Employment litigation follows patterns. Employers are not using them.
Employment litigation including wrongful termination, discrimination, harassment, wage and hour, and class action follows statistically identifiable patterns by industry, jurisdiction, employer size, and claim type. The companies with the most exposure are the least likely to have systematic prediction infrastructure. Most manage employment litigation reactively, after claims are filed. Criterica moves that window forward.
The statistical patterns are clear. Jurisdictions vary dramatically in plaintiff win rates. Certain claim types in certain industries carry outsized settlement exposure. Class action probability correlates with organizational and geographic factors that are knowable before any claim is filed. None of this intelligence reaches employers today. Criterica changes that.
Quantify the litigation probability of employment decisions.
Outcome probability modeling for terminations by industry, jurisdiction, protected class status, and termination type. Know the statistical profile of the decision before it's made.
Early warning for wage and hour and discrimination class exposure.
Identify the organizational and jurisdictional factors that predict class action certification and success. The signal is in the data: most employers just do not have access to it.
Employment practice liability pricing and reserve modeling.
Claim severity prediction for employment practices liability claims. Settlement band analysis by claim type, jurisdiction, and employer profile. Reliable reserve inputs for EPLI carriers.
Data-driven settlement strategy for employment disputes.
Settlement probability curves by claim type and case age. What does the historical distribution of outcomes say about this claim at this stage? Answer that question before you negotiate.
Employment litigation coverage across federal circuits and all major state court jurisdictions. Wage and hour, discrimination, harassment, wrongful termination, and class action outcome records drawn from real filed cases.
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.