Patent ID: 12243081

DETAILED DESCRIPTION

Reference will now be made in greater detail to a preferred embodiment of the invention, an example of which is illustrated in the accompanying drawings. Wherever possible, the same reference numerals will be used throughout the drawings and the description to refer to the same or like parts.

As used in this application, the terms “component”, module,” “system,” “interface,” or the like are generally intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a controller and the controller can be a component. One or more components can reside within a process and/or thread of execution and a component can be localized on one computer and/or distributed between two or more computers. As another example, an interface can include I/O components as well as associated processor, application, and/or API components.

FIG.1is a flow diagram of an embodiment of interactive method10for interactively presenting one or more relevant benefits products based on eligibility to a user and enrolling of the user with determined benefits products. In step11, a session with a virtual assistant is initiated through an interface. For example, the user can initiate the session with the system using an interface of a phone, SMS, chat, mobile app, or Messenger. Once a session is initiated, in step11, the user is introduced to a virtual assistant. The virtual assistant can greet and prompt the user to answer a series of pre-qualifying questions in step12. In one embodiment, the system can internalize the user's answers and not repeat questions which limits buyer or consumer frustration. The virtual assistant presents audio to the user and receives audio from the user. The virtual assistant is artificial intelligence based to receive voice via an audio interface which is transferred to a server to be interpreted with artificial intelligence in real time. Responses from the server can be sent back via audio to the user's audio interface.

In step13, during the session between the user and the virtual assistant, the system can adjust parameters of the virtual assistant to accommodate the user. For example, language and tone of the virtual assistant can be selected or adjusted. The virtual assistant can utilize commercial technologies including, for example, Sentiment Analysis, Tone Analyzer and Personality Insights to adjust parameters of the virtual assistant.

In step14, the virtual assistant prompts the user to describe the benefits products which are of interest to the user for purchase. In step15, the system can evaluate the user's level of intent or urgency to purchase the benefits product in real time. In step16, the system can identify and present relevant benefits products to the user through the virtual assistant based on eligibility determined by responses from the user presented to the virtual assistant. In one embodiment, the virtual assistant can utilize third party rate quoting services and specific underwriting guidelines and requirements from multiple benefits providers to identify and present relevant benefits products through the virtual assistant to the user.

In step17, the virtual assistant can scan a network of live producers in a resident state of a user to identify a producer offering benefits products presented to the user during the session. In step18, the virtual assistant can transfer the user, which can be a buyer or consumer, to a selected producer for enrollment. In one embodiment, the virtual assistant automatically transfers the user to the selected producer for enrollment. In some embodiments, the transfer of the user to a producer is made via a telephone or audio connection. Alternatively, the transfer of the user to a producer is made via an email or text. The user can select the medium for the type of transfer. In some embodiments, if after step11, step12cannot be completed, the virtual assistant can transfer the buyer or consumer to a selected producer enrollment in step18. In some embodiments, if after step12, step13cannot be completed, the virtual assistant can transfer the buyer or consumer to a selected producer for enrollment in step18. In some embodiments, if after step13, step14cannot be completed, the virtual assistant can transfer the buyer or consumer to a selected producer for enrollment in step18. In some embodiments, if after step14, step15cannot be completed, the virtual assistant can transfer the buyer or consumer to a selected producer for enrollment in step18. In some embodiments, if after step15, step16cannot be completed, the virtual assistant can transfer the buyer or consumer to a selected producer for enrollment in step18.

FIG.2is a schematic diagram of an implementation of system100. System100includes user interface102which is accessed by user101. User interface102can be an electronic device such as a mobile telephony device including for example a mobile device, cell phone or smartphone. Mobile telephony devices can communicate with fourth generation (4G) or fifth generation (5G) cellular communications. It will be appreciated that other mobile telephony devices and networks can be used in accordance with the teachings of the present invention. User interface102communicates audio103to virtual assistant104. Alternatively, user101communicates directly with virtual assistant104.

Virtual assistant104can be a component which is artificial intelligence based to receive audio103. Audio103can be digitized or interpreted by virtual assistant104into data105. In one embodiment automated speech recognition (ASR)120can be performed at virtual assistant104or automated speech recognition (ASR)121can be performed server108to digitally convert received audible speech into transcribed text. Virtual assistant104can utilize commercial technologies including for example Sentiment Analysis, Tone Analyzer and Personality Insights to analyze data105and adjust parameters of virtual assistant104. Virtual assistant104can be implemented in a natural language conversational manner for receiving information from user101and automatically generating responses to user101during the conversation. Virtual assistant104can have cognitive learning abilities. Virtual assistant104can include natural language processing and context switching. Virtual assistant104can include semantic memory, episodic memory for learning from past conversations, analytic memory for understanding trend of data, affective memory for understanding emotion and deep back projection networks for learning process flows via empirical learning. In some embodiments, the part of speech of content of the utterance of virtual assistant104is determined based on using a natural language parser (e.g., Stanford Natural Language Processing Group software or others as are known in the art) to parse the utterance. The part of speech of content of the utterance can indicate if the content is a noun phrase, verb phrase, and/or theme. In some embodiments, the type of speech of content of the utterance of virtual assistant104is determined based on using a natural language parser (e.g., Stanford Natural Language Processing Group software or others as are known in the art) to parse the utterance. Virtual assistant104using artificial intelligence techniques can employ one of numerous methodologies for learning from data and then drawing inferences and/or making determinations related to dynamically storing information across multiple storage units (e.g., Hidden Markov Models (HMMs) and related prototypical dependency models, more general probabilistic graphical models, such as Bayesian networks, e.g., created by structure search using a Bayesian model score or approximation, linear classifiers, such as support vector machines (SVMs), non-linear classifiers, such as methods referred to as “neural network” methodologies, fuzzy logic methodologies, and other approaches that perform data fusion, etc.) in accordance with implementing various automated aspects described herein. The type of speech of content of the utterance can indicate if the content is a noun phrase, verb phrase, and/or theme. In some embodiments, the domain of the content of the utterance of virtual assistant104is determined based on pattern matching. Virtual assistant104can include components such as a processor, memory, storage, microphone, learning module, and operating system. An example, virtual assistant or virtual producer is described in U.S. Pat. No. 9,812,151 hereby incorporated by reference into this application. In some embodiments, virtual assistant104is a bot. A bot can be a software program that performs automated, repetitive, pre-defined tasks. Bots typically imitate or replace human user behavior. In some embodiments, virtual assistant104is a chatbot. A chatbot can be a software application used to conduct an on-line chat conversation via text or text-to-speech, in lieu of providing direct contact with a live human agent. The chatbot can simulate the way a human would behave as a conversational partner. In some embodiments, virtual assistant104uses conversational artificial intelligence (AI). In some embodiments, virtual assistant104is a cognitive digital assistant including a cognitive platform based on artificial intelligence (AI).

Data105is transferred over network106to server108. For example, network106can be the Internet. Server108accesses third party data interface109. For example, server108can access data105directly from databases of third party providers. For example, third party data interface109can be an interface to a third-party system for accessing third-party rate quote data. For example, server108can access third party data115directly from databases of third party providers. In one embodiment, application programming interface (API)113of server108or application programming interface (API)111of virtual assistant104is activated to communicate with application programming interface (API)114of third party data interface109to access data115from third party data interface109. Alternatively, server108can access data115over network106. For example, third party data interface109can include third party rate quoting services and specific underwriting guidelines and requirements from multiple benefits providers. Virtual assistant104may include a server, computer, laptop, PC, mobile device, or the like that includes a processor, a memory, and a communication device. Virtual assistant104and server108may include a plurality of computing devices connected together, e.g., via a network. The processor may include any general purpose or application-specific processor. The memory may include one or more tangible, non-transitory, machine-readable media.

Virtual assistant104and server108can connect to benefits providers' interface110over network106. In one embodiment, benefits providers' interface110includes one or more application programming interface(s) (API(s))132. One or more benefits providers112communicate data131directed to benefits products using benefits providers' interface110. In one embodiment, application programming interface (API)113of server108or application programming interface (API)111of virtual assistant104is activated to communicate with application programming interface (API)132of benefits providers interface110to access data131from benefits provider interface110. Virtual assistant104or server108can scan one or more benefits providers112over network106. Virtual assistant104can establish a connection between one or more benefits providers112and user101using virtual assistant104and user interface102. Data105, third-party data115and application requirements data131can be stored in memory150of system server108. In one embodiment, API111, API113, API114and API132are web based APIs.

FIG.3is a flow diagram of an illustrative embodiment of a method to implement step15ofFIG.1for evaluating a user's level of intent or urgency to purchase a benefits product. In step302, the description of the benefits products which are of interest to the user for purchase which was received by the virtual assistant is converted to text. For example, a speech to text conversion can be performed at server108with automated speech recognition (ASR)121or virtual assistant105with automated speech recognition (ASR)120as shown inFIG.2. The text can include one or more words, phrases or sentences.

Referring toFIG.3, in step304, a value of a tone score for each word, phrase or sentence in the text is determined. The tone score can be based on each individual word within the phrase or sentence. The tone score is the likelihood the word, phrase or sentence has characteristics of a particular tone. Example, tones can include tentative, anger, analytical, fear, joy, sadness and confidence. The tone score can be determined on a scale of 0 to 1.0 with a minimum score of 0 and a maximum score of 1.0. It will be appreciated that other scales can be used in accordance with the teachings of the present invention. In step306, an analysis of the tone scores determined for one or more pre-selected types of tones is performed. For example, the analysis of the tone scores can be an average of each of the tone scores received for a particular tone, such as for example, tentative, anger and analytical.

In step308, from the analysis of the tone scores, a determination is made to either transfer the call or to terminate the call. For example, it can be determined if the call should be transferred to a producer. The determination can be made from comparing the analyzed tone scores to a threshold tolerance value. For example, if one or more of the analyzed tone scores are less than the threshold tolerance value, the call will be transferred, and if one or more of the analyzed tone scores are greater than the threshold tolerance value, the call will be terminated.

An example of implementation of the method for evaluating a user's level of intent or urgency to purchase a benefits product is described by reference toFIGS.2,3and4A-4E. An example, virtual assistant statement402can be uttered by virtual assistant104as shown inFIG.2andFIG.4A. In response to virtual assistant statement402, a user statement404is uttered by user101at user interface102. Speech to text conversion of user statement404can be performed at server108or virtual assistant104. Referring toFIG.4B, each sentence of text405of user statement404is assigned a sentence identification406. An implementation of step304determines a value of a tone score408of each type of tone409for each sentence identification406. Referring toFIG.4C, an implementation of step306, determines analysis score410of tone scores408for each type of tone409. For example, analysis score410of tone scores408can be an average of each of the tone scores408received for a particular tone409. Referring toFIG.4D, an implementation of step308determines result420from analysis score410of tone scores404to either transfer the call or to terminate the call based on a comparison of analysis score410to threshold tolerance value422. If result420indicates it is acceptable to transfer since analysis score410is less than threshold score422, virtual assistant104utters virtual assistant statement430. If result420indicates the call should be terminated since analysis score410is greater than threshold score422, virtual assistant105or server108terminates the call session.

Embodiments of the present invention can be implemented in connection with a special purpose or general purpose computer device that includes both hardware and/or software components, including special purpose or general purpose computers.

Embodiments can also include physical computer-readable media and/or intangible computer-readable media for carrying or having computer-executable instructions, data structures, and/or data signals stored thereon. Such physical computer-readable media and/or intangible computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such physical computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, other semiconductor storage media, or any other physical medium which can be used to store desired data in the form of computer-executable instructions, data structures and/or data signals, and which can be accessed by a general purpose or special purpose computer. Within a general purpose or special purpose computer, intangible computer-readable media can include electromagnetic means for conveying a data signal from one part of the computer to another, such as through circuitry residing in the computer.

When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computer, hardwired devices for sending and receiving computer-executable instructions, data structures, and/or data signals (e.g., wires, cables, optical fibers, electronic circuitry, chemical, and the like) should properly be viewed as physical computer-readable mediums while wireless carriers or wireless mediums for sending and/or receiving computer-executable instructions, data structures, and/or data signals (e.g., radio communications, satellite communications, infrared communications, and the like) should properly be viewed as intangible computer-readable mediums. Combinations of the above should also be included within the scope of computer-readable media.

Computer-executable instructions include, for example, instructions, data, and/or data signals which cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions. Although not required, aspects of the invention have been described herein in the general context of computer-executable instructions, such as program modules, being executed by computers, in network environments and/or non-network environments. Generally, program modules include routines, programs, objects, components, and content structures that perform particular tasks or implement particular abstract content types. Computer-executable instructions, associated content structures, and program modules represent examples of program code for executing aspects of the methods disclosed herein.

While the subject matter has been described above in the general context of computer-executable instructions of a program that runs on one or more computers, those skilled in the art will recognize that the subject matter described herein also can be implemented in combination with other program modules. Generally, program modules include routines, programs, components, data structures, etc. that perform particular tasks and/or implement particular abstract data types. Moreover, those skilled in the art will appreciate that the inventive methods can be practiced with other computer system configurations, including single-processor, multiprocessor or multi-core processor computer systems, mini-computing devices, mainframe computers, as well as personal computers, hand-held computing devices (e.g., personal digital assistant (PDA), phone, watch . . . ), microprocessor-based or programmable consumer or industrial electronics, and the like. The illustrated aspects can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. However, some, if not all aspects of the claimed subject matter can be practiced on stand-alone computers. In a distributed computing environment, program modules can be located in both local and remote memory storage devices.

Embodiments may also include computer program products for use in the systems of the present invention, the computer program product having a physical computer-readable medium having computer readable program code stored thereon, the computer readable program code comprising computer executable instructions that, when executed by a processor, cause the system to perform the methods of the present invention.

It is to be understood that the above described embodiments are illustrative of only a few of the many possible specific embodiments, which can represent applications of the principles of the invention. Numerous and varied other arrangements can be readily devised in accordance with these principles by those skilled in the art without departing from the spirit and scope of the invention.