US Patent Application 17826240. SYSTEMS AND METHODS FOR VALIDATING THE ACCURACY OF AN AUTHENTICATED, END-TO-END, DIGITAL RESPONSE SYSTEM simplified abstract
SYSTEMS AND METHODS FOR VALIDATING THE ACCURACY OF AN AUTHENTICATED, END-TO-END, DIGITAL RESPONSE SYSTEM
Organization Name
Inventor(s)
Ganesh Chandrasekar of Plano TX (US)
SYSTEMS AND METHODS FOR VALIDATING THE ACCURACY OF AN AUTHENTICATED, END-TO-END, DIGITAL RESPONSE SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 17826240 titled 'SYSTEMS AND METHODS FOR VALIDATING THE ACCURACY OF AN AUTHENTICATED, END-TO-END, DIGITAL RESPONSE SYSTEM
Simplified Explanation
This patent application describes a system and method for validating the accuracy of a digital response system.
- The system curates a database of training data, including historical profile data and interaction data.
- Profile data includes user names, identifiers, and financial instruments.
- Interaction data includes records of user interactions with the digital response system.
- The system uses a machine-learning engine to generate a test profile with fake information and authentication data.
- The test profile is logged into the digital response system, and a simulated conversation is fed as input.
- The system receives a response from the digital response system and scores its accuracy.
- An accuracy report is generated based on the score and submitted to a system administrator.
Original Abstract Submitted
Systems and methods for validating the accuracy of an authenticated, end-to-end, digital response system are provided. Methods may include curating a database of training data, including historical profile data and historical interaction data. Profile data may include a name, an identifier, and a set of financial instruments for a plurality of system users. Interaction data may include records of multi-step interactions between the system users and the digital response system. Methods may include generating, via a machine-learning (ML) engine and based on the training data: a test profile including a fictitious name, a fictitious identifier, and a fictitious set of financial instruments; authentication data for the test profile including a username and password that are operational for authenticating the test profile to the digital response system; and a simulated conversation for the test profile including an utterance that is associated with an intended request. Methods may include: initiating a validation session by logging the test profile into the digital response system using the authentication data; feeding the simulated conversation as an input to the digital response system; receiving a response from the digital response system; scoring the accuracy of the response vis-à-vis the intended request; generating an accuracy report based on the accuracy score; and submitting the accuracy report to a system administrator.
