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Tokyo Reinsurer

40% Retro Cost Reduction

Retrocession Analytics

The Challenge

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.

The Solution

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.

AI Agents Deployed
Retrocession Agent
Capital Agent
Portfolio Optimization Agent

Implementation

Phase 1: Program Analysis
4 weeks

Analyzed existing retro program including treaty terms, pricing, and historical recoveries. Built baseline efficiency metrics across all layers.

Phase 2: Scenario Modeling
5 weeks

Developed Monte Carlo simulation engine testing 10,000+ program structures. Optimized for capital efficiency, counterparty risk, and cost-effectiveness.

Phase 3: Continuous Optimization
3 weeks

Created ongoing monitoring system recommending program adjustments based on portfolio changes, market pricing, and capital requirements.

Results

Cost Reduction
40%

Reduced retro program cost from $120M to $72M annually

Capital Efficiency
+$180M

Freed $180M in excess capital through optimized program structure

Coverage Quality
Maintained

Maintained protection quality while reducing cost through better layer design

Analysis Time
From Weeks to Hours

Retro program analysis reduced from 3 weeks to 4 hours

"We were overpaying for the wrong coverage. The optimization revealed $48M in annual savings we didn't know existed."

Chief Risk Officer
Major Japanese Reinsurer

Technology Stack

Retrocession Agent
Capital Agent
Monte Carlo Simulation Engine
Counterparty Risk Platform