Free Whitepaper

What Workers's Comp Claims Data Reveals About Underwriting Data Quality

Workers’ comp performance is strong, but pricing pressure is already underway. For underwriting leaders, the next advantage depends on how well teams can use the data they already receive to move faster, select risk more precisely, and price with confidence.

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Find out what's inside below

Built on Insurance Quantified proprietary claims intelligence

200M+

Rows of processed commercial insurance claim detail

2.45M

Closed workers’ comp claims analyzed from 2011 to 2018

Nearly 14x

The closed claim volume of the published NLM study used for comparison

50K+

Raw captured values normalized into usable claim intelligence

Why Workers’ Comp Data Quality Matters Now

Workers’ compensation remains one of the strongest-performing commercial lines, but strong performance has created a more competitive market. As rates decline and margin protection becomes more important, underwriting teams need more than speed. They need data they can trust.

Across the industry, we’ve heard workers’ comp teams focus on the same priorities: faster quote turnaround, stronger risk selection, and a better agent experience. Each one depends on the quality, structure, and usability of the data behind the decision.

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Inside the Workers' Comp Claims Analysis

Inside the guide, you’ll see.

How our workers’ comp claims dataset compares with published National Library of Medicine research using NCCI-defined classification

How to assess whether your own data foundation is ready to support faster, more confident underwriting decisions

Why claim costs vary by state, injury type, and classification

How raw loss run data can produce 50,000+ unique values before normalization

Where loss runs, class codes, payroll schedules, e-mod worksheets, and third-party data create friction

Is your data foundation supporting the underwriting decision?

The guide includes a quick self-diagnostic to help you identify where submission data may be adding friction before an underwriter can act.

You'll assess four areas:

Intake pain

How much time your team spends ingesting, inspecting, and preparing submission data

Third-party data

How much effort it takes to source the external data underwriters need

Data reconciliation

How often submission data needs to be reconciled against third-party sources

Underwriter bandwidth

Whether underwriters spend more time preparing data than assessing risk

 

Your data foundation shapes every underwriting decision.

Download the guide to see where Workers’ Comp data quality may be affecting quote speed, risk selection, and pricing confidence.

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