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. Slowly.
Neural-Symbolic Models for Legal Outcome Prediction
Generative AI is a text engine, not a crystal ball. To forecast litigation outcomes accurately, you must fundamentally separate the act of reading a claim file from the mathematics of predicting its cost.
Litigation Funding and the New Math of Claim Exposure
Third-party capital has fundamentally altered the incentives driving bodily injury claims. When the plaintiff's side plays a portfolio game to maximize returns, defense strategies built on historical payout curves become obsolete.
Designing for Traceability: Every Forecast Links to Evidence
A forecast is useless to a claims professional if they cannot defend it. Traceability requires engineering the system to link every predicted outcome directly to the source document that generated it.
Generation Is Not Prediction
Large language models are built to produce plausible text, not accurate forecasts. Confusing a statistical parrot for a mathematical pricing engine is a fast way to misprice your entire claims portfolio.
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