Abstract: Methods and systems described in this disclosure are directed to authentication of calling parties. The authentication of calling parties applies to simultaneous voice and/or data communications with multiple parties over multiple electronic mediums including a variety of electronic devices. A user can continue to maintain a data exchange session with a representative of an entity offering the goods or services of interest to the user across more than one user device. In some embodiments, a user can invite other parties in a multi-party call involving the user and the representative. Various embodiments for multi-party and multi-device authentication mechanisms are described herein. In some embodiments, the system calculates an estimated call waiting time for a user to speak with the representative.

Abstract: Techniques provided herein relate to registering secondary authentication information with a blockchain. A block chain is stored, having primary authentication information, secondary authentication information, or both that is used in authenticating one or more electronic data action requests provided by a client system to a backend system. The client system, a secondary device, or both registers the secondary device with blockchain node, such that secondary device data is stored as the primary authentication information, the secondary authentication information, or both in the blockchain node.

Abstract: Methods and systems for routing multimedia traffic are described. A method may include receiving a communication originating from a user, transposing an alias transport network over one or more existing networks to route the communication, and routing the communication based on mapping rules.

Abstract: Methods and systems for multiple channel authentication are described. In one embodiment, a request for an interaction is initiated from within a mobile application. The request may include authentication information and contextual information relating to a current exchange between the mobile application and an organization. The user may be authenticated with the authentication information and the request may be routed to a representative based on the contextual information to continue the exchange.

Abstract: A method for routing customer service requests to call centers includes collecting data associated with customer service experience between a customer and a call center regarding a completed customer call. The collected data is analyzed to determine a quality of customer service for one or more completed calls between the customer and the call center. A nature of an incoming customer call is determined. The incoming customer call is routed to a call center based upon making reference to the analyzed collected data such that the nature of the customer call matches with corresponding one or more favorable attributes of the call center.

Abstract: Methods and systems described in this disclosure describe an integration of video sessions across platforms, transforming the user experience. In some embodiments, a user can participate in an interaction via a channel. Next, the system can determine whether the interaction is eligible for a video session with a representative. When the interaction is eligible for the video session, an option for the video session can be displayed on a user interface of the device. After receiving a request for the video session, the video session can be routed to a uniquely skilled representative, where the uniquely skilled representative is determined based, at least in part, on the interaction.

Abstract: Techniques are described for generating metrics about an individual's experience. One of the method describes providing, by at least one processor, the session record as input to at least one computer-processable model that determines, based on the session record, at least one metric for the service session, the at least one model having been trained, using machine learning and based at least partly on survey data for previous service sessions, to provide the at least one metric associated with the individual's experience. The method includes associating, by at least one processor, the metric of the individual's experience with the individual. The method also includes communicating, by at least one processor, the at least one metric for presentation through a user interface of a computing device.

Abstract: Techniques are described for generating metric(s) that predict survey score(s) for a service session. Model(s) may be trained, through supervised or unsupervised machine learning, using training data from previous service sessions between service representative(s) and individual(s). Training data may include, for previous service session(s), a session record (e.g., audio record) of the session and a set of survey scores provided by the serviced individual to rate the session on one or more criteria (e.g., survey questions). The model(s) may be trained to output, based on an input session record, metric(s) that each correspond to a survey score that would have been provided by the individual had they completed the survey. The model may be a concatenated model that is a combination of a language model output from a language classifier recurrent neural network, and an acoustic model output from an acoustic feature layer convolutional neural network.

Abstract: Techniques are described for real time monitoring and tagging of media content generated during a service session between an individual and a service representative (SR). Media content received during a service session may be dynamically tagged with one or more metadata tags during the service session, the tag(s) indicating portion(s) of the media content that potentially include sensitive information. Tagging may be based on a SR's gestures, clicks, keystrokes, mouse-overs, and/or other actions performed in a SR user interface (UI) during the service session. The media content may be redacted based on the tags to remove and/or obfuscate potentially sensitive information.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for coordinating callers with customer service representatives. One of the methods includes in response to receiving identification information from a caller, selecting a virtual machine from a plurality of virtual machines, the virtual machine configured to generate a virtual user interface for an application executing on the virtual machine. The method includes populating the virtual user interface with information about the caller based on the received identification information. The method includes sharing the virtual user interface with an application executing on a computer of a customer service representative. The method includes connecting the caller with the customer service representative.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media are used for coordinating callers with customer service representatives. One of the methods includes identifying a number of callers. The method also includes dynamically adjusting a number of customer service representatives based on the number of callers.

Abstract: Methods and systems for routing multimedia traffic are described. A method may include receiving a communication originating from a user, transposing an alias transport network over one or more existing networks to route the communication, and routing the communication based on mapping rules.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a coordinating callers with customer service representatives is described. One of the methods includes identifying a number of callers. The method also includes dynamically adjusting a number of customer service representatives based on the number of callers.

Abstract: Techniques are described for generating metric(s) that predict survey score(s) for a service session. Model(s) may be trained, through supervised or unsupervised machine learning, using training data such as communications from previous service sessions between service representative(s) and individual(s), and survey scores provided by the serviced individual to rate the session on one or more criteria (e.g., survey questions). The model(s) may be trained to output, based on an input session record, metric(s) that each correspond to a survey score that would have been provided by the individual had they completed the survey. The model may be a concatenated model that combines a language model output from a language classifier recurrent neural network, and an acoustic model output from an acoustic feature layer convolutional neural network. Individuals can be clustered according to the metric(s) and/or other factors, and the cluster(s) can be employed for routing incoming service requests.

Abstract: A method for routing customer service requests to call centers includes collecting data associated with customer service experience between a customer and a call center regarding a completed customer call. The collected data is analyzed to determine a quality of customer service for one or more completed calls between the customer and the call center. A nature of an incoming customer call is determined. The incoming customer call is routed to a call center based upon making reference to the analyzed collected data such that the nature of the customer call matches with corresponding one or more favorable attributes of the call center.

Abstract: Techniques are described for adjusting policy characteristics based on a determined similarity between routes. A similarity metric may be determined indicating the similarity between a first route followed by a vehicle and/or driver and a second (e.g., previous) route followed by the vehicle and/or driver. A similarity metric may indicate the similarity in movements, and changes in movement, exhibited by the vehicle on the routes. The similarity metric may be determined through analysis of real time data collected by in-vehicle sensor(s), mobile user device(s), external sensors or other data sources. Based on the similarity metric, a premium, a deductible, a price, or other characteristic(s) of a policy may be determined. In some examples, policy characteristics may be adjusted (e.g., in real time) based on the analysis according to changing risk conditions if a driver is following routes that are dissimilar from typical routes.

Abstract: Systems and methods are provided for secure access to data actions. In one embodiment, a request to perform an action on electronic data is received from a client device. Primary authentication information is received from the client system, a secondary device, or both. The request is authenticated by: in response to the primary authentication information matching the expected primary authentication of the user profile associated with the primary authentication information, providing expected secondary authentication information to supplement the primary authentication to the client system, the secondary device, or both; receiving inputted secondary authentication information from the client system, the secondary device, or both; and authenticating the request only when the inputted secondary authentication information matches the expected secondary authentication information.

Abstract: Techniques provided herein relate to electronic authentication on public systems. A backend system receives at least one electronic data action request from a publicly available client system that is shared amongst a plurality of users. At least a portion of the primary authentication information is received from a secondary device separate from the publicly available client system. The electronic data action request is authenticated by determining if the primary authentication information matches expected primary authentication information that is expected to complete the electronic data action request. Performance of the electronic data action request is facilitated when the primary authentication information matches the expected primary authentication information.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for sending a forked media stream of an electronic communication between a customer and an agent to an analysis system for a duration. Receiving analysis results obtained from one or more analytics performed on the forked media stream. Then, determining whether to perform one or more operations in response to the analysis results.

Abstract: A method includes in response to receiving identification information from a caller, selecting a virtual machine from a plurality of virtual machines, the virtual machine configured to generate a virtual user interface for an application executing on the virtual machine. The method includes populating the virtual user interface with information about the caller based on the received identification information. The method includes sharing the virtual user interface with an application executing on a computer of a customer service representative. The method includes connecting the caller with the customer service representative.