within the integrated circuit in response to the processing region running the one instruction; the processing region being configured to compare the measured first temperature with a predefined temperature at the first temperature measuring region when the processing region runs the one instruction and to trigger an event when the measured first temperature exceeds the predefined temperature by a threshold value.

Abstract: A privacy-enhancing system, method, and non-transitory computer-readable medium for securely identifying or verifying an individual over time without retaining sensitive biometric data (e.g., biometric images or biometric templates) for the purpose of securely storing data regarding the individual.

Abstract: The disclosure includes systems and methods for determining a change window for taking an application off-line. The systems and methods include mapping application programming interfaces (APIs) to one or more applications, and based on the API mapping, determining a priority level for each of the applications. A network traffic volume for each of the APIs mapped to the applications is predicted. Based on the predicted network traffic volume and the priority level of each of the applications, the systems and methods determine a change window for taking the applications off-line.

Abstract: An authentication server computing device is provided. The authentication server computing device is configured to receive a transaction request from an audio interface device, generate a first audio file including a first audio transmission, wherein the first audio transmission includes a primary security artifact and at least one secondary security artifact and the primary security artifact is an encoding of a one-time password, store a reference data file including the first audio transmission, transmit the first audio file to a verified user computing device associated with the account identifier, receive a second audio file from the audio interface device, wherein the second audio file includes a second audio transmission, verify the second audio transmission by comparing the second audio transmission to the reference data file including the primary security artifact and the at least one secondary security artifact, and authorize the transaction based on verifying the second audio transmission.

Abstract: Described herein is a data security system for enabling tokenized access to sensitive data, including a token provider configured to initiate a secure connection with a remote client computing device of a first data subject, and receive, from the remote client computing device, a request for an access token to provide a service provider with access to sensitive data associated with the first data subject. The request includes a data definition and authorization parameters including a data source identifier. The token provider is also configured to generate the access token that enables access to the sensitive data from the data source, store the access token in a token database, and transmit, to the remote client computing device, a response including the access token and instructions that enable the remote computing device to display the access token to the first data subject or transmit the access token to the service provider.

Abstract: The disclosure herein describes a system and method for predictive identification of breached entities. Identification number and expiration date pairs associated with compromised records in a source file are analyzed to identify a set of candidate entities having records at least partially matching the source file data pairs having events occurring during a selected time period. Probability vectors are calculated for records associated with each identified entity. A divergence value is calculated which represents a distance between probability distribution vectors for each entity and probability distribution vectors for the source file. A predicted breached entity is identified based on the divergence values. The predicted breached entity is notified of the predicted breach. The notification can include an identification of the breached entity, identification of breached records, predicted time of breach, and/or a recommendation to take action to mitigate the predicted breach.

Abstract: A system and a method are provided for generating a digital receipt for purchases made utilizing a digital wallet or with other payment procedures. The digital receipt is stored in the cloud in a digital receipts repository for later retrieval. The digital receipt can be standardized to facilitate data processing of the data contained in data fields of the digital receipt. The data fields are text/field searchable and actionable so that the receipts and the data therein can be viewed in any manner desired by the user of the digital wallet.

Abstract: Techniques for training a classification model to improve the classification of open banking transactions are presented. The techniques include receiving raw training data from a data source. The raw training data includes historical transaction data made up of a plurality of individual transactions. The raw training data is input into the classification model. The raw training data is processed by performing a data preparation operation on the raw training data. The data preparation operation includes removing numerical characters, repeating special characters, and accent words from the textual data of each transaction. Vocabulary training is then performed on the processed training data, including tokenizing the text of each transaction and converting the tokenized text into a transformer model specific format. The classification model is then trained using a transformer model, which uses the tokenized text. The trained classification model is then stored in a database.

Abstract: A system and computer-implemented method for identifying fraudulent healthcare providers receives raw claims data from one or more data sources. The raw claims data includes claims associated with a selected healthcare provider. Each of the claims includes one or more claim lines. A first model is executed on the raw claims data. The first model determines a first score for the healthcare provider. A second model is executed on the raw claims data. The second model determines a second score for the healthcare provider. In addition, a third model is executed on the raw claims data. The third model determines a third score for the healthcare provider. A final provider-level risk score is determined for the healthcare provider based on the first, second, and third scores.

Abstract: Techniques for training an entity resolution model are presented. The techniques include inputting raw training data into the entity resolution model. The training data includes historical transaction data including a plurality of transactions. A label dictionary is generated by performing natural language processing (NLP) on the training data. The NLP includes scanning text of each transaction, extracting one or more entities from the text, and storing the label dictionary in a database. The label dictionary includes the extracted entities. Tagged data is generated from the training data using the label dictionary. Vocabulary training is performed on the training data, including tokenizing the text of each transaction and converting the tokenized text into a transformer model specific format. The entity resolution model is then trained using a transformer model, which uses the tokenized text and the tagged data. The trained entity resolution model is then stored in a database.

Abstract: Techniques for training an entity resolution model are presented. The techniques include receiving a minimum viable data product (MVDP) scope, a product scope, and a data mining scope from a user. A data mining goal is determined based on the MVDP scope, product scope, and data mining scope. One or more proof of concept (PoC) models are defined based on the data mining goal, and one of the PoC models is selected for training. A trained deep learning model is generated by iteratively training the selected PoC model. The trained deep learning model is then tested and validated against a predefined achievable loss metric using a sample labelled dataset for testing.

Abstract: A swap check oracle receives a transfer request from a user or smart contract on a first blockchain indicating a first digital asset to be transferred. The swap check oracle verifies the authenticity of the user and/or digital asset and instructs the smart contract to transfer the first digital asset to a custodial blockchain address on the first blockchain. Another swap check oracle performs the same process for a second digital asset from a second user on a second blockchain. A central processing server is notified of the successful transfer of the digital assets to the custodial addresses on both blockchains, verifies the holding of the digital assets by the custodial addresses, and then initiates a release of the digital assets to the new parties on both of the blockchains.

Abstract: Systems and methods for reducing false positives for financial transaction fraud monitoring using machine learning techniques. Using an original model for separating transactions into high risk and low risk categories for fraud, transactions falling into the high-risk category may be labeled as a false positive or a true positive. The labels and data associated with the transactions may be used to train two or more false positive reduction models (FPRMs) using iterative machine learning techniques. Once training is complete, a future transaction may be processed using the original model, and, if the original model indicates that the future transaction is high risk, data associated with the future transaction may be processed by the trained FPRM(s), which may determine whether the future transaction is at a high risk or a low risk of being fraudulent.

Abstract: A method for optimized validation of a blockchain transaction through the use of a parallel database and date management includes: receiving a new blockchain transaction that includes unspent transaction outputs; identifying, in a parallel database, a start date for a blockchain wallet involved in the new transaction; identifying a subset of blocks in the blockchain that have been added to the blockchain since the start date; validating the new blockchain transaction by validating the unspent transaction outputs using the subset of blocks; and, if the validation is successful, adding the new transaction to the blockchain, or, if the validation is unsuccessful, notifying the submitter of the failed validation.