Hartford Fire Insurance Compnay

Kelly J McLaughlin

James A Russo

Lawrence J Opena

Cindy S DeLeón

Wangyang Hu

Gregory Paul Goddu

Upendra D Belhe

Kathleen F Maurer

Natalie Mohanty

Shane Eric Barnes

Tracey Ellen Steger

Bixia Li

Kathleen H Galia

Huimin Xiong

David Gamble

Kathleen F Mauer

Jonathan Kaleb Adams

Carmen L Sharp

Kathleen E Maurer

Christopher D Rice

A system and method for processing and administering insurance policy premium discounts for mobile device disabling technology to promote safer driver is disclosed. An insurance policy premium discount is determined based on the level of disabling technology implemented by a user on a user's mobile device.

Mobile device disabling and verification system and method

Text input data for an electronic record may be aggregated and mapped to create composite text input data. A semantic event in the composite text input data may be automatically detected, and a text mining result database may be updated by adding an entry identifying the detected semantic event and a triggering semantic rule. An indication of the electronic record may then be transmitted to a back-end application computer server that also determines at least one parameter corresponding to a characteristic of the electronic record. The computer server may then execute a computerized predictive model to predict a future performance characteristic indicator for the electronic record based on the at least one parameter and the indication received from the text mining platform, wherein the future performance characteristic indicator is indicative of a likelihood of an actual value of the electronic record differing from a predicted value of the electronic record.

System to predict future performance characteristic for an electronic record

Mediums, apparatus, computer program code, and means may be provided to evaluate relative risks based at least in part on source inputs received via a distributed communication network by an automated back-end application computer server. According to some embodiments, the server may access a data store containing electronic files associated with a set of entities to retrieve, for each of a plurality of the entities in the set of entities, electronic files associated with that entity. The server may also retrieve structured data elements, unstructured data elements, and external, third-party data elements for that entity. The server may then execute an automated risk model to assign a risk score to that entity based on the electronic files, the structured data elements, the unstructured data elements, and the external, third-party data elements for that entity and transmit indications of the risk scores for the plurality of entities.

Proving ground assisted automated model

System and method for mobile device disabling and verification

System and method for administering insurance discounts for mobile device disabling technology

Text input data for an electronic record may be aggregated and mapped to create composite text input data. A semantic event in the composite text input data may be automatically detected, and a text mining result database may be updated by adding an entry identifying the detected semantic event and a triggering semantic rule. An indication for the electronic record may then be transmitted to a back-end application computer server that also determines at least one parameter corresponding to a characteristic of the electronic record. The computer server may then execute a computerized predictive model to predict a future performance characteristic indicator for the electronic record based on the at least one parameter and the indication received from the text mining platform, wherein the future performance characteristic indicator is indicative of a likelihood of an actual value of the electronic record differing from a predicted value of the electronic record.

Processing system for data elements received via source inputs

The invention relates generally to data analysis, and to systems and methods for the computation of the volatility of a loss. The system comprises a module for receiving a data parameter, a database for storing the parameter, a computerized predictive model, and a business logic processor for executing the predictive model. The volatility is used to, among other things, determine an appropriate work flow for handling the loss.

System and method for processing data relating to insurance claim volatility

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.

Systems and methods for administering extended absence insurance

A computer system includes a data storage device. The data storage module receives, stores, and provides access to historical claim data. A categorical aggregation component comprising program instructions stored in a program memory provides categorized and aggregated historical claim data by identifying claim categories based on the historical claim data, each of the one or more claim categories associated with a respective set of claim characteristics, identifying claims of the historical claim data associated with one of the claim categories, assigning each identified claim to one of a plurality of total severity ranges based on the total severity of the identified claim, and determining an average cost per claim year for claims of each total severity range when executed by a computer processor.

System and method for calculating estimated claim costs

System and method for processing data relating to insurance claim stability indicator

System for evaluating potential claim outcomes using related historical data

System and method for predicting and responding to likelihood of volatility

Growing community of inventors

Cobalt, CT, United States of America

Kelly J McLaughlin