Job: assemble retention and cession inputs from cited wordings and bordereaux so a human can choose structure. It does not pick the programme.
AI-powered retention optimization that models thousands of scenarios across different retention levels, program structures, and reinsurance costs. Provides recommendations that maximize return on capital while meeting risk appetite constraints.
Model 1,000+ scenarios in hours vs. weeks
Optimize capital efficiency by 20-30%
Balance risk transfer cost vs. volatility reduction
Compare proportional vs. excess structures
Board-ready optimization reports
Annual reinsurance program optimization
New line of business retention analysis
Capital efficiency improvement projects
Risk appetite calibration and testing
Job: assemble pricing inputs (exposure, experience, cited attachment) so a human can set technical price. The agent does not silently bind a layer.
Job: gather filing-relevant fields that already exist in the pack and list what is still missing for a capital conversation.
Job: extract retrocession structure, attachment, and reporting fields from the contracts you already have, with gaps instead of guessed layers.