Abstract: A method for reducing pre-authorization turnaround time is disclosed. The method includes, at a database, receiving historical data including a historical pre-authorization request and clinical information associated with a historical pre-authorization request. The method further includes receiving real-time data using an API gateway including real-time pre-authorization requests wherein the real-time data includes the real-time pre-authorization procedure and a clinical document category. The method further includes removing irrelevant data from real-time data and historical data to produce clean historical data and clean real-time data. The method further includes extracting data features required to train a machine learning model from the clean historical data and clean real-time data. The method further includes training the machine learning model by applying the extracted data features from the clean historical data and clean real-time data.

Abstract: A system for real-time health care insurance underwriting is described comprising a quotation module, a verification module, and an underwriting module. The quotation module receives user input relating to a user's health status via an online user interface. The verification module verifies the user input against information stored in a database to form a list of inconsistencies and present the user via the online user interface with a request to validate at least some information within the user input. The underwriting module automatically creates a debit score based on one or more of at least a portion of the user input and the validated information and generates an underwriting decision based at least in part on the debit score. The quotation module presents one or more offers to sell insurance to the user via the online user interface, the one or more offers based on the underwriting decision.