Predictive Model Development

Custom and insurance industry-specific predictive model development and implementation


Predictive models are built specifically to help you more quickly and confidently assess risk, verify data accuracy, price competitively and effectively, and gain insights into new markets.


Benefits

Enhance Volume and Profitability
Segment risks into proper categories using predictive models to help improve your volume and profitability.

Improve Acquisition and Channel Selections
Enhance acquisition and retention results with analytics models that identify and target ideal prospects based on your criteria and priorities.

Gain Efficiencies in the Claims Process
From first notice of loss through the life of the claim, predictive analytics models embedded directly into your workflow can help decrease the age of a claim, detect fraud earlier, uncover hidden patterns and better align resources to priority cases.


Features

Be Confident You Are with an Industry Leader
400+ predictive models in production for acquisition and retention, risk, fraud prevention and competitive analysis.

Leverage Best-in-class Models to Meet Your Objectives
Partner with an advanced analytics provider that is experienced in developing predictive models that can help insurance customers achieve specific business goals.

Regulatory Consideration and Review
A dedicated, experienced team socializes models during development and production with respective state regulatory bodies to address questions and gain feedback.
Due to the nature of the origin of public record information, the public records and commercially available data sources used in reports may contain errors. Source data is sometimes reported or entered inaccurately, processed poorly or incorrectly, and is generally not free from defect. This product or service aggregates and reports data, as provided by the public records and commercially available data sources, and is not the source of the data, nor is it a comprehensive compilation of the data. Before relying on any data, it should be independently verified.