In some embodiments, a system transmits a shared presentation to user devices associated with users. Then, in response to an inquiry from a first user associated with a first viewing device, the system identifies that an answer to this inquiry was covered in a previous portion of the presentation, and generates auxiliary data (e.g., an auxiliary video stream of the shared presentation) corresponding to the previous portion of the presentation. The system then causes the first viewing device to display the auxiliary data corresponding to the previous portion of the presentation, which includes an answer to the first user's inquiry, in lieu of the shared presentation. In an example, the auxiliary data may be played back at a speed that is faster than the default speed of the shared presentation.
H04N 21/4788 - Services additionnels, p.ex. affichage de l'identification d'un appelant téléphonique ou application d'achat communication avec d'autres utilisateurs, p.ex. discussion en ligne
H04N 21/236 - Assemblage d'un flux multiplexé, p.ex. flux de transport, en combinant un flux vidéo avec d'autres contenus ou données additionnelles, p.ex. insertion d'une adresse universelle [URL] dans un flux vidéo, multiplexage de données de logiciel dans un flu; Remultiplexage de flux multiplexés; Insertion de bits de remplissage dans le flux multiplexé, p.ex. pour obtenir un débit constant; Assemblage d'un flux élémentaire mis en paquets
2.
INTELLIGENT SORTING OF TIME SERIES DATA FOR IMPROVED CONTEXTUAL MESSAGING
Systems for intelligent sorting of time series data for improved contextual messaging are included herein. An intelligent sorting server may receive time series data comprising a plurality of chat messages. The intelligent sorting server may determine a first order of the plurality of chat messages based on a chronologic order. The intelligent sorting server may use one or more machine learning classifiers to identify candidates for reordering the chat messages. The intelligent sorting server may generate a second order of the chat messages based on the identified candidates for reordering. Accordingly, the intelligent sorting server may present, to a client device, a transcript of the chat messages associated with the second order and an indication that at least one chat message has been repositioned.
A computer-implemented method may include: receiving financial information regarding a user; categorizing transaction information of the user based on the financial information; displaying the categorized transaction information of the user; receiving information regarding at least one financial preference and at least one transaction preference of the user; training a machine learning engine based on the at least one financial preference and at least one transaction preference of the user to determine one or more activities available to the user; calculating, for each of the one or more activities available to the user, an estimated influence on the at least one financial preference; displaying the estimated influence on the at least one financial preference based on a user selected one of the one or more activities available to the user; filtering the one or more activities available to the user with a positive estimated influence to the at least one financial preference; and presenting a recommendation of action relating to the one of the one or more activities available to the user, wherein the recommendation of action relating to the one of the one or more activities available to the user is presented by at least one of voice notification, application notification, tactile notification, or graphic notification.
A system receives an image including a live facial image of the user and an identity document including a photograph of the user. Moreover, the system calculates a facial match score by comparing facial features in the live facial image to facial features in the photograph. The system recognizes data objects and characters in the identity document using optical character recognition (OCR) and computer vision, and then identifies, based on the recognized data objects and characters, a type of the identity document. Further, the system calculates a document validity score by comparing the recognized characters and data objects to character strings and data objects known to be present in the identified type of the identity document. Additionally, the system determines and outputs the user's identity verification status based on comparing the facial match score to a facial match threshold and comparing the document validity score to a document validity threshold.
G06V 30/413 - Classification de contenu, p.ex. de textes, de photographies ou de tableaux
G06V 30/416 - Extraction de la structure logique, p.ex. chapitres, sections ou numéros de page; Identification des éléments de document, p.ex. des auteurs
G06V 40/16 - Visages humains, p.ex. parties du visage, croquis ou expressions
Disclosed herein are system, method, and computer readable medium embodiments for machine learning systems to process interactive communications between at least two participants. Speech and text within the interactive communications are analyzed using machine learning models to infer insights located within the interactive communications. The inferred insights are converted to descriptive text or audio and tagged to the interactive communication as graphics or audio whispers reflecting the insights added to the interactive communication.
Disclosed embodiments may include a method for generic aspect-based sentiment analysis. The system may receive training data, which is used to train one or more machine learning models. The system may receive data, which may be transcribed call data. The system may extract one or more aspects from the call data using one machine learning model. For each aspect, the system may determine a sentiment polarity. The system may filter the aspects and sentiment polarities and analyze trends based on the filtered aspects and sentiment polarities. The system may output a result to a dynamic graphical user interface based on the trends. This may allow a user to detect customer attitudes toward a variety of subjects and trends over time without training machine learning models for specific domains.
G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06N 20/20 - Techniques d’ensemble en apprentissage automatique
7.
SYSTEMS AND METHODS FOR PROVIDING CARD INTERACTIONS
A method including receiving a first application user credential associated with a user profile; comparing, for a first match, the first application user credential with a stored second application user credential, wherein the stored second application user credential is associated with a user identity; and responsive to finding a first match, verifying the user identity by performing the following: communicating with a card using near field communication; receiving a public key of a key pair of the card and cardholder identification information of an account holder of the card; instructing the card to generate a digital signature; receiving the digital signature from the card; verifying the digital signature using the public key; and comparing, for a second match, at least a portion of the user identity with at least a portion of the cardholder identification information.
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
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 magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
8.
AUTOMATED PREDICTIVE CACHING OF CLOUD-SOURCED DATA AND METHODS OF USE THEREOF
Systems and methods of the present disclosure enable intelligent dynamic caching of data by accessing an activity history of historical electronic activity data entries associated with a user account, and utilizing a trained entity relevancy machine learning model to predict a degree of relevance of each entity associated with the historical electronic activity data entries in the activity history based at least in part on model parameters and activity attributes of each electronic activity data entry. A set of relevant entities are determined based at least in part on the degree of relevance of each entity. Pre-cached entities are identified based on pre-cached entity data records cached on the user device, and un-cached relevant entities from the set of relevant entities are identified based on the pre-cached entities. The cache on the user device is updated to cache the un-cached entity data records associated with the un-cached relevant entities.
G06F 12/0802 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p.ex. mémoires cache
9.
SYSTEMS AND METHODS FOR CONTROLLING PERMISSIONS IN BLOCKCHAINS
Methods and systems for controlling users' access to data available on blockchains are described herein, comprising: determining a first right for a first user to first data; determining a location in a permissioned blockchain comprising the first data, the location being a first fork of the permissioned blockchain; determining a first privilege required to access the first fork; determining that the first user corresponds to a first cryptographic address; and assigning the first privilege to the first cryptographic address.
In some implementations, a device may train the model to generate embeddings for log files associated with an application, and to enable the model to generate embeddings for sensitive information included in a set of training log files. The device may receive a log file associated with the application. The device may generate a compressed log file including a set of embedding vectors associated with records included in the log file, where a record that includes sensitive information is associated with one or more embedding vectors for the sensitive information and one or more embedding vectors for other information included in the record. The device may store the compressed log file including the set of embedding vectors where a size of the compressed file is less than a size of the log file, and the embedding vectors obfuscate the records included in the log file.
Systems and methods for managing models for call data are disclosed. For example, the system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving, from a user device, an input indicating a segment of a first recorded call and an attribute associated with the segment. The operations may include determining a parameter of a model, wherein the model is associated with the attribute. The operations may include changing the parameter based on the input. The operations may include generating an updated model based on the changed parameter, wherein the updated model may be configured to analyze recorded calls having one or more segments with the same attribute.
Disclosed embodiments may include a system for predicting cash flow. The system may aggregate transaction information associated with cash inflows and outflows of a user account. The system may generate a GUI displaying current cash inflows and outflows, including cash outflow categories, for the user account. The system may predict, via a trained MLM, a future time period in which the future cash outflows will exceed the future cash inflows associated with the user account. The system may update the GUI to display the future cash inflows and outflows associated with the future time period by rearranging the cash outflow categories in order of predicted use in the future time period. The system may transmit a notification to a user device associated with the user account to reduce cash outflow associated with a cash outflow category associated with a highest predicted use.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 40/02 - Opérations bancaires, p.ex. calcul d'intérêts ou tenue de compte
13.
SYSTEMS AND METHODS FOR PROVIDING MANUFACTURER-BASED FINANCIAL SERVICE ACCOUNTS
The disclosed embodiments include a mobile client device for providing real-time manufacturer-based financing. In one embodiment, the mobile device is configured to receive a product code associated with a manufacturer product offered for sale at a merchant location. The mobile device may further provide the product code to a financial service provider system configured to create a manufacturer-based financial service account associated with the product manufacturer. Further, the mobile device may provide, to the financial service provider system, information associated with a received account application, where the financial service provider system may create the manufacturer-based financial service account based on the received information and the product code. The mobile device may also receive a purchase code for purchasing the product using the manufacturer-based financial service account, provide it at the merchant POS location, and receive a confirmation of product purchase.
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
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
A device receives document information associated with a document, and receives a request to identify insights in the document information. The device performs, based on the request, natural language processing on the document information to identify words, phrases, and sentences in the document information, and utilizes a first machine learning model with the words, the phrases, and the sentences to identify information indicating abstract insights, concrete insights, and non-insights in the document. The device utilizes a second machine learning model to match the abstract insights with particular concrete insights that are different than the concrete insights, and utilizes a third machine learning model to determine particular insights based on the non-insights. The device generates an insight document that includes the concrete insights, the abstract insights matched with the particular concrete insights, and the particular insights determined based on the non-insights.
G06N 20/20 - Techniques d’ensemble en apprentissage automatique
G06F 16/30 - Recherche d’informations; Structures de bases de données à cet effet; Structures de systèmes de fichiers à cet effet de données textuelles non structurées
G06F 18/2413 - Techniques de classification relatives au modèle de classification, p.ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
G06F 40/216 - Analyse syntaxique utilisant des méthodes statistiques
G06F 40/284 - Analyse lexicale, p.ex. segmentation en unités ou cooccurrence
A method and system include identifying, by a processor, departing flight information that designates departure airports and departure times in payment card transaction data of a plurality of users. Airport-specific data for a departure airport before a departure time of a departing flight of a user from the plurality of users is received. The airport-specific data is inputted into a machine learning model that outputs a user-specific airport processing time for the user to reach a departure gate upon arriving to the departure airport. A travel time from a geographical location of the computing device of the user to the departure airport is received from a navigation system. The computing device displays a time for the user to start travel to the departure airport based on the user-specific airport processing time and the travel time to the departure airport for the user to reach the departure gate by the departure time.
G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06Q 10/02 - Réservations, p.ex. pour billetterie, services ou manifestations
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
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 30/0201 - Modélisation du marché; Analyse du marché; Collecte de données du marché
G06Q 50/26 - Services gouvernementaux ou services publics
G06Q 50/40 - Procédés d’affaires s’appliquant à l’industrie du transport (expédition G06Q 10/83)
G07C 11/00 - Dispositions, systèmes ou appareils pour vérifier, p.ex. l'occurrence d'un fait ou d'une situation, non prévus ailleurs
16.
DOCUMENT AUTHENTICITY DETECTION IN A COMMUNICATION NETWORK
System, apparatus, device, method and/or computer program product are disclosed for detecting the authenticity of an image file transferred from a device to a server based on an image authenticity detection configuration determined by a server application. A device application is operated by a device, and a server application is operated by a server. The device application sends, to the server application, user data, device data, or environment data. The server application determines an image authenticity detection configuration to indicate one or more parameters to be used by the device to generate a first image file, and authorized changes to be made to the first image file to generate a second image file. The device application sends the second image file to the server application. The server application detects whether the received second image file contains changes matching authorized changes indicated by the image authenticity detection configuration.
An EMV enabled terminal may communicate transaction related information to a user via a standard user interface of the terminal, for example, within a user interface displayed on a display screen of the terminal. The transaction related information may be spoken out loud to the user by the terminal. However, users with visual, audio, or other physical impairments may be unable to access the display of the terminal, view the displayed information, or hear the spoken information. Systems and methods disclosed herein communicate transaction related information via an alternate user interface. Instead of relying on the standard user interface related communications, information about the status of a transaction or transaction related information may be determined based on monitoring and evaluating the communications between an EMV secure element of a dynamic transaction card and the terminal via a contact connection.
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
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
A device may capture a plurality of preview frames of a document, and for each preview frame of the plurality of preview frames, process the preview frame to identify an object in the preview frame. Processing the preview frame may include converting the preview frame into a grayscale image, generating a blurred image based on the grayscale image, detecting a plurality of edges in the blurred image, defining at least one bounding rectangle based on the plurality of edges, and determining an outline of the object based on the at least one bounding rectangle. The device may determine whether a value of an image parameter, associated with the one or more preview frames, satisfies a threshold, and provide feedback to a user of the device, or automatically capture an image of the document, based on determining whether the value of the image parameter satisfies the threshold.
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p.ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersections; Analyse de connectivité, p.ex. de composantes connectées
G06V 30/414 - Extraction de la structure géométrique, p.ex. arborescence; Découpage en blocs, p.ex. boîtes englobantes pour les éléments graphiques ou textuels
Aspects described herein may provide detection of a feature of an authorization code image (ACI) incorporated onto a document, thereby allowing for validation of the document. According to some aspects, these and other benefits may be achieved by an instance of a variable protocol that may specify how to generate the ACI to have a particular feature as well as how to detect the particular feature of the ACI. A recipient of the document incorporating the ACI may detect the particular feature of the ACI. If the detected feature matches an expected feature, then the ACI and the document may be determined to be authentic.
B41J 3/28 - Machines à écrire ou mécanismes d'impression ou de marquage sélectif caractérisés par le but dans lequel ils sont construits pour l'impression de haut en bas des surfaces planes, p.ex. de livres, dessins, boîtes
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 magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
A system, method, and computer-readable medium for generating synthetic data are described. Improved data models for databases may be achieved by improving the quality of synthetic data upon for modeling those databases. According to some aspects, these and other benefits may be achieved by using numeric distribution information in a schema describing one or more numeric fields and, based on that schema, distribution-appropriate numerical data may be generated. The schema may be compared against actual data and the schema adjusted to more closely match the actual data. In implementation, this may be effected by storing a schema with distribution information and/or one or more parameters, generating synthetic numerical data based on the schema, and, based on a comparison with actual data, modify the schema until the synthetic data is statistically similar to the actual data. A benefit may include improved database performance and indexing based on repeatable, statistically appropriate, synthetic data.
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06F 16/215 - Amélioration de la qualité des données; Nettoyage des données, p.ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
21.
COMPUTER-BASED SYSTEMS UTILIZING SPEECH PATTERN RECOGNITION MACHINE LEARNING MODELS AND METHODS OF USE THEREOF
A method receiving at least one transcribed speech file of at least one person; identifying a plurality of utterance-delimited multiword units in the at least one transcribed speech file; generating a plurality of utterance-based data vectors corresponding to the plurality of utterance-delimited multiword units by assigning a numerical data token to each word in each utterance-delimited multiword unit; determining at least one utterance-delimited multiword unit from the plurality of utterance-delimited multiword units having question-indicative word patterns by inputting the plurality of utterance-based data vectors into at least one machine learning model, configured to identify the question-indicative word patterns by computing a probability of a word or groups of words in each of the plurality of utterance-delimited multiword units; and identifying at least one question in the at least one transcribed speech file of the speech of the at least one person using the question-indicative word patterns.
G10L 15/06 - Création de gabarits de référence; Entraînement des systèmes de reconnaissance de la parole, p.ex. adaptation aux caractéristiques de la voix du locuteur
G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p.ex. dialogue homme-machine
Provided are approaches for customizing transaction cards using a pressure sensitive modification area. In some approaches, a transaction card may include a body having a first main side opposite a second main side, wherein a chip is coupled to the first main side of the body, wherein a first outer layer extends along the first main side, and wherein a second outer layer extends along the second main side. The transaction card may further include an internal layer between the first and second outer layers, and a plurality of microspheres and a pigmented substance positioned between the internal layer and the first outer layer.
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
B32B 5/16 - Produits stratifiés caractérisés par l'hétérogénéité ou la structure physique d'une des couches caractérisés par le fait qu'une des couches est formée de particules, p.ex. de copeaux, de fibres hachées, de poudre
B32B 5/22 - Produits stratifiés caractérisés par l'hétérogénéité ou la structure physique d'une des couches caractérisés par la présence de plusieurs couches qui comportent des fibres, filaments, grains ou poudre, ou qui sont sous forme de mousse ou essentiellement poreuses
23.
Methods and arrangements for a payment instrument with a unique design
A payment instrument comprising a bottom layer; one or more intermediate layers, wherein at least one of the one or more intermediate layers comprises: a chip comprising a processor and memory; an antenna coupled with the chip; an absorbent medium; and one or more reservoirs comprising beads, each of the beads comprising dyes of one or more colors, the beads configured to release the dyes onto the absorption medium. The dyes cure on the absorption medium at a rate based on a curing agent applied to the absorbent medium or included in beads of the reservoirs. The payment instrument may also comprise a top layer having at least a partially translucent portion above the absorption medium, wherein the absorption medium is at least partially visible through the at least one partially translucent portion.
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 20/20 - Systèmes de réseaux présents sur les points de vente
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 magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
24.
SYSTEMS AND METHODS FOR DETERMINING FINANCIAL SECURITY RISKS USING SELF-SUPERVISED NATURAL LANGUAGE EXTRACTION
Systems and methods for dynamic detection of security features based on self-supervised natural language extraction from unstructured data sets are disclosed. The system may receive an unstructured data array including a full text of financial narrative. The system may serialize the unstructured data array to form one or more first data arrays including portions of the full text as discrete financial risk narratives. The system may build a tokenization dictionary and determine condensed summaries for each portion of the full text. The system may determine a relevancy score and a sentiment score for each condensed summary and calculate an overall relevancy score as a weighted average of the relevancy score and the sentiment score. When the overall risk score exceeds a predetermined threshold, the system may execute one or more security actions.
Methods and systems are also described for an integrated cyber incident management system that may store native data corresponding to fields of cyber incident management system (or other non-integrated systems) and integration data (e.g., viewable through a user interface of the integrated cyber incident management system), which describes a relationship of the native data to the integrated cyber incident management system, at a structure node in the architecture of the integrated cyber incident management system. The structure node may correspond to the convergence of two structures in the architecture of the integrated cyber incident management system. Each structure may itself correspond to a native hierarchal relationship in a non-integrated cyber incident management system.
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 16/22 - Indexation; Structures de données à cet effet; Structures de stockage
A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform steps of a method. The system may receive an authentication request from a computing device and determine whether the authentication request corresponds with stored authentication data. Based on the determination, the system may store identification data associated with a smart device corresponding to the authentication request. The system may receive detection data when the smart device is detected within a predetermined area and, in response to a detection, obtain an identifier from the smart device. The system may determine whether the obtained identifier corresponds with the stored identification data. Based on the determination, the system may direct an electronic lock to transition from a locked state to an unlocked state.
G07C 9/00 - Enregistrement de l’entrée ou de la sortie d'une entité isolée
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 magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G07C 9/21 - Enregistrement de l’entrée ou de la sortie d'une entité isolée comportant l’utilisation d’un laissez-passer muni d’un code d’accès variable
G07C 9/27 - Enregistrement de l’entrée ou de la sortie d'une entité isolée comportant l’utilisation d’un laissez-passer une station centrale gérant l’enregistrement
G07F 17/14 - Appareils déclenchés par pièces de monnaie pour la location d'articles; Installations ou services déclenchés par pièces de monnaie pour tourniquets
In some implementations, a device may receive an indication of information associated with a stored value medium. The device may populate a database with the information associated with the stored value medium, where the database includes a table to link the information associated with the stored value medium with an entity identifier of an entity associated with the stored value medium. The device may receive an indication of an exchange associated with the entity identifier of the entity, where the exchange is not associated with the stored value medium. The device may parse the database using the entity identifier associated with the entity to identify the information associated with the stored value medium indicated in the database. The device may communicate, with a backend system, to enable the exchange to be at least partially completed using the resources associated with the stored value medium.
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
28.
Third Party Data Processing for Improvement of Authentication Questions
Methods, systems, and apparatuses are described herein for improving the accuracy of synthetic authentication questions by analyzing third party account data. A request for access to a first account associated with a user may be received. The first account may be managed by a first organization. A transactions database might be queried for first account data. Second account data corresponding to a second account associated with the user might be received. That second account may be managed by a second organization different from the first organization. One or more second transactions, unique to the second account, may be identified. A synthetic transaction, configured to be different from transactions in the first account and the one or more second transactions, may be generated. An authentication question may be generated based on the synthetic transaction. Access to the first account might be provided based on a response to the authentication question.
Methods and systems for parallel processing of batch communications during data validation using a plurality of independent processing streams. For example, the system may receive a plurality of communications for batch processing during a predetermined time period. The system may process, with a batch configuration file, a first alphanumeric data string of a first communication of the plurality of communications. The system may process, with the batch configuration file, a second alphanumeric data string of a second communication of the plurality of communications. The system may direct the first communication to a first micro-batch for processing within the predetermined time period based on the first metadata tag, wherein the first micro-batch is processed using a first validation and enrichment protocol and a first micro-batch configuration file, wherein the first validation and enrichment protocol and the first micro-batch configuration file are specific to the first source.
In some implementations, an edge device may receive a request from a client application indicating one or more search parameters associated with one or more search queries. The edge device may determine an identity of the client application and a type of the request based on the one or more search parameters. The edge device may selectively either cache metadata associated with search results for the one or more search queries or cache the search results, based on the identity of the client application and the type of the request. Accordingly, the edge device may deliver the cached metadata or at least a portion of the cached search results to the client application.
Machine classifiers in accordance with embodiments of the invention capture long-term temporal dependencies in the dialogue data better than the existing RNN-based architectures. Additionally, machine classifiers may model the joint distribution of the context and response as opposed to the conditional distribution of the response given the context as employed in sequence-to-sequence frameworks. Machine classifiers in accordance with embodiments further append random paddings before and/or after the input data to reduce the syntactic redundancy in the input data, thereby improving the performance of the machine classifiers for a variety of dialogue-related tasks. The random padding of the input data may further provide regularization during the training of the machine classifier and/or reduce exposure bias. In a variety of embodiments, the input data may be encoded based on subword tokenization.
G06F 18/21 - Conception ou mise en place de systèmes ou de techniques; Extraction de caractéristiques dans l'espace des caractéristiques; Séparation aveugle de sources
G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
G06F 40/284 - Analyse lexicale, p.ex. segmentation en unités ou cooccurrence
G06F 40/35 - Représentation du discours ou du dialogue
G10L 15/06 - Création de gabarits de référence; Entraînement des systèmes de reconnaissance de la parole, p.ex. adaptation aux caractéristiques de la voix du locuteur
G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p.ex. dialogue homme-machine
32.
BIOMETRIC VERIFICATION FOR MANAGING ACCESS TO A CARD
A fingerprint sensor of a contactless card may receive input. A processor of the contactless card may compare the input to a fingerprint template stored in a memory of the contactless card. The processor may determine that the comparison results in a match and enable a near-field communication (NFC) antenna of the contactless card based on the determination that the comparison results in the match.
G06F 21/32 - Authentification de l’utilisateur par données biométriques, p.ex. empreintes digitales, balayages de l’iris ou empreintes vocales
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 20/38 - Architectures, 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 magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06T 1/00 - Traitement de données d'image, d'application générale
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Disclosed herein are system, method, and computer program product embodiments for creating a personalized visual code for completing a transaction at an Automated Teller Machine (ATM). An embodiment operates by receiving a request to complete a transaction from a mobile application on a user device, pairing the transaction with an ATM, retrieving information unique to the user, generating a personalized visual code based on the information unique to the user, and generating a rule for presenting the personalized visual code on the ATM, the rule including at least one of: i) when the personalized visual code should be presented, ii) how long the personalized visual code is to be presented, or iii) how the personalized visual code should move when presented on the ATM.
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de banque à domicile
G07F 19/00 - Systèmes bancaires complets; Dispositions à déclenchement par carte codée adaptées pour délivrer ou recevoir des espèces ou analogues et adresser de telles transactions à des comptes existants, p.ex. guichets automatiques
A device for conducting a transaction by generating and displaying QR codes in the infrared spectrum, by generating a first QR code; displaying the first QR code via the infrared array for a predetermined duration of time; receiving a confirmation that a user device has entered paired state with the transaction device based on the user device scanning the first QR code; receiving authentication data indicating that the paired user device is authorized to complete the transaction; completing the transaction.
A computer-implemented method of fraud protection is described. A server may receive one or more keywords and a likelihood of fraud from an external source. The server may receive an image of a document from a user device, wherein the document comprises at least one of a written communication or a printed communication. The server may extract text from the image of the document, compare the extracted text to the one or more stored keywords, and calculate a confidence level of fraud. The server may send an indication of the confidence level of fraud to the user device.
Cards having a hybrid construction including a biodegradable portion and related methods are disclosed. A card can include a card body having a top surface and a bottom surface opposite the top surface, the top and bottom surfaces meeting at a peripheral edge of the card body; and a first portion secured to a second portion such that the top surface of the card body spans both the first and second portions and the bottom surface is formed entirely of the second portion. The card can further include a chip secured to the first portion of the card body; wherein the peripheral edge includes at least an insertion edge of the first portion; wherein the second portion of the card body comprises a biodegradable material; and wherein the first portion and a recyclable portion meet at a frangible junction on the top surface of the card body.
G06K 19/02 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par l'utilisation de matériaux spécifiés, p.ex. pour éviter l'usure pendant le transport à travers la machine
G06K 19/077 - Supports d'enregistrement avec des marques conductrices, des circuits imprimés ou des éléments de circuit à semi-conducteurs, p.ex. cartes d'identité ou cartes de crédit avec des puces à circuit intégré - Détails de structure, p.ex. montage de circuits dans le support
37.
SYSTEMS AND METHODS FOR CONTACTLESS AND SECURE DATA TRANSFER
In one embodiment, a method comprises receiving a unique identifier from an item and sending a communication to an electronic device requesting that a user confirm a pending transaction, receiving input from the electronic device associated, and sending the received input to an authentication system for completing a transaction. In another embodiment, a system comprises a sensor, an authentication system, and a transaction processing system. The sensor is configured to emit energy and receive at least one first identifier, send at least one communication to an electronic device requesting a second identifier, receive at least one second identifier, and send the at least one first identifier and the at least one second identifier to the authentication system.
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 magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/42 - Confirmation, p.ex. contrôle ou autorisation de paiement par le débiteur légal
38.
MONITORING MACHINE LEARNING MODELS USING SURROGATE MODEL OUTPUT
In some aspects, a computing system may use a surrogate machine learning model to detect whether a production or other machine learning model has a tendency to generate different output depending on which subpopulation a particular sample belongs to. The surrogate machine learning model may be trained using features/outputs that are not included in the data used by the production model. For example, by using demographic information in lieu of the original labels of a dataset that was used to train a production model, a surrogate model may be used to detect whether the production model is able to discern one or more characteristics associated with but not present in a sample using other features of the dataset. Output of the surrogate machine learning model may be clustered to detect whether certain subpopulations are treated differently by the production model.
Systems and methods for generating real-time location-based notifications are described. In some aspects, the system receives a recurring user activity that is recurring at a previous location during a recurring time period. Based on detecting that a current location of the user is in proximity of the previous location during an instance of the recurring time period, the system determines whether any user activity was executed while the user is present at the current location. Based on determining that a current user activity was executed by the user different from the recurring user activity, the system determines whether the current user activity is a substitute for an instance of the recurring user activity. The system updates a measure of elasticity of the recurring user activity based on determining that the current user activity is a substitute for the instance of the recurring user activity.
Provided are approaches for concealing or obscuring transaction card numbers. In some approaches, a transaction card may include a body comprising a first main side opposite a second main side, and a plurality of structures extending from at least one of the first or second main sides. In a bent configuration of the body, the plurality of structures separate from one another, in a substantially flat configuration of the body, adjacent structures of the plurality of structures abut one another.
G06K 19/07 - Supports d'enregistrement avec des marques conductrices, des circuits imprimés ou des éléments de circuit à semi-conducteurs, p.ex. cartes d'identité ou cartes de crédit avec des puces à circuit intégré
B42D 25/30 - Caractéristiques d’identification ou de sécurité, p.ex. pour empêcher la falsification
41.
RESTRICTIVE ENDORSEMENT DETECTION AND MERGER DURING UPLOAD PROCESS
Systems for performing endorsement-based techniques on document during a document upload process are disclosed. During the document upload process, a document upload application may determine whether an endorsement is required on the document to be uploaded, the type of endorsement that is required, and whether the required endorsement is present on the document. Upon determining that an endorsement is required but is missing from the document, document upload application may retrieve and merge the required endorsement with the document as part of the document upload process.
G06V 10/94 - Architectures logicielles ou matérielles spécialement adaptées à la compréhension d’images ou de vidéos
G06V 10/26 - Segmentation de formes dans le champ d’image; Découpage ou fusion d’éléments d’image visant à établir la région de motif, p.ex. techniques de regroupement; Détection d’occlusion
G06V 30/226 - Reconnaissance de caractères caractérisés par le type d’écriture de l’écriture cursive
G06V 30/262 - Techniques de post-traitement, p.ex. correction des résultats de la reconnaissance utilisant l’analyse contextuelle, p.ex. le contexte lexical, syntaxique ou sémantique
42.
SYSTEM AND METHOD FOR INCORPORATING RISK RELATED TOPICS INTO CHATBOT FUNCTIONALITY
A system and method employs a chatbot into which a user can input an inquiry/question regarding a risk related topic is disclosed. The user can obtain an answer to the inquiry. The system and method can receive, via a chatbot interface, an inquiry. An intent of the inquiry can be determined using a natural language processing (NLP) model. The inquiry can be matched, using a classifier, to a related data set based on the determined intent. An output can be generated based on the related data set in response to the inquiry. The output can be transmitted for display on the chatbot interface.
G06F 40/35 - Représentation du discours ou du dialogue
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 comport
G06F 3/04842 - Sélection des objets affichés ou des éléments de texte affichés
G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
43.
USING TOKENS FROM PUSH NOTIFICATION PROVIDERS TO ENHANCE DEVICE FINGERPRINTING
Embodiments disclosed are directed to a system that performs steps to perform enhanced device fingerprinting. The system at least at receives from an application, a plurality of device attributes identifying a client device on which the application is being used. The plurality of device attributes includes a push token provided by a push token service to the client device. The push token is uniquely paired to the client device. The system further transmits, to a device database, the plurality of device attributes for storage in a device profile. The system also transmits, to the application, a push notification based on the push token. The system receives, from the application, a deliverable status indicating whether the push notification was successfully transmitted to the client device, and transmits, to a notification database, the deliverable status for storage in a notification delivery profile. The system can use the information to authenticate a device.
A system may receive, via a web browser plugin on a user device, a first timestamp associated with first click data at a website associated with a merchant, a referring uniform resource location (URL), a current URL, and first user identification data. The system may also receive transaction data including a second timestamp, second user identification data, and a first merchant name associated with a transaction with the merchant. The system may determine whether the first timestamp is within a predetermined period of the second timestamp and determine whether the first user identification data corresponds with the second user identification data. When the system determines that the first timestamp is within the predetermined period of the second timestamp and the first user identification data corresponds with the second user identification data, the system may store the referring URL and the current URL with the first merchant name in a database.
G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p.ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
45.
CROWDSOURCED ANNOTATION AND TAGGING SYSTEM FOR DIGITAL TRANSACTIONS
A system for crowdsourcing annotations for transactions includes a crowdsourcing annotation database and a processor. The database stores crowdsourced annotations associated with merchants. The crowdsourced annotations are shared among, and contributed by, users of a community. The processor receives transaction data for a transaction by a user with a merchant. Relevant crowdsourced annotations associated with the merchant are retrieved from the database and sent to the user to enable to the user to annotate the transaction. The user provides an annotation for the transaction. The system dynamically updates the database based on the annotation provided by the user.
A transaction card includes a near-field communication (NFC) component, a security component, a wireless component, one or more memories, and one or more processors communicatively coupled to the one or more memories. The device receives a signal from a user device attempting to access a secure application, and energizes the NFC component based on the signal received from the user device. The device causes the security component to generate an encrypted code based on the NFC component being energized, and provides, via the security component, the encrypted code to the wireless component. The device provides, via the wireless component, the encrypted code to the user device to permit the user device to utilize the encrypted code as authentication for accessing the secure application.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
G06F 21/35 - Authentification de l’utilisateur impliquant l’utilisation de dispositifs externes supplémentaires, p.ex. clés électroniques ou cartes à puce intelligentes communiquant sans fils
G06Q 20/10 - Architectures 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 40/02 - Opérations bancaires, p.ex. calcul d'intérêts ou tenue de compte
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
A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform steps of a method for providing an interactive virtual environment. The system may receive environmental data, and augment the environmental data by adding virtual environmental data. The system may then provide this virtual environment to two or more devices. The system can then receive user input, and modify the virtual environment in response to those inputs.
The present disclosure describes image analysis techniques that identify the source of a document. Once the source of the document is determined, the image analysis may locate one or more anchor fields in the document. The anchor fields may identify one or more additional fields that contain time-sensitive data and/or information. The image analysis performed herein may identify the time-sensitive data and/or information and process the data and/or information to schedule due dates and reminders.
G06V 30/413 - Classification de contenu, p.ex. de textes, de photographies ou de tableaux
G06F 18/21 - Conception ou mise en place de systèmes ou de techniques; Extraction de caractéristiques dans l'espace des caractéristiques; Séparation aveugle de sources
G06V 10/40 - Extraction de caractéristiques d’images ou de vidéos
G06V 30/412 - Analyse de mise en page de documents structurés avec des lignes imprimées ou des zones de saisie, p.ex. de formulaires ou de tableaux d’entreprise
49.
SYSTEMS AND METHODS FOR DETERMINING SOFTWARE PARITY
Systems and methods for determining that a new software program is in parity with a legacy software program. In some aspects, the system receives information for multiple threads processed by a legacy software program. The system processes the information using the new software program, which is executed in parallel with the legacy software program. If an output of a particular thread from the new software program varies outside a threshold distance from a corresponding output for the thread from the legacy software program, the system ceases further processing of the particular thread by the new software program. Otherwise, the system allows processing of the particular thread by the new software program to continue.
Systems and methods for determining a difference in performance for a software program processing input data for multiple threads based on different termination time periods for handling an exception. In some aspects, the system receives input data and corresponding performance data for multiple threads with respect to a first termination time period for terminating the thread when an exception is detected. The system processes the input data to generate corresponding performance data for the multiple threads with respect to a second termination time period for terminating the thread when the exception is detected. The system determines a difference in performance for a particular thread based on performance data with respect to the first termination time period and corresponding performance data with respect to the second termination time period.
Systems and methods for migrating data from a legacy software program to a new software program. In some aspects, the system captures a snapshot of the current state of static data for multiple threads from the legacy software program. The system processes the static data for the multiple threads using the new software program to generate dynamic data for a period of time. During the same period of time, the legacy software program also produces dynamic data for the multiple threads. If there is a mismatch between dynamic data from the new and legacy software programs for at least one thread, the system generates metadata for the at least one thread to supplement static data for the at least one thread for processing by the new software program.
Systems and methods for transforming data for a batch-based legacy software program into data suitable for processing by a streaming-based new software program. In some aspects, the system generates an information stream for multiple threads from batch information received from the legacy software program. The system processes the information stream for the multiple threads using the new software program. If there is a mismatch between outputs of the legacy and new software programs for at least one thread, the system adjusts a data model of the new software program to address the mismatch and generates an updated information stream for processing by the new software program.
Methods and systems are described herein for identifying performance degradation in machine learning models based on comparisons of actual and predicted results. The system may receive predicted and actual results datasets for features within a system with the predicted results being generated by a machine learning model corresponding to the feature. The system may access a hierarchy associated with the features and select a level of the hierarchy having a subset of features. The subset of features may be associated with a target feature. Impact values may then be generated for the subset, where the impact values indicate contributions of the corresponding features to a difference, in the target feature, between predicted and actual results. The system may select a new target feature, from the subset, associated with a highest impact value and may retrain a machine learning model associated with the new target feature.
Methods and systems are described herein for leveraging artificial intelligence to sanitize sensitive data and prevent the data from leaving the mobile device and/or be exposed to unauthorized third parties. More specifically, methods and systems are described for a novel and unconventional architecture for a data sanitization application, a novel and unconventional delivery format for the data sanitization model, and a novel and unconventional output format of the data sanitization model.
Methods and systems are described herein for authorizing limited user access to resources of other users using NFTs. A resource access system may be used to authorize access. The system may receive a first request for performing an action using a resource associated with a first user, and in response to the first request, obtain an encrypted payload from a blockchain node of a blockchain. The system may transmit a command to the second device to decrypt the encrypted payload using the second cryptography-based storage application and receive the access token and the one or more access parameters from the second device. In response to determining that metadata of the first request matches the one or more access parameters of the access token, the system may transmit a request to perform the action.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Systems and methods for executing sequential suboperations over multiple communication networks. In some aspects, the system receives, via a first communication network, from an external system, an operation related to an aggregated virtual container. The system generates sequential suboperations including a first suboperation associated with a provider of the aggregated virtual container and the external system and a second suboperation associated with the user and the provider of the aggregated virtual container. If the first suboperation is executed successfully, the system transmits the second suboperation to a user system associated with the aggregated virtual container. If the second suboperation is executed successfully, the system generates a first message indicating that the operation has been executed and transmits the first message via the first communication network to the external system.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
57.
SYSTEMS AND METHODS FOR ADJUSTING DATA PROCESSING COMPONENTS FOR NON-OPERATIONAL TARGETS
Systems and methods for adjusting data processing components. In some aspects, the systems and methods include training a first machine learning model using a similarity graph generated based on training entries to predict whether a target system related to a node in the similarity graph will be non-operational within a future period of time, processing using the trained first machine learning model an updated similarity graph generated based on training and inference entries to predict for each node for the inference entries whether a target system related to the node will be non-operational within the future period of time, processing using a second machine learning model predictions and associated inference entries to predict that a target system related to a node for an entry will be non-operational within the future period of time, and adjusting data processing components related to the target system.
G06N 3/063 - Réalisation physique, c. à d. mise en œuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurone utilisant des moyens électroniques
G06N 20/20 - Techniques d’ensemble en apprentissage automatique
Disclosed herein are system, method, and computer program product embodiments for generating an alert to a user for a change between weather conditions. An application can be operated by a processor to perform operations include determining a first weather condition at a geographic location at a first time when a user of the device enters a structure located within the geographic location. In addition, the operations can include, based on information received from the server, predicting a second weather condition at the geographic location at a second time while the user remains in the structure. Afterwards, the operations can include alerting the user for a change between the first and second weather conditions.
H04W 4/90 - Services pour gérer les situations d’urgence ou dangereuses, p.ex. systèmes d’alerte aux séismes et aux tsunamis
G01W 1/02 - Instruments pour indiquer des conditions atmosphériques par mesure de plusieurs variables, p.ex. humidité, pression, température, nébulosité ou vitesse du vent
G01W 1/10 - Dispositifs pour la prévision des conditions météorologiques
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 4/12 - Messagerie; Boîtes aux lettres; Annonces
Disclosed embodiments may include a system for data monitoring. The system may receive data associated with a user. The system may determine a rating corresponding to the user based on the received data. The system may dynamically generate a score by aggregating the rating and a respective second rating of additional user(s). The system may determine whether the score satisfies a first threshold. Responsive to determining the score satisfies the first threshold, the system may cause a user device to display, via a GUI, the score in a first format. Responsive to determining the score does not satisfy the first threshold, the system may determine whether the score satisfies a second threshold. Responsive to determining the score satisfies the second threshold, the system may generate a first modified GUI comprising the score in a second format, and may cause the user device to display the first modified GUI.
G06Q 40/02 - Opérations bancaires, p.ex. calcul d'intérêts ou tenue de compte
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 comport
Methods, systems, devices, and computer-readable media for a payment delegation and linking system are provided. The system may generate a delegation request to send to an individual for payment of a portion of a value of a transaction. The delegation request may be sent to the individual with a payment URL embedded with a token. Upon initiation of payment in response to the delegation request, the token may be embedded in an unused field of a payment transaction record generated at the individual's device and may be transmitted from the individual's device to a payment processing system for processing and settlement. The payment transaction record may ultimately be received at the requestor's bank with the token intact. The token may be used to link the received payment transaction with the original delegated transaction. The original delegated transaction and the received payment transaction may be displayed together in a transaction summary.
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 20/38 - Architectures, 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 magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
61.
WIRELESS DEVICES FOR STORING A FINANCIAL ACCOUNT CARD AND METHODS FOR STORING CARD DATA IN A WIRELESS DEVICE
A non-transitory computer-readable medium stores instructions causing a processor to generate a menu displaying representations of a plurality of cards, the cards having associated card data; receive, from a user input device, a selection corresponding to a selected one of the cards; update the menu to display a representation of the selection; and authorize transmission of the card data associated with the selected card to complete a transaction.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06K 7/08 - Méthodes ou dispositions pour la lecture de supports d'enregistrement avec des moyens de perception des modifications d'un champ électrostatique ou magnétique, p.ex. par perception des modifications de la capacité entre des électrodes
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
G06K 19/08 - 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 utilisant des marquages de différentes sortes sur le même support d'enregistrement, p.ex. un marquage étant lu optiquement et l'autre par des moyens magnétiques
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
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
G07C 9/25 - Enregistrement de l’entrée ou de la sortie d'une entité isolée comportant l’utilisation d’un laissez-passer combiné à une vérification d’identité du titulaire du laissez-passer utilisant des données biométriques, p.ex. des empreintes digitales, un balayage de l’iris ou une reconnaissance de la voix
62.
SYSTEMS AND METHODS FOR IMAGE DATA PROCESSING TO CORRECT DOCUMENT DEFORMATIONS USING MACHINE LEARNING SYSTEM
Systems and methods for processing image data representing a document to remove deformations contained in the document are disclosed. A system may include one or more memory devices storing instructions and one or more processors configured to execute the instructions. The instructions may instruct the system to provide, to a machine learning system, a training dataset representing a plurality of documents containing a plurality of training deformations. The instructions may also instruct the system to use the machine learning system to process image data representing a target document containing a target document deformation. The machine learning system may generate restored image data representing the target document with the target document deformation removed. The instructions may further instruct the system to provide the restored image data to at least one of a graphical user interface, an image storage device, or a computer vision system.
G06F 18/213 - Extraction de caractéristiques, p.ex. en transformant l'espace des caractéristiques; Synthétisations; Mappages, p.ex. procédés de sous-espace
G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
G06T 7/194 - Découpage; Détection de bords impliquant une segmentation premier plan-arrière-plan
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 30/19 - Reconnaissance utilisant des moyens électroniques
G06V 30/40 - Reconnaissance des formes à partir d’images axée sur les documents
G06V 30/412 - Analyse de mise en page de documents structurés avec des lignes imprimées ou des zones de saisie, p.ex. de formulaires ou de tableaux d’entreprise
G06V 30/414 - Extraction de la structure géométrique, p.ex. arborescence; Découpage en blocs, p.ex. boîtes englobantes pour les éléments graphiques ou textuels
63.
FACILITATING RESPONDING TO MULTIPLE PRODUCT OR SERVICE REVIEWS ASSOCIATED WITH MULTIPLE SOURCES
A monitoring platform may obtain information that identifies a product or service and may collect one or more reviews associated with the product or service from a plurality of sources, wherein each review includes respective review information. The monitoring platform may process the one or more reviews to determine respective additional review information associated with each review of the one or more reviews. The monitoring platform may select, using a machine learning model, a particular review, of the one or more reviews, based on the review information and the additional review information associated with the one or more reviews. The monitoring platform may cause display, on a display of a client device, of a prompt for a response to the particular review and may obtain the response from the client device. The monitoring platform may cause the response to be posted to a source associated with the particular review.
A system may receive first level authentication data from a first user, authorize first level access to a secure device, and transmit a push notification including a second factor authentication key to a first user device responsive to first factor authentication data matching stored authentication data for the first user. The system may receive a wireless communication from the first user device attenuated by one or more beam attenuating materials to form a first attenuated beam profile. In response to a match of the first attenuated beam profile to a stored beam profile beyond a predetermined threshold, the system may associate the second factor authentication key as an authorized login credential for the first user. The system may receive the second factor authentication key from the first user and authorize the second factor authentication data to grant the first user second level access to the secure device.
In some implementations, a terminal device may obtain exchange information associated with an exchange initiated at the terminal device. The exchange information may identify a medium used in the exchange. The terminal device may be configured to present a terminal-side user interface for performing a signing operation of the exchange. The terminal device may selectively obtain user information associated with the medium used in the exchange. The user information may identify a user device associated with the medium. The terminal device may transmit, to the user device and based on obtaining the user information, presentation information that identifies content for a user-side user interface for performing the signing operation at the user device. The terminal device may receive, from the user device, signing information associated with a performance of the signing operation at the user device via the user-side user interface.
Aspects described herein may relate to methods, systems, and apparatuses for generating synthetic data based on time series predictions and plural machine learning models. Generating the synthetic data may include receiving one or more data records that include transaction data of a user, categorizing and/or segmenting the one or more data records, determining a first predicted time step based on the categorizing and/or segmenting, and performing an iterative process that determines further predicted time steps. The first predicted time step may be determined using one model of a plurality of machine learning models. The iterative process may determine the further predicted time steps using the plural machine learning models. Based on iterations of the iterative process, potential time series may be determined. The synthetic time series may be determined from the potential time series. The synthetic time series may be used by additional processes, such as additional machine-learning processes.
Methods and systems are described herein for leveraging artificial intelligence to sanitize sensitive data and prevent the data from leaving the mobile device and/or be exposed to unauthorized third parties. More specifically, methods and systems are described for a novel and unconventional architecture for a data sanitization application, a novel and unconventional delivery format for the data sanitization model, and a novel and unconventional output format of the data sanitization model.
Methods and systems are described herein for leveraging artificial intelligence to sanitize sensitive data and prevent the data from leaving the mobile device and/or be exposed to unauthorized third parties. More specifically, methods and systems are described for a novel and unconventional architecture for a data sanitization application, a novel and unconventional delivery format for the data sanitization model, and a novel and unconventional output format of the data sanitization model.
In some aspects, a computing system may aggregating multiple counterfactual samples so that machine learning explanations can be generated for sub-populations. In addition, methods and systems described herein use machine learning and counterfactual samples to determine text to use in an explanation for a model's prediction. A computing system may also train machine learning models to not only determine whether a request to perform an action should be accepted, but also to generate output that is consistent with output generated by previous machine learning models. Further, a computing system may generate counterfactual samples based on user preferences. A computing system may obtain preferences and then apply a penalty or adjustment parameter such that when a counterfactual sample is created, the computing system is forced to change one or more features indicated by the preferences to create the counterfactual sample.
In some aspects, a computing system may aggregating multiple counterfactual samples so that machine learning explanations can be generated for sub-populations. In addition, methods and systems described herein use machine learning and counterfactual samples to determine text to use in an explanation for a model's prediction. A computing system may also train machine learning models to not only determine whether a request to perform an action should be accepted, but also to generate output that is consistent with output generated by previous machine learning models. Further, a computing system may generate counterfactual samples based on user preferences. A computing system may obtain preferences and then apply a penalty or adjustment parameter such that when a counterfactual sample is created, the computing system is forced to change one or more features indicated by the preferences to create the counterfactual sample.
In some aspects, a computing system may aggregating multiple counterfactual samples so that machine learning explanations can be generated for sub-populations. In addition, methods and systems described herein use machine learning and counterfactual samples to determine text to use in an explanation for a model's prediction. A computing system may also train machine learning models to not only determine whether a request to perform an action should be accepted, but also to generate output that is consistent with output generated by previous machine learning models. Further, a computing system may generate counterfactual samples based on user preferences. A computing system may obtain preferences and then apply a penalty or adjustment parameter such that when a counterfactual sample is created, the computing system is forced to change one or more features indicated by the preferences to create the counterfactual sample.
Methods and systems for uses and/or improvements to blockchain technology. In particular, the methods and systems described herein implement a novel cryptographic resource standard that provides functionality for complex communications. The novel cryptographic resource standard allows for blockchain functions that may involve single cryptographic resource transfers or batch cryptographic resource transfers as well as on-chain batching of one or more cryptographic resources.
Methods and systems for uses and/or improvements to blockchain technology. In particular, the methods and systems described herein implement a novel cryptographic resource standard that provides functionality for complex communications. The novel cryptographic resource standard allows for blockchain functions that may involve single cryptographic resource transfers or batch cryptographic resource transfers as well as on-chain batching of one or more cryptographic resources.
Systems and methods for executing sequential suboperations at an aggregated virtual container provider system. In some aspects, based on an operation related to an aggregated virtual container, the system generates sequential suboperations including a first suboperation associated with a provider of the aggregated virtual container and an external system and a second suboperation associated with a user of the aggregated virtual container and the provider of the aggregated virtual container. If the first suboperation is executed successfully, the system selects a token from a plurality of tokens connected to the aggregated virtual container and transmits, to a user system associated with the selected token. If the second suboperation is executed successfully, the system generates a first message that the operation has been executed and transmits the first message to the external system.
G06F 9/455 - Dispositions pour exécuter des programmes spécifiques Émulation; Interprétation; Simulation de logiciel, p.ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
75.
SYSTEMS AND METHODS FOR SUCCESSIVELY EXECUTING AN OPERATION OVER MULTIPLE COMMUNICATION NETWORKS
Systems and methods for successively executing an operation over multiple communication networks. In some aspects, the system obtains first access information received from a physical token and generates an operation related to an aggregated virtual container. The system determines a first communication network from the first access information and transmits, via the first communication network, the operation associated with the aggregated virtual container. If the operation was not transmitted successfully via the first communication network, the system obtains second access information received from the physical token, determines a second communication network from the second access information, and transmits, via the second communication network, the operation associated with the aggregated virtual container. If the operation was transmitted successfully via the second communication network, the system generates for display a notification that the operation has been executed.
G06F 12/14 - Protection contre l'utilisation non autorisée de mémoire
76.
COMPUTER-BASED SYSTEMS AND/OR COMPUTING DEVICES CONFIGURED FOR ORCHESTRATION OF ANONYMOUS BACKEND COMMUNICATIONS BETWEEN DEVICES AND MAINTAINING/UPDATING SIMULATION STATES AND METHODS OF USE THEREOF
A method includes determining a first state of a simulation being run by a system and sending first data indicative of the first state of the simulation to a first computing device. The method further includes receiving, after the first data is sent, second data from the first computing device. The second data includes at least one first instruction configured to cause a first move associated with the simulation and is formatted according to a specification. The method further includes determining a second state of the simulation based on the second data received from the first computing device and sending third data indicative of the second state of the simulation to a second computing device. The method further includes receiving, after sending the third data, fourth data from the second computing device. The fourth data includes at least one second instruction configured to cause a second move.
Systems and methods for providing stream-based database alteration architecture are disclosed. The systems and methods can receive a plurality of client tracking identification numbers in a data stream from a database via a communication network, wherein the plurality of client tracking identification numbers comprises customer metadata. The received plurality of client tracking identification numbers is assigned to one or more virtual consumer processors for encrypting or decrypting a client record associated with each of the plurality of received client tracking identification numbers. The client record associated with each of the received plurality of client tracking identification numbers is encrypted or decrypted. A database is updated to indicate the client record associated with each of the received plurality of client tracking identification numbers is encrypted or decrypted using the assigned one or more virtual consumer processors.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet
Systems and methods for predicting change points in tabular data. In some aspects, the systems and methods provide for generating time-stamped graphs based on data entries and corresponding time stamps. Each graph of the time-stamped graphs corresponds to a data entry and is representative of one or more events associated with a time stamp corresponding to the data entry. The graph is independent of any events before or after the time stamp. For each graph of the time-stamped graphs, a set of graph embeddings is generated based on the graph and processed using a machine learning model to predict an occurrence of a change point in the data entries.
Systems and methods for predicting differentiating features from tabular data for two different populations. In some aspects, the systems and methods provide for receiving first data entries and second data entries and generating a first graph based on a data entry from the first data entries and a second graph based on a data entry from the second data entries. A first node in the first graph is determined to correspond to a second node in the second graph. A first set of graph embeddings is generated based on the first graph. A second set of graph embeddings is generated based on the second graph. Using a machine learning model, the first set of graph embeddings and the second set of graph embeddings are processed to identify at least one feature indicative of a difference between the first data entries and the second data entries.
Systems and methods for authorizing a source for virtual certification number (VCN) use include receiving a VCN use request from an external entity, the VCN use request including the VCN and transaction data associated with the VCN use request, determining that a VCN binding for the VCN is a strict binding, mapping the transaction data to a transaction source having a transaction source identifier based on the VCN binding being the strict binding, determining a VCN source identifier for the source associated with the VCN, based on a registration authentication of the VCN with the source, comparing the VCN source identifier to the transaction source identifier, determining that the VCN source identifier corresponds to the transaction source identifier based on comparing the VCN source identifier to the transaction source identifier, outputting an approved authorization indicating that the VCN is associated with the source and the source is the transaction source.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06N 3/088 - Apprentissage non supervisé, p.ex. apprentissage compétitif
Computer-based systems and/or computing devices programmed for instant issuance of a replacement physical access instrument; and methods of use thereof
A computer-based method includes receiving an activity data associated with a user; where a first user activity profile of the activity data is associated with: a) a first profile identifier, and b) a first instrument, where the first instrument comprises a first security measure; receiving an authentication request to authenticate an identity of the user; generating a security challenge to identify the user; the security challenge being based on a second user activity profile of the activity data; receiving a security response to the a security challenge from an instrument generation module; the security response comprising a second profile identifier associated with a second instrument; authenticating the user based on the security response; generating a third profile identifier to replace the first profile identifier; instructing the instrument generation module to dispense a third instrument; where the third instrument includes: a) the third profile identifier, and b) a second security measure.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
83.
SYSTEMS AND METHODS FOR RECORDING MAJOR INCIDENT RESPONSE INFORMATION
A system for recordation and retrieval of incident resolution action information is provided. A recordation system processor is provided with a recordation application configured to receive a response action initiation instruction identifying an action taken to resolve an incident on a target system, The processor determines one or more responsible responders each having a responder data processor that displays a responder dashboard. The processor transmits a recordation instruction to the responder data processor of each responsible responder. The recordation instruction includes an instruction to begin recording responder dashboard information. The recordation application is also configured to receive a response action termination instruction and to transmit a recordation termination instruction to the responder data processor of each responsible responder. A data storage unit is configured for receiving, from the responder data processors, real-time responder dashboard information recordings.
Disclosed are a system and methods enabling updating of a card number of a payment card and thereby reissuing the payment card utilizing a reissue application associated with the payment card. The reissue application, when executed communicates with a service provider that manages the payment card. The payment card includes processing circuitry and a rewriteable visual display. Using cryptographic techniques, the reissue application and payment card are authenticated to the service provider. Upon verification, an updated card number is obtained and provided via near-field communication to the payment card. In response to the update payment card number received from the reissue application, the rewriteable visual display on the payment card is updated with the updated card number. Other information may also be presented on the rewriteable visual display of the payment card based on user preferences.
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 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
85.
SYSTEMS AND METHODS FOR PROVIDING A SEPARATE INTEREST RATE FOR AN INDIVIDUAL TRANSACTION
Systems and methods for providing a separate interest rate for an individual transaction are disclosed. A system may provide a service associated with a account having an account balance and an associated first interest rate. The system may include a service device having one or more memory devices storing instructions and one or more processors configured to execute the instructions to perform a separate interest rate service process. The process may include providing a separate interest rate service offer to a client device and receiving a separate interest rate selection from the client device. The process may also include determining a selected portion of the account balance corresponding to an amount to which a second interest rate, different from the first interest rate, is to be applied based on the separate interest rate selection.
System and devices for live captioning events is disclosed. The system may receive event calendar data and a first plurality of caption files and preselect a first caption file based on the event calendar data. The system may then access an audiovisual recorder of a user device, and receive a first feedback from the recorder. The system may then determine whether the first caption file matches the first feedback. When there is a match, the system may determine a first synchronization between the caption file and the feedback. When there is no match, the system may determine if there is a match with a second caption file of the first plurality of caption files and determine a second synchronization. When the second caption file does not match, the system may receive at least a third caption file over a mobile network and determine a third synchronization for display.
H04N 21/43 - Traitement de contenu ou données additionnelles, p.ex. démultiplexage de données additionnelles d'un flux vidéo numérique; Opérations élémentaires de client, p.ex. surveillance du réseau domestique ou synchronisation de l'horloge du décodeur; Intergiciel de client
87.
FRAUD DETECTION BASED ON AN ANALYSIS OF MESSAGES IN A MESSAGING ACCOUNT
A device may obtain a notification that a transaction occurred, where the transaction is associated with a financial account of a user, and a merchant. The device may determine that the merchant is associated with providing confirmation messages for transactions, and may process, based on determining that the merchant is associated with providing confirmation messages, one or more messages in a messaging account associated with the user to determine whether the messaging account includes a confirmation message associated with the transaction. The device may determine that the messaging account does not include any confirmation message associated with the transaction, may determine a likelihood that the transaction was unauthorized based on the messaging account not including a confirmation message, and may perform an action associated with the financial account of the user based on the likelihood that the transaction was unauthorized.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
A system for determining candidate answers during an interview. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include capturing, by an image sensor, a plurality of images comprising a plurality of candidate answers; detecting, based on the captured images, a first bounding box comprising the plurality of the candidate answers; detecting, based on the captured images, a second bounding box comprising a plurality of alphanumeric characters, a first one of the alphanumeric characters being located on a line of software code; calculating a distance from a side of a first bounding box to a side of a second bounding box; and determining, based on the calculated distance, a source code alignment.
G06V 30/414 - Extraction de la structure géométrique, p.ex. arborescence; Découpage en blocs, p.ex. boîtes englobantes pour les éléments graphiques ou textuels
Methods and systems as described herein may enable customized navigation flow for websites/applications. Navigation flows (e.g., the pages, user interfaces, views, etc. that are displayed to a user) may be customized for each user. Navigation parameters may be generated for a user and may indicate a customized navigation flow for the user. The navigation parameters may indicate one or more pages of a website/application and an order that each of the one or more pages should be displayed to the user. The navigation parameters may indicate a trigger for each page. A trigger may indicate an action and/or event that causes a change in display to the next page in the navigation flow. Navigation parameters may be shared between devices, which may enable the user to experience the same navigation flow across multiple websites/applications.
A device may provide a verification indicator to a device associated with a website. The verification indicator may be associated with verifying access to the website. The device may detect that the verification indicator has been associated with code associated with the website based on processing the code. The device may provide a script to the device. The script may be included in the code. The script may be associated with monitoring operations of the website. The device may receive data related to the operations. The device may analyze the data using a model. The model may be associated with making a prediction related to at least one of: a value to be received via the website, or traffic associated with the website. The device may perform one or more actions related to the website based on a result of the analyzing.
In some implementations, a user device may present, on a user interface (UI) associated with a user account, a first UI element. The user device may detect a user interaction, with the user device, indicating the first UI element. The user device may present, on the UI and based on the user interaction, a second UI element, which increases in length in a first direction from a start point, along a closed path around the first UI element and ending at the start point, while the user interaction is being detected. The second UI element completes the closed path when an interaction duration satisfies a duration threshold, which indicates a confirmation of a request for an action associated with the user account. The duration threshold is based on one or more parameters associated with one or more of the action, the user account, or the user interaction.
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
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 comport
G06F 3/04883 - 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 exer utilisant un écran tactile ou une tablette numérique, p.ex. entrée de commandes par des tracés gestuels pour l’entrée de données par calligraphie, p.ex. sous forme de gestes ou de texte
92.
IDENTIFYING WEB ELEMENTS BASED ON USER BROWSING ACTIVITY AND MACHINE LEARNING
A computer-implemented method includes tracking, by a computing device, user browsing activity of a first page having known elements; mapping, by the computing device, the user browsing activity to the known elements; storing, by the computing device, mapping information that maps the user browsing activity to the known elements; tracking, by the computing device, user browsing activity of a second page having unknown elements; identifying, by the computing device, the unknown elements based on the mapping information and the user browsing activity of the second page; and executing, by the computing device, one or more computer-based instructions based on the determining the unknown elements that were identified.
In some implementations, a device may obtain the biometric token associated with an account via a registration procedure associated with a first platform that is associated with a host. The server device may store an indication of the biometric token in a database. The server device may receive a login request associated with the account for a second platform that is associated with the host. The server device may identify that biometric authentication is enabled for the account based on the indication of the biometric token being stored in the database. The server device may provide an authentication challenge associated with the biometric token. The server device may receive a response to the authentication challenge indicating whether the authentication device has authenticated biometric information associated with a user based on the biometric token. The server device may authenticate the login request for the second platform based on the response.
In some aspects, a computing system may use a machine learning model to determine whether a computer security policy should be modified to reduce the likelihood of a cyber security incident. Through the use of a machine learning model, unsafe combinations of access grants or permissions may be identified and modified to prevent cyber security incidents from occurring. The computing system may input a representation of a computer security policy into a machine learning model, which has been trained on a dataset that includes representations of computer security policies. The computing system may generate output indicating a likelihood that the first computing system will be involved in a cyber security incident. Based on the output satisfying a first threshold, the computing system may generate a recommendation to modify the first computer security policy. The computing system may modify the first computer security policy based on the recommendation.
In some implementations, a system may identify a set of data processing jobs to track for SLA compliance. The system may trigger a step function for each data processing job tracked for SLA compliance, wherein the step function associated with each data processing job includes a wait time based on a time when an SLA associated with the respective data processing job must be satisfied. The system may determine whether information indicating a success state for each data processing job is available in a storage location. The system may send one or more messages for one or more data processing jobs in the set of data processing jobs that are associated with an SLA breach, wherein the one or more data processing jobs are identified based on determining that information indicating the success state for the one or more data processing jobs is not present in the storage location.
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
A transaction card is provided. The transaction card can include a luminous layer having a sensitive information component. The sensitive information component includes personal account data and can be selectively illuminated by a light source by refracting light emitted by the light source. A switch and power source are provided to selectively energize the light source.
G06K 19/077 - Supports d'enregistrement avec des marques conductrices, des circuits imprimés ou des éléments de circuit à semi-conducteurs, p.ex. cartes d'identité ou cartes de crédit avec des puces à circuit intégré - Détails de structure, p.ex. montage de circuits dans le support
In some implementations, a transaction card may include a card body having a first surface and a second surface opposite the first surface. The transaction card may include an integrated circuit (IC) chip embedded in the card body, and a plurality of first electrical contact sets electrically accessible from the first surface of the card body, where the plurality of first electrical contact sets have electrical connections to the IC chip. The transaction card may include a plurality of first magnetic stripe areas readable from the first surface of the card body. The transaction card may include a plurality of second electrical contact sets electrically accessible from the second surface of the card body, where the plurality of second electrical contact sets have electrical connections to the IC chip. The transaction card may include a plurality of second magnetic stripe areas readable from the second surface of the card body.
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
G06K 19/077 - Supports d'enregistrement avec des marques conductrices, des circuits imprimés ou des éléments de circuit à semi-conducteurs, p.ex. cartes d'identité ou cartes de crédit avec des puces à circuit intégré - Détails de structure, p.ex. montage de circuits dans le support
G06K 19/08 - 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 utilisant des marquages de différentes sortes sur le même support d'enregistrement, p.ex. un marquage étant lu optiquement et l'autre par des moyens magnétiques
98.
SYSTEMS AND METHODS FOR GENERATING AND PROCESSING ELECTRONIC FORMS
A computer-implemented method of generating and processing electronic forms may include: generating and storing a plurality of prompts; receiving a first form request from a first user device; generating a first form including a first set of prompt instances; causing the first form to be displayed on the first user device; receiving a first set of user inputs, each of the first set of user inputs being associated with one or more of the first set of prompt instances; and storing the first set of prompt instances and the first set of user inputs while maintaining the plurality of prompts.
Methods and systems are described herein for modifying scheduled events based on bandwidth availability. To modify the scheduled event, the system determines a plurality of user devices corresponding to an event. The system receives first network conditions for a first user device and generates a feature input based on the first network conditions. The system inputs the feature input into an artificial intelligence model to determine a first available bandwidth metric and aggregates the first available bandwidth metric with respective available bandwidth metrics for other user devices of the plurality of user devices to determine a composite available bandwidth metric. The system can compare the composite available bandwidth metric to a threshold available bandwidth metric and in response to determining that the composite available bandwidth metric equals or exceeds the threshold available bandwidth metric, the system generates for display, on a user device interface, a recommendation for modifying the event.
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
G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform steps of a method for providing customer data access during a migration process. The system may initiate a transfer of customer data from a source data server to a system platform and transfer a subset of the customer data to a temporary data storage. The system may modify the temporary copy of customer data and generate an instruction to modify the permanent copy of customer data. In response to the completion of the transfer of customer data from the source data server to the system mainframe, the system may then transfer and execute the instruction to modify the permanent copy of customer data.
brevets
