Abstract: The present embodiments relate to on demand generation of curated audio content. Responsive to initiation of an electronic communication by a client, audio relating to a client speaking to the operator can be processed to derive a series of insights relating to features of the audio. Previously recorded audio relating to the operator can be combined with a text-based script to generate audio content. The audio content can be modified using the series of derived insights. The modified audio content can include a series of disclaimers that are played back to the client. Generation of the modified audio content can be dynamically generated responsive to detecting a trigger that allows for on-demand generation of the modified audio content.

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: Systems and methods are provided for secure access to data actions. In one embodiment, secondary devices are identified based upon communicative coupling with a primary device. The secondary devices are registered as trusted devices for subsequent authentication.

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: A system for measuring effectiveness of a customer service platform comprises a server configured to receive a first set of data related to an interaction between a first person and an automated communication channel, receive a second set of data related to a conversation between the first person and a second person on a call, determine, from the first set of data, a third set of word(s) that describe an intent of the first person to perform a task via the customer service platform, determine, from the second set of data, a fourth set of word(s) that describes an outcome accomplished during the call, calculate a value that describes a similarity between the third set of word(s) and the fourth set of word(s), and determine an effectiveness measure of the customer service platform based at least in part on a comparison of the value with a pre-determined threshold.

Abstract: Techniques provided herein relate to electronic data access requests. An access system receives at least one electronic data action request from a client. At least a portion of the data access authentication information is sourced from a secondary device connected to an intermediary device. The electronic data action request is authenticated based upon the data access authentication information.

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: 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: 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: A system and method for intelligently routing calls between customers and agents. The system and method use knowledge graphs to generate route recommendations for a route selection system. The system uses dynamically selected objective functions to generate the route recommendations. The objective functions may be selected according to the intent of the call. The system and method can also be used to reroute ongoing calls when the intent of the call changes.

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: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving first voice data from a user, receiving behavior data associated with the user, and determining that the user is authentic at least partially based on voice recognition of the first voice data, and behavior analysis of the behavior data, and subsequently: prompting one or more spoken commands from the user, receiving second voice data representative of at least one spoken command of the user to trade at least one financial instrument, providing trade data for executing the trade of the at least one financial instrument, and determining that the trade data is valid at least partially based on the second voice data, and in response, initiating execution of the trade.

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, secondary device data is associated with a user profile, such that the secondary device data may be subsequently used to authenticate a user associated with the user profile.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for accessing an electronic contract that includes a provision that is verifiable through control of a remote device. Sending instructions to the remote device that cause the remote device to obtain data representative of whether the provision in the electronic contract has been performed. Determining based on the data, that at least a portion of the provision has been performed. In response to determining that at least a portion of the provision has been performed, causing a term of the electronic contract to be at least partially executed.

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 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 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 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 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.