Posts on what we actually think.
Essays on conformal prediction, social inflation, and where generative AI helps and where it doesn't. Written by the team.
Building Forecasts When Comparables Report Verdicts
Legal analytics tools often fail because they treat public jury awards as ground-truth prices. Building a reliable claims forecasting system requires isolating the selection bias of trials from the reality of private settlements.
Why Comparable Verdicts Overstate Settlement Exposure
Public trial verdicts are terrible predictors of settlement value. The data is systematically biased toward extreme disagreement, leading models and adjusters alike to radically over-reserve.
Reserving Under Social Inflation
Social inflation has broken traditional reserving methodologies. When claims teams rely on historical averages to set day-one reserves, they guarantee quarter-over-quarter volatility and misallocated defense spend.
From Demo to Deployment: Onboarding a Carrier
A sales demo runs on pristine data, but real claims environments run on massive files and legacy mainframes. Transitioning a carrier from pilot to full deployment exposes the gap between software that looks good and software that works.
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