Abstract: Methods and systems for providing merchant in-context checkout are described. A user is authenticated based on credentials received from a first application running on a computing device. An authentication code is provided to the first application. A signed verifier and the authentication code is then received from a second application running on the computing device. The authentication code and the signed verifier received from the second application are then validated, and a device token is provided to the second application upon validation. The device token is exchangeable by the second application for an access token that is usable for making payment calls from the second application.

Abstract: A method includes accessing a retention policy and a partitioning strategy for a database. The database includes a control table and a plurality of data tables, and each data table of the plurality of data tables includes one or more data entries. The method also includes populating the control table with control entries based on the retention policy and the partitioning strategy. The populated control entries in the control table represent the plurality of data tables. At each predetermined time interval, the method also includes purging data entries from a first data table of the plurality of data tables based on a retention policy of a first control entry of the populated control entries, and generating future partitions for a second data table of the plurality of data tables based on a partitioning strategy of a second control entry of the populated control entries.

Abstract: A method may include allocating a number of public keys, where each respective public key is allocated to a respective entity of a number of entities; storing a number of private keys, where each respective private corresponds to a respective public key; storing one or more decryption algorithms, where each respective decryption algorithm is configured to decrypt data previously encrypted using at least one encryption algorithm of the encryption algorithms. Each respective encryption algorithm may be configured to encrypt data using at least one public key. Each respective decryption algorithm may be configured to decrypt data using at least one private key. The method may include receiving encrypted data, where the encrypted data is encrypted using a first public key and a first encryption algorithm, and the encrypted data is provided over a network.

Abstract: The disclosed computer-implemented method may include determining a taxonomy of an object from its textual description and also standardized attributes of the object from the description and the taxonomy using a language model, according to embodiments. The method may also include building a graph data structure by using the standardized attributes for a node and connecting the node to other nodes using edges for common attributes. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Methods and systems are presented for reducing computer power consumption and speeding system response times by dynamically generating and deploying one or more small language models (SLMs) to facilitate automated interactions with users. A context is derived for a chat session based on an utterance submitted by the user and other contextual information associated with the chat session. A SLM is generated specifically for the chat session based on the context. The SLM can be generated by extracting one or more portions of an internal structure of a large language model (LLM), or by merging two or more pre-generated SLMs. The SLM is deployed to generate content for the chat session. When it is detected that the context has changed, the SLM can be updated by incorporating additional parameters from the LLM to continue facilitating automated interactions with the user during the chat session.

Abstract: Techniques are disclosed relating to item representations. A computer system may access information identifying a first set of items and generate a representation of the first set of items that positions them in an embedding space. The computer system may send a request to another computer system for information pertaining to an item selected from the first set of items and receive correlation information that identifies recorded user behavior indicative of correlations between a second set of items and the selected item. The computer system may update the representation based on the correlation information, such that at least one of the first set of items that is included in the second set is moved closer to the selected item in the embedding space and at least one of the first set of items that is not included in the second set is moved farther away from the selected item.

Abstract: There are provided systems and methods for a computing framework for enforcement of data privacy consent through device fingerprints. A service provider, including an electronic transaction processor, may provide consent management and enforcement through device fingerprints server-side in place of using device-side cookies or other data. When a device interacts with a service provider and provides or generates user data, the user of the device may opt-in to consenting to share or use that user data for targeted content and/or personalized services. The device may be fingerprinted using unique device parameters and a fingerprinting algorithm to generate a unique device identifier. User segments may then be built for the user based on the user data and to hide or obfuscate the user data. The device fingerprint may then be shared with the user segments so that when the device is further detected, targeted content and personalization may be provided.

Abstract: Systems, methods, apparatus, processes, computer program code and means for conducting transactions are described which allow a first party to a transaction to identify a second party to a transaction.

Abstract: A machine learning engine may be trained using artificial intelligence techniques and used according to techniques discussed herein. While an initial electronic transaction for a resource may be permitted, a subsequent related transaction to the initial electronic transaction may be analyzed in view of additional electronic information that was not available at the time of the initial transaction. Analysis of the subsequent related transaction, using the machine learning engine, may indicate a new classification related to the resource and/or the acquisition of the resource. Based on this new classification, usage of the resource may be restricted and/or denied, and the initial transaction for the resource may even be canceled retroactively.

Abstract: There are provided systems and methods for dynamic user interfaces and content with reduced code development using an intelligent scenario simulation engine. A service provider, such as an online transaction processor, may provide computing services to users, such as electronic transaction processing, which may be facilitated and/or assisted by agents of the service provider. To provide dynamic user interfaces and content tailored to a user experience and based on different simulated scenarios of the user experience, the service provider may utilize a simulation engine to simulate permutations of user interfaces and content from combinations of the user and/or agents data and service states of available services that may be accessed and used through the user interfaces. This may utilize a large language model and/or generative AI to simulate such scenarios, as well as computing code for the user interfaces and calls to provide content via the services.

Abstract: A system and/or method may be provided to silently authenticate a user. An example method of silently authenticating a user includes receiving a request to complete a transaction associated with a merchant application. The request includes a data file including an identifier from the user device. The request is from a user device. The method also includes determining whether the data file includes a refresh token and determining whether the refresh token is valid if the data file includes the refresh token. The method further includes receiving an access token from the user device if the refresh token is valid. The access token includes an authorization scope. The method also includes determining whether the transaction is within the authorization scope. The method further includes authenticating a user if the transaction is within the authorization scope.

Abstract: Systems, methods, and computer program products for using artificial intelligence (AI) models, machine learning, and large language models to identify root causes of issues in a computing environment where multiple applications and computing devices operate. One or more AI models may determine adverse trends from one or more issue metrics, where an issue metric corresponds to issues occurring in a computing system. The AI models may identify issues corresponding to the adverse trends. From the identified issues, the AI models may determine root causes from the issues and the impacted area information and process information from the issues. From the issues and the impacted area information and process information from the issues the AI models may determine recommendations for rectifying the issues. The relations between the root causes, the impacted area information, the process information, and the issues may be formatted and displayed as a traversable network graph.

Abstract: Systems and methods for real-time electronic service processing adjustments are disclosed. In an embodiment, a computer system may determine that a user account activity has triggered an assessment checkpoint from a plurality of assessment checkpoints in a life cycle of a user account. The computer system may retrieve data from the assessment checkpoint and update a lifetime score for the user account based on the retrieved data. The computer system may update the lifetime score by weighting the retrieved data as one or more features in a linear-weighted lifetime score model, for the life cycle. The computer system may adjust a response threshold for the assessment checkpoint based on the updated lifetime score.

Abstract: There are provided systems and methods for on-device accessibility options for checkout data using short-range wireless transmissions without needing a user or device identifier. A user may engage in a transaction with another user, such as a purchase of goods, services, or other items from a merchant at a physical merchant location. The merchant may provide options to receive checkout data on a mobile device so that the checkout data may be presented with accessibility options that assist a user in consuming the data. The checkout data may be transmitted via data exchanges using short-range wireless communications. A message may be generated that includes a webpage address or another identifier allowing for retrieval of a webpage or user interface data for the checkout data. The checkout data may also be updated by the user on the mobile device, which may be provided to the merchant device.

Abstract: Methods and systems are presented for providing a framework for analyzing graphs that exhibit non-homophilous behavior. Under the framework, a structural analysis and a feature-based analysis will be performed on a sequence of graphs. When performing the feature-based analysis, various features are extracted from each node in the sequence of graphs, and clusters of nodes are identified from each graph based on the features. A set of evolving prototypes is generated to represent evolving characteristics of the clusters of nodes, and a set of persistent prototypes is generated to represent persistent characteristics of the clusters of nodes. Information derived from the structural analysis of the graphs, the set of evolving prototypes, and the set of persistent prototypes are embedded within the nodes of the graphs. The embedded information is then used to classify the nodes.

Abstract: There are provided systems and methods for dynamic autoscaling of server resources using intelligent demand analytic systems. A service provider, such as an electronic transaction processor for digital transactions, may utilize different computing resource to provide computing resources to users. During use of such computing resources by end users and their computing devices, different demand and needs may be required by such users and devices. The service provider may utilize an intelligent machine learning system to predict computing resource needs and demands at different future time periods based on past usages over similar time periods, computing requests and demands, and network communications. The machine learning engines may identify one or more usages curves, which may be of one or more degrees of curvature, to determine potential future usage. Using these past analytics, the service provider may dynamically scale automatic provision of computing resources.

Abstract: A computer-implemented method may include receiving an image to analyze for potential objects; providing the image as input to a pretrained machine learning model, where the pretrained machine learning model is trained to detect a known object that corresponds to a predefined category within the pretrained machine learning model or a generic object; determining based on output from the pretrained machine learning model, that the image comprises an instance of a generic object; performing, based on determining that the image comprises an instance of a generic object, a similarity search between the image and a library of images; and determining, for the instance of the generic object, a specific category defined by the library of images based at least in part on the similarity search. Various other methods and systems are also disclosed.

Abstract: Methods and systems are presented for providing a framework for facilitating token sharing with contract issuers based on processing of smart contract transactions. The framework provides a mechanism for allowing one or more computer nodes within a blockchain network to opt-in to a token sharing agreement with a contract issuer and a mechanism for an opted-in computer node to share tokens with the contract issuer in a decentralized manner. When a computer node has opted-in to the token sharing agreement, the computer node, by executing a smart contract, performs a set of computer procedures that is non-productive to the processing of the smart contract transaction. The execution of the set of non-productive computer procedures provides an additional amount of processing fee based on the processing of the smart contract transaction. The computer node then transfers a portion of the additional amount of processing fee to an account of the contract issuer as part of the processing of the smart contract.

Abstract: A method for facilitating secured execution of blockchain transactions includes generating and training one or more models using real-world blockchain transaction data corresponding to one or more blockchains, wherein each of the one or more models corresponds to a respective blockchain of the one or more blockchains, receiving a request to perform a simulation of one or more transactions on a first blockchain of the one or more blockchains, and in response to receiving the request, identifying a first model of the one or more models that corresponds to the first blockchain, determining a transactional stress level for the simulation, determining a number of nodes for the simulation, and executing, using the first model, the simulation based on the request to predict a result of the one or more transactions if they were executed on the first block-chain.

Abstract: Techniques are disclosed relating to maintaining a point in time (PIT) database. A database system updates a snapshot table included in the PIT database according to a snapshot table time-to-live (TTL) value of 3K/2. In some embodiments, the updated snapshot table is configured to provide accurate data for queries up to K years prior to points in time at which the queries are executed. The system may update a binlog table included in the PIT database according to a binlog table TTL value of K. The system may receive a request to access PIT data stored in the PIT database. Based on a timestamp specified in the request, the system may access the PIT database. The system transmits a set of PIT data that corresponds to the timestamp and includes accurate data for K years prior to the timestamp.