Systems and methods for external account authentication are disclosed herein. They include receiving a call to pair the external account with a secure account, extracting external data from the external account, the external data corresponding to external account content, providing user activity data from the secure account as an input to an authentication machine learning model, providing the external data as an input to the authentication machine learning model, the authentication machine learning model configured to output a certainty level that the external account is associated with a user of the secure account based on the external data and the activity data, receiving the certainty level from the authentication machine learning model, determining that the certainty level meets a certainty threshold, and pairing the external account with the secure account based on determining that the certainty level meets the certainty threshold.
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 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
2.
PAYMENT ALERT SYSTEM AND TECHNIQUES BASED ON GEOGRAPHIC FOOTPRINT
A non-transitory computer-readable storage medium storing computer-readable program code executable by a processor to retrieve a customer data record including bill payment activity associated with a provider account for a customer of a financial institution; and define a geographical footprint for the customer. The geographical footprint may be defined by identifying a customer set including the customer from a plurality of customers of a provider of the provider account, having customer records indicating geographic proximity, and determining that a predetermined fraction of the customer set are associated with a common billing cycle for the provider. The computer-readable program code may be executable by the processor to send a bill payment alert for transmission to the customer via electronic communication or telephonic communication, when the bill payment activity meets a threshold condition, wherein the threshold condition is determined at least in part by the geographical footprint.
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de banque à domicile
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
G06Q 50/06 - Fourniture d'électricité, de gaz ou d'eau
3.
METHOD FOR PROVISIONING MERCHANT-SPECIFIC PAYMENT APPARATUS
Various embodiments are directed to a method and system for provisioning a merchant-specific payment apparatus, such as a temporary payment card, via a computing device, such as an automated teller machine (ATM). A user, such as a customer, may specify a merchant. A record of known payment acceptance types at that merchant may be returned, which may be used to determine what type of temporary payment card gets issued to the user.
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 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p.ex. cartes à puces ou cartes magnétiques
4.
REFRESH OF STALE REFERENCE TO PHYSICAL FILE LOCATIONS
In some implementations, a server device may identify a first file location for storing data associated with an application and a reference to a file path for the first file location. The server device may store a data stream associated with the application to the first file location using the reference. The server device may periodically execute first instructions associated with checking whether a valid physical file exists in the first file location by opening a connection via the file path, wherein the first instructions are executed independently of second instructions associated with storing the data stream. The server device may selectively cause the data stream to be stored in the first file location or a second file location based on determining whether the valid physical file exists in the first file location.
The present disclosure provides systems and methods for creating and updating vehicle listings using crowdsourced images. An exemplary embodiment of the disclosed systems and methods includes at least one processor and at least one non-transitory computer-readable medium containing instructions. The instructions, when executed by the at least one processor, cause the system to perform operations. The operations include communicating with a listing system to create a listing for a vehicle and receiving, from an identification application executing on a mobile device distinct from the listing system, an identifier for the vehicle and an image of the vehicle. The operations further include identifying the listing using the received identifier, determining one or more parameters associated with an image quality for the received image, and updating the listing for the vehicle to include the received image based on the determined one or more parameters for the received image.
Aspects described herein may allow for authenticating a user by generating a customized set of authentication questions based on patterns that are automatically detected and extracted from user data. The user data may include transaction data collected over a period of time. By automatically detecting user patterns that correspond to user behavior over a period of time, an authentication system may be able to generate information that is recognizable to an authentic user but difficult to guess or circumvent for any other user.
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
G06F 18/23213 - Techniques non hiérarchiques en utilisant les statistiques ou l'optimisation des fonctions, p.ex. modélisation des fonctions de densité de probabilité avec un nombre fixe de partitions, p.ex. K-moyennes
Techniques for data quality analysis may include the determination of data quality metrics using reconfigurable quality components. Access to the data may be based on the determined quality metrics. The configurable quality components may determine quality metrics for corresponding datasets. The quality components may be configured automatically based on quality configurations. The configuration of the quality components may be facilitated using a data orchestrator.
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
8.
Managing Trusted User Devices Via Silent Push Notifications
Methods, systems, and apparatuses for managing the preauthorization of user devices to access resources in one or more remote servers are described herein. Preauthorized user devices may access the resources without repeatedly going through multiple-factor authentication processes. Data for such preauthorized user devices may be maintained in a list of trusted user devices. To determine whether user devices are still eligible to be included in the list of trusted user devices, silent push notifications may be sent to the user devices. The silent push notifications may be configured not to cause outputs of any displays at the user devices or modify any current displays. Based on deliverability statistics that indicate whether the user devices acknowledged the silent push notifications, user devices may be kept in the list of trusted devices or removed from the list of trusted devices.
In some implementations, a system may receive interaction data corresponding to an interaction associated with a particular user of a plurality of users. The system may determine, based on the interaction data, one or more interaction categories associated with the interaction. The system may store the interaction data as historical interaction data associated with historical interactions of the particular user. The system may determine, based on the historical interaction data, experience statuses associated with the particular user in at least a subset of the plurality of categories. The system may receive, from a user device of the particular user, review data indicating a review associated with a historical interaction of the particular user. The system may store the review as historical review data. The review may be associated with one or more experience statuses of the particular user in the one or more interaction categories associated with the historical interaction.
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
G06Q 30/01 - Services de relation avec la clientèle
G06Q 40/02 - Opérations bancaires, p.ex. calcul d'intérêts ou tenue de compte
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
11.
SYSTEMS AND METHODS FOR ANONYMIZED VALIDATION AND LOGIN
A method for facilitating anonymized interactions and/or identifying or validating a user via a virtual number may include: receiving a login request from a user device associated with a user that identifies the user via a virtual number; in response to receiving the login request, determining whether the virtual interaction item number is valid; in response to determining that it is valid: validating the login request; and identifying an entity associated with the virtual number; receiving from the user device, an interaction-completion request; in response to receiving the interaction-completion request, transmitting a user information request to the entity associated with the virtual number; receiving a reply to the user-information request from the entity; and in response to receiving the reply, completing the interaction-completion request using the reply.
A system and method that facilitates a private transaction is disclosed. The system can retrieve textual information of a webpage containing vehicle sale related information for a vehicle listed for sale by an individual. Using a natural language processing (NLP) model, the textual information may be analyzed to extract vehicle sale related information for the vehicle. The system can compare the vehicle sale related information to known parameters for the vehicle to verify the authenticity of the vehicle sale related information. Based on verifying the authenticity of the vehicle sale related information, the system can determine whether to approve financing for the vehicle. Based on determining to approve financing for the vehicle, financing terms may be generated for the vehicle. The financing terms may be transmitted to client devices.
System and methods for handling on-chain cryptographic resources based on conditions generated responsive to an off-chain trigger. The system may receive a transfer request that includes a resource allocation request, generate a first blockchain function request for a list of contributor identifiers and condition sets, receive the list of contributor identifiers and condition sets, determine a subset of the list of contributor identifiers and condition sets, generate a second blockchain function request, and transmit the second operation request to a blockchain node.
H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
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
14.
SCALABLE AND CUSTOMIZABLE COMPUTATION USING A MODULARIZED CODE ARCHITECTURE
In some implementations, a device may obtain, based on a characteristic associated with an account, a set of forecasted values from a dataset of forecasted values. The set of forecasted values may include forecasted values for a plurality of forecasting metrics for a plurality of time periods. The device may generate, for the account, feature metric values, for the plurality of time periods, for a plurality of feature metrics based on the set of forecasted values. The device may compute, for the account, at least one present or future value metric based on the feature metric values for the plurality of feature metrics.
Disclosed herein are system, method, and computer program product embodiments for providing secure access to a locker of a locker system based on a token that includes token data and a message authentication code (MAC) to authenticate the token data. The token data includes at least the unique locker identifier for the locker. The MAC can be generated using a secret key. The secret key can be obtained based on a unique derivation key associated with a master key. The locker system can determine whether the token is valid based on the token data, the MAC, and the secret key. In response to a determination that the token is valid, the locker system can send a signal to unlock the locker.
G07C 9/22 - 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
G07C 9/00 - Enregistrement de l’entrée ou de la sortie d'une entité isolée
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
Aspects described herein may allow an automated generation of an interactive multimedia content with annotations showing vehicle damage. In one method, a server may receive vehicle-specific identifying information of a vehicle. Image sensors may capture multimedia content showing aspects associated with exterior regions of the vehicle, and may send the multimedia content to the server. For each of the exterior regions of the vehicle, the server may determine, using a trained classification model, instances of damage. Furthermore, the server may generate an interactive multimedia content that shows images with annotations indicating instances of damage. The interactive multimedia content may be displayed via a user interface.
G06F 16/48 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
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
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p.ex. des objets vidéo
Disclosed embodiments pertain to determining and communicating purchasing power through a visualization. A trained machine learning model can be invoked on a credit card without a preset limit to predict a dynamic spending limit based on credit card data or credit score data. Purchasing power can be computed as the difference between the dynamic spending limit and a current balance, and a purchase power class can be determined based on the purchasing power. Further, a graphic representation of a purchasing power class can be determined. Subsequently, presentation of the graphic representation can be triggered in a manner that overlays the graphic representation on or around the physical card.
G06Q 40/02 - Opérations bancaires, p.ex. calcul d'intérêts ou tenue de compte
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 19/00 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie
18.
SYSTEM AND METHOD FOR THE DYNAMIC ALLOCATION OF FUNDS
The disclosed embodiments include a system and method for generating a predictive model and allocating, based on the model's findings, an ideal amount into a user's account. The system includes a user device and a server. The server can retrieve the user's information, analyze the information, generate the predictive model, train the model, calculate a savings amount and allocate the amount to the appropriate account.
In some embodiments, a shared presentation, which includes a set of spatial regions, is transmitted to user devices associated with users. Then, based on a user input indicating a first spatial region of the shared presentation for a first user, first auxiliary data (e.g., auxiliary video stream of the shared presentation) that corresponds to the first spatial region is generated. Moreover, based on the user input indicating the first user, a first user device associated with the first user is caused to display the first spatial region at a first time without displaying one or more other spatial regions of the set of spatial regions at the first time. As an example, the first auxiliary data is transmitted to the first user device, which causes the first user device to display the first spatial region without displaying the other spatial regions.
A computer-implemented method for using a machine-learning trained predictive engine to predict failures includes receiving electronic prior transaction data corresponding to a plurality of prior successful transactions and a plurality of prior unsuccessful transactions, and training a machine learning predictive engine based on the plurality of prior successful transactions and the plurality of prior unsuccessful transactions. Electronic transaction data may be received, the electronic transaction data being associated with a user, an item, and candidate transaction terms, the electronic transaction data being associated with a candidate transaction. The machine learning predictive engine may determine a likelihood of success of the candidate transaction based on the electronic transaction data, and display the likelihood of success of the candidate transaction.
G06Q 30/0202 - Prédictions ou prévisions du marché pour les activités commerciales
G06F 18/2137 - Extraction de caractéristiques, p.ex. en transformant l'espace des caractéristiques; Synthétisations; Mappages, p.ex. procédés de sous-espace basée sur des critères de préservation de la topologie, p.ex. positionnement multidimensionnel ou cartes auto-organisatrices
G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
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
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
G06Q 30/0201 - Modélisation du marché; Analyse du marché; Collecte de données du marché
In some implementations, a transaction card includes a card body having a first surface and a second surface opposite the first surface, and the card body may be in a configuration that defines a storage area for a physical key. The transaction card may include at least one of an integrated circuit chip or a magnetic stripe accessible from at least one of the first surface or the second surface of the card body. The transaction card may include a connecting element to connect the physical key to the card body. The connecting element may be configured to enable movement of the physical key between a storage position, in which at least a portion of the physical key occupies the storage area, and a use position, in which at least a portion of the physical key is outside of the storage area.
G06K 19/04 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par la forme
22.
SYSTEMS AND METHODS FOR ANONYMIZED VALIDATION AND LOGIN
A method for facilitating anonymized interactions and/or identifying or validating a user via a virtual number may include: receiving a login request from a user device associated with a user that identifies the user via a virtual number; in response to receiving the login request, determining whether the virtual interaction item number is valid; in response to determining that it is valid: validating the login request; and identifying an entity associated with the virtual number; receiving from the user device, an interaction-completion request; in response to receiving the interaction-completion request, transmitting a user information request to the entity associated with the virtual number; receiving a reply to the user-information request from the entity; and in response to receiving the reply, completing the interaction-completion request using the reply.
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.
24.
CONTENT SHARING WITH PLAYBACK CONTROLS TO FACILITATE INDIVIDUALIZED PLAYBACK IN A MULTI-VIEWER SESSION
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
25.
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
30.
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
31.
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
32.
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
36.
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
39.
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
44.
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
46.
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
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.
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
52.
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.
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
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
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
56.
SYSTEMS AND METHODS FOR GENERATING REAL-TIME LOCATION-BASED NOTIFICATIONS
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.
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.
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
59.
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
64.
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
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
67.
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
68.
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]
70.
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
74.
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
82.
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
85.
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.
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.
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.
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
92.
SYSTEMS AND METHODS FOR SANITIZING SENSITIVE DATA AND PREVENTING DATA LEAKAGE FROM MOBILE DEVICES
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
100.
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.
