The moment a claim enters litigation, the actuarial framework breaks down.
Insurance already operates with quantitative precision on frequency, severity, reinsurance structure, and loss development. But the moment a claim enters litigation, that precision disappears. Reserve setting becomes adjuster judgment. Defense strategy becomes instinct. Settlement timing becomes negotiation without benchmarks against actual historical outcomes at the jurisdiction level.
Criterica brings actuarial rigor to the legal dimension of claims. Jurisdiction-specific outcome models, tuned on real court records, give claims organizations the same quantitative foundation for litigation decisions that they already apply to everything else. This is not legal AI. This is the actuarial layer that legal has never had.
Jurisdiction-specific severity predictions for claims in litigation.
Set reserves based on the statistical outcome distribution of similar claims in the same venue. Not adjuster estimates or industry averages. Checked against what actually happened in real filed records, not settlement databases that underrepresent verdict severity.
When should a claim settle?
Settlement probability by case stage, venue, judge, and opposing counsel profile. Understand where a claim sits on the timeline curve and whether early resolution or continued defense is statistically optimal.
Which approach has the highest probability of favorable outcome in this venue?
Motion-level probability modeling by judge and jurisdiction. Defense tactic scoring against historical outcomes in cases with matching profiles. Replace instinct with reliable data.
Aggregate litigation exposure across claims portfolios.
Concentration risk by jurisdiction, case type, and severity band. Correlation analysis across open claims. Stress test litigation exposure against adverse outcome scenarios with historical grounding.
P&C, professional liability, D&O, and E&O litigation records across federal districts and state jurisdictions. Tested against real court records spanning the venues where claims are litigated.
Statistics shown reflect historical or illustrative model outputs derived from real case data. They are not predictions or guarantees of any individual outcome. Litigation results depend on facts, jurisdiction, judge, and counsel, and vary case by case. Model accuracy is subject to selection effects and changing legal dynamics.