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.

Abstract: Methods, systems, and computer-readable media, and apparatuses for optimizing policy underwriting and insurance policy coverage are described herein. Insurance information related to a new homeowner insurance policy may be retrieved from one or more insurance system databases. The insurance information may comprise an insurance policy premium. An unrestrained rating plan premium may be determined based on a plurality of premium components. The plurality of premium components may comprise at least one multiplicative factor and at least one additive factor determined from the insurance information. An underwriting score may be determined based on the unrestrained rating plan premium and the insurance policy premium. In response to determining that the underwriting score fails to meet a predetermined underwriting score threshold, the new homeowner insurance policy may be rejected.

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.

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.

Abstract: Computer executable instructions may be used to configure a special purpose computing device to perform a method for determining whether an unbound property insurance lead may be associated with a property for which a property inspection is not required. The computer executable instructions, when executed by a processor may cause the special purpose computing device to access a data repository storing a plurality of unbound property insurance leads, process each of the plurality of unbound property insurance leads using an adaptable inspection model to determine an insurability risk score for each of the unbound property insurance leads, compare each insurability risk score to a constraint, and communicate an indication of whether a property inspection is necessary for each of the plurality of unbound property insurance leads.

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.

Abstract: Methods, systems, and computer-readable media, and apparatuses for optimizing policy underwriting and insurance policy coverage are described herein. Insurance information related to a new homeowner insurance policy may be retrieved from one or more insurance system databases. The insurance information may comprise an insurance policy premium. An unrestrained rating plan premium may be determined based on a plurality of premium components. The plurality of premium components may comprise at least one multiplicative factor and at least one additive factor determined from the insurance information. An underwriting score may be determined based on the unrestrained rating plan premium and the insurance policy premium. In response to determining that the underwriting score fails to meet a predetermined underwriting score threshold, the new homeowner insurance policy may be rejected.

Abstract: A first amount of insurance may be determined for a first set of at least one insured entities covered under a single insurance policy. Replacement cost factor data relating to the single insurance policy may be received from at least one source. Received replacement cost factor data may be used to determine a first replacement cost for the first set of at least one insured entities covered under the single insurance policy. A determination may be made that the first amount of insurance is greater than the first replacement cost. A first insurance premium may be calculated for the single insurance policy using at least the first amount of insurance and the first replacement cost. The calculated insurance premium may be less than a second insurance premium for a second set of at least one insured entities for which a second amount of insurance and a second replacement cost are both equal to the first amount of insurance.