Abstract: A single sign-on system using blockchain is disclosed. The single sign-on system may interconnect various organization systems over a peer-to-peer network, with each organization system having a blockchain node and an application programming interface (API). The blockchain node invokes and uses a smart contract to write registration credentials to the blockchain during a registration process. During a login process, the blockchain node invokes the smart contract to determine whether login credentials match stored login credentials in the blockchain. In response to matching login credentials, the API may generate a single sign-on token that can be used by a user device to access one or more organization systems connected over the network.

Abstract: A system may receive a query configured to access a column in a data table. The data table may be in a flat file in a big data storage format. The system may detect the language type of the query and validate the query against the syntax of the language type. The system may also validate an access permission for data in the data table. The access permission may be stored in a permissions database. The system may generate a temporary table including the column with the temporary table configured to support the language type. The system may execute the query against the temporary table to generate a query result based on the temporary table as though it were the underlying data table. The system may enforce column-level or row-level access permissions by excluding columns or rows from the temporary table.

Abstract: A transaction card can be manufactured from rigid materials, such as glass, stone, or ceramics. The transaction card can have a first rigid layer having a first external surface and a first internal surface, with a pocket within the first external surface of the first rigid layer. The transaction card can have a second rigid layer having a second external surface and a second internal surface. A binding layer can be located between the first rigid layer and the second rigid layer can affix the first rigid layer to the second internal layer. An integrated circuit chip can be affixed within the pocket of the first rigid layer. A rim can extend from the first external surface of first rigid layer around a first edge of the first rigid layer and a second edge of the second rigid layer and onto the second external surface of the second rigid layer.

Abstract: Disclosed are various embodiments for decentralizing the authentication or verification of data. An identity key can be generated for a data item. A request can then be sent to an authentication provider for authentication of the data item, the request comprising the identity key and the data item. A verified claim for the data item can then be received in response. Subsequently, an identity document is generated, the identity document comprising the identity key for the data item and the verified claim. Finally, the identity document can be stored in a distributed ledger.

Abstract: Disclosed are various embodiments for authenticating a user using non-fungible tokens (NFTs). A trusted token issuer verifies a user's identity according to identifying credentials (e.g., government issued identification, passport, driver's license, etc.) presented by the user and creates a non-fungible token in response to verifying the credentials. The non-fungible token is associated with a user identifier and can be used by an access provider to authenticate a user requesting access to restricted content provided by the access provider. For example, when a client device associated with the user requests access from an access provider to an access-restricted website or other type of access-restricted area (e.g., building, concert venue, network, etc.), the access provider (e.g., website server, building computing device, venue system, etc.) uses the properties of the non-fungible token to verify one's identity and permit access upon verification.

Abstract: Disclosed are various embodiments for authenticating users of applications using decentralized data models for storing a user's identity. A fingerprint for a computing device is received from an application executing on the computing device. An identity key associated with the fingerprint for the computing device is then obtained, the identity key being linked to a signed claim. The signed claim is retrieved and evaluated. The application executing on the computing device is then granted access to the computing resource in response to evaluating the signed claim.

Abstract: Disclosed are various embodiments for using decision trees for machine-learning when data is missing from a data set. A first attribute for splitting a plurality of records is identified. Then, the plurality of records are split into a first subset of records and a second subset of records. The first subset of records can include each of the plurality of records where a value is present for the first attribute and the second subset of records comprising each of the plurality of records where the value is absent for the first attribute. Finally, a node can be added to a decision tree that reflects the split of the plurality of records into the first subset of records and the second subset of records.

Abstract: Disclosed are various embodiments for implementing a decentralized messaging system that allows users to exchange messages via an inbox maintained through a distributed ledger. A messaging inbox can be created for a user in a distributed ledger using an inbox address that includes a string of alphanumeric numbers without an identifying domain name or identifying information about the user. Furthermore, a user may define content preferences associated with the inbox that can be used by the distributed ledger to filter content received in the inbox to minimize unwanted or undesired content provided to the user.

Abstract: At least some embodiments of the present disclosure are directed to an exemplary system including an application server; a cache memory storage; and a datastore; where the application server is at least configured to: receive, from one or more web client sessions, real-time user-related activity data that is representative of one or more activities performed by a user during a day; store the real-time user-related activity data in a temporary cache user profile data structure of the at least one cache memory storage; upon the receipt of the real-time user-related activity data, invoke, in real-time, a plurality of APIs that are configured to determine a user-specific eligibility data, generate a fixed activity plan; and attribute, in real-time, an activity performance to the fixed activity plan based on a pre-determined allocating rule.

Abstract: A zero-knowledge proof purchase system and process using blockchain is disclosed. The system may comprise a customer device, a merchant system, an issuer system, and a blockchain network having a zero-knowledge proof (ZKP) smart contract. The system may implement a zero-knowledge proof algorithm haying a key generator function, a proof function, and a validate function. Each function may be configured to perform various tasks in the system to support and enable zero-knowledge proof purchases.

Abstract: The systems and methods described herein may be used to recommend an item to a consumer. The methods may comprise determining, based on a collaborative filtering algorithm, a consumer relevance value associated with an item, and transmitting, based on the consumer relevance value, information associated with the item to a consumer. A collaborative filtering algorithm may receive as an input at least one of: a transaction history associated with the consumer, a demographic of the consumer, a consumer profile, a type of transaction account, a transaction account associated with the consumer, a period of time that the consumer has held a transaction account, a size of wallet, a share of wallet, and/or the like.

Abstract: The system may be configured to perform operations including receiving a transaction history comprising transaction information associated with a plurality of transactions for an entity; analyzing transaction information associated with a transaction of the plurality of transactions; and detecting a leakage event associated with the transaction. Detecting the leakage event may comprise determining a payment method for the transaction in response to the analyzing the transaction information; and comparing the payment method to a desired payment method, wherein the leakage event is detected in response to the payment method differing from the desired payment method.

Abstract: The systems and methods may be used to recommend an item to a consumer. The methods may comprise determining, based on a collaborative filtering algorithm, a consumer relevance value associated with an item, and transmitting, based on the consumer relevance value, information associated with the item to a consumer. A collaborative filtering algorithm may receive as an input a transaction history associated with the consumer, a demographic of the consumer, a consumer profile, a type of transaction account, a transaction account associated with the consumer, a period of time that the consumer has held a transaction account, a size of wallet, and/or a share of wallet. The method may further comprise generating a ranked list of items based upon consumer relevance values, transmitting a ranked list of items to a consumer, and/or re-ranking a ranked list of items based upon a merchant goal.

Abstract: At least some embodiments are directed to an exemplary computer-based electronic activity tracking system that detects activity patterns receiving data values that represent at least one electronic activity. The exemplary electronic activity tracking system includes a detector of unsecure electronic activities that identifies electronic activity patterns performed by a user or non-person entity. The detector of unsecure electronic activities utilizes unsupervised machine learning techniques to detect the electronic activity patterns. The detected electronic activity patterns correspond to unsecure or malicious electronic activities. The electronic activity tracking system outputs notifications indicative of identified unsecure or malicious activity patterns and identifies entities associated with such unsecure or malicious activity patterns. The exemplary electronic activity tracking system implements a graphical user interface operated from a client computing device.

Abstract: Systems and methods for presenting a personalized value added offer during an advanced verification process are provided. An access control server may receive an enrollment verification request comprising data relating to an account holder. The server may determine an enrollment status of the account holder and determine a value added offer based on the account holder. The server may display an advanced verification interface for user input. The advanced verification interface may include the value added offer and/or a security credential prompt. The server may personalize the advanced verification interface and/or the value added offer based on monitoring the system and compiling historical transaction data.

Abstract: A reward points transfer system and process using blockchain is disclosed. Transaction account issuers may write reward transfer messages to the blockchain to initiate a transfer of reward points for a transaction account holders account to one or more rewards partners. Rewards partners may retrieve the reward transfer messages from the blockchain, and write a reward transfer response message to the blockchain to confirm receipt of the reward points transfer and to update the status of the transfer. The transaction account issuers and rewards partners may encrypt the messages and generate hashes based on the messages prior to writing to the blockchain, to ensure that the messages are not tampered with during the transfer process.

Abstract: Systems and methods for identifying data of interest are disclosed. The system may retrieve unstructured data from an internet data source via an alert system or RSS feed. The system may input the unstructured data into various models and scoring systems to determine whether the data is of interest. The models and scoring systems may be executed in order or in parallel. For example, the system may input the unstructured data into a Naïve Bayes machine learning model, a long short-term memory (LSTM) machine learning model, a named entity recognition (NER) model, a semantic role labeling (SRL) model, a sentiment scoring algorithm, and/or a gradient boosted regression tree (GBRT) machine learning model. Based on determining that the unstructured data is of interest, a data alert may be generated and transmitted for manual review or as part of an automated decisioning process.

Abstract: Systems and methods for the calculation of a dynamic trust score are disclosed. The dynamic trust score may indicate a likelihood that the consumer will complete the transaction in a positive manner. The system may calculate the dynamic trust score based on various static and dynamic variables including digital identity data, internal data, third-party data, private data, and/or data from the transaction initiated by the consumer.

Abstract: A consumer may initiate a transaction using a transaction account. The transaction account issuer may transmit a notification to the consumer that the transaction has been authorized. The consumer may select requestees with whom to split the transaction. The transaction account issuer may transmit notifications to requestees to request payment from the requestees. The transaction account issuer may transfer the payment from a transaction account of the requestee to the consumer's transaction account.

Abstract: The systems, methods and computer program products (collectively “system”) described herein relate to customized real time data delivery. The system may be configured to receive, by a performance marketing cluster, first data from a first data source. The system may also receive, by the performance marketing cluster, second data from a second data source. The system may determine, by the marketing cluster, an analysis scheme for the first data and the second data based on the first data source. The system may also determine, by the marketing cluster, at least one of a propensity to act or a recommendation selected from a predefined number of available options for a population based on the analysis scheme and the first data source.