Abstract: Described herein is computing device for machine learning based risk analysis and decision automation in intelligent underwriting. In accordance with one aspect of the framework, input data of underwriting cases is preprocessed and used to train a predictive model. The predictive model may be cross-validated and tested for accuracy. The predictive model may then be applied to a current underwriting case in order to automatically identify and assess associated risks and provide a decision recommendation.

Abstract: A method and an apparatus for extracting information are provided. The method according to an embodiment includes: receiving and parsing voice information of a user to generate text information corresponding to the voice information; extracting to-be-recognized contact information from the text information; acquiring an address book of the user, the address book including at least two pieces of contact information; generating at least two types of matching information based on the to-be-recognized contact information; determining, for each of the at least two types of matching information, a matching degree between the to-be-recognized contact information and each of at least two pieces of contact information based on the type of matching information; and extracting contact information matching the to-be-recognized contact information from the address book based on the determined matching degree.

Abstract: A method and an apparatus for extracting information are provided. The method according to an embodiment includes: receiving and parsing voice information of a user to generate text information corresponding to the voice information; extracting to-be-recognized contact information from the text information; acquiring an address book of the user, the address book including at least two pieces of contact information; generating at least two types of matching information based on the to-be-recognized contact information; determining, for each of the at least two types of matching information, a matching degree between the to-be-recognized contact information and each of at least two pieces of contact information based on the type of matching information; and extracting contact information matching the to-be-recognized contact information from the address book based on the determined matching degree.

Abstract: Described herein is computing device for machine learning based risk analysis and decision automation in intelligent underwriting. In accordance with one aspect of the framework, input data of underwriting cases is preprocessed and used to train a predictive model. The predictive model may be cross-validated and tested for accuracy. The predictive model may then be applied to a current underwriting case in order to automatically identify and assess associated risks and provide a decision recommendation.