Abstract: A data analytics system may include a first risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a first risk relationship provider. Similarly, a second risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a second risk relationship provider. A back-end application computer server may include a data mining engine that analyzes a set of electronic records in the first and second risk relationship data stores to identify flags corresponding to risk drivers. A predictive analytics engine may then calculate a risk score associated with the set of electronic records based on the associated entity attribute values and the identified flags corresponding to risk drivers. An insight platform may automatically generate a recommended action for the enterprise to lower the calculated risk score.

Abstract: A data analytics system may include a first risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a first risk relationship provider. Similarly, a second risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a second risk relationship provider. A back-end application computer server may include a data mining engine that analyzes a set of electronic records in the first and second risk relationship data stores to identify flags corresponding to risk drivers. A predictive analytics engine may then calculate a risk score associated with the set of electronic records based on the associated entity attribute values and the identified flags corresponding to risk drivers. An insight platform may automatically generate a recommended action for the enterprise to lower the calculated risk score.

Abstract: A data analytics system may include a first risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a first risk relationship provider. Similarly, a second risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a second risk relationship provider. A back-end application computer server may include a data mining engine that analyzes a set of electronic records in the first and second risk relationship data stores to identify flags corresponding to risk drivers. A predictive analytics engine may then calculate a risk score associated with the set of electronic records based on the associated entity attribute values and the identified flags corresponding to risk drivers. An insight platform may automatically generate a recommended action for the enterprise to lower the calculated risk score.

Abstract: A data analytics system may include a first risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a first risk relationship provider. Similarly, a second risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a second risk relationship provider. A back-end application computer server may include a data mining engine that analyzes a set of electronic records in the first and second risk relationship data stores to identify flags corresponding to risk drivers. A predictive analytics engine may then calculate a risk score associated with the set of electronic records based on the associated entity attribute values and the identified flags corresponding to risk drivers. An insight platform may automatically generate a recommended action for the enterprise to lower the calculated risk score.

Abstract: A data analytics system may include a first risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a first risk relationship provider. Similarly, a second risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a second risk relationship provider. A back-end application computer server may include a data mining engine that analyzes a set of electronic records in the first and second risk relationship data stores to identify flags corresponding to risk drivers. A predictive analytics engine may then calculate a risk score associated with the set of electronic records based on the associated entity attribute values and the identified flags corresponding to risk drivers. An insight platform may automatically generate a recommended action for the enterprise to lower the calculated risk score.

Abstract: A data analytics system may include a first risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a first risk relationship provider. Similarly, a second risk relationship data store containing electronic records that represent a plurality of risk relationships between the enterprise and a second risk relationship provider. A back-end application computer server may include a data mining engine that analyzes a set of electronic records in the first and second risk relationship data stores to identify flags corresponding to risk drivers. A predictive analytics engine may then calculate a risk score associated with the set of electronic records based on the associated entity attribute values and the identified flags corresponding to risk drivers. An insight platform may automatically generate a recommended action for the enterprise to lower the calculated risk score.

Abstract: A system and method for providing and utilizing a proxy to provide group benefits products is disclosed. The system and method include providing at least one variable for calculating applicability and cost of a group benefits product by proxy, wherein the proxy is provided by information included in at least a workers compensation (WC) system. The at least one variable may include WC average salary, area, industry, blue score and/or median household age. The group benefit product may be a long term disability insurance product and/or a life insurance product.

Abstract: A computer system accesses payroll-related insurance premium data at an individual employee level and provides the data at the individual employee level, including cost of insurance at the individual employee level, on a client device. A computer system compares stored data with payroll data and identifies employees lacking occupation classification information for payroll-based premium determination. The computer system provides a fillable form on a user device for the user to provide occupation classification data, and receives the occupation classification data. The computer system provides fillable forms on a user device for a user to provide payroll data for receipt by the system, runs business rules on the received payroll data, determines premiums for payroll-based insurance coverage.

Abstract: A computer system accesses payroll-related insurance premium data at an individual employee level and provides the data at the individual employee level, including cost of insurance at the individual employee level, on a client device. A computer system compares stored data with payroll data and identifies employees lacking occupation classification information for payroll-based premium determination. The computer system provides a fillable form on a user device for the user to provide occupation classification data, and receives the occupation classification data. The computer system provides fillable forms on a user device for a user to provide payroll data for receipt by the system, runs business rules on the received payroll data, determines premiums for payroll-based insurance coverage.

Abstract: A computer system accesses payroll-related insurance premium data at an individual employee level and provides the data at the individual employee level, including cost of insurance at the individual employee level, on a client device. A computer system compares stored data with payroll data and identifies employees lacking occupation classification information for payroll-based premium determination. The computer system provides a fillable form on a user device for the user to provide occupation classification data, and receives the occupation classification data. The computer system provides fillable forms on a user device for a user to provide payroll data for receipt by the system, runs business rules on the received payroll data, determines premiums for payroll-based insurance coverage.

Abstract: A computer system accesses payroll-related insurance premium data at an individual employee level and provides the data at the individual employee level, including cost of insurance at the individual employee level, on a client device. A computer system compares stored data with payroll data and identifies employees lacking occupation classification information for payroll-based premium determination. The computer system provides a fillable form on a user device for the user to provide occupation classification data, and receives the occupation classification data. The computer system provides fillable forms on a user device for a user to provide payroll data for receipt by the system, runs business rules on the received payroll data, determines premiums for payroll-based insurance coverage.

Abstract: A computer system accesses payroll-related insurance premium data at an individual employee level and provides the data at the individual employee level, including cost of insurance at the individual employee level, on a client device. A computer system compares stored data with payroll data and identifies employees lacking occupation classification information for payroll-based premium determination. The computer system provides a fillable form on a user device for the user to provide occupation classification data, and receives the occupation classification data. The computer system provides fillable forms on a user device for a user to provide payroll data for receipt by the system, runs business rules on the received payroll data, determines premiums for payroll-based insurance coverage.

Abstract: A computer system accesses payroll-related insurance premium data at an individual employee level and provides the data at the individual employee level, including cost of insurance at the individual employee level, on a client device. A computer system compares stored data with payroll data and identifies employees lacking occupation classification information for payroll-based premium determination. The computer system provides a fillable form on a user device for the user to provide occupation classification data, and receives the occupation classification data. The computer system provides fillable forms on a user device for a user to provide payroll data for receipt by the system, runs business rules on the received payroll data, determines premiums for payroll-based insurance coverage.