Disclosed methods and systems include monitoring, by a computer system, online activity associated with a plurality of entities and a plurality of user devices that have respective pluralities of tokens provided by the token management system. The computer system may detect particular online activity related to a first token of a first of the pluralities of tokens, associated with a first user device. The computer system may determine that the particular online activity affects a status of the first token. In response to the determining, the computer system may modify data within the first token using information within the particular online activity. In response to identifying a second token of the first plurality of tokens, the computer system may determine that the particular online activity also affects a status of the second token, and modify, without receiving input from the first user device, the second token using the information.
Methods and systems are presented for providing a framework for facilitating storage and querying of vectors. Under the framework, different portions of a vector database are stored in different types of memories to improve storage and querying efficiency. One or more index portions of the vector database is stored in a volatile memory, and one or more vector portions of the vector database is stored in a non-volatile memory. Each index portion includes an index that represents multiple levels of vector partitions, including a first level of vector partitions and a second level of vector partitions. Each vector partition in the first level of vector partitions is linked to a different subset of vector partitions in the second level of vector partitions, and each vector partition in the second level of vector partitions corresponds to a group of vectors.
Computer security improvements relating to defenses using behavior pattern identification and extraction from unique traits of activities in time-series data are disclosed. A service provider may utilize a framework having computing operations for detecting and protecting from fraud and other behaviors indicative of risk, account takeovers, or other malicious activity. In this regard, the service provider may utilize a pattern analysis tool that may analyze computing log histories for account activities performed by devices using digital accounts. The activities may be correlated based on their traits having the same or similar data values, where sharing of these traits for activities at or over a threshold with a target account group in contrast to another account group may indicate a particular behavior. Behavior patterns may be extracted by comparing the activities by their traits in the target group, and the behavior patterns may be used for AI model training.
Computer security improvements relating to fraud detection and data correlations through large-scale graph clustering of graph transformations and embeddings are disclosed. A service provider may utilize a framework having computing operations for detecting fraud and other malicious or suspicious activities by groups of accounts and fraudsters. In this regard, the service provider may transform relationship graphs of account networks and relationships between accounts and account data captured in the nodes and edges of such graphs. The service provider may merge nodes that edges connecting to other nodes of a certain type of account data, while other types of account data and nodes may not be merged. Edges may also be merged and weighted, and the resulting transformed graph may undergo graph embedding to generate vectors that may be clustered using an AI clustering algorithm. The clusters may then be used for AI model training and inferencing.
G06F 21/50 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation
The disclosed computer-implemented method may include detecting a user authentication request from a user device for a session, determining a confidence score for identifying a device fingerprint of the user device, and authenticating the user device in response to the user authentication request. The authenticating may be based on the confidence score satisfying a confidence threshold. The method may also include identifying other active sessions for other devices associated with the user device, and providing session management for the other active sessions. Various other methods, systems, and computer-readable media are also disclosed.
Methods and systems are presented for signed document image analysis and fraud detection. An image of a document may be received from a user's device. A first layer of a machine learning engine is used to identify a signature and a name of the user within different areas of the received image. A second layer of the machine learning engine is used to extract a plurality of features from the different areas of the image. The plurality of features includes at least one visual feature representing the signature and at least one textual feature representing the name. A combined feature representation of the signature and the name is generated based on the plurality of features extracted from the image. A third layer of the machine learning engine is used to determine whether the signature of the user has been digitally altered, based on the combined feature representation.
G06V 40/30 - Reconnaissance d’auteurLecture et vérification des signatures
G06Q 50/26 - Services gouvernementaux ou services publics
G06V 10/70 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique
G06V 30/18 - Extraction d’éléments ou de caractéristiques de l’image
G06V 30/19 - Reconnaissance utilisant des moyens électroniques
G06V 30/416 - Extraction de la structure logique, p. ex. chapitres, sections ou numéros de pageIdentification des éléments de document, p. ex. des auteurs
Methods and systems are presented for providing a framework that configures a machine learning model to be insensitive to changes in input features. A computer modeling system determines data sources from which attribute values associated with transactions can be obtained. Instead of configuring the machine learning model to accept the attribute values as inputs, the computer modeling system may configure the machine learning model to accept a vector representation in a multi-dimensional space as input values. The computer modeling system then generates an encoder for each data source. Each encoder is configured to encode attribute values from a corresponding data source to a representation representing the attribute values. Further, each encoder is trained to minimize a variance between outputs of the different encoders. The computer modeling system determines a vector representation based on the representations generated by the encoders and provide the vector representation to the machine learning model.
System and methods for providing stand-in services at a domain can include obtaining a service request at a domain, determining one or more services at the domain to fulfill the service request, in response to determining a service of the one or more services is unavailable, providing a model as a stand-in service for the service, determining, by the one or more services and the model, a decision based on the service request, and sending, in response to the service request, the decision as output by the domain level. The model can provide the stand-in service by obtaining data for the service based on the service request context, identifying one or more keys based on the obtained context data, retrieving, based on the one or more keys, data from a cache, and applying the data to the model, the decision being based on the data applied to the model.
There are provided systems and methods for automated updating of computing code for software platform integrations with computing services. An online transaction processor or other service provider may provide computing services and platforms to entities including merchants for electronic transaction processing and other account services. To provide for code integrations of the computing services with software platforms, the service provider may provide a tool where merchants may update legacy code integrations of the computing services on their software platforms to new computing code for new code integrations, such as to facilitate the use of new APIs, endpoints, and the like. The tool may provide mappings for legacy code parameters to new code parameters, which may each be associated with code limitations in the legacy code and new code integrations. Further, the tool may provide an automatic converter of the legacy code to the new code using these mappings.
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
10.
FRAMEWORK FOR GENERATING RELEVANT QUERIES FOR ARTIFICIAL INTELLIGENCE MODEL
Methods and systems are presented for providing a framework that provides information associated with a particular domain to an artificial intelligence (AI) model. The framework includes a query condenser model that reformulates user-generated queries, such that the reformulated query can be used to retrieve a set of documents that can be used by the AI model to generate a response to the user-generated query. The query condenser model is trained using outputs generated by a teacher model. When the reformulated query generated by the query condenser model does not satisfy a set of criteria, the teacher model is configured to generate an improved version of the reformulated query for retraining the query condenser model.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for processing electronic payments and
for transferring funds to and from others; downloadable
software for facilitating money transfer services,
electronic funds transfer services, bill payment remittance
services, electronic processing and transmission of payments
and payment data; downloadable computer software and
downloadable mobile application software for facilitating
electronic commerce transactions; downloadable software for
use as a digital wallet; downloadable software for
connecting digital wallets; downloadable software for
connecting, integrating, and enabling transfer of funds
between digital wallets and financial accounts; downloadable
software for linking independent financial accounts and
digital wallets, enabling migration of data and transfers of
funds between independent third party financial accounts and
digital wallets, and establishing secure connections between
independent financial accounts and digital wallets;
downloadable computer software for use for financial account
management, namely, software for managing and facilitating
financial transactions and funds transfers for bank
accounts, credit card accounts, debit card accounts, and
digital wallets; downloadable authentication software for
controlling access to and communications with computers and
computer networks; downloadable software for currency
conversion. Providing business information regarding money transfer
services; business consulting services in the field of
online payments; business managing and tracking credit card,
debit card, ACH, prepaid cards, payment cards, and other
forms of payment transactions via electronic communications
networks for business purposes; business information
management, namely, electronic reporting of business
analytics relating to payment processing, authentication,
tracking, and invoicing. Electronic payment services involving electronic processing
and subsequent transmission of bill payment data; payment
transaction processing services; providing electronic
processing of electronic funds transfer, ACH, credit card,
debit card, electronic check and electronic payments;
financial information processing; money transfer services;
electronic funds transfer services; bill payment services;
providing payment services via a network for facilitating
transactions from digital wallets; providing financial
services, namely, bill payment services provided via a
digital wallet and providing secure commercial transactions;
transaction processing services for bank accounts, debit
cards, and credit cards on embedded digital wallets,
cross-border money transfers to banks and mobile wallets
with real time currency exchange rates; clearing financial
transactions via a global computer network and wireless
networks; credit card and debit card transaction processing
services; processing of electronic wallet payments; currency
exchange services; electronic commerce payment services,
namely, establishing funded accounts used to facilitate
transactions and purchases on the internet. Providing temporary use of online non-downloadable software
for processing electronic payments and for transferring
funds to and from others; application service provider (ASP)
featuring application programming interface (API) software
for facilitating payment transactions and financial
information processing; providing temporary use of online
non-downloadable software for facilitating money transfer
services, electronic funds transfer services, bill payment
remittance services, electronic processing and transmission
of payments and payment data; providing temporary use of
online non-downloadable software for facilitating electronic
commerce transactions; providing temporary use of online
non-downloadable software for use as a digital wallet;
providing temporary use of online non-downloadable software
for connecting digital wallets; providing temporary use of
online non-downloadable software for connecting,
integrating, and enabling transfer of funds between digital
wallets and financial accounts; providing temporary use of
online non-downloadable software for linking independent
financial accounts and digital wallets, enabling migration
of data and transfers of funds between independent third
party financial accounts and digital wallets, and
establishing secure connections between independent
financial accounts and digital wallets; providing temporary
use of online non-downloadable software for use for
financial account management, namely, software for managing
and facilitating financial transactions and funds transfers
for bank accounts, credit card accounts, debit card
accounts, and digital wallets; providing temporary use of
online non-downloadable authentication software for
controlling access to and communications with computers and
computer networks; providing temporary use of online
non-downloadable software for currency conversion.
12.
DYNAMICALLY CUSTOMIZING A USER INTERFACE OF AN ELECTRONIC PLATFORM VIA MACHINE LEARNING
Via one or more electronic communication channels of an electronic platform, a request is detected from a user to interact with the electronic platform. Via a Natural Language Processing (NLP) model, an intent of the user behind the request to interact with the electronic platform is predicted. Via an Explainable Artificial Intelligence (XAI) model, one or more features associated with the user that contributed to the predicted intent are determined. Via a Large Language Model (LLM), a personalized message is generated for the user. The personalize message refers to the intent predicted by the NLP model or the one or more features associated with the user determined by the XAI model that contributed to the predicted intent. The personalized message is provided to the user via the one or more electronic communication channels.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
13.
SEARCH AND ANSWER GENERATION ENGINE FOR DATA SUMMARIZATION FROM MULTIPLE DATA SOURCES
There are provided systems and methods for a search and answer generation engine for data summarization from multiple data sources. An online transaction processor or other service provider may provide computing services and platforms to entities, which may include live agent and self-service assistance features for answering users'questions. To provide more comprehensive searching and automated answer generation, the service provider may utilize an answer engine that may search multiple data sources in different data formats. Keywords may be extracted from a natural language question using an embedding LLM, and API calls to search features of each data source may be executed to retrieve relevant content. A summarization LLM may then concisely summarize the different content in different formats so that an answer may be provided. The user may then refine their question with further questions or requests, which may adjust the keywords and/or summarization.
A computer system performs a processing operation in real time on an aggregated value stored in a counter of a set of counters corresponding to time periods associated with events. The computer system maintains the set of counters usable to store aggregated values of an event metric. In response to detection of the events, the computer system stores, in a database, event details for the received events and updates those counters of the set of counters that correspond to time periods associated with the received events. In response to receipt, in a current time period, of an update to a particular event of the received events associated with a previous time period, the computer system, in real time, retrieves, from the set of counters, a particular aggregated value of the event metric for the previous time period and performs a processing operation based on the particular aggregated value.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
Methods and systems are presented for identifying different users who share a user account with an online service provider and dynamically processing transactions for the user account differently based on which user initiates the transaction request. In some embodiments, an account decomposition system may decompose the user account into distinct users who share the user account. The account decomposition system may identify different users who are sharing a user account by analyzing past transactions associated with the user account and different user devices that were used to conduct the past transactions. The account decomposition system may determine different user profiles for the different users, and may use the different user profiles to process incoming transaction requests initiated by different users of the user account.
G06F 18/23213 - Techniques non hiérarchiques en utilisant les statistiques ou l'optimisation des fonctions, p. ex. modélisation des fonctions de densité de probabilité avec un nombre fixe de partitions, p. ex. K-moyennes
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
Techniques are disclosed for automatically generating and updating a control group. In disclosed techniques, a server computer system trains, using a plurality of transactions, a machine learning model. During training the machine learning model learns a feature distribution of both a current set of control group (CG) transactions and a current set of non-control group (non-CG) transactions included in the plurality of transactions. The system inputs the current set of CG transactions into the trained machine learning model. Based on the output of the trained machine learning model for the current set of CG transactions, the system modifies the current set of CG transactions to generate an updated set of CG transactions. Based on the updated set of CG transactions, the server performs one or more preventative measures for a transaction processing system. The disclosed techniques may advantageously improve the accuracy e.g., of a transaction processing system.
G05B 13/02 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
G06N 3/088 - Apprentissage non supervisé, p. ex. apprentissage compétitif
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
17.
AUTOMATED UPDATING OF COMPUTING CODE FOR SOFTWARE PLATFORM INTEGRATIONS WITH COMPUTING SERVICES
There are provided systems and methods for automated updating of computing code for software platform integrations with computing services. An online transaction processor or other service provider may provide computing services and platforms to entities including merchants for electronic transaction processing and other account services. To provide for code integrations of the computing services with software platforms, the service provider may provide a tool where merchants may update legacy code integrations of the computing services on their software platforms to new computing code for new code integrations, such as to facilitate the use of new APIs, endpoints, and the like. The tool may provide mappings for legacy code parameters to new code parameters, which may each be associated with code limitations in the legacy code and new code integrations. Further, the tool may provide an automatic converter of the legacy code to the new code using these mappings.
A computer system performs a processing operation in real time on an aggregated value stored in a counter of a set of counters corresponding to time periods associated with events. The computer system maintains the set of counters usable to store aggregated values of an event metric. In response to detection of the events, the computer system stores, in a database, event details for the received events and updates those counters of the set of counters that correspond to time periods associated with the received events. In response to receipt, in a current time period, of an update to a particular event of the received events associated with a previous time period, the computer system, in real time, retrieves, from the set of counters, a particular aggregated value of the event metric for the previous time period and performs a processing operation based on the particular aggregated value.
Various techniques are disclosed for providing gateway services between a client system and downstream service systems for a service system. The disclosed gateway service system is capable of providing a final decision response to a service request from the client system based on responses received from the downstream service systems. The gateway service system internally determines the final decision response through implementation of a decision determination processor in combination with a configuration file and a response mapping table. The configuration file provides information that allows the decision determination processor to determine the final decision response based on decision mapping in the response mapping table. In some instances, the decision determination processor may access a dynamic decision mapping model when the response mapping table does not provide a final decision response determination.
G06Q 30/015 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
H04L 67/566 - Regroupement ou agrégation de demandes de service, p. ex. pour un traitement unifié
20.
SECURE ELEMENTS BROKER (SEB) FOR APPLICATION COMMUNICATION CHANNEL SELECTOR OPTIMIZATION
Systems and methods for managing concurrent secure elements on a mobile device to coordinate with an application or “app” running on the mobile device and an appropriate communications protocol for conducting transactions using the mobile device include: informing, by the processor, the reader device of a preferred app and a communication protocol usable by the preferred app; receiving, by the processor, information about which apps and communication protocols are supported by a reader for processing a transaction; locating, by the processor, a secure element supporting an app and a communication protocol supported by the reader; channeling the communication protocol for the specific configuration of the app and the supporting secure element; activating the secure element that supports the app; and processing, with the activated secure element, using the supported app and communication channel, the transaction with the reader.
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
H04L 67/1095 - Réplication ou mise en miroir des données, p. ex. l’ordonnancement ou le transport pour la synchronisation des données entre les nœuds du réseau
H04W 4/60 - Services basés sur un abonnement qui utilisent des serveurs d’applications ou de supports d’enregistrement, p. ex. boîtes à outils d’application SIM
H04W 4/80 - Services utilisant la communication de courte portée, p. ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie
The disclosed computer-implemented method may include receiving, by a merchant server, user information of a user visiting a merchant website, and sending, from the merchant server to a bidding exchange, a bid request for displaying a payment interface on the merchant website. The bidding exchange may be connected to multiple payment processor servers that may provide payment interface code to the merchant server. The method may also include receiving, by the merchant server from the bidding exchange, the payment interface code in response to the bid request, and presenting, on the merchant website using the payment interface code, a customized payment interface. Various other methods, systems, and computer-readable media are also disclosed.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
22.
Dynamically Adjustable eXplainable Artificial Intelligence (XAI) Model
Techniques are disclosed for enhancing the transparency and interpretability of machine learning (ML) models using explainable artificial intelligence (XAI). In some embodiments, a computing system generates an XAI model that provides reasons for the outputs of a first ML model by selecting from a set of predefined reasons based on an aggregation function. This aggregation function combines importance scores for various features associated with the ML model's output, where each feature is mapped to a corresponding reason. The computing system may determine one or more parameters for the aggregation function to improve the accuracy of the selected reason, allowing for adjustments in how the aggregation function processes the importance scores. In certain cases, the system may involve an imitation model that is trained to replicate the first ML model's outputs.
Methods and systems are presented for providing a framework that improves the logic induction capabilities of an artificial intelligence (AI) model. Under the framework, different logics are encapsulated in a logic knowledge graph. Embeddings are extracted from different portion of the logic knowledge graph, and guiding questions are generated for each logic that is encapsulated within the graph based on the embeddings. A logic database is constructed using the embeddings and the guiding questions. In order for the AI model to perform a task, the logic database is queried to obtain a set of guiding questions corresponding to the task. The guiding questions, along with other information associated with the task, are incorporated into a prompt, which is then provided to the AI model. Based on the guiding questions included in the prompt, the AI model can generate content that follows a particular logic.
Techniques are disclosed for enhancing the transparency and interpretability of machine learning (ML) models using explainable artificial intelligence (XAI). In some embodiments, a computing system generates an XAI model that provides reasons for the outputs of a first ML model by selecting from a set of predefined reasons based on an aggregation function. This aggregation function combines importance scores for various features associated with the ML model's output, where each feature is mapped to a corresponding reason. The computing system may determine one or more parameters for the aggregation function to improve the accuracy of the selected reason, allowing for adjustments in how the aggregation function processes the importance scores. In certain cases, the system may involve an imitation model that is trained to replicate the first ML model's outputs.
Techniques are disclosed for detecting whether an entity associated with a node of a summary graph is suspicious by retrieving, from a graph database storing a network graph representing a plurality of electronic communications, a portion of the network graph that includes a set of target nodes. Based on the target nodes included in the portion of the network graph, the server system generates community graphs that includes at least a target node and nodes connected to the target node. The server system assigns, based on similarities between the community graphs, the community graphs to clusters and generates a closure graph for clusters, including combining two or more community graphs within respective clusters. Based on respective closure graphs, the server system performs preventative actions relative to entities represented by nodes included in respective closure graphs and connected to the target nodes.
Techniques are disclosed relating to methods that include receiving an indication of an access by a user to a web page that includes a beacon, and calculating a readiness score for triggering the beacon. The methods may also include determining, based on the readiness score, whether to perform a client-side or server-side triggering of the beacon. The triggering causes data associated with the access to be transmitted to a third-party computer system.
Methods and systems are presented for tagging an account associated with a user based on a predicted likelihood of an event associated with the user. A set of features is determined for data associated with the user. Values from the data are aggregated over time intervals for each feature to create time series data. The time series data is used as input to a neural network configured to accept input with the determined features. A predictive value indicating the likelihood of an event associated with the user is received from the neural network and used to determine whether to tag a user account. Determinations regarding the user are made based on the existence of absence of a tag on the user's account.
A method for verifying transactions is discussed. The method includes receiving a transaction request for performing a transaction between a user account and a merchant account. The method includes determining, based on authentication of the user account, a common identifier associated with the user account, the common identifier indicating the user account being authorized for use at a plurality of merchant accounts including the merchant account. The method includes determining a payment token for performing the transaction, the determining the payment token based on the common identifier and a user associated with the user account. The method also includes providing the payment token for completing the transaction.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
There are provided systems and methods for automated code generation using large language models (LLMs) for software platform integrations with computing services. An online transaction processor or other service provider may provide computing services and platforms to entities including merchants for electronic transaction processing and other account services. To provide for conde integrations of the computing services with software platforms of merchants, such as software systems for merchant websites and applications, the service provider may provide for an automated code generation tool that processes data for the software platform and the service to be integrated and provides recommendations and source code. An LLM may be prompted in parts to generate the code after analyzing legacy code from previous integrations and information for the merchant's software platform, and the merchant may be provided new code for testing and implementation.
There are provided systems and methods for an application and website development platform for automated recommendations of code integration options. An online transaction processor or other service provider may provide computing services and platforms to entities including merchants for electronic transaction processing and other account services. To provide for code integrations of the computing services with software platforms of merchants, such as software systems for merchant websites and applications, the service provider may provide a merchant development platform where merchants may provide information to an AI assistance and engine that may assist the merchant with identifying computing services of interest and use by the merchant for their software platform. The computing services may require integration with the software platform, such as through implementation of computing code to call APIs of the computing service, which may be intelligently generated and provided via the development platform.
Methods and systems are presented for providing a framework for facilitating storage and querying of vectors. Under the framework, different portions of a vector database are stored in different types of memories to improve storage and querying efficiency. One or more index portions of the vector database is stored in a volatile memory, and one or more vector portions of the vector database is stored in a non-volatile memory. Each index portion includes an index that represents multiple levels of vector partitions, including a first level of vector partitions and a second level of vector partitions. Each vector partition in the first level of vector partitions is linked to a different subset of vector partitions in the second level of vector partitions, and each vector partition in the second level of vector partitions corresponds to a group of vectors.
As disclosed herein, a token and/or a public/private key can be stored in a secure enclave that can be later used when a user logs into the payment provider's website. At that time, the user can simply swipe a fingerprint to complete a transaction. Thus, biometric authentication may be applied to complete the transaction. Moreover, the transaction can be completed across different browsers. In an implementation, a long-term token is not utilized. Instead, when a user opts into the disclosed implementation, a private and public key pair is generated on the client side device. The private key may be stored in the secure enclave and the public key may be sent to the payment provider. Thus, there may be no token involved to complete the transaction.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
H04L 9/14 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité utilisant plusieurs clés ou algorithmes
H04L 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
33.
AUTOMATED CODE GENERATION USING LARGE LANGUAGE MODELS FOR SOFTWARE PLATFORM INTEGRATIONS WITH COMPUTING SERVICES
There are provided systems and methods for automated code generation using large language models (LLMs) for software platform integrations with computing services. An online transaction processor or other service provider may provide computing services and platforms to entities including merchants for electronic transaction processing and other account services. To provide for conde integrations of the computing services with software platforms of merchants, such as software systems for merchant websites and applications, the service provider may provide for an automated code generation tool that processes data for the software platform and the service to be integrated and provides recommendations and source code. An LLM may be prompted in parts to generate the code after analyzing legacy code from previous integrations and information for the merchant's software platform, and the merchant may be provided new code for testing and implementation.
Methods and systems are presented for classifying a particular user account as a fraudulent user account by analyzing links between the user account and two or more known fraudulent user accounts collectively. Attributes of the particular user account are compared against attributes of a plurality of known fraudulent accounts to determine that the particular user account has shared attributes with a first known fraudulent account and a second known fraudulent account. The shared attributes with the first known fraudulent account and the second known fraudulent account are analyzed collectively to determine a risk level for the particular user account. The risk level may indicate a likelihood that the particular user account corresponds to a fraudulent account.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
There are provided systems and methods for data privacy protection and removal for artificial intelligence model training and deployment. An online transaction processor or other service provider may provide computing services and platforms to entities, which may include use of machine learning (ML) models including large language models (LLMs). To comply with data privacy protections and copyright enforcement, a system may provide unlearning of content from ML models. The system may receive a request to unlearn a content and, after verifying the request is valid, identify the content used for during training of or inferencing by an ML model. The system may then map the content to concepts and correlate those concepts with ML model outputs using projections in a vector space. Based on the mapped concepts and outputs, neuron activation of the ML model may be analyzed to identify a negation vector and perform selective parameter dampening.
Methods and systems are presented for providing a retrieval-augmented generation (RAG) framework that provides information associated with a particular domain to an artificial intelligence (AI). The RAG framework includes a query generation module that generates additional queries based on an original user query. A set of documents is retrieved from a corpus based on the user query and the additional queries. The RAG framework further includes an evaluation module for evaluating a relevancy of each retrieved document with respect to the original user query. Any documents determined to be irrelevant to the original user query may be eliminated, and the remaining documents along with the original user query are used to generate a prompt for the AI model, which in turn, generates a response to the user query.
Techniques are disclosed relating to implementing a unified application programming interface (API) to facilitate operations across multiple service provider systems. A computer system implements a portion of the unified API that enables it to issue requests in a common format to a variety of service provider systems capable of performing operations of a particular type. The computer system receives a request to facilitate an operation of the particular type through a target service provider system and identifies an appropriate connector associated with the target service provider system based on the request. The computer system then sends a request conforming to the unified API to the identified connector to facilitate the operation at the target service provider system. The identified connector conforms content of the request into a format ingestible by the target service provider system and then forwards that request to the target service provider system for processing.
Techniques are disclosed relating to facilitating secure communication of private user data between different entities for a verification process conducted during an electronic interaction between the user and a verifier entity. In disclosed embodiments, a verification service executing on a server computer system for a verification session for verifying a holder entity on behalf of a verifier entity receives a verification request from a remote computer system. The verification request includes an attestation proof generated from one or more credentials and the verification service communicates with a holder service that manages an identity storage storing credentials for the holder entity. The verification service transmits, to the verifier service, the attestation proof and then receives, from the verifier service based on the proof, verification results that are usable by the verifier to determine whether to process an action requested by the holder prior to requesting verification.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Techniques are disclosed relating to implementing a unified application programming interface (API) to facilitate operations across multiple service provider systems. A computer system implements a portion of the unified API that enables it to issue requests in a common format to a variety of service provider systems capable of performing operations of a particular type. The computer system receives a request to facilitate an operation of the particular type through a target service provider system and identifies an appropriate connector associated with the target service provider system based on the request. The computer system then sends a request conforming to the unified API to the identified connector to facilitate the operation at the target service provider system. The identified connector conforms content of the request into a format ingestible by the target service provider system and then forwards that request to the target service provider system for processing.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for implementing algorithms and programs in the field of artificial intelligence, machine learning, deep learning, high performance computing, distributed computing, virtualization, natural language generation, statistical learning, supervised learning, un-supervised learning, predictive analytics and business intelligence; downloadable software for developing, training, and scaling AI agents; downloadable software for agentic online shopping, namely, online shopping featuring digital agents powered by artificial intelligence; downloadable data analytics software in the field of online shopping; downloadable software using artificial intelligence to recommend, promote, upsell, and cross-sell the goods and services of others; downloadable application programming interface (API) software; downloadable intelligent personal assistant software for online shopping; downloadable software featuring artificial intelligence and AI agents for electronic payment and financial transfer processing and management; downloadable software for implementing algorithms and programs in the field of artificial intelligence and the agentic processing of electronic payments and financial transfers; downloadable intelligent personal assistant software for making and processing electronic payments and financial transfers Banking services Providing temporary use of online non-downloadable software for implementing algorithms and programs in the field of artificial intelligence, machine learning, deep learning, high performance computing, distributed computing, virtualization, natural language generation, statistical learning, supervised learning, un-supervised learning, predictive analytics and business intelligence; providing temporary use of online non-downloadable software for developing, training, and scaling AI agents; providing temporary use of online non-downloadable software for agentic online shopping, namely, online shopping featuring digital agents powered by artificial intelligence; providing temporary use of online non-downloadable data analytics software in the field of online shopping; providing temporary use of online non-downloadable software using artificial intelligence to recommend, promote, upsell, and cross-sell the goods and services of others; providing temporary use of online non-downloadable application programming interface (API) software; providing temporary use of online non-downloadable intelligent personal assistant software for online shopping; providing temporary use of online non-downloadable software featuring artificial intelligence and AI agents for electronic payment and financial transfer processing and management; providing temporary use of online non- downloadable software for implementing algorithms and programs in the field of artificial intelligence and the agentic processing of electronic payments and financial transfers; providing temporary use of online non- downloadable intelligent personal assistant software for making and processing electronic payments and financial transfers
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for implementing algorithms and programs in the field of artificial intelligence, machine learning, deep learning, high performance computing, distributed computing, virtualization, natural language generation, statistical learning, supervised learning, un-supervised learning, predictive analytics and business intelligence; downloadable software for developing, training, and scaling AI agents; downloadable software for agentic online shopping, namely, online shopping featuring digital agents powered by artificial intelligence; downloadable data analytics software in the field of online shopping; downloadable software using artificial intelligence to recommend, promote, upsell, and cross-sell the goods and services of others; downloadable application programming interface (API) software; downloadable intelligent personal assistant software for online shopping; downloadable software featuring artificial intelligence and AI agents for electronic payment and financial transfer processing and management; downloadable software for implementing algorithms and programs in the field of artificial intelligence and the agentic processing of electronic payments and financial transfers; downloadable intelligent personal assistant software for making and processing electronic payments and financial transfers Banking services Providing temporary use of online non-downloadable software for implementing algorithms and programs in the field of artificial intelligence, machine learning, deep learning, high performance computing, distributed computing, virtualization, natural language generation, statistical learning, supervised learning, un-supervised learning, predictive analytics and business intelligence; providing temporary use of online non-downloadable software for developing, training, and scaling AI agents; providing temporary use of online non-downloadable software for agentic online shopping, namely, online shopping featuring digital agents powered by artificial intelligence; providing temporary use of online non-downloadable data analytics software in the field of online shopping; providing temporary use of online non-downloadable software using artificial intelligence to recommend, promote, upsell, and cross-sell the goods and services of others; providing temporary use of online non-downloadable application programming interface (API) software; providing temporary use of online non-downloadable intelligent personal assistant software for online shopping; providing temporary use of online non-downloadable software featuring artificial intelligence and AI agents for electronic payment and financial transfer processing and management; providing temporary use of online non- downloadable software for implementing algorithms and programs in the field of artificial intelligence and the agentic processing of electronic payments and financial transfers; providing temporary use of online non- downloadable intelligent personal assistant software for making and processing electronic payments and financial transfers
Techniques are disclosed relating to determining whether input data is authentic. A system detects input data, that includes text data and typing data, at a computing device. The system may generate, using a string model, a string-level prediction for the input data, where the string model is trained to increase a similarity between embeddings of authentic text data and corresponding sequences of typing data. Using a character model, the system may generate a character-level prediction for the set of input data, where the character-level model predicts an intended sequence of characters based on the text data and a sequence of typing actions included in the input data. Using machine learning, the system determines, based on the string-level prediction and the character-level prediction, whether the input data is authentic input. The system transmits, to the device, a decision that is generated based on determining whether the input data is authentic.
A payment device comprising of a housing, a slot for insertion of a user instrument located on a front surface of the housing, and wherein the housing includes a smart card interface integrated circuit that is configured to read an EMV chip located on the user instrument, and a universal serial bus (USB) type C male connector configured to be inserted into a female connector on a computing device, wherein the USB type C male connector is located on a back surface of the housing, and wherein a size of the USB type C male connector is configured so that when the USB type C male connector is inserted into the female connector on the computing device, the back surface of the housing is within a distance of three centimeters of a surface of the computing device.
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G07F 7/08 - Mécanismes actionnés par des objets autres que des pièces de monnaie pour déclencher ou actionner des appareils de vente, de location, de distribution de pièces de monnaie ou de papier-monnaie, ou de remboursement par carte d'identité codée ou carte de crédit codée
44.
DATA PRIVACY PROTECTION AND REMOVAL FOR ARTIFICIAL INTELLIGENCE MODEL TRAINING AND DEPLOYMENT
There are provided systems and methods for data privacy protection and removal for artificial intelligence model training and deployment. An online transaction processor or other service provider may provide computing services and platforms to entities, which may include use of machine learning (ML) models including large language models (LLMs). To comply with data privacy protections and copyright enforcement, a system may provide unlearning of content from ML models. The system may receive a request to unlearn a content and, after verifying the request is valid, identify the content used for during training of or inferencing by an ML model. The system may then map the content to concepts and correlate those concepts with ML model outputs using projections in a vector space. Based on the mapped concepts and outputs, neuron activation of the ML model may be analyzed to identify a negation vector and perform selective parameter dampening.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software and mobile application
software for processing electronic payments, transferring
funds to and from others, and issuing receipts regarding
electronic payment transactions; downloadable software for
use in issuing digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; downloadable software for accepting, buying,
selling, transmitting, and exchanging digital currency,
virtual currency, cryptocurrency, stablecoins, digital and
blockchain assets, digitized assets, digital tokens, crypto
tokens and utility tokens; downloadable software for
electronically trading, storing, sending, receiving,
validating, verifying, accepting, tracking, and transferring
digital currency, cryptocurrency, virtual currency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
downloadable software for managing, implementing, and
validating digital currency, virtual currency,
cryptocurrency, stablecoin, digital asset, blockchain asset,
digitized asset, digital token, crypto token and utility
token payment and exchange transactions; downloadable
software for use in payments, purchases, and investments
using digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
downloadable software for use as a digital currency, virtual
currency, cryptocurrency, stablecoin, digital asset, digital
token, crypto token, and utility token wallet; downloadable
software for currency conversion; downloadable software for
creating tokens that may be used to pay for products and
services, and traded or exchanged for cash value;
downloadable software for managing and facilitating money
transfers, electronic funds transfers, commodity transfers,
bill payment remittance, and secure transactions. Electronic transfer of funds; clearing financial
transactions via a global computer network and wireless
networks; providing electronic mobile payment services for
others in the nature of providing secure commercial
transactions and payment options using a mobile device at a
point of sale; electronic foreign exchange payment
processing services; issuance of stablecoins and tokens of
value; stablecoin payment processing; stablecoin trading
services; stablecoin exchange services; financial services,
namely, providing digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens for use by others; financial services, namely,
digital currency, virtual currency, cryptocurrency,
stablecoin, digital and blockchain asset, digitized asset,
digital token, crypto token and utility token transfer,
exchange, and payment processing services; financial
exchange services; providing a financial exchange for
trading digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
currency exchange services, currency trading services,
foreign currency dealing, and broker-dealer financial
services in the field of cryptocurrency, digital currency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
currency transfer services; electronic transfer of
cryptocurrency, digital currency, stablecoins, digital and
blockchain assets, digitized assets, digital tokens, crypto
tokens and utility tokens; electronic wallet payment
services; electronic wallet services for trading, storing,
sending, receiving, validating, verifying, accepting,
tracking, transferring, and transmitting digital currency,
virtual currency, cryptocurrency, stablecoins, digital and
blockchain assets, digitized assets, digital tokens, crypto
tokens, and utility tokens, and for managing digital
currency, virtual currency, cryptocurrency, stablecoin,
digital and blockchain asset, digitized asset, digital
token, crypto token, and utility token payment and exchange
transactions; electronic payment processing of payments made
via digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens, and utility tokens;
digital currency, virtual currency, cryptocurrency,
stablecoin, digital and blockchain asset, digitized asset,
digital token, crypto token and utility token transaction
processing services for others; financial management of
digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens, and utility tokens. Providing temporary use of online non-downloadable software
for electronic payment processing, transferring funds to and
from others, and issuing receipts regarding electronic
payment transactions; application service provider (ASP)
services featuring software for use in digital currency,
virtual currency, cryptocurrency, stablecoin, digital and
blockchain asset, digitized asset, digital token, crypto
token and utility token exchanges and transactions;
providing temporary use of online non-downloadable software
for use in issuing digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for accepting, buying, selling, transmitting, and
exchanging digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for electronically trading, storing, sending,
receiving, validating, verifying, accepting, tracking, and
transferring digital currency, cryptocurrency, virtual
currency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for managing, implementing, and validating digital
currency, virtual currency, cryptocurrency, stablecoin,
digital asset, blockchain asset, digitized asset, digital
token, crypto token and utility token payment and exchange
transactions; providing temporary use of online
non-downloadable software for use in payments, purchases,
and investments using digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for users to buy and sell products using digital
currency, virtual currency, cryptocurrency, stablecoins,
digital and blockchain assets, digitized assets, digital
tokens, crypto tokens and utility tokens; providing
temporary use of online non-downloadable software for
currency conversion; providing temporary use of online
non-downloadable software for use as a digital currency,
virtual currency, cryptocurrency, stablecoin, digital asset,
digital token, crypto token, and utility token wallet;
providing temporary use of online non-downloadable software
for encryption; providing temporary use of online
non-downloadable software for verifying, evaluating, and
securing transactions with blockchain technology; providing
temporary use of online non-downloadable software for
managing and facilitating money transfers, electronic funds
transfers, commodity transfers, bill payment remittance, and
secure transactions.
46.
FAILURE TRACKING WITH REAL-TIME DATA EVENT STREAMING FOR DATA QUALITY CHECKS
Accuracy and speed improvements for data computing results are provided herein, particularly in the context of data event streaming services and downstream data computing processes. There are provided systems and methods for failure tracking with real-time data event streaming for data quality checks. A service provider may utilize different computing services for event processing and storing for downstream applications and services in a production computing environment. Due to issues in data loading and/or processing, certain events when streamed may fail to be processed and/or stored for availability to further system components. A failed event tracker may be implemented where, when events fail to process in an original processing queue, the tracker may detect the failure and write an identifier for the event to a table in an accessible database. The tracker may the republish the event via a retry processing queue using the identifier and may track for completion.
There are provided systems and methods for pairwise graph querying, merging, and computing for account linking. A service provider may provide an account graph system to identify pairwise similarities between different accounts based on shared data that may be identified through one or more linking characteristics. When providing pairwise graph similarities, a service provider may receive a query identifying two or more accounts and/or an account with a parameter for graph exploration and querying.
There are provided systems and methods for pairwise graph querying, merging, and computing for account linking. A service provider may provide an account graph system to identify pairwise similarities between different accounts based on shared data that may be identified through one or more linking characteristics. When providing pairwise graph similarities, a service provider may receive a query identifying two or more accounts and/or an account with a parameter for graph exploration and querying.
The service provider may utilize connection, link, or relationship graphs, queried and generated using a graph database, to determine pairwise similarities between the designated seed account and one or more selected accounts. The graph may include vertices for different queried data points and edges connecting such queries, where directionality of the edges or other vectors may be used to identify links or hops between accounts for data querying and exploration.
Systems and methods for providing merchant/customer interaction include determining that a tablet computer is in a merchant orientation, retrieving merchant product information according to a received instruction and merchant orientation information, and displaying a merchant screen on the tablet computer that includes the merchant product information according to the merchant orientation information. A change in the orientation of the tablet computer enclosure/stand is then detected from the merchant orientation to a customer orientation. In response, the merchant screen is transitioned on the tablet computer display to a customer screen as the tablet computer enclosure/stand changes orientations by moving the merchant screen and the customer screen linearly while in a stacked orientation. The customer screen includes the merchant product information displayed according to customer orientation information such that the merchant product information is displayed differently on the customer screen relative to the merchant screen.
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
G06F 3/03 - Dispositions pour convertir sous forme codée la position ou le déplacement d'un élément
G06F 3/0346 - Dispositifs de pointage déplacés ou positionnés par l'utilisateurLeurs accessoires avec détection de l’orientation ou du mouvement libre du dispositif dans un espace en trois dimensions [3D], p. ex. souris 3D, dispositifs de pointage à six degrés de liberté [6-DOF] utilisant des capteurs gyroscopiques, accéléromètres ou d’inclinaison
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/0487 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
Historical performance information of a plurality of autonomous agents configured to handle a plurality of tasks is accessed. The historical performance information indicates, for each autonomous agent, a successful outcome or a failed outcome for each of the tasks handled by the autonomous agent. A Markov chain comprising a plurality of states is constructed based on the autonomous agents. Each autonomous agent corresponds to a different state of the states. For each autonomous agent, a first score and a second score are calculated based on the Markov chain. The first score corresponds to an expected number of transitions from the autonomous agent to other autonomous agents until the successful outcome or the failed outcome is reached, The second score corresponds to a probability of the autonomous agent ultimately achieving the successful outcome. The autonomous agents are evaluated based on the first score and the second score.
A source database and a target database are accessed. The source database contains data to be migrated over to the target database. The read operations from the target database and the write operations to the target database are ceased, while the read operations from the source database and the write operations to the source database are maintained. The data from the source database is replicated to the target database. During the replication, the read operations from the source database are maintained but the write operations to the source database are ceased, while the read operations from the target database and the write operations to the target database are also ceased. After the replication has been completed, the read operations from the source database and the write operations to the source database are ceased. The read operations from the target database and the write operations to the target database are resumed.
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
Embodiments of the present invention relate to systems, methods, processes, computer program code, and means for creating digital wallets for users. In some embodiments, digital wallets are created, at least in part, on information obtained from payment transactions conducted by users.
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 30/0207 - Remises ou incitations, p. ex. coupons ou rabais
G06Q 30/0226 - Systèmes d’incitation à un usage fréquent, p. ex. programmes de miles pour voyageurs fréquents ou systèmes de points
There are provided systems and methods for a low latency gateway service for asynchronous handling of data processing requests with downstream computing services. A service provider, such as an electronic transaction processor for digital transactions, may utilize different computing services that implement rules and artificial intelligence models for decision-making of data including data in production computing environment. In this regard, the service provider may utilize an API gateway at gateway decision services to assist with execution of workflows to schedule and process tasks with downstream computing services. The API gateway may asynchronously call the downstream services based on the workflow so that responses can be obtained quickly and without introducing latency based on different response times. The API gateway may utilize the workflows that are highly configurable so that new decision services and changes to decision services may be introduced with minimal service disruptions.
Techniques are disclosed relating to training a prediction model using a pipeline of machine learning models. A system embeds values of records of at least two different data sources within a multi-dimensional embedding space. The system may calculate similarity scores for respective pairs of clusters within the multi-dimensional embedding space. Based on the similarity scores, the system identifies correlations between values of records from the two different data sources. Based on the identified correlations, the system generates matching features and inputs the matching features into a matching model. Based on output of the matching model for the matching features, the system combines similar records from the at least two different data sources, where the combining produces an enhanced data source. The system may then input the enhanced data source into the prediction model. The disclosed record matching techniques may advantageously provide customized matching for prediction models.
A system or method may be provided to facilitate automatic user authentication for electronic transactions. In particular, the system or method may automatically authenticate a customer such that the customer may make complete hands free payments without the intervention of the customer or the merchant. The automatic authentication may include a check-in process and a payment authentication process. When a customer enters a designated area of a merchant, a BLE beacon device of the merchant may automatically check in the customer at the designated area of the merchant. After the customer is checked in at the merchant's designated area, the merchant may identify the customer who is about to make a payment from a plurality of other customers who also are checked in at the merchant via Bluetooth proximity and facial recognition in parallel. Thus, the customer may automatically be authenticated to make payments by facial recognition or Bluetooth proximity.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
A method for processing computer code in order to identify an attribute of the code may comprise receiving a block of code; processing the block of code to identify at least one relevant chunk, generating a set of prompts, each of the set of prompts comprising a respective relevant chunk, and an instruction for a machine learning model configured to cause the machine learning model to generate an output based on the respective relevant chunk. From there, the method may include transmitting the set of prompts to the machine learning model, and generating a conclusion regarding the received block of code based on a set of outputs received from the machine learning model in response to the set of prompts.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software and mobile application
software for processing electronic payments, transferring
funds to and from others, and issuing receipts regarding
electronic payment transactions; downloadable software for
use in issuing digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; downloadable software for accepting, buying,
selling, transmitting, and exchanging digital currency,
virtual currency, cryptocurrency, stablecoins, digital and
blockchain assets, digitized assets, digital tokens, crypto
tokens and utility tokens; downloadable software for
electronically trading, storing, sending, receiving,
validating, verifying, accepting, tracking, and transferring
digital currency, cryptocurrency, virtual currency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
downloadable software for managing, implementing, and
validating digital currency, virtual currency,
cryptocurrency, stablecoin, digital asset, blockchain asset,
digitized asset, digital token, crypto token and utility
token payment and exchange transactions; downloadable
software for use in payments, purchases, and investments
using digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
downloadable software for use as a digital currency, virtual
currency, cryptocurrency, stablecoin, digital asset, digital
token, crypto token, and utility token wallet; downloadable
software for currency conversion; downloadable software for
creating tokens that may be used to pay for products and
services, and traded or exchanged for cash value;
downloadable software for managing and facilitating money
transfers, electronic funds transfers, commodity transfers,
bill payment remittance, and secure transactions. Electronic transfer of funds; clearing financial
transactions via a global computer network and wireless
networks; providing electronic mobile payment services for
others in the nature of providing secure commercial
transactions and payment options using a mobile device at a
point of sale; electronic foreign exchange payment
processing services; issuance of stablecoins and tokens of
value; stablecoin payment processing; stablecoin trading
services; stablecoin exchange services; financial services,
namely, providing digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens for use by others; financial services, namely,
digital currency, virtual currency, cryptocurrency,
stablecoin, digital and blockchain asset, digitized asset,
digital token, crypto token and utility token transfer,
exchange, and payment processing services; financial
exchange services; providing a financial exchange for
trading digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
currency exchange services, currency trading services,
foreign currency dealing, and broker-dealer financial
services in the field of cryptocurrency, digital currency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
currency transfer services; electronic transfer of
cryptocurrency, digital currency, stablecoins, digital and
blockchain assets, digitized assets, digital tokens, crypto
tokens and utility tokens; electronic wallet payment
services; electronic wallet services for trading, storing,
sending, receiving, validating, verifying, accepting,
tracking, transferring, and transmitting digital currency,
virtual currency, cryptocurrency, stablecoins, digital and
blockchain assets, digitized assets, digital tokens, crypto
tokens, and utility tokens, and for managing digital
currency, virtual currency, cryptocurrency, stablecoin,
digital and blockchain asset, digitized asset, digital
token, crypto token, and utility token payment and exchange
transactions; electronic payment processing of payments made
via digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens, and utility tokens;
digital currency, virtual currency, cryptocurrency,
stablecoin, digital and blockchain asset, digitized asset,
digital token, crypto token and utility token transaction
processing services for others; financial management of
digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens, and utility tokens. Providing temporary use of online non-downloadable software
for electronic payment processing, transferring funds to and
from others, and issuing receipts regarding electronic
payment transactions; application service provider (ASP)
services featuring software for use in digital currency,
virtual currency, cryptocurrency, stablecoin, digital and
blockchain asset, digitized asset, digital token, crypto
token and utility token exchanges and transactions;
providing temporary use of online non-downloadable software
for use in issuing digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for accepting, buying, selling, transmitting, and
exchanging digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for electronically trading, storing, sending,
receiving, validating, verifying, accepting, tracking, and
transferring digital currency, cryptocurrency, virtual
currency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for managing, implementing, and validating digital
currency, virtual currency, cryptocurrency, stablecoin,
digital asset, blockchain asset, digitized asset, digital
token, crypto token and utility token payment and exchange
transactions; providing temporary use of online
non-downloadable software for use in payments, purchases,
and investments using digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for users to buy and sell products using digital
currency, virtual currency, cryptocurrency, stablecoins,
digital and blockchain assets, digitized assets, digital
tokens, crypto tokens and utility tokens; providing
temporary use of online non-downloadable software for
currency conversion; providing temporary use of online
non-downloadable software for use as a digital currency,
virtual currency, cryptocurrency, stablecoin, digital asset,
digital token, crypto token, and utility token wallet;
providing temporary use of online non-downloadable software
for encryption; providing temporary use of online
non-downloadable software for verifying, evaluating, and
securing transactions with blockchain technology; providing
temporary use of online non-downloadable software for
managing and facilitating money transfers, electronic funds
transfers, commodity transfers, bill payment remittance, and
secure transactions.
57.
RISK DETERMINATION ENABLED CRYPTO CURRENCY TRANSACTION SYSTEM
Systems and methods for providing risk determination in a crypto currency transaction include receiving, through a network via a broadcast by a first payer device, a first crypto currency transaction that includes a first payee public address. A first request for a determination of risk associated with the first crypto currency transaction is then identified in the first crypto currency transaction, with the first request including risk criteria. A first payee involved in the first crypto currency transaction is then identified using the first payee public address, and first payee risk information is accessed via at least one external risk information database based on the identification of the first payee. If it is determined that the first payee risk information satisfies the at least one risk criteria in the first request, the first crypto currency transaction is provided for addition to a block in a crypto currency public ledger.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/06 - Circuits privés de paiement, p. ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
A method for adapting content for multiple targets may include receiving a document from a user computing device, the document comprising a plurality of text portions, tagging, via a first machine learning model, each of the plurality of text portions as either dynamic or static based on at least one characteristic of the respective text portion, receiving, from the user computing device, an indication of a content parameter, generating, via a second machine learning model for each of the plurality of text portions tagged as dynamic, a replacement portion based on the content parameter, and transmitting, to the user computing device, an updated document comprising a plurality of replacement portions and the plurality of text portions tagged as static.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software and mobile application
software for processing electronic payments, transferring
funds to and from others, and issuing receipts regarding
electronic payment transactions; downloadable software for
use in issuing digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; downloadable software for accepting, buying,
selling, transmitting, and exchanging digital currency,
virtual currency, cryptocurrency, stablecoins, digital and
blockchain assets, digitized assets, digital tokens, crypto
tokens and utility tokens; downloadable software for
electronically trading, storing, sending, receiving,
validating, verifying, accepting, tracking, and transferring
digital currency, cryptocurrency, virtual currency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
downloadable software for managing, implementing, and
validating digital currency, virtual currency,
cryptocurrency, stablecoin, digital asset, blockchain asset,
digitized asset, digital token, crypto token and utility
token payment and exchange transactions; downloadable
software for use in payments, purchases, and investments
using digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
downloadable software for use as a digital currency, virtual
currency, cryptocurrency, stablecoin, digital asset, digital
token, crypto token, and utility token wallet; downloadable
software for currency conversion; downloadable software for
creating tokens that may be used to pay for products and
services, and traded or exchanged for cash value;
downloadable software for managing and facilitating money
transfers, electronic funds transfers, commodity transfers,
bill payment remittance, and secure transactions. Electronic transfer of funds; clearing financial
transactions via a global computer network and wireless
networks; providing electronic mobile payment services for
others in the nature of providing secure commercial
transactions and payment options using a mobile device at a
point of sale; electronic foreign exchange payment
processing services; issuance of stablecoins and tokens of
value; stablecoin payment processing; stablecoin trading
services; stablecoin exchange services; financial services,
namely, providing digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens for use by others; financial services, namely,
digital currency, virtual currency, cryptocurrency,
stablecoin, digital and blockchain asset, digitized asset,
digital token, crypto token and utility token transfer,
exchange, and payment processing services; financial
exchange services; providing a financial exchange for
trading digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
currency exchange services, currency trading services,
foreign currency dealing, and broker-dealer financial
services in the field of cryptocurrency, digital currency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens and utility tokens;
currency transfer services; electronic transfer of
cryptocurrency, digital currency, stablecoins, digital and
blockchain assets, digitized assets, digital tokens, crypto
tokens and utility tokens; electronic wallet payment
services; electronic wallet services for trading, storing,
sending, receiving, validating, verifying, accepting,
tracking, transferring, and transmitting digital currency,
virtual currency, cryptocurrency, stablecoins, digital and
blockchain assets, digitized assets, digital tokens, crypto
tokens, and utility tokens, and for managing digital
currency, virtual currency, cryptocurrency, stablecoin,
digital and blockchain asset, digitized asset, digital
token, crypto token, and utility token payment and exchange
transactions; electronic payment processing of payments made
via digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens, and utility tokens;
digital currency, virtual currency, cryptocurrency,
stablecoin, digital and blockchain asset, digitized asset,
digital token, crypto token and utility token transaction
processing services for others; financial management of
digital currency, virtual currency, cryptocurrency,
stablecoins, digital and blockchain assets, digitized
assets, digital tokens, crypto tokens, and utility tokens. Providing temporary use of online non-downloadable software
for electronic payment processing, transferring funds to and
from others, and issuing receipts regarding electronic
payment transactions; application service provider (ASP)
services featuring software for use in digital currency,
virtual currency, cryptocurrency, stablecoin, digital and
blockchain asset, digitized asset, digital token, crypto
token and utility token exchanges and transactions;
providing temporary use of online non-downloadable software
for use in issuing digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for accepting, buying, selling, transmitting, and
exchanging digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for electronically trading, storing, sending,
receiving, validating, verifying, accepting, tracking, and
transferring digital currency, cryptocurrency, virtual
currency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for managing, implementing, and validating digital
currency, virtual currency, cryptocurrency, stablecoin,
digital asset, blockchain asset, digitized asset, digital
token, crypto token and utility token payment and exchange
transactions; providing temporary use of online
non-downloadable software for use in payments, purchases,
and investments using digital currency, virtual currency,
cryptocurrency, stablecoins, digital and blockchain assets,
digitized assets, digital tokens, crypto tokens and utility
tokens; providing temporary use of online non-downloadable
software for users to buy and sell products using digital
currency, virtual currency, cryptocurrency, stablecoins,
digital and blockchain assets, digitized assets, digital
tokens, crypto tokens and utility tokens; providing
temporary use of online non-downloadable software for
currency conversion; providing temporary use of online
non-downloadable software for use as a digital currency,
virtual currency, cryptocurrency, stablecoin, digital asset,
digital token, crypto token, and utility token wallet;
providing temporary use of online non-downloadable software
for encryption; providing temporary use of online
non-downloadable software for verifying, evaluating, and
securing transactions with blockchain technology; providing
temporary use of online non-downloadable software for
managing and facilitating money transfers, electronic funds
transfers, commodity transfers, bill payment remittance, and
secure transactions.
60.
FINE-TUNING SYSTEM FOR LARGE LANGUAGE MODELS TRAINED FOR OPEN-ENDED DOMAIN-SPECIFIC TASKS
There are provided systems and methods for a fine-tuning system for large language models trained for open-ended domain-specific tasks. An online transaction processor or other service provider may provide computing services and platforms to entities, which may include chatbots, information retrieval systems, question-and-answer systems, and the like. To provide better LLM training and fine-tuning, which may improve LLM performance in answering users' questions in an automated manner, the service provider may implement a fine-tuning system that may utilize automated annotations of training data, such as query and response pairs. An LLM may be prompted to determine an annotation to such pairs, and the annotations may be used to label the training data. A fine-tuning system and operations may then be implemented to fine-tune the LLMs using different processes including question-answering, retrieval augmented generation, or a continuous fine-tuning based on a size of the training data.
G06F 16/383 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
61.
SHORT-RANGE TRANSMISSION OF RECEIPT DATA WITHOUT CONTACT IDENTIFIERS
There are provided systems and methods for short-range transmission of receipt data without contact identifiers. 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 a receipt, where conventional digital receipt transmission would require the user to enter their contact information, such as an email address or phone number. Instead, the user may be provided with an option to receive a digital version of the receipt via short-range wireless communications without entering contact information. A message may be generated having a webpage address or another identifier allowing for retrieval of the digital receipt from a storage system, and the message may then be broadcast locally to the user's device. The broadcast may the cause the user's device to load and present the digital receipt.
There are provided systems and methods for identifying relevance of documents for automated retrieval models using large language models. An online transaction processor or other service provider may provide computing services and platforms to entities, which may include chatbots, information retrieval systems, question-and-answer systems, and the like. To provide better retrieval model training and refinement, the service provider may generate training data from user interaction logs, which may include user feedback that may be used to determine if documents are relevant to queries, and therefore should be retrieved for answering those queries by automated retrieval models. An LLM may be used as a judge to determine whether chatbot responses reference certain document. If not references, the query may be analyzed to determine whether certain retrieved documents are relevant. Data pairs may be generated for the training data from these processes and used for model refinement.
There are provided systems and methods for dynamic creation of data specification-driven AI-based executable strategies for high availability of evaluation services. A service provider, such as an electronic transaction processor for digital transactions, may utilize different decision services that implement rules and artificial intelligence models for decision-making of data including data in production computing environment. A decision service may normally be used for data processing and decision-making. However, at certain times, the decision service may fail or the services and/or a gateway for such services may be inaccessible. To provide higher availability and better SLA times, a client-side executable strategy for decision service execution may be determined using the pathways for strategy execution and available data from called resources. This strategy may be loaded in parallel to calling the decision service, and when failure occurs, may be used as a fallback to request processing.
H04L 41/5009 - Détermination des paramètres de rendement du niveau de service ou violations des contrats de niveau de service, p. ex. violations du temps de réponse convenu ou du temps moyen entre l’échec [MTBF]
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
Systems and methods for use with a service provider and a consumer electronic device include a trusted remote attestation agent (TRAA) configured to perform a set of checking procedures or mechanisms to help ensure the security status of a consumer electronic device (e.g., a mobile terminal or phone) that holds financial instruments. The checking procedures may include: self-verifying integrity by the TRAA; checking for presence of a provisioning SIM card (one that was present when the financial instruments were enabled on the device); checking that a communication connection between the consumer electronic device and the service provider is available and active; and checking that communication connectivity to a home mobile network is available and active. The frequency of the checking mechanisms may be adjusted, for example, according to a risk-profile of a user associated with the device or the location (e.g., GPS location) of the device. The checks may be used, for example, to temporarily disable or limit the use of the financial instruments from the device.
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
There are provided systems and methods for a fine-tuning system for large language models trained for open-ended domain-specific tasks. An online transaction processor or other service provider may provide computing services and platforms to entities, which may include chatbots, information retrieval systems, question-and- answer systems, and the like. To provide better LLM training and fine-tuning, which may improve LLM performance in answering users' questions in an automated manner, the service provider may implement a fine-tuning system that may utilize automated annotations of training data, such as query and response pairs. An LLM may be prompted to determine an annotation to such pairs, and the annotations may be used to label the training data. A fine-tuning system and operations may then be implemented to fine-tune the LLMs using different processes including question- answering, retrieval augmented generation, or a continuous fine-tuning based on a size of the training data.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software and mobile application software for processing electronic payments, transferring funds to and from others, and issuing receipts regarding electronic payment transactions; downloadable software for use in issuing digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; downloadable software for accepting, buying, selling, transmitting, and exchanging digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; downloadable software for electronically trading, storing, sending, receiving, validating, verifying, accepting, tracking, and transferring digital currency, cryptocurrency, virtual currency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; downloadable software for managing, implementing, and validating digital currency, virtual currency, cryptocurrency, stablecoin, digital asset, blockchain asset, digitized asset, digital token, crypto token and utility token payment and exchange transactions; downloadable software for use in payments, purchases, and investments using digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; downloadable software for use as a digital currency, virtual currency, cryptocurrency, stablecoin, digital asset, digital token, crypto token, and utility token wallet; downloadable software for currency conversion; downloadable software for creating tokens that may be used to pay for products and services, and traded or exchanged for cash value; downloadable software for managing and facilitating money transfers, electronic funds transfers, commodity transfers, bill payment remittance, and secure transactions Electronic transfer of funds; clearing financial transactions via a global computer network and wireless networks; providing electronic mobile payment services for others in the nature of providing secure commercial transactions and payment options using a mobile device at a point of sale; electronic foreign exchange payment processing services; issuance of stablecoins and tokens of value; stablecoin payment processing; stablecoin trading services; stablecoin exchange services; financial services, namely, providing digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens for use by others; financial services, namely, digital currency, virtual currency, cryptocurrency, stablecoin, digital and blockchain asset, digitized asset, digital token, crypto token and utility token transfer, exchange, and payment processing services; financial exchange services; providing a financial exchange for trading digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; currency exchange services, currency trading services, foreign currency dealing, and broker-dealer financial services in the field of cryptocurrency, digital currency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; currency transfer services; electronic transfer of cryptocurrency, digital currency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; electronic wallet payment services; electronic wallet services for trading, storing, sending, receiving, validating, verifying, accepting, tracking, transferring, and transmitting digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens, and utility tokens, and for managing digital currency, virtual currency, cryptocurrency, stablecoin, digital and blockchain asset, digitized asset, digital token, crypto token, and utility token payment and exchange transactions; electronic payment processing of payments made via digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens, and utility tokens; digital currency, virtual currency, cryptocurrency, stablecoin, digital and blockchain asset, digitized asset, digital token, crypto token and utility token transaction processing services for others; financial management of digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens, and utility tokens Providing temporary use of online non-downloadable software for electronic payment processing, transferring funds to and from others, and issuing receipts regarding electronic payment transactions; application service provider (ASP) services featuring software for use in digital currency, virtual currency, cryptocurrency, stablecoin, digital and blockchain asset, digitized asset, digital token, crypto token and utility token exchanges and transactions; providing temporary use of online non-downloadable software for use in issuing digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; providing temporary use of online non-downloadable software for accepting, buying, selling, transmitting, and exchanging digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; providing temporary use of online non-downloadable software for electronically trading, storing, sending, receiving, validating, verifying, accepting, tracking, and transferring digital currency, cryptocurrency, virtual currency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; providing temporary use of online non-downloadable software for managing, implementing, and validating digital currency, virtual currency, cryptocurrency, stablecoin, digital asset, blockchain asset, digitized asset, digital token, crypto token and utility token payment and exchange transactions; providing temporary use of online non-downloadable software for use in payments, purchases, and investments using digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; providing temporary use of online non-downloadable software for users to buy and sell products using digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; providing temporary use of online non-downloadable software for currency conversion; providing temporary use of online non-downloadable software for use as a digital currency, virtual currency, cryptocurrency, stablecoin, digital asset, digital token, crypto token, and utility token wallet; providing temporary use of online non-downloadable software for encryption; providing temporary use of online non-downloadable software for verifying, evaluating, and securing transactions with blockchain technology; providing temporary use of online non-downloadable software for managing and facilitating money transfers, electronic funds transfers, commodity transfers, bill payment remittance, and secure transactions
67.
Intelligent detection and acquisition of authentic product reviews for cross-platform availability
There are provided systems and methods for intelligent detection and acquisition of authentic product reviews for cross-platform availability. A service provider may provide computing services to merchants and users for processing various interactions, such as purchasing items electronically. When items or other products are purchased, users may leave reviews. To determine an authenticity of the reviews, the service provider may utilize an intelligent system that may include an LLM or other generative AI. The system may automatically generate questions for users that may be designed by the LLM to elicit responses that verify whether a review is authentic and/or relevant. This may include receiving responses and scoring those responses to verify the user is providing an authentic review. If so, the review may be written to a blockchain, which may allow the review to be pushed to users and/or automatically injected to product pages and checkout flows.
There are provided systems and methods for dynamic authentication through user information and intent. A user may wish to purchase an item that they view on a merchant marketplace using a computer of mobile phone. The merchant for the merchant marketplace may register the user's intent to purchase the item by receiving the user's actions while browsing the marketplace. The user may further provide user information with the merchant, such as a biometric reading, identifier, or other information. When the user then arrives at a merchant location to purchase the item and complete a transaction using a payment instrument, the merchant may process the user's intent and information to determine how confident the merchant is that the user is entitled to utilize the payment method. Such confidence rating may correspond to whether the merchant believes the transaction is fraudulent or if the user is misrepresenting their identity.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
69.
Semantic Search Architecture for Information Retrieval with Natural Language Queries
Techniques are disclosed relating to operating, by a computer system, a semantic search engine to retrieve records from a data store. The technique includes training, by the computer system using a plurality of training data sets that include queries and corresponding records, a retrieval model for use in the semantic search engine. The technique may further include generating, by the trained retrieval model, a particular output vector representing a received semantic search query, and generating, using the particular output vector, a respective similarity score for ones of candidate records identified in the data store. The trained retrieval model may send the particular output vector to a late interaction model, and the late interaction model may sort, using the particular output vector, candidate records with respective similarity scores that satisfy a threshold score.
Methods and systems described herein may implement blockchain asset authentication. A verification system may generate an encryption key associated with a digital asset, wherein the digital asset is associated with a first entity. The verification system may sign the digital asset using the encryption key. The verification system may generate a first key and a second key based on the encryption key, wherein the first key and the second key are part of a set of multi-party secret keys. The verification system may send the first key to the first entity and store the second key on the verification system. The verification system may receive a request to authenticate the digital asset. The verification system may in response to the request to authenticate, generate the encryption key based on the first key and the second key. The verification system may authenticate the digital asset based on the recreated first secret.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
A payment button on a device, such as a mobile phone, allows the user to remain on the window or page from which an item was selected for purchase. When the user is ready to purchases, the button is selected, and the user simply enters an identifier, such as a password or PIN, and the transaction is processed. The button remains on the same screen and changes during different stages of the payment process.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
G06Q 20/12 - Architectures de paiement spécialement adaptées aux systèmes de commerce électronique
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G07F 7/10 - Mécanismes actionnés par des objets autres que des pièces de monnaie pour déclencher ou actionner des appareils de vente, de location, de distribution de pièces de monnaie ou de papier-monnaie, ou de remboursement par carte d'identité codée ou carte de crédit codée utilisée simultanément avec un signal codé
72.
SCALABLE SERVICE DISCOVERY AND LOAD BALANCING USING DIRECT CLIENT CONNECTIONS TO SERVERS
There are provided systems and methods for scalable service discover and load balancing using direct client connections to servers. A service provider, such as an electronic transaction processor for digital transactions, may provide different computing services to users through client devices, which utilize server instances from server pools and the like to provide the computing services to users. This may include providing servers to handle client requests and process data with users. When client devices connect to the service provider's system, service discovery may be performed to find an available server instance to handle client requests. To provide scalable service discovery, load balancers may, instead of managing client requests through the load balancers, ping server instances from a server pool to identify a network address of an available server. This may be returned to the client device and a direction connection may be made between the device and server.
Techniques are disclosed relating to generating trained machine learning modules to identify whether user interfaces accessed by a computing device match user interfaces associated with a set of Internet domain names. A server computer system receives a set of Internet domain names and generates screenshots for user interfaces associated with the set of Internet domain names. The server computer system then trains machine learning modules that are customized for the set of Internet domain names using the screenshots. The server then transmits the machine learning modules to the computing device, where the machine learning modules are usable by an application executing on the computing device to identify whether a user interface accessed by the device matches a user interface associated with the set of Internet domain names. Such techniques may advantageously allow servers to identify whether user interfaces are suspicious without introducing latency and increased page load times.
G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p. ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
An example method includes receiving a request for a transaction; associating the request with a user; receiving, from the user, identification information; retrieving, from a database, first stored authentication information associated with the user; retrieving, from a distributed ledger, second stored authentication information associated with the user; and determining that the received authentication information matches the first stored authentication details and the second stored authentication details and, in response, outputting, by the computing system, a proof of authentication to enable the transaction.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
Methods and systems are presented for providing a machine learning model framework that provides an adaptive machine learning model base on providing quick and incremental trainings to the machine learning model. Instead of using the entire available training dataset to train the machine learning model, a subset of the available training dataset that accurately represents the characteristics of the training data set is extracted to be used in each iteration of incremental training. Furthermore, labels of unmatured dataset are imputed to provide additional training datasets that correspond to any emerging pattern. Synthetic training datasets are also generated to mimic datasets that correspond to an emerging pattern to strengthen the machine learning model's ability to recognize the emerging pattern.
Methods and systems are presented for providing an artificial intelligence (AI) model framework that uses an AI model to assist a machine learning (ML) model in classifying data, such that data corresponding to emerging patterns unrecognizable by the ML model can be classified accurately. Emerging patterns that are not recognizable by the ML model are detected. Representations of the emerging patterns are generated and provided to the AI model along with data to be classified in a prompt. The AI model is configured to use the ML model to classify the data if the data does not correspond to the emerging pattern. The AI model is further configured to use the representations to classify the data without using the ML model if the data corresponds to the emerging pattern.
There are provided systems and methods for vehicle identification and device communication through directional wireless signaling. A user's device may include a directional wireless transceiver that may be used to provide wireless signaling in a specific target direction. The user may direct the device at a particular vehicle, where the vehicle may has a transceiver located within or attached to the vehicle that responds to the particular wireless signaling. The vehicle's transceiver may respond to the device of the user with a unique identifier that allows for communication with the vehicle's operator. The unique identifier may therefore allow for message content to be sent directly to a device for the vehicle's operator, or may allow for a service provider to process the message. Additionally, the vehicle's operator may establish privacy settings for communications, which may be utilized to determine whether the message content will be provided to the device.
H04L 51/48 - Adressage des messages, p. ex. format des adresses ou messages anonymes, alias
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
H04L 51/212 - Surveillance ou traitement des messages utilisant un filtrage ou un blocage sélectif
H04W 4/02 - Services utilisant des informations de localisation
H04W 4/021 - Services concernant des domaines particuliers, p. ex. services de points d’intérêt, services sur place ou géorepères
H04W 4/40 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons
H04W 8/20 - Transfert de données utilisateur ou abonné
H04W 76/14 - Établissement de la connexion en mode direct
78.
USER INTERFACE MODIFICATION FROM RECOMMENDATION ENGINE
The disclosed computer-implemented method may include generating a first recommendation using a first model that uses a first reward function for potential actions and generating a second recommendation using a second model that is independent from the first model and uses a second reward function for the potential actions. The method may also include determining a third recommendation by combining the first recommendation and the second recommendation and updating a user interface based on the third recommendation. Various other methods, systems, and computer-readable media are also disclosed.
A computer-implemented method includes collecting information respective of one or more transactions stored on a public blockchain, determining that a first private account hosted by the computing system is associated with a first transaction of the one or more transactions, determining that a second private account hosted by the computing system is associated with a second transaction of the one or more transactions, associating the first private account with the second private account based on a connection of the first transaction to the second transaction on the public blockchain, and training a machine learning model according to the association of the first private account with the second private account.
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
80.
MULTI-DIMENSIONAL CODED REPRESENTATIONS OF ENTITIES
Methods and systems are presented for providing a framework that enables a computer system to analyze and compare changes to different account characteristics of different accounts that occurred over a time period. A code is generated for an account to represent changes to different account characteristics of the account within the time period. Changes to different account characteristics may be highlighted in the code using different colors or patterns. By analyzing the code, overlapping changes from different account characteristics that occurred within the same time frame may be detected. The different change patterns associated with the user account may then be used to assess a risk for the user account and/or a transaction involving the user account.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
Techniques are disclosed relating to the execution of queries in an online manner. For example, in some embodiments, a server system may include a distributed computing system that, in turn, includes a distributed storage system operable to store transaction data associated with a plurality of users, and a distributed computing engine operable to perform distributed processing jobs based on the transaction data. In various embodiments, the server system preemptively creates a compute session on the distributed computing engine, where the compute session provides access to various functionalities of the distributed computing engine. The distributed computing engine may then use these preemptively created compute sessions to execute queries (e.g., for end users of the server system) against the transaction data and return the results dataset to the requesting users in an online manner.
G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
82.
METHOD, MEDIUM, AND SYSTEM FOR AUTOMATIC DATA EXTRACTION FROM WEB PAGES AND ANALYSIS THEREOF
The present disclosure provides a method of automatically extracting data from web pages and analyzing the extracted data to generate an output. A plurality of web pages of a plurality of merchants is accessed. Based on the accessing of the web pages, a subset of the plurality of web pages is identified as inventory pages that contain information about products or services offered for sale. The inventory pages are electronically scanned to extract a price for each of the products or services. An output is generated that includes a listing of the products or services and prices associated with the products or services, respectively.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Downloadable software for processing electronic payments and for transferring funds to and from others; downloadable software for facilitating money transfer services, electronic funds transfer services, bill payment remittance services, electronic processing and transmission of payments and payment data; downloadable computer software and downloadable mobile application software for facilitating electronic commerce transactions; downloadable software for use as a digital wallet; downloadable software for connecting digital wallets; downloadable software for connecting, integrating, and enabling transfer of funds between digital wallets and financial accounts; downloadable software for linking independent financial accounts and digital wallets, enabling migration of data and transfers of funds between independent third party financial accounts and digital wallets, and establishing secure connections between independent financial accounts and digital wallets; downloadable computer software for use for financial account management, namely, software for managing and facilitating financial transactions and funds transfers for bank accounts, credit card accounts, debit card accounts, and digital wallets; downloadable authentication software for controlling access to and communications with computers and computer networks; downloadable software for currency conversion. (1) Providing business information regarding money transfer services; business consulting services in the field of online payments; business managing and tracking credit card, debit card, ACH, prepaid cards, payment cards, and other forms of payment transactions via electronic communications networks for business purposes; business information management, namely, electronic reporting of business analytics relating to payment processing, authentication, tracking, and invoicing.
(2) Electronic payment services involving electronic processing and subsequent transmission of bill payment data; payment transaction processing services; providing electronic processing of electronic funds transfer, ACH, credit card, debit card, electronic check and electronic payments; financial information processing; money transfer services; electronic funds transfer services; bill payment services; providing payment services via a network for facilitating transactions from digital wallets; providing financial services, namely, bill payment services provided via a digital wallet and providing secure commercial transactions; transaction processing services for bank accounts, debit cards, and credit cards on embedded digital wallets, cross-border money transfers to banks and mobile wallets with real time currency exchange rates; clearing financial transactions via a global computer network and wireless networks; credit card and debit card transaction processing services; processing of electronic wallet payments; currency exchange services; electronic commerce payment services, namely, establishing funded accounts used to facilitate transactions and purchases on the internet.
(3) Providing temporary use of online non-downloadable software for processing electronic payments and for transferring funds to and from others; application service provider (ASP) featuring application programming interface (API) software for facilitating payment transactions and financial information processing; providing temporary use of online non-downloadable software for facilitating money transfer services, electronic funds transfer services, bill payment remittance services, electronic processing and transmission of payments and payment data; providing temporary use of online non-downloadable software for facilitating electronic commerce transactions; providing temporary use of online non-downloadable software for use as a digital wallet; providing temporary use of online non-downloadable software for connecting digital wallets; providing temporary use of online non-downloadable software for connecting, integrating, and enabling transfer of funds between digital wallets and financial accounts; providing temporary use of online non-downloadable software for linking independent financial accounts and digital wallets, enabling migration of data and transfers of funds between independent third party financial accounts and digital wallets, and establishing secure connections between independent financial accounts and digital wallets; providing temporary use of online non-downloadable software for use for financial account management, namely, software for managing and facilitating financial transactions and funds transfers for bank accounts, credit card accounts, debit card accounts, and digital wallets; providing temporary use of online non-downloadable authentication software for controlling access to and communications with computers and computer networks; providing temporary use of online non-downloadable software for currency conversion.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for creating, editing, and sharing image files consisting of digital avatars, graphic icons, symbols, images representing individuals, fanciful designs, phrases, and graphical depictions of people, places and things; downloadable image files featuring digital avatars, graphic icons, symbols, images representing individuals, fanciful designs, phrases, and graphical depictions of people, places and things Advertising, marketing, and promotion services featuring digital avatars, graphic icons, symbols, images representing individuals, fanciful designs, phrases, and graphical depictions of people, places and things; creating digital advertising material featuring digital avatars, graphic icons, symbols, images representing individuals, fanciful designs, phrases, and graphical depictions of people, places and things Providing online non-downloadable image files featuring digital avatars, graphic icons, symbols, images representing individuals, fanciful designs, phrases, and graphical depictions of people, places and things Providing online non-downloadable software for creating, editing, and sharing image files consisting of digital avatars, graphic icons, symbols, images representing individuals, fanciful designs, phrases, and graphical depictions of people, places and things; graphic design services
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for processing electronic payments and for transferring funds to and from others; downloadable software for facilitating money transfer services, electronic funds transfer services, bill payment remittance services, electronic processing and transmission of payments and payment data; downloadable computer software and downloadable mobile application software for facilitating electronic commerce transactions; downloadable software for use as a digital wallet; downloadable software for connecting digital wallets; downloadable software for connecting, integrating, and enabling transfer of funds between digital wallets and financial accounts; downloadable software for linking independent financial accounts and digital wallets, enabling migration of data and transfers of funds between independent third party financial accounts and digital wallets, and establishing secure connections between independent financial accounts and digital wallets; downloadable computer software for use for financial account management, namely, software for managing and facilitating financial transactions and funds transfers for bank accounts, credit card accounts, debit card accounts, and digital wallets; downloadable authentication software for controlling access to and communications with computers and computer networks; downloadable software for currency conversion Providing business information regarding money transfer services; business consulting services in the field of online payments; business managing and tracking credit card, debit card, ACH, prepaid cards, payment cards, and other forms of payment transactions via electronic communications networks for business purposes; business information management, namely, electronic reporting of business analytics relating to payment processing, authentication, tracking, and invoicing Electronic payment services involving electronic processing and subsequent transmission of bill payment data; Payment transaction processing services; providing electronic processing of electronic funds transfer, ACH, credit card, debit card, electronic check and electronic payments; financial information processing; money transfer services; electronic funds transfer services; bill payment services; providing a payment network for facilitating transactions from digital wallets; providing financial services, namely, bill payment services provided via a digital wallet and providing secure commercial transactions; transaction processing services for bank accounts, debit cards, and credit cards on embedded digital wallets, cross-border money transfers to banks and mobile wallets with real time currency exchange rates; clearing financial transactions via a global computer network and wireless networks; credit card and debit card transaction processing services; processing of electronic wallet payments; currency exchange services; electronic commerce payment services, namely, establishing funded accounts used to facilitate transactions and purchases on the internet Providing temporary use of online non-downloadable software for processing electronic payments and for transferring funds to and from others; Application Service Provider (ASP) featuring Application Programming Interface (API) software for facilitating payment transactions and financial information processing; providing temporary use of online non-downloadable software for facilitating money transfer services, electronic funds transfer services, bill payment remittance services, electronic processing and transmission of payments and payment data; providing temporary use of online non-downloadable software for facilitating electronic commerce transactions; providing temporary use of online non-downloadable software for use as a digital wallet; providing temporary use of online non-downloadable software for connecting digital wallets; providing temporary use of online non-downloadable software for connecting, integrating, and enabling transfer of funds between digital wallets and financial accounts; providing temporary use of online non-downloadable software for linking independent financial accounts and digital wallets, enabling migration of data and transfers of funds between independent third party financial accounts and digital wallets, and establishing secure connections between independent financial accounts and digital wallets; providing temporary use of online non-downloadable software for use for financial account management, namely, software for managing and facilitating financial transactions and funds transfers for bank accounts, credit card accounts, debit card accounts, and digital wallets; providing temporary use of online non-downloadable authentication software for controlling access to and communications with computers and computer networks; providing temporary use of online non-downloadable software for currency conversion
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.
Embodiments described herein disclose a mobile device system for displaying contactless payment options to a user of a mobile device. A location of the device may be detected. The location may be transmitted to a payment services provider, and information indicating that the location corresponds to a merchant having contactless payment options may be received. In response, graphical depictions of payment options associated with a plurality of payment sources are displayed on a touch-sensitive display of the mobile device. A selection of one of the graphical depictions is received, and in response, one or more transceivers of the mobile device, such as one or more NFC transceivers, may be activated. The activation may cause the transceivers to transmit a personal account number to a point-of-sale terminal. Thus, the user is presented with contactless payment options based on a geographical location, and may be presented with a suggested payment source.
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06K 7/00 - Méthodes ou dispositions pour la lecture de supports d'enregistrement
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p. ex. forme, nature, code
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
88.
MULTI-PARTY COMPUTATION IN A COMPUTER SHARDING ENVIRONMENT
Methods and systems are presented for providing a framework for facilitating multi-party computation within a sharding environment. After a blockchain is divided into multiple shard chains, a multi-party computation system obtains attributes associated with a first shard chain. The attributes may represent characteristics of the first shard chain, characteristics of transactions recorded in the first shard chain, and characteristics of the computer nodes configured to manage the first shard chain. Based on the attributes, the multi-party computation system determines a multi-party computation scheme that specifies a minimum threshold number of nodes required to participate in a transaction validation process and at least one required node required to participate in the transaction validation process for the first shard chain. The multi-party computation system configures the computer nodes configured to manage the first shard chain to perform the transaction validation process according to the multi-party computation scheme.
There are provided systems and methods for document image forgery and integration detection using generative artificial intelligence. A service provider, such as an electronic transaction processor for digital transactions, may provide computing services to users, which may be used to engage in interactions with other users and entities including for electronic transaction processing. When utilizing these services, document verification may be required to verify a document. A document may be submitted for document verification, which may be analyzed to determine if the document is forged. To train a machine learning model for document forgery detection a generative adversarial network may be used to generate fake documents of forgeries based on trends in forgeries of real documents. These fake documents may be provided as additional training data to more robustly train a model and keep up on changes in forgery techniques.
Techniques are disclosed relating to partitioning batch queries for multi-engine execution. A system receives a batch query specifying query data and including a request for geospatial data for regions corresponding to the query data. Based on locations corresponding to the query data, the system partitions the query data into subsets. The system may assign the subsets of query data to query engines corresponding to the locations of the subsets. The system may cause the engines to retrieve geographic region data corresponding to the locations included in the subsets, where the retrieving is performed by a given query engine for a corresponding subset by accessing an in-memory index of the given engine that stores geographic region data for a geographic partition within which the corresponding subset of query data is located. The system may store region data retrieved by the engines for the subsets in an aggregated data store.
Methods and systems described herein may implement non-fungible tokens that implement a programmable grammar-based syntax in a variety of environments. In an embodiment, a first non-fungible token that implements a programmable grammar-based syntax standard and includes a first updatable programmable section is generated. The first non-fungible token includes at least one of first executable instructions or first data, and a first portion of the at least one of the first executable instructions or the first data is stored, according to the grammar-based syntax standard, in the first updatable programmable section. The first non-fungible token may then be stored at a first blockchain address on a blockchain, and the first portion of the at least one of the first executable instructions or the first data in the first updatable programmable section of the first non-fungible token is subsequently changed to at least one of second executable instructions or second data.
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
G06F 40/211 - Parsage syntaxique, p. ex. basé sur une grammaire hors contexte ou sur des grammaires d’unification
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
92.
DOCUMENT IMAGE FORGERY AND INTEGRITY DETECTION USING GENERATIVE ARTIFICIAL INTELLIGENCE
There are provided systems and methods for document image forgery and integration detection using generative artificial intelligence. A service provider, such as an electronic transaction processor for digital transactions, may provide computing services to users, which may be used to engage in interactions with other users and entities including for electronic transaction processing. When utilizing these services, document verification may be required to verify a document. A document may be submitted for document verification, which may be analyzed to determine if the document is forged. To train a machine learning model for document forgery detection a generative adversarial network may be used to generate fake documents of forgeries based on trends in forgeries of real documents. These fake documents may be provided as additional training data to more robustly train a model and keep up on changes in forgery techniques.
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/776 - ValidationÉvaluation des performances
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 30/414 - Extraction de la structure géométrique, p. ex. arborescenceDécoupage en blocs, p. ex. boîtes englobantes pour les éléments graphiques ou textuels
G06V 30/418 - Appariement de documents, p. ex. d’images de documents
93.
Batch Query Partitioning for Multi-engine Execution
Techniques are disclosed relating to partitioning batch queries for multi-engine execution. A system receives a batch query specifying query data and including a request for geospatial data for regions corresponding to the query data. Based on locations corresponding to the query data, the system partitions the query data into subsets. The system may assign the subsets of query data to query engines corresponding to the locations of the subsets. The system may cause the engines to retrieve geographic region data corresponding to the locations included in the subsets, where the retrieving is performed by a given query engine for a corresponding subset by accessing an in-memory index of the given engine that stores geographic region data for a geographic partition within which the corresponding subset of query data is located. The system may store region data retrieved by the engines for the subsets in an aggregated data store.
System and methods for predicting content items using a neural network model and performing reinforcement learning as continual learning for training the neural network model includes obtain a first dataset of user actions of a plurality of users at a plurality of user devices and a second dataset of historical data for the plurality of users, extract a first set of embeddings and a second set of embeddings from the first dataset and the second dataset, output a trained model based on applying the first and second set of embeddings, determine a set of candidate content items by the trained model, determine a prediction value for each respective candidate content item of the set of candidate content items by the trained model, and output one or more content items of the set of candidate content items based on the prediction value determined for each respective first candidate content item.
H04N 21/25 - Opérations de gestion réalisées par le serveur pour faciliter la distribution de contenu ou administrer des données liées aux utilisateurs finaux ou aux dispositifs clients, p. ex. authentification des utilisateurs finaux ou des dispositifs clients ou apprentissage des préférences des utilisateurs pour recommander des films
The disclosed computer-implemented method may include generating an interface code configured to connect to a payment server and generating, in response to loading a merchant website hosted on a merchant server that integrates the interface code, a payment interface with the interface code. The interface code may bypass the merchant server to connect to the payment server. The method may also include completing a payment using the payment interface that bypasses the merchant server to connect to the payment server. Various other methods, systems, and computer-readable media are also disclosed.
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/06 - Circuits privés de paiement, p. ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/12 - Architectures de paiement spécialement adaptées aux systèmes de commerce électronique
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
The disclosed computer-implemented method may include generating an interface code configured to connect to a payment server and generating, in response to loading a merchant website hosted on a merchant server that integrates the interface code, a payment interface with the interface code. The interface code may bypass the merchant server to connect to the payment server. The method may also include completing a payment using the payment interface that bypasses the merchant server to connect to the payment server. Various other methods, systems, and computer-readable media are also disclosed.
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
97.
MECHANISMS FOR IMPLEMENTING VIRTUAL LINKING NODES FOR GRAPH NEURAL NETWORKS
Techniques are disclosed pertaining to classifying an event. A computer system may receive event information identifying event features of the event. The computer accesses a graph neural network model trained based on modified graph data describing a graph data structure having a plurality of event nodes representing events and a plurality of feature nodes representing combinations of event features. The graph data structure includes a virtual linking node that links a first node group to a second node group to enable a first set of event nodes of the first group to influence a second set of event nodes of the second group during a training phase in which the graph neural network model is trained based on the modified graph data. The computer system generates an event node representation of the event and then classifies the event based on the event node representation and the graph neural network model.
During a live test of changes to a current set of event processing filters, a computer system may determine a selected set of event processing filters with which to evaluate a live event (either a current set of event processing filters or a new set of event processing filters in one example). The computer system evaluates the live event according to the selected set of event processing filters. Based on the evaluation, the computer system updates metrics for events evaluated during the live test. The metrics may include a first set of metrics for events evaluated during the live test using the current set of event processing filters and a second set of metrics for events evaluated using the new set of event processing filters. The metrics may be used to decide whether to promote the new set of event processing filters to the current set of event processing filters.
The present disclosure provides techniques for efficient blockchain transaction processing. In one embodiment, a computer system broadcasts a first transaction to a blockchain network for addition to a block in a blockchain. The computer system may broadcast a second transaction to the blockchain network for addition to the block in the blockchain, where the second transaction descends from the first transaction and includes a placeholder fee. The computer system monitors and determines that the first transaction has not been confirmed to the block in the blockchain for a duration of time (e.g., stuck in the mempool). In response to determining that the first transaction is stuck, the computer system may transmit a request to replace the placeholder fee with a transaction fee that is sufficiently high to cause the first transaction and the second transaction to be confirmed to a block in the blockchain, thereby unsticking the first transaction.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/06 - Circuits privés de paiement, p. ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
A source database and a target database are accessed. The source database contains data to be migrated over to the target database. The read operations from the target database and the write operations to the target database are ceased, while the read operations from the source database and the write operations to the source database are maintained. The data from the source database is replicated to the target database. During the replication, the read operations from the source database are maintained but the write operations to the source database are ceased, while the read operations from the target database and the write operations to the target database are also ceased. After the replication has been completed, the read operations from the source database and the write operations to the source database are ceased. The read operations from the target database and the write operations to the target database are resumed.
G06F 16/20 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données structurées, p. ex. de données relationnelles
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
