Prioritization of insurance requotations

Abstract

A computer-assisted method for providing re-quotations for insurance coverage may include receiving a list of insurance leads corresponding to individuals who received a previous quotation for insurance coverage but did not purchase the insurance coverage and identifying a difference between the previous quotation and a new quotation. This difference may include an increase in offered insurance coverage and/or a reduction in cost. A computing device may calculate a probability for each of the individuals on the list using a regression model based, at least in part, on the identified difference. In some cases, the regression model may be associated with individual states. In other cases, the regression model may correspond to a plurality of states. The regression model may output a probability that a resident of a particular state will purchase insurance in response to a re-quotation for insurance coverage, where individuals may then be ranked based on the probability.

What is claimed is: 
     
         1 . A system comprising:
 one or more computer devices comprising:
 a processor; and 
 a non-transitory memory device storing instructions that, when executed by the processor, cause the one or more computer devices to: 
 generate an insurance lead list based on a plurality of previously non-binding insurance quotations, wherein the previously non-binding insurance quotations are stored in a data repository communicatively coupled to the one or more computer devices; 
 generate a re-quotation for insurance coverage for each lead included in the insurance lead list, wherein the re-quotation includes a difference from a previously non-binding insurance quotation and wherein the difference comprises at least one of an increase in offered insurance coverage and a reduction in cost; 
 calculate a likelihood of binding for each of the leads included in the insurance lead list using a state regression model based on information associated with the re-quotation, wherein the state regression model corresponds to a state of residence of each individual associated with the insurance lead list; and 
 determine a score for each of the leads based on the likelihood of binding output by the state regression model, wherein the score of each lead is determined in relation to other leads on the list.