Writing on prediction, claims, and the science behind the platform
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.
Showing 6 posts · Science
Clear filtersNeural-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.
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.
Conformal Prediction for Claims: Ranges, Not Point Guesses
A machine learning model that predicts a precise settlement dollar amount for a casualty claim is lying to you. Litigation is probabilistic, and your forecasting models must mathematically respect that reality.
Why LLMs Can't Predict Legal Outcomes
A language model generates text that looks like an answer. It does not calculate probabilities based on historical claim geometries. Confusing the two is a fast way to misprice your reserves.
AI as a Building Block in Insurance Analytics
Generative AI makes large, complex legal documents accessible to purpose-built predictive algorithms — when integrated correctly into the analytics pipeline.
Can You Trust LLMs to Predict the Outcome of an Insurance Claim?
Language models generate verbal predictions that sound sensible — but they were trained to sound logical, not to be mathematically sound.
Want to talk to an executive?
Press, partners, investors, candidates — the inbox is monitored. Tell us who you are and we'll route it to the right person within two business days.