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Predictive Analytics for Insurance Claims

Updated: Jul 4, 2023

How does predictive analytics for claims help insurance carriers? Below are four major reasons for implementation:

Settlements vs. Litigation:

Understand what claims should be disputed or settled by evaluating the likelihood of success for your case (win rate) and the expected quantum granted (recovery rate) to create cost-effective strategies for closing a claim.

Optimize Payouts:

Stop overpaying: predictive analytics for insurance claims assists you in understanding what drives the value of a settlement. Anticipate your costs and get the right preparation for difficult cases while saving on mock trials expenses, other legal fees, and increasing your confidence against aggressive plaintiffs.

Anticipate Devastating Verdicts:

Detect early on latent outlying cases and protect your company from devastating verdicts while exploring the influence of specific litigation micro-variables such as venues, judges, jury compositions, attorneys, and experts to mitigate social inflation.

Obtain a High Return on Investment:

The use of predictive analytics helps insurance carriers reduce their loss ratio up to 10 points over time through optimized payouts, reduced legal spending, lowered litigation rates and eliminated devastating verdicts.


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