Background
In Q1 2025, a leading global reinsurer faced a high-stakes challenge: pricing a $22 million facultative submission involving a diversified portfolio of industrial facilities across four continents. The portfolio included offshore energy assets, high-hazard manufacturing, and sites exposed to both political and natural catastrophe risks. Historically, pricing such a complex deal required weeks of manual modeling, actuarial oversight, and fragmented input from regional underwriters.
The reinsurer had two goals:
- Improve speed and consistency in pricing complex risks.
- Maximize underwriting profitability through better risk segmentation and calibration.
The Challenge
The original risk-adjusted premium estimate for the $22M submission hovered around $4.1M—based on internal catastrophe models, historical loss experience, and qualitative judgment from the lead underwriter. However, several pain points remained:
- Opaque Pricing Drivers: Risk layers were not clearly distinguished, particularly in the multi-peril zones.
- Geopolitical Risk Undervalued: Emerging market instability was not fully priced in.
- Inefficient Collaboration: Risk engineering data and actuarial forecasts were siloed, leading to redundant effort.
The team suspected the premium was underpriced—but lacked the tools to quantify this accurately and swiftly.
The Solution
The reinsurer engaged InsightLayer, a risk analytics platform specializing in complex underwriting support. The goal was to reassess the submission using dynamic modeling, third-party exposure data, and machine learning–enhanced RAP calculators.
Key interventions included:
- Geospatial Layering: Overlaying satellite imagery with historical loss heatmaps and predictive hazard scores.
- Dynamic RAP Modeling: Using real-time actuarial simulations tailored for high-complexity multi-location submissions
- Peril Calibration: Explicit modelling of political risk, secondary perils, and long-tail liability potential.
Through these interventions, the reinsurer was able to re-segment the portfolio into granular risk buckets—each priced independently, with visibility into contribution margin per exposure node.