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 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: Various embodiments may be generally directed to techniques for planning currency exchange transactions based on customer-provided budgeting information associated with international travel. In some embodiments, an apparatus may comprise a network interface and processing circuitry coupled to the network interface, and the processing circuitry may be operative to forecast future requirements for one or more currencies based on travel budgeting information associated with scheduled international travel. In an example embodiment, the processing circuitry may receive travel budgeting information indicating one or more budgeted amounts of a first currency, determine a marginal currency requirement projection for a second currency based on the one or more budgeted amounts of the first currency, and update a currency requirement forecast for the second currency based on the marginal currency requirement projection. The embodiments are not limited in this context.

Abstract: A platform receives transaction information for an entity, where the transaction information identifies a plurality of transactions associated with the entity, and receives entity information associated with the entity. The platform identifies, using a first model, a selected set of transactions based on the transaction information and the entity information, where the first model outputs information identifying the selected set of transactions based on the selected set of transactions being associated with an event, a theme, or a transaction parameter. The platform determines, using a second model, potential modifications to a document based on the selected set of transactions, where the second model receives the information identifying the selected set of transactions or information identifying the event, the theme, or the transaction parameter, and where the second model outputs information identifying the potential modifications.

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 processing platform may receive a plurality of images. The processing platform may determine respective asset types of the plurality of assets based on a computer vision technique. The processing platform may determine respective estimated values of the plurality of assets based on the respective asset types. The processing platform may provide information identifying the respective estimated values of the plurality of assets to two or more recipients. The processing platform may receive allocation information. The processing platform may determine a selected allocation of the plurality of assets for the two or more recipients based on the allocation information and using a second model. The processing platform may perform one or more actions based on the selected allocation.

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 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 platform receives transaction information for an entity, where the transaction information identifies a plurality of transactions associated with the entity, and receives entity information associated with the entity. The platform identifies, using a first model, a selected set of transactions based on the transaction information and the entity information, where the first model outputs information identifying the selected set of transactions based on the selected set of transactions being associated with an event, a theme, or a transaction parameter. The platform determines, using a second model, potential modifications to a document based on the selected set of transactions, where the second model receives the information identifying the selected set of transactions or information identifying the event, the theme, or the transaction parameter, and where the second model outputs information identifying the potential modifications.

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 processing platform may receive a plurality of images. The processing platform may determine respective asset types of the plurality of assets based on a computer vision technique. The processing platform may determine respective estimated values of the plurality of assets based on the respective asset types. The processing platform may provide information identifying the respective estimated values of the plurality of assets to two or more recipients. The processing platform may receive allocation information. The processing platform may determine a selected allocation of the plurality of assets for the two or more recipients based on the allocation information and using a second model. The processing platform may perform one or more actions based on the selected allocation.

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 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: 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: 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 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: 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 processing platform may receive a plurality of images. The processing platform may determine respective asset types of the plurality of assets based on a computer vision technique. The processing platform may determine respective estimated values of the plurality of assets based on the respective asset types. The processing platform may provide information identifying the respective estimated values of the plurality of assets to two or more recipients. The processing platform may receive allocation information. The processing platform may determine a selected allocation of the plurality of assets for the two or more recipients based on the allocation information and using a second model. The processing platform may perform one or more actions based on the selected allocation.

Abstract: A platform receives transaction information for an entity, where the transaction information identifies a plurality of transactions associated with the entity, and receives entity information associated with the entity. The platform identifies, using a first model, a selected set of transactions based on the transaction information and the entity information, where the first model outputs information identifying the selected set of transactions based on the selected set of transactions being associated with an event, a theme, or a transaction parameter. The platform determines, using a second model, potential modifications to a document based on the selected set of transactions, where the second model receives the information identifying the selected set of transactions or information identifying the event, the theme, or the transaction parameter, and where the second model outputs information identifying the potential modifications.

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.