Abstract: An automated teller machine (ATM) may include an input component and one or more processors. The input component may be configured to detect multi-factor input associated with an account. The multi-factor input may include at least two of: a sequence of characters input via the input component, a force with which at least one character, of the sequence of characters, is input via the input component, a length of time over which at least one character, of the sequence of characters, is input via the input component, or a combination of at least two characters, of the sequence of characters, that are input concurrently via the input component. The ATM may receive the multi-factor input, validate the multi-factor input in association with the account, and selectively permit or deny access to one or more actions associated with the account based on validating the multi-factor input.

Abstract: A transaction card assembly may include a card body comprising a first face and a second face opposite the first face; a receiving portion formed on the first face of the card body; and a first removable magnetic strip assembly comprising a first magnetic strip and a first attachment portion. In a first configuration, the first removable magnetic strip assembly may be coupled to the card body via engagement between the first attachment portion and the first magnetic strip, and in a second configuration, the first removable magnetic strip assembly may be uncoupled from the card body by disengagement between the first attachment portion and the first magnetic strip. In the second configuration, the first removable magnetic strip assembly is configured for reuse with an additional card body, the additional card body being different than the card body.

Abstract: The present disclosure describes a machine learning model trained to identify social engineering attacks. A prompt may be provided to a generative artificial intelligence to create communications resembling social engineering attacks. The communications may be inputted into a machine learning model to train the machine learning model to identify social engineering attacks. The machine learning model may also be trained on actual social engineering attacks. Once trained, the machine learning model may be deployed to monitor a plurality of communication channels to detect social engineering attacks. Upon detecting a social engineering attack, a system may implement one or more remedial actions to mitigate the detected social engineering attack.

Abstract: Aspects provided may allow for an entity to deactivate a virtual card number (VCN). In particular, aspects provide for deactivating VCNs based on a frequency or periodicity of an interaction. After deactivation, the entity may block future charges to the VCN. Further aspects provide for using incoming charge data sent to one or more previous users to train a machine learning model to determine the frequency or periodicity of the interaction. Additional aspects may also provide for including trial length when determining the deactivation date, providing VCN configuration options to a user, and notifying the user based on upcoming and current VCN status changes.

Abstract: Embodiments disclosed herein generally related to a system and method for authenticating a transfer request. A computing system receives a transfer request from a client device. The computing system determines that the monetary amount specified in the transfer request exceeds a threshold. The computing system identifies an automated teller machine (ATM) based on at least location information associated with a user of the client device. The computing system prompts the user to authenticate the transfer request at the identified ATM by transferring a message to the client device to be displayed thereon. The computing system receives an authentication attempt of the user from the ATM. The computing system compares authentication information in the authentication attempt to personal identification information associated with the user. The computing system determines that the authentication information at least partially matches personal identification information associated with the user.

Abstract: 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.

Abstract: A system and method of establishing a communication session is disclosed herein. A computing system receives, from a client device, a content item comprising text-based content. The computing system generates a mark-up version of the content item by identifying one or more characters in the text-based content and a relative location of the one or more characters in the content item. The computing system receives, from the client device, an interrogatory related to the content item. The computing system analyzes the mark-up version of the content item to identify an answer to the interrogatory. The computing system generates a response message comprising the identified answer to the interrogatory. The computing system transmits the response message to the client device.

Abstract: Aspects described herein may improve predictions of real-time user intent by generating multi-modal embeddings based on previous user interactions. The previous user interaction data may be received from multiple different modalities. The interaction data may be analyzed and labeled with user intent for each previous user interaction, then sequentially organized. The multi-modal embeddings may be generated by modal-specific encoders and a multi-modal embeddings generator. A trained machine learning model may use, as input, the multi-modal embeddings and personal data to determine real-time user intent at the beginning of an interaction. The multi-modal embeddings may act as a set of unique and specific output vectors that allow a computing device to recognize and correlate synonymous terms and interrelated subjects, usually a difficult task for computing devices, thereby improving the technological process of analyzing, in real-time, user intent.

Abstract: The present disclosure provides an exemplary method, system, and computing device that may include the steps of receiving a first indication that information of a user has been detected at one or more dark web resources; classifying the item of the compromised information into an information type category; receiving a permission indicator to detect communications by the computing device; receiving a second indication of a communication; receiving a third indication that the user engages an interaction with the communication; instructing the computing device to execute a technique to obtain data for the communication; receiving the data for the communication; determining the communication is a spam communication; determining a current information type category being discussed during the spam communication; making a determination that the current information type category corresponds to the information type category; and instructing a graphical user interface to display an alert to the user.

Abstract: In some implementations, a compliance monitoring device may detect a trigger event associated with a compliance-based interaction. The compliance-based interaction may be associated with a secure location, a user device of a user, a sensor associated with a secure object, and one or more cameras. The compliance monitoring device may cause the one or more cameras to capture a set of images associated with the compliance-based interaction. The compliance monitoring device may receive the images and may extract image information from the set of images. The compliance monitoring device may receive positioning information associated with the user device and status information associated with the secure object. The compliance monitoring device may analyze at least one of the image information, the positioning information, or the status information to identify a compliance rule violation. The compliance monitoring device may provide an alert indication based on identifying the compliance rule violation.

Abstract: Provided, in an aspect, is a method for performing an online transaction using a graphical construct. The method can include receiving, by a client device, inputs to generate the graphical construct; transmitting to a server in communication with the client device, a request to generate the graphical construct; receiving, by the client device, the generated graphical construct and a summary information from the server; displaying, through a user interface of the client device, a summary screen including the generated graphical construct and the summary information; embedding, by the client device, the generated graphical construct on a third-party application running on the client device; sending, by the client device, a transaction request to perform the online transaction using the generated graphical construct; and presenting for display, through the user interface of the client device, a notification including a status of the online transaction.

Abstract: A humidifier system includes a base module comprising a wet-pack assembly, a fan module or a bypass module structured to draw air through the base module, and a cover assembly structured to couple to each of the base module and the fan module or the bypass module, where the cover assembly is structured to retain the wet-pack assembly within the base module.

Abstract: A disposal assembly includes a motor coupled to operate a grinding mechanism of a food waste disposer. A first switch is coupled to selectively inhibit the supply of power from a power source to a main winding of the motor, and a second switch is coupled to selectively inhibit the supply of power from the power source to a start winding of the motor. A control circuit is configured to close the first and second switches during an initial startup time period, detect a voltage of at least one of the windings, and open the second switch in response to detection of the voltage above a start voltage threshold value. The control circuit is also configured to subsequent to opening the second switch, close the second switch in response to detection of the voltage below a low voltage threshold value indicative of an excess load condition of the motor.

Abstract: Systems and computer-implemented methods disclosed herein relate to detecting errors in manually entered data. In one embodiment, the system can identify a named entity automatically from a conversation between a customer and service agent with a named entity recognition model that employs natural language processing and machine learning to detect a word or string of words in the conversation that corresponds to a named entity category. In another embodiment, the system can determine whether data entered into a field on a service platform by the service agent includes an error by comparing the data entered with the named entity. In another embodiment, the system can transmit an alert to the service agent through the service platform when there is a mismatch between the named entity and the data entered.

Abstract: Presented herein are systems and methods for performing federated learning across vehicles. A computing device having one or more processors coupled with memory can maintain, on the memory, a first machine learning (ML) comprising a first plurality of parameters for determining values identifying a characteristic of a vehicle function on at least one of a plurality of vehicles. The computing device can receive a second plurality of parameters generated by a second ML used by each respective vehicle. The computing device can update the first plurality of parameters of the first ML in accordance with the second plurality of parameters received from each respective vehicle of the plurality of vehicles. The computing device can transmit, to a vehicle, the updated first plurality of parameters to update the second plurality of parameters of the second ML on the vehicle.

Abstract: Methods, systems, and apparatuses are described herein for improving computer authentication processes by using physical environment information. A computing device may receive video depicting a physical environment and process that video to identify one or more first objects. The computing device may receive a request for access to an account. The computing device may send a prompt for a physical environment description and receive, in response, an indication of one or more second objects. The indication of the one or more second objects may comprise video of the physical environment, a verbal description of the physical environment, and/or text describing the physical environment. The computing device may grant the user device access to the account based on comparing the one or more first objects to the one or more second objects.

Abstract: In some implementations, a server device may receive, from a client device, a script identifier, that identifies a script, and an indication of whether the script was successfully executed by the client device. The server device may determine whether a condition associated with disabling the script is satisfied based on the script identifier, the indication of whether the script was successfully executed by the client device, and stored information determined based on a plurality of indications of whether the script was successfully executed by a plurality of other client devices. The server device may selectively cause a data structure to be updated to indicate that the script is disabled based on determining whether the condition is satisfied. The data structure may be used to indicate whether the script is enabled prior to execution of the script.

Abstract: Methods, systems, and apparatuses are described herein for associating past auction bidding activity with subsequent financial transactions. A computing device may receive, from a web browser plugin of a web browser application executing on a user computing device, bid information relating to bids placed by a user on an auction website. Such information may be collected by, for example, scraping the Document Object Model of the website. After the auction ends, the computing device may determine a plurality of different candidate financial transactions for the user. Based on an estimated payment amount, the computing device may select, from the plurality of different candidate financial transactions, a matching financial transaction, then output an association between a bid and the matching financial transaction.

Abstract: Disclosed embodiments accelerate web form completion based on email address analytics. An email address can be input with respect to a web form and identified. The email address can be parsed into a username and a domain name and analyzed. A value of a web form field can be determined based on data extracted from the username, domain name, or both. The determined value can then be employed to automatically complete a corresponding web form field Values for additional fields can be computed based on the determined value alone or combined with data from other sources. User input and interaction with a web form can be monitored and used as a basis to dynamically complete additional fields, alter fields, or clear field values.

Abstract: Disclosed embodiments may include a system for intelligent alerting. The system may receive data and activity status information corresponding to a user. Based on the data and activity status information, the system may determine whether a first user alert is required, and if so, may determine a first type of alert and a first time to present the first type of alert to the user. The system may cause a user device to present the first type of alert to the user at the first time.