Abstract: Systems and methods for generating personalized navigation menus 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 account data associated with a plurality of accounts and receiving navigation menu data associated with the accounts. The operations may include training a model based on the account data and the navigation menu data. The operations may include receiving a request associated with a user and receiving user account data associated with the user. The operations may include generating, using the model, a navigation menu based on the request and the user account data. The operations may include providing the navigation menu.

Abstract: A device causes a communication session to be established between the device and a user device to allow the device and the user device to communicate speech, and receives user speech from the user device. The device processes the user speech using a natural language processing technique to determine a plurality of characteristics of the user speech, and updates a speech generation setting of a plurality of speech generation settings based on the plurality of characteristics of the user speech. The device generates, after updating the speech generation setting, device speech using a text-to-speech technique based on the speech generation setting, and sends the device speech to the user device.

Abstract: First data indicative of a first plurality of transactions by a user may be processed to generate first behavioral information describing the user. The first behavioral information may be displayed by an interactive user interface. A user input made in response to the first behavioral information may be received and analyzed to generate user preference information indicating a relationship between the first user input and the first behavioral information. Second data indicative of a second plurality of transactions by the user may be received and processed with the user preference information to generate second behavioral information describing the user. The second behavioral information may be displayed by the interactive user interface differently from the first behavioral information by the interactive user interface as a result of the processing of the second data and the user preference information together.

Abstract: 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 providing biometric detection of coercion of a user. The system may detect a trigger event associated with a potential transfer of funds and may receive user biometric data. The system may determine, based on stored user biometric data and the detected user biometric data, a confidence level that the stored user biometric data is indicative of biological information representative of a user being in a stressed state. The system may initiate one or more precautionary safety measures.

Abstract: A device communicates with a user device via a communication session, determines user information relating to the user device or a user of the user device, and determines that the user device is placed on a hold status. The device determines, using a machine learning model, a type of media item to be presented to the user device, where the machine learning model has been trained to identify types of media items to present to user devices when the user devices are placed in the hold status, and selects a media item corresponding to the type of media item. The device presents the media item to the user device via the communication session, determines that the user device is no longer placed on the hold status, and causes the media item to cease being presented.

Abstract: A device receives, from a user device, a communication request that includes information identifying a user of the user device, an organization, and at least one reason for the communication request. The device determines, based on the communication request, information concerning the user, a telephone number associated with the organization, and a menu of an interactive voice response (IVR) system device associated with the telephone number. The device communicates, based on the information concerning the user, the menu of the IVR system device, and the at least one reason for the communication request, with the IVR system device via a communication session initiated based on the telephone number. The device determines, based on communicating with the IVR system device, a time that the user is to interact with the IVR system device via the communication session, and causes the user device to join the communication session at the time.

Abstract: A device receives, from a user device, a communication associated with a support issue encountered by a user of the user device and assigns the communication to a position in a support queue based on when the communication is received, wherein the support queue includes data identifying positions of other communications received from other users, and data identifying when the other communications were received. The device processes data identifying the communication and historical communication data describing prior communications associated with the user, with a model, to determine an average time spent on hold by the user for the prior communications. The device modifies the position of the communication in the support queue based on the average time and performs one or more actions based on modifying the position of the communication in the support queue.

Abstract: A device causes a communication session to be established between the device and a user device to allow the device and the user device to communicate speech, and receives user speech from the user device. The device processes the user speech using a natural language processing technique to determine a plurality of characteristics of the user speech, and updates a speech generation setting of a plurality of speech generation settings based on the plurality of characteristics of the user speech. The device generates, after updating the speech generation setting, device speech using a text-to-speech technique based on the speech generation setting, and sends the device speech to the user device.

Abstract: 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 providing biometric detection of coercion of a user. The system may detect a trigger event associated with a potential transfer of funds and may receive user biometric data. The system may determine, based on stored user biometric data and the detected user biometric data, a confidence level that the stored user biometric data is indicative of biological information representative of a user being in a stressed state. The system may initiate one or more precautionary safety measures.

Abstract: 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 providing biometric detection of coercion of a user. The system may detect a trigger event associated with a potential transfer of funds and may receive user biometric data. The system may determine, based on stored user biometric data and the detected user biometric data, a confidence level that the stored user biometric data is indicative of biological information representative of a user being in a stressed state. The system may initiate one or more precautionary safety measures.

Abstract: A device communicates with a user device via a communication session, determines user information relating to the user device or a user of the user device, and determines that the user device is placed on a hold status. The device determines, using a machine learning model, a type of media item to be presented to the user device, where the machine learning model has been trained to identify types of media items to present to user devices when the user devices are placed in the hold status, and selects a media item corresponding to the type of media item. The device presents the media item to the user device via the communication session, determines that the user device is no longer placed on the hold status, and causes the media item to cease being presented.

Abstract: First data indicative of a first plurality of transactions by a user may be processed to generate first behavioral information describing the user. The first behavioral information may be displayed by an interactive user interface. A user input made in response to the first behavioral information may be received and analyzed to generate user preference information indicating a relationship between the first user input and the first behavioral information. Second data indicative of a second plurality of transactions by the user may be received and processed with the user preference information to generate second behavioral information describing the user. The second behavioral information may be displayed by the interactive user interface differently from the first behavioral information by the interactive user interface as a result of the processing of the second data and the user preference information together.

Abstract: Provided, in an aspect, is a method for improved management of transaction data from a financial services computer network. The method includes receiving details for a first purchase, detecting that the first purchase is a trigger purchase, obtaining secondary details for the first purchase, receiving details for a later-made second purchase and additional purchases made between the first purchase and second purchase, and determining that the first purchase and the second purchase belong to the same experience set and that the additional intervening purchases do not belong to the same experience set as the first purchase and the second purchase.

Abstract: Provided, in an aspect, is a system for managing transactions from a financial services computer network. The system has a scalable architecture, and includes a database, one or more processors, a plurality of experience matchers, and a transaction hub. Each experience matcher is associated with a different experience set type, and can receive a transaction list and return an identified experience set. The transaction hub can communicate with multiple experience matchers, and can receive experience sets from the matchers after sending them a list of transactions.

Abstract: Provided, in an aspect, is a method for improved visualization of transaction data from a financial services computer network. The method includes receiving, at a computing device, a plurality of experience sets; presenting, on a display of the computing device, a graphical user interface (GUI); and updating the GUI in response to receiving a revision to the plurality of experience sets. Each experience set contains one or more transactions that relate to each other. The GUI includes a scrollable list having at least a portion of the experience set name for experience sets within a selected time period; and a calendar for the time period showing, for each day with at least one experience, a graphical element indicative of a total of all experience set amounts in that day.

Abstract: A device obtains information concerning a plurality of customer service representatives to identify a customer service representative and a user device associated with the customer service representative. The device selects a test issue of a plurality of test issues to be presented to the customer service representative, and, based on the test issue, a virtual assistant to converse with the customer service representative. The device initiates, based on an availability of the user device, a communication session with the user device, and causes the virtual assistant to converse with the customer service representative regarding the test issue. The device obtains data concerning a performance of the customer service representative during the communication session, processes the data using a machine learning model to determine a performance score for the customer service representative, and causes, based on the performance score for the customer service representative, at least one action to be performed.

Abstract: A device receives, from a user device, a communication associated with a support issue encountered by a user of the user device and assigns the communication to a position in a support queue based on when the communication is received, wherein the support queue includes data identifying positions of other communications received from other users, and data identifying when the other communications were received. The device processes data identifying the communication and historical communication data describing prior communications associated with the user, with a model, to determine an average time spent on hold by the user for the prior communications. The device modifies the position of the communication in the support queue based on the average time and performs one or more actions based on modifying the position of the communication in the support queue.

Abstract: A device causes a communication session to be established between the device and a user device to allow the device and the user device to communicate speech, and receives user speech from the user device. The device processes the user speech using a natural language processing technique to determine a plurality of characteristics of the user speech, and updates a speech generation setting of a plurality of speech generation settings based on the plurality of characteristics of the user speech. The device generates, after updating the speech generation setting, device speech using a text-to-speech technique based on the speech generation setting, and sends the device speech to the user device.

Abstract: A device receives, from a user device, a communication request that includes information identifying a user of the user device, an organization, and at least one reason for the communication request. The device determines, based on the communication request, information concerning the user, a telephone number associated with the organization, and a menu of an interactive voice response (IVR) system device associated with the telephone number. The device communicates, based on the information concerning the user, the menu of the IVR system device, and the at least one reason for the communication request, with the IVR system device via a communication session initiated based on the telephone number. The device determines, based on communicating with the IVR system device, a time that the user is to interact with the IVR system device via the communication session, and causes the user device to join the communication session at the time.

Abstract: A device communicates with a user device via a communication session, determines user information relating to the user device or a user of the user device, and determines that the user device is placed on a hold status. The device determines, using a machine learning model, a type of media item to be presented to the user device, where the machine learning model has been trained to identify types of media items to present to user devices when the user devices are placed in the hold status, and selects a media item corresponding to the type of media item. The device presents the media item to the user device via the communication session, determines that the user device is no longer placed on the hold status, and causes the media item to cease being presented.