Abstract: Embodiments of the present disclosure relate to systems and methods for notifying an entity of a requested payment. In addition, embodiments of the present disclosure relate to solutions for identifying information about an intended recipient of a payment. Embodiments of the present disclosure also relate to solutions for sending a notification to a recipient regarding a payment. Embodiments of the present disclosure further relate to solutions for allowing a recipient to track a payment.

Abstract: Systems and methods of the present disclosure enable the prediction of activity distribution across mediums of activities by employing processors that receive an activity record history across channels of mediums of activity. A candidate activity channel profile of a future activity channel is received that includes candidate channel attributes including: a medium attribute identifying the medium, and an activity category attribute identifying a category of activities of the future activity channel. Cannibalization forecasting models are used to predict channel metrics based on the candidate channel attributes and model parameters trained on the activity record history. New candidate channel attributes are automatically generated that improve the at least one channel metric based on the at least one channel metric, and a new candidate activity channel profile is automatically modified using the new candidate channel attributes. The channel metrics are displayed on computing devices associated with users.

Abstract: Systems and methods of the present disclosure enable the generation and use of secure offline tokens for account activity authentication. A processor receives an activity record including activity details including an entity identifier. The processor determines a flight booking associated with the activity record when the entity identifier includes an airline, and determines flight data associated with the flight booking. The processor automatically generates an offline token associated with the user account, including account access restrictions. The account access restrictions include a token activation period that binds the offline token to a duration of the flight, and a token entity binding that binds the offline token to use with the airline for performing in-flight account activity requests. The processor automatically causes a computing device to download the offline token to enabling performing the in-flight account activity requests with the entity during the offline token activation period.

Abstract: A browser extension may insert code into a document used to generate a web page. For example, the browser extension may detect that the web page is associated with an entity that is associated with one or more delivery estimates. The browser extension may transmit web page information that identifies the entity associated with the web page and/or a date threshold determined based on user input provided to or stored by the browser extension. The browser extension may receive presentation information that identifies a plurality of delivery estimates for a plurality of entities based on transmitting the web page information. The browser extension may insert the code into the document used to generate the web page based on the presentation information. The code may cause an estimated delivery date and/or an indication of whether the date threshold can be satisfied to be provided for display via the web page.

Abstract: Systems and methods of the present disclosure enable context-aware haptic error notifications. The systems and methods include a processor to receive input segments into a software application from a character input component and determine a destination. A context identification model predicts a context classification of the input segments based at least in part on the software application and the destination. Potential errors are determined in the input segments based on the context classification. An error characterization machine learning model determines an error type classification and an error severity score associated with each potential error and a haptic feedback pattern is determined for each potential error based on the error type classification and the error severity score of each potential error of the one or more potential errors. And a haptic event latency is determined based on the error type classification and the error severity score of each potential error.

Abstract: A rule-based reasoning system may receive first transaction-level data for a first transaction that indicates a first transaction amount of the first transaction and a first merchant associated with the first transaction. The system may determine first item-level data for the first transaction that indicates one or more line items associated with the first transaction. The system may infer second item-level data for a second transaction based on the first item-level data and based on: a determination that a second merchant, associated with the second transaction, matches the first merchant associated with the first transaction, and a determination that a second transaction amount, associated with the second transaction, matches the first transaction amount or satisfies a condition that is based on a calculation performed using the first transaction amount and the second transaction amount. The system may output an indication of the second item-level data associated with the second transaction.

Abstract: An apparatus is disclosed herein. The apparatus includes a first liner, a second liner, one or more fastening components, and one or more prongs. The one or more fastening components couples the first liner to the second liner, defining an opening between. The one or more prongs are positionable between a closed position within the opening and an open position exterior to the opening. The one or more prongs include a payment prong. The payment prong includes a body free, a payment chip receptacle, and a payment chip. The body is free from any personal identification information. The payment chip receptacle is attached to the body. The payment chip is positioned in the payment chip receptacle. The payment chip is removable therefrom.

Abstract: A device receives a communication associated with a support issue encountered by a user, and receives information identifying one or more self-support actions performed by the user in relation to the support issue. The device assigns the communication to a position in a support queue. The support queue includes information identifying positions of other communications received from other users, when the other communications are received, and self-support actions performed by the other users. The device associates the information identifying the one or more self-support actions with information identifying the position of the communication and applies respective weights to the one or more self-support actions. The device generates a score for the communication based on applying the respective weights and modifies the position of the communication based on the score. The device performs one or more actions based on modifying the position of the communication.

Abstract: Electronic voter registration information from a voting jurisdiction can be received. The electronic voter registration information can be matched to verified identity information for a customer of the financial institution. A vote selection for an election can be accepted at a mobile computer device of the customer. The vote selection can be sent to the financial institution.

Abstract: The present disclosure relates to systems and methods for an Automated Teller Machine to issue a secured bank card. An Automated Teller Machine to issue a secured bank card includes one or more memories storing instructions and one or more processors configured to execute instruction to perform operations.

Abstract: In some implementations, a printing system may include a card printer that includes a printing controller and a marking device. The card printer may be configured to receive a first printing instruction or a second printing instruction associated with printing an account identifier on a card. The card printer may receive one of the first printing instruction or the second printing instruction based on whether a risk score, associated with the account identifier, satisfies a threshold. The card printer may print a full account identifier, associated with the card, on a surface of the card based on receiving the first printing instruction. The card printer may print the card without the full account identifier on the surface of the card based on receiving the second printing instruction.

Abstract: Various embodiments are generally directed to the secure transfer of account tokens between devices. For example, a first device may receive an account token stored on a second device using web Bluetooth application programming interfaces (APIs). As another example, the second device may push the account token to the first device.

Abstract: Embodiments disclosed herein generally related to a system and method for rideshare vehicle routing. A computing system receives, from one or more facilities, one or more transaction requests associated with one or more accounts of an organization associated with the computing system. The computing system maps one or more customers to a respective transaction request. For each facility of the one or more facilities, the computing device identifies a geographic location thereof. The computing system categorizes each of the one or more facilities into one or more boundaries. For each boundary, the computing system determines an estimated number of rideshare vehicles to deploy, based at least on a transaction history of each customer of the one or more customers. The computing system transmits the estimated number of rideshare vehicles to be deployed to each boundary to a rideshare computing system.

Abstract: An income analysis platform may receive information associated with employment-related activity of a user, wherein the employment-related activity is associated with an employment status of the user. The income analysis platform may analyze, using an employment analysis model, the information to determine the employment status of the user. The income analysis platform may determine, based on the information and using the employment analysis model, that there is a change in the employment status of the user. The income analysis platform may identify, based on the determined change in the employment status of the user, a service associated with a transaction account of the user. The income analysis platform may determine, based on the change in the employment status, that one or more terms of the service are to be adjusted. The income analysis platform may perform an action associated with adjusting the one or more terms of the service.

Abstract: Identifying unreported issues in computing applications based on customer service interactions and website analytics. A computing system may receive communication data between a CSP and a user. The system may analyze the communication data using an NLP algorithm to identify a plurality of concepts in the communication data. The system may identify, based on the concepts, a target application associated with the communications between the CSP and the user. The system may receive analytics data from a web server hosting the target application and identify a feature of the target application that is not functioning. The system may then assign a priority to the feature of the target application that is not functioning based on a type of the feature and the received analytics data and generate a service issue record for the feature of the target application that is not functioning and the assigned priority.

Abstract: The present disclosure relates to systems and method for securely entering a confidential access code into a user device. A system for allowing secure entry of a confidential access code into a user device may include one or more memories storing instructions and one or more processors configured to execute instruction to perform operations. The operations may include receiving a request for confidential access, prompting the user, via the user interface, to enter a group of inputs into a single-entry field, receiving a dummy sequence of inputs, receiving or providing an indicator signal, receiving an access sequence of inputs, parsing the group of inputs received to identify the access sequence of inputs based on the location of the indicator signal, comparing the access sequence of inputs to the confidential access code associated with the user, and granting or denying access to the confidential information based on the results.

Abstract: Aspects described herein may allow for the application of machine learning techniques to the classification of transactions and/or the prediction of shipping means for such transactions. This may have the effect of generating better insights into user shopping behavior and providing users with better predictions as to how they may expect to receive their purchases. A browser application may be monitored to determine that a user is shopping. A machine learning model may be used to predict shipping data associated with a product and/or merchant associated with the shopping of the user. Predicted shipping data may be displayed to the user, and user feedback may be requested and received to confirm model predictions and review purchases and shipping experiences.

Abstract: In order to facilitate machine learning for prediction using distinct dataset types, systems and methods include collecting content information from archived websites databases. Collecting historical event information from online sources, where the historical event information is associated with a plurality of historical events. Generating event-dependent products training datasets based on the content information and the historical event information, where the event-dependent content training datasets defines for content historical events that are associated with attributes of the content, attribute change of the content, or both. Training an attribute prediction machine learning model based on the event-dependent content training datasets. Applying the trained attribute prediction machine learning model to additional event information to predict, for content, a future attribute estimate, a future attribute change estimate, or both.

Abstract: A device may receive event data associated with a calendar event of a digital calendar of a user and determine, using a machine learning model, a transaction score associated with a probability that the calendar event involves an event transaction. The machine learning model may be trained based on calendar data associated with historical calendar events and transaction data associated with historical transactions. The device may cause, based on the transaction score satisfying a score threshold, the machine learning model to analyze a transaction log of a transaction account of the user to identify transaction information associated with the calendar event. The device may perform an action associated with the transaction information and the calendar event.

Abstract: A method includes displaying on a graphic user interface (GUI) of a computing device of a user, a log of computing operations performed by the user at computing terminals of entity servers respectively managed by entities. The user uses a unique authorization identifier provided by the authorizing entity to authorize the computing operations at the computing terminals of the entity servers. The user provides a fraud indication through the GUI that at least one computing operation in the log is fraudulent. Memory jogging visual units are displayed on the GUI to the user that cause the user to recall performing the at least one computing operation identified as being fraudulent. An entry of the at least one computing operation in an operation database is marked as a valid operation authorized by the user when receiving a recognition indication and potentially fraudulent when no recognition indication by the user.