Illustrations / Tokyo Reinsurer
Illustrated workflow: Retrocession Analytics
This is a teaching scenario for a fictional desk, not a customer testimonial. Figures in the source story are not audited results and must not be quoted as ROI.
Situation
A Japanese reinsurer purchasing $800M in retrocessional protection struggled with optimal program structure. Manual retro modeling was time-consuming, and the company suspected it was overpaying for coverage while leaving capital inefficiencies unaddressed.
Workflow
Implemented Retrocession Agent to analyze retro program efficiency, model alternative structures, and optimize coverage layers. The system simulates thousands of scenarios to identify optimal attachment points, limits, and counterparty diversification.
- Retrocession Agent
- Capital Agent
- Portfolio Optimization Agent
Steps
- Phase 1: Program Analysis. Analyzed existing retro program including treaty terms, pricing, and historical recoveries. Built baseline efficiency metrics across all layers.
- Phase 2: Scenario Modeling. Developed Monte Carlo simulation engine testing 10,000+ program structures. Optimized for capital efficiency, counterparty risk, and cost-effectiveness.
- Phase 3: Continuous Optimization. Created ongoing monitoring system recommending program adjustments based on portfolio changes, market pricing, and capital requirements.
Illustrated scenario, not a named customer: “We were overpaying for the wrong coverage. The optimization revealed $48M in annual savings we didn't know existed.”