User interaction artificial intelligence chat engine for integration of automated machine generated responses

A system for guiding a user interaction during a phone call or a chat session, said system comprising:

• a computer with one or more processor and memory, where the computer executes a machine learning algorithm configured to guide dialog and actions during a phone call or a chat session with a user concerning a user matter;
• and
• a network connection operatively connecting the user via a user device to the computer,
• where the machine learning algorithm includes a neural network configured to perform steps including:
• asking an initial question of the user and receiving a response from the user;
• determining a next step based on the response, where the next step is determined by the machine learning algorithm based on probability of a most rapid resolution of the user matter, and where the next step is selected from a group consisting of asking another question of the user and performing an action;
• determining a next question when the next step is asking another question of the user;
• determining a next action when the next step is performing an action, where the next action is selected from a group consisting of authenticating an identity of the user, providing account information to the user, performing an account transaction for the user, providing assistance to the user in logging into an electronic data system, and connecting a live agent;
• connecting a live agent into the phone call or the chat session when connecting the live agent is determined as the next action, where connecting the live agent is determined as the next action for reasons including ambiguity in the response from the user and complexity of the user matter;
• presenting the next question or the next action to the user;
• receiving a user response to the next question or next action which was presented;
• determining if the user matter has been resolved based on the user response;
• returning to determining a next step when the user matter has not been resolved;
• and
• ending the phone call or the chat session and storing data describing the user interaction when the user matter has been resolved,
• and where the neural network is initially trained via supervised learning using a dataset of previous user interactions supplemented with decision points, actions which resulted in matter resolution, and user satisfaction level.

A method for guiding a user interaction during a phone call or a chat session, said method comprising:

• providing a computer with one or more processor and memory, where the computer executes a machine learning algorithm configured to guide dialog and actions during a phone call or a chat session with a user concerning a user matter, and the computer uses a network connection to connect to the user via a user device,
• where the machine learning algorithm is configured to perform steps including:
• asking an initial question of the user and receiving a response from the user;
• determining a next step based on the response, where the next step is determined by the machine learning algorithm based on probability of a most rapid resolution of the user matter, and where the next step is selected from a group consisting of asking another question of the user and performing an action;
• determining a next question when the next step is asking another question of the user;
• determining a next action when the next step is performing an action, where the next action is selected from a group comprising consisting of authenticating an identity of the user, providing account information to the user, performing an account transaction for the user, providing assistance to the user in logging into an electronic data system, and connecting a live agent;
• connecting a live agent into the phone call or the chat session when connecting the live agent is determined as the next action, where connecting the live agent is determined as the next action for reasons including ambiguity in the response from the user and complexity of the user matter;
• presenting the next question or the next action to the user;
• receiving a user response to the next question or next action which was presented;
• determining if the user matter has been resolved based on the user response;
• returning to determining a next step when the user matter has not been resolved;
• and
• ending the phone call or the chat session and storing data describing the user interaction when the user matter has been resolved.