Methods and systems for physiologically informed account metrics utilizing artificial intelligence

Abstract

A system for physiologically informed account metrics. The system includes a computing device configured to receive from a remote device operated by a third party, an account inquiry. The computing device is further configured to identify a biological extraction related to a particular user. The computing device is further configured to calculate a user account profile utilizing the biological extraction wherein the user account profile contains at least an element of user behavior data and at least an element of user hazard data. The computing device is further configured to generate an account machine-learning model and determine a response to the account inquiry utilizing an account metric.

What is claimed is: 
     
         1 . A system for physiologically informed account metrics utilizing artificial intelligence, the system comprising a computing device, the computing device designed and configured to:
 receive, from a remote device operated by a third party, an account inquiry;   identify a biological extraction related to the particular user;   calculate a user account profile utilizing the user biological extraction, wherein the user account profile contains at least an element of user hazard data, wherein in hazard data describes a user's predisposition to monetary risk based on a user's biological extraction;   generate an account machine-learning model, wherein the account machine-learning model utilizes the user account profile as an input and outputs an account metric; and   determine a response to the account inquiry utilizing the account metric.   
     
     
         2 . The system of  claim 1 , wherein the account inquiry identifies a particular user and an account operation related to the particular user. 
     
     
         3 . The system of  claim 2 , wherein the account operation includes a current proposed monetary agreement between the particular user and the third-party. 
     
     
         4 . The system of  claim 1 , wherein the biological extraction further comprises at least an element of user physiological data. 
     
     
         5 . The system of  claim 1 , wherein the user account profile further contains at least an element of user behavior data. 
     
     
         6 . The system of  claim 1 , wherein the computing device is further configured to authenticate the account inquiry. 
     
     
         7 . The system of  claim 1 , wherein the computing device is further configured to calculate the user account profile to contain a user account score. 
     
     
         8 . The system of  claim 7 , wherein the user account score further comprises at least an account history factor. 
     
     
         9 . The system of  claim 1 , wherein the computing device is further configured to generate the account machine-learning model utilizing account training data and a first machine-learning algorithm. 
     
     
         10 . The system of  claim 9 , wherein the account training data comprises a plurality of account profiles and a plurality of correlated account metrics. 
     
     
         11 . A method for physiologically informed account metrics utilizing artificial intelligence, the method comprising:
 receiving, by a computing device, from a remote device operated by a third party, an account inquiry;   identifying, by the computing device, a biological extraction related to the particular user;   calculating, by the computing device, a user account profile utilizing the user biological extraction, wherein the user account profile contains at least an element of user hazard data, wherein in hazard data describes a user's predisposition to monetary risk based on a user's biological extraction;   generating, by the computing device, an account machine-learning model, wherein the account machine-learning model utilizes the user account profile as an input and outputs an account metric; and   determining, by the computing device, a response to the account inquiry utilizing the account metric.   
     
     
         12 . The method of  claim 11 , wherein the account inquiry identifies a particular user and an account operation related to the particular user. 
     
     
         13 . The method of  claim 12 , wherein the account operation includes a current proposed monetary agreement between the particular user and the third-party. 
     
     
         14 . The method of  claim 11 , wherein the biological extraction further comprises at least an element of user physiological data. 
     
     
         15 . The method of  claim 11 , wherein the user account profile further contains at least an element of user behavior data. 
     
     
         16 . The method of  claim 11 , further comprising authenticating, by the computing device, the account inquiry. 
     
     
         17 . The method of  claim 11 , further comprising calculating, by the computing device, the user account profile to contain a user account score. 
     
     
         18 . The method of  claim 17 , wherein the user account score further comprises at least an account history factor. 
     
     
         19 . The method of  claim 1 , further comprising generating, by the computing device, the account machine-learning model utilizing account training data and a first machine-learning algorithm. 
     
     
         20 . The method of  claim 19 , wherein the account training data comprises a plurality of account profiles and a plurality of correlated account metrics.