Abstract: Aspects of the present disclosure describe a system comprising a computer-readable storage medium storing a program and method for analyzing one or more electronic submissions based on a rule set to generate a risk assessment of an applicant. In particular, some embodiments analyze one or more electronic submissions for an applicant of an insurance policy (or insurance product) based on a rule set (e.g., structured, machine-readable rule set) that describes one or more rules, guidelines, or parameters that codify an insurance carrier's risk appetite. Based on the analysis, various embodiments generate a risk assessment for the applicant, where the risk assessment can include a risk summary, a risk classification, a risk score, a listing of detected risk signals, or some combination thereof for the applicant.

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for extracting rules and determining risk parameters from an underwriting manual. The program and method provide for receiving an underwriting manual for an insurance carrier, wherein the underwriting manual comprises text describing rules, guidelines and parameters defining a risk appetite of the insurance carrier; processing the underwriting manual using one or more neural network models, the one or more neural network models having been trained with domain-specific data to analyze text across plural underwriting manuals; determining, based on the processing, insurance rules and risk parameters for the text in the underwriting manual; and generating a set of rules based on the insurance rules and risk parameters.

Abstract: Systems herein describe an inconsistency detection system to improve insurance underwriting. The inconsistency detection system accesses medical records associated with a patient user, extracts data from the medical records, compares the extracted data to a database of medical data, identifies inconsistencies between the extracted data and the database of medical records, based on the identified inconsistencies, automatically generates a textual summary of the identified inconsistencies and displays the identified inconsistencies, and the generated textual summary of the identified inconsistencies to a user.

Abstract: Aspects of the present disclosure describe a system comprising a computer-readable storage medium storing a program and method for analyzing one or more electronic submissions based on a rule set to generate a risk assessment of an applicant. In particular, some embodiments analyze one or more electronic submissions for an applicant of an insurance policy (or insurance product) based on a rule set (e.g., structured, machine-readable rule set) that describes one or more rules, guidelines, or parameters that codify an insurance carrier's risk appetite. Based on the analysis, various embodiments generate a risk assessment for the applicant, where the risk assessment can include a risk summary, a risk classification, a risk score, a listing of detected risk signals, or some combination thereof for the applicant.

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for extracting rules and determining risk parameters from an underwriting manual. The program and method provide for receiving an underwriting manual for an insurance carrier, wherein the underwriting manual comprises text describing rules, guidelines and parameters defining a risk appetite of the insurance carrier; processing the underwriting manual using one or more neural network models, the one or more neural network models having been trained with domain-specific data to analyze text across plural underwriting manuals; determining, based on the processing, insurance rules and risk parameters for the text in the underwriting manual; and generating a set of rules based on the insurance rules and risk parameters.