Abstract: A system and method for payment notification using blockchain. The system and method relate to real-time monitoring and updating of a list of accounts that have not satisfied a minimum payment amount due. The real-time monitoring and updating of the list occurs through the use of a blockchain monitoring payment information by a user to the account. The blockchain is continually updated every time a payment is made. A notification system receives each update and is aware, in real-time, whether a user has satisfied a minimum payment amount due and thus whether an account is current or in need of a collections notification.

Abstract: Embodiments disclosed are directed to a computing system that performs steps to perform enhanced device fingerprinting using user contacts data. The computing system receives, from an application, a first plurality of device attributes identifying a client device on which the application is being used. The first plurality of device attributes includes first device identification data and first user contacts data. Subsequently, when a user is attempting to perform a transaction using the application on the client device, the computing system receives, from the application, a second plurality of device attributes identifying the client device on which the application is being used. The second plurality of device attributes includes second device identification data and second user contacts data. The computing system compares the second plurality of device attributes to the first plurality of device attributes to determine whether the user is authorized to perform the transaction.

Abstract: A system method of managing a software repository. The method including receiving a dataset comprising a set of computer instructions, retrieving feature-related data from the dataset, determining, by a machine learning model executing on the computing device, a function of the computer instructions based on the feature-related data, and generating a synopsis of the function of the computer instructions. The method can include transmitting the synopsis to a user interface and receiving feedback from a user indicative of whether the synopsis accurately describes the function of the computer instructions. If the feedback indicates that the synopsis accurately describes the function of the computer instructions, the method can include storing the synopsis in a memory of the computing device. If the feedback indicates that the synopsis inaccurately describes the function of the computer instructions, the method can include generating a revised synopsis of the function of the computer instructions.

Abstract: Methods and computer-readable media for repeated holdout validation include collecting independent data representing independent variables; collecting dependent data representing a dependent variable; correlating the independent data with the dependent data; creating a data set comprising the correlated independent and dependent data; generating a plurality of unique seeds; creating a plurality of training sets and a plurality of validation sets; associating each training set with a single validation set; training the neural network a plurality of times with the training sets and seeds to create a plurality of models; calculating accuracy metric values for the models using the validation sets associated with the training sets used to create respective models; performing a statistical analysis of the accuracy metric values; and ranking the independent variables by a strength of correlation of individual independent variables with the dependent variable, when a metric of the statistical analysis exceeds a thres

Abstract: Systems, apparatuses, computer-readable media, and methods are provided for activating a contactless card. A server may transmit, to a web browser on a client device, a web page. The server may receive, from the web browser, a request to activate a contactless card, the request including a cryptogram. The server may decrypt the cryptogram based on a key associated with the contactless card. The server may transition, based on the decryption of the cryptogram, the contactless card from an inactive payment state to an active payment state. The server may transmit, to the web page and based on the transition of the contactless card from the inactivated payment state to the activated payment state, an indication to activate a payment applet of the contactless card.

Abstract: Disclosed herein are system, method, and computer program product embodiments for protecting a device from skill squatting by verifying the legitimacy of a skill to a user before operating the skill based on user instructions. Upon receiving an audio signal from a user to operate a skill on a device, the skill can retrieve unique and non-confidential information related to the user or the device, and further present the unique and non-confidential information to the user such that the information is used to verify the legitimacy of the skill. Upon a verification of the legitimacy of the skill, the user can operate the skill by voice or audio instructions.

Abstract: In some aspects, a computing system may train a machine learning model to classify a plurality of samples of a training dataset. The computing system may generate a plurality of counterfactual samples. The computing system may determine a distance score between the training dataset and a first counterfactual sample of the plurality of counterfactual samples. Based on determining that the distance between the training dataset and the first counterfactual sample is smaller than other distances corresponding to other counterfactual samples of the plurality of counterfactual samples, the computing system may generate a recommendation to use the first counterfactual sample.

Abstract: A computer-implemented method for processing items or services in a container may include: initiating execution of a web module or an application installed on a user device based on user input; identifying an alternative for an item or service in the container; providing a user interface including: first information related to the item or the service in a first portion, second information related to alternative in a second portion, and one or more user interface elements overlaying the first portion or the second portion; detecting input to the one or more user interface elements, the input including: a command to cycle through display of the alternative item or service, selection of the alternative item or service, and/or an indication of a preference for the alternative item or service; and performing one or more actions based on the input.

Abstract: A computer-implemented method may include: receiving, from at least one camera, image data associated with a first user at a public access user computing device; detecting, based on the received image data, by employing a machine learning model trained using a dataset of actions collected from a plurality of previous users, that the first user has moved away from the public access user computing device; automatically encrypting, based upon the detection, a user session associated with the first user, wherein the encrypted user session is configured to be subsequently activated by the first user; and initiating a new generic user session on the public access user computing device for a second user.

Abstract: Computer-implemented methods and systems are provided for automatically performing a task on a remote computer. During a registration stage, the system receives personal information of a human user, obtains an IP address and a device configuration for a computing device, and stores the personal information, IP address, and the device configuration in record in a database. The system receives a request to interact with a remote website to perform a task, the request including the personal information of the human user. The system then retrieves the record from the database using the personal information. The system creates a virtual machine based on the device configuration for the computing device, selects one of a geographically distributed set of proxy servers having an IP geographically address resembling the IP address for the computing device, and executes instructions causing the virtual machine to interact with the remote website using the proxy server to perform the task.

Abstract: Described are methods and systems are for generating dynamic conversational queries. For example, as opposed to being a simply reactive system, the methods and systems herein provide means for actively determining a user's intent and generating a dynamic query based on the determined user intent. Moreover, these methods and systems generate these queries in a conversational environment.

Abstract: Embodiments disclosed herein generally related to a method and system for customizing a customer experience. In one embodiment, a method is provided herein. A computing system receives from a computing device positioned in a facility one or more video streams. The one or more video streams capture a customer in the facility. The computing system identifying an identity of the customer by parsing the one or more video streams to identify one or more audio or visual cues of the customer. The computing system determines, based on the identity of the customer, that the customer has one or more previous transactions at the facility. The computing system predicts, based on the one or more previous transactions, a new transaction at the facility. The computing system notifies the computing device positioned in the facility in preparation of the new transaction.

Abstract: Disclosed herein are system, method, and computer program product embodiments for determining a probability of a device at risk. The device may be associated with a plurality of security parameters. For a security parameter, the device can be in multiple states. A probability value corresponding to a security parameter can indicate the security parameter being in a state among the multiple states. A probabilistic graphical model may be used to represent dependences of the plurality of security parameters. A device security risk prediction module may determine a probability of the device at risk based on the probabilistic graphical model and the probability assignments to the plurality of nodes of the probabilistic graphical model, and further determine a user action instruction to be provided to a user of the device based on the probability of the device at risk.

Abstract: In some embodiments, a system may obtain first feedback indicating one or more first signal-strength-related results corresponding with one or more first token interactions occurring in connection with presentation of one or more first components at one or more first locations of a user interface of a user device. Based on the first feedback, the system may obtain one or more second locations of the user interface and cause presentation of one or more second components at the one or more second locations of the user interface. The system may obtain second feedback indicating one or more second signal-strength-related results corresponding with one or more second token interactions. Using the first and second feedback, the system may update a user interface presentation location at which to present a component for a token interaction within a profile associated with a user of the user device.

Abstract: In order to facilitate dynamic graphing of entity networks based on activity, systems and methods include a processor receiving entity-specific data records and a plurality of entity-related activity records for a plurality of entities, where each entity-specific activity record includes activity data regarding at least one activity associated with an entity. The processor generates graph nodes for an entity activity graph based on the plurality of entity-specific data records, where each graph node of the plurality of graph nodes represents the particular entity and then generating an activity data structure, including the graph nodes and edges between the graph nodes, where the edges represent characteristics of the activities between graph nodes based on the entity-related activity record.

Abstract: Example embodiments of systems and methods for data transmission system between transmitting and receiving devices are provided. In an embodiment, each of the transmitting and receiving devices can contain a master key. The transmitting device can generate a diversified key using the master key, protect a counter value and encrypt data prior to transmitting to the receiving device, which can generate the diversified key based on the master key and can decrypt the data and validate the protected counter value using the diversified key.

Abstract: The system and methods described herein allow users to give their applicant information when seeking to submit an inquiry associated with a product provided by at least one entity, and have various lender microservices run in parallel, segregated by entity, in a jailed and self-contained, autonomous environment. The result of these microservices may be returned as a response to the inquity, being determined autonomously for each respective entity based on one or more respective rule sets or executable logic for each respective entity. Payloads for multiple entities may be combined in a single output from the jailed and self-contained environment due to outputs from the environment being encrypted in a universal format, wherein the outputs are decrypted in a user session in an application, allowing the user to see the results of the respective responses of each of the at least one entity, to their inquiry.

Abstract: Systems and methods disclosed herein provide automatic expense categorization of transactions or expenditures based on a machine learning (ML) model trained using anonymized transactional data for expenditures that are stored in a public blockchain. The anonymized transactional data for the expenditure and the expense category, may be distributed throughout the blockchain network and recorded in the blockchain. In some implementations, an expenditure may be submitted to the blockchain network for expense categorization. The transactional data for the expenditure may be anonymized to remove confidential and personal identifying information (PII) before it is distributed throughout the blockchain network. Each participating node of the blockchain network may utilize the ML model to identify an expense category for the expenditure. The participating nodes may provide a consensus mechanism in order to arrive at a shared understanding of how to categorize the expenditure.

Abstract: 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.

Abstract: A system including: one or more processors; a memory storing instructions that, when executed by the one or more processors are configured to cause the system to receive primary and secondary user account data. The system generates one or more predictive model systems based on the primary and secondary user account data. The system receives a first input from the primary user corresponding to a first spending limitation for the secondary user. The system identifies a first transaction of the secondary user exceeding the spending limitation and determines using the one or more predictive model systems whether to authorize a spending limitation override. The system automatically authorizes the spending limitation override when the first transaction exceeds the spending limitation by less than a predetermined threshold. The system can also identify and automatically fund recurring transactions with an associated funding account using the one or more predictive model systems.