Patent ID: 11915319
Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 12:
13. A system comprising:
a claim loss reporting tool, executed by a computing device, configured to:
generate, based on input provided via the claim loss reporting tool during a communication session associated with an insurance claim, a loss report associated with the insurance claim; and

a dialogue advisor, executed by the computing device or a second computing device, that is associated with the claim loss reporting tool and is configured to:
generate, during the communication session, a preliminary destination prediction of a destination, selected from a set of possible destinations, for claim data associated with the insurance claim, wherein:
the preliminary destination prediction is generated, using a dialogue advisor machine learning model, based on current information in the loss report associated with the insurance claim,
the dialogue advisor machine learning model is an instance of a machine learning model that a claim router, different from the claim loss reporting tool and the dialogue advisor, is configured to use following completion of the communication session to generate a final destination prediction indicating the destination for the claim data, and
the preliminary destination prediction, generated based on the current information, is associated with a first confidence level;

identify, during the communication session, an empty field in the loss report based on the current information;
determine, during the communication session, a set of possible values for the empty field;
generate, during the communication session, and using the dialogue advisor machine learning model, one or more theoretical destination predictions that:
have second confidence levels, and
are based on the current information in the loss report in combination with individual values, of the set of possible values, for the empty field;

determine, during the communication session, that the second confidence levels of the one or more theoretical destination predictions are greater than the first confidence level of the preliminary destination prediction;
determine, during the communication session, and based on determining that the second confidence levels are greater than the first confidence level, that filling the empty field with a value would increase a confidence level of the final destination prediction generated by the claim router following the completion of the communication session; and
cause, based on determining that filling the empty field would increase the confidence level of the final destination prediction, a user interface of the claim loss reporting tool to display, during the communication session, a prompt requesting that the empty field be filled,

wherein the machine learning model is trained, based on a training data set associated with assignments of previous insurance claims to destinations based on corresponding loss reports, to identify features that are predictive of the destinations that processed the previous insurance claims.