Abstract: A computer system includes a data storage module which receives, stores, and provides access to determinate data, raw indeterminate data, and extracted indeterminate data captured by an indeterminate data capture module. The computer system also includes a computer processor, a model training component, and a screening module. The model training component generates the predictive model based upon historical determinate and indeterminate data, and continuously adapts the predictive model with new historical data. The screening module categorizes current claims according to whether they are suitable for predictive analysis by the predictive model. The predictive model is applied to the current claims suitable for predictive analysis to determine a value for each claim indicative of whether the current claim transaction is questionable. The system also includes an output device which outputs the determined value for each claim, and a routing modules which routes claim workflow based on the outputted values.

Abstract: A computer system includes a data storage module which receives, stores, and provides access to determinate data, raw indeterminate data, and extracted indeterminate data captured by an indeterminate data capture module. The computer system also includes a computer processor, a model training component, and a screening module. The model training component generates the predictive model based upon historical determinate and indeterminate data, and continuously adapts the predictive model with new historical data. The screening module categorizes current claims according to whether they are suitable for predictive analysis by the predictive model. The predictive model is applied to the current claims suitable for predictive analysis to determine a value for each claim indicative of whether the current claim transaction is questionable. The system also includes an output device which outputs the determined value for each claim, and a routing modules which routes claim workflow based on the outputted values.

Abstract: A computer system includes a data storage module. The computer system also includes an indeterminate data capture module. The data storage module receives, stores, and provides access to both determinate data and indeterminate data that was captured by the indeterminate data capture module. The computer system also includes a computer processor and a program memory. The computer processor executes programmed instructions and stores and retrieves the data stored in the data storage module. The data stored in the data storage module is related to historical claim transactions and current claim transactions. A predictive model component is coupled to the data storage module, and determines whether to refer a current claim transaction to an investigation unit. A model training component is coupled to the computer processor and functions to train the predictive model.

Abstract: According to some embodiments, historical claim data may be stored in a computer storage unit. The historical claim data may be used to train and verify a predictive model, the predictive model being associated with an evaluation of claim transactions to determine whether to refer each claim transactions to a nurse intervention program. Data for current claim transactions may be processed, and the trained and verified predictive model may be applied to the data for the current claim transactions to generate a respective output for each of the current claim transactions. Some of the current claim transactions may be selectively routed to a case management center associated with the nurse intervention program based on the outputs generated by the predictive model.

Abstract: According to some embodiments, historical claim data may be stored in a computer storage unit. The historical claim data may be used to train and verify a predictive model, the predictive model being associated with an evaluation of transactions to determine whether to refer each transaction to an intervention program. Data for current transactions may be processed, and the trained and verified predictive model may be applied to the data for the current transactions to generate a respective output for each of the current transactions. Some of the current transactions may be selectively routed to a management computer associated with the intervention program based on the outputs generated by the predictive model.

Abstract: A computer receives rating information relating to proposed issuance of an insurance policy endorsement. The rating information relates to a proposed insured that employs a number of employees. The computer processes the rating information to generate a premium amount to be charged for the insurance policy endorsement. The endorsement is then issued. The endorsement may provide reimbursement to the insured for losses incurred by the insured arising from absence from work by one or more of the employees.

Abstract: A computer receives rating information relating to proposed issuance of an insurance policy endorsement. The rating information relates to a proposed insured that employs a number of employees. The computer processes the rating information to generate a premium amount to be charged for the insurance policy endorsement. The endorsement is then issued. The endorsement may provide reimbursement to the insured for losses incurred by the insured arising from absence from work by one or more of the employees.

Abstract: According to some embodiments, historical claim data may be stored in a computer storage unit. The historical claim data may be used to train and verify a predictive model, the predictive model being associated with an evaluation of claim transactions to determine whether to refer each claim transactions to a nurse intervention program. Data for current claim transactions may be processed, and the trained and verified predictive model may be applied to the data for the current claim transactions to generate a respective output for each of the current claim transactions. Some of the current claim transactions may be selectively routed to a case management center associated with the nurse intervention program based on the outputs generated by the predictive model.

Abstract: According to some embodiments, historical claim data may be stored in a computer storage unit. The historical claim data may be used to train and verify a predictive model, the predictive model being associated with an evaluation of claim transactions to determine whether to refer each claim transactions to a nurse intervention program. Data for current claim transactions may be processed, and the trained and verified predictive model may be applied to the data for the current claim transactions to generate a respective output for each of the current claim transactions. Some of the current claim transactions may be selectively routed to a case management center associated with the nurse intervention program based on the outputs generated by the predictive model.

Abstract: Systems and methods are disclosed herein for determining an insurance evaluation based on an industrial classification. The system includes a content processor, a computerized predictive model, and a business logic processor. The content processor retrieves content from a website related to an entity seeking an insurance policy and extracts data from the website content. The computerized predictive model accepts the data extracted from the website content from the content processor, processes the extracted data, and outputs data indicative of at least one industrial classification associated with the entity. The business logic processor determines an insurance evaluation of the entity based on its industrial classification(s).

Abstract: A computer receives rating information relating to proposed issuance of an insurance policy endorsement. The rating information relates to a proposed insured that employs a number of employees. The computer processes the rating information to generate a premium amount to be charged for the insurance policy endorsement. The endorsement is then issued. The endorsement may provide reimbursement to the insured for losses incurred by the insured arising from absence from work by one or more of the employees.

Abstract: According to some embodiments, historical claim data may be stored in a computer storage unit. The historical claim data may be used to train and verify a predictive model, the predictive model being associated with an evaluation of claim transactions to determine whether to refer each claim transactions to a nurse intervention program. Data for current claim transactions may be processed, and the trained and verified predictive model may be applied to the data for the current claim transactions to generate a respective output for each of the current claim transactions. Some of the current claim transactions may be selectively routed to a case management center associated with the nurse intervention program based on the outputs generated by the predictive model.

Abstract: A method includes a data storage device for receiving, storing, and providing access to building characteristic information, a computer processor for executing program instructions and for retrieving the building characteristic information and hazard information from the data storage device, a memory, coupled to the computer processor, for storing program instructions for execution by the computer processor, a quoting system and a validation engine.

Abstract: A computer system includes a data storage module. The data storage module receives, stores, and provides access to both aggregate claims file data and insurance policy data. The computer system also includes a computer processor and a program memory. The computer processor executes programmed instructions and stores and retrieves the data stored in the data storage module. A text mining component is coupled to the data storage module, and analyzes unstructured text in the aggregate claims file data to detect indicators of possible premium fraud. A routing module in the computer system routes for investigation insurance policies that correspond to the claim files in which indicators of possible premium fraud were detected.

Abstract: A computer system includes a data storage module. The computer system also includes an indeterminate data capture module. The data storage module receives, stores, and provides access to both determinate data and indeterminate data that was captured by the indeterminate data capture module. The computer system also includes a computer processor and a program memory. The computer processor executes programmed instructions and stores and retrieves the data stored in the data storage module. The data stored in the data storage module is related to historical claim transactions and current claim transactions. A predictive model component is coupled to the data storage module, and determines whether to refer a current claim transaction to an investigation unit. A model training component is coupled to the computer processor and functions to train the predictive model.