Gross Consulting's Comprehensive Insurance Review

To understand its business, an insurer should analyze all of its data.

Most insurers have embraced predictive modeling in the eternal quest to refine and improve their underwriting and pricing capabilities, as they should. But the models ignore measurable differences in loss development, leaving carriers exposed to devastating adverse development and adverse selection.

Gross Consulting’s Comprehensive Insurance Review avoids these modeling traps, identifying risk characteristics that are predictive of loss occurrence, severity, and development pattern.

A Comprehensive Insurance Review produces actionable information, reliable management information, and superior underwriting results

DEVELOPMENT DIFFERENCES

Losses from different types of policies and with different claim characteristics develop very differently.

CASE RESERVE BIAS

Disparate levels of case reserve bias can create distortions in management reporting, with broad negative impacts.

“To gain further insight into our portfolio, we engaged Gross Consulting to conduct a Comprehensive Insurance Review.  Their approach to the analysis produced valuable insights utilizing expertise & techniques that merged cutting edge with real world practicality.  The outputs were of high value on a technical basis as well as actionable by management.”

John Binder – President, Crum & Forster Commercial Lines

Our Comprehensive Insurance Review Produces

Indications of needed changes in rate, highlighting development distortions that would otherwise be ignored

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Customized algorithms to provide actuarial estimates for each open claim and alternative “actuarial case-incurred” triangles

Claims emergence indications that can be applied to policies during the underwriting process

This detailed review of your risk portfolio also uncovers changes in risk profile that may not have been captured by your existing management reporting framework, providing guidance for needed rate and underwriting actions and informing strategic decisions for growth and desired policy characteristics and coverage features

Additional Information

State of the Art Analytical Software

Subject Matter Expertise

Collaborative Process

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