The Cost of Manual Structuring Workflows
ART teams typically stitch together RMS ExposureIQ outputs, historical NOAA series, and ERA5 reanalysis data by hand — each new structure requiring a custom set of scripts, analyst hours, and vendor reviews. Basis-risk analysis alone can stretch a product timeline by weeks. The dependency on external structuring advisors adds cost and creates bottlenecks that slow client proposals and inflate per-product spend well into the six-figure range.
How an AI Agent Runs Trigger Calibration
An agent ingests your team's existing calibration scripts and climate data processing workflows, then operates continuously against RMS ExposureIQ and NOAA/ERA5 datasets. It auto-runs historical trigger backtests across configurable return periods, calculates attachment probability and exhaustion-point return periods, and drafts the financial model underlying each term sheet. Your Head of ART reviews and approves trigger thresholds before any client deliverable is produced — the agent handles the computation, not the judgment.
The Business Case: Reclaiming Structuring Margin
Parametric products are a growth vehicle, but structuring costs erode that margin before a policy is even bound. An agent in this workflow can reduce structuring advisory vendor costs by roughly 30%, while compressing calibration cycle time by 50–70% in comparable deployments. Teams typically go live and start producing results in about 12 weeks. The compounding benefit is capacity: when your analysts aren't locked in backtesting cycles, they can structure more products in parallel and respond to client RFPs faster — a direct driver of new premium volume.
Does the agent replace actuarial or ART expertise?
No. The agent automates the computational and documentation layers — running backtests, calculating return periods, and drafting term sheet models. Trigger threshold approval and final structuring judgment remain with your Head of ART before anything goes to a client.
What data sources and tools does the agent work with?
The agent is built around your existing workflows — typically RMS ExposureIQ, NOAA climate datasets, and ERA5 reanalysis data, along with whatever calibration scripts your team already runs. Integration starts by mining your team's existing processing threads and scripts.
How long does it take to get a working agent deployed?
Most ART teams are live and producing results in approximately 12 weeks, depending on data-environment complexity and the number of product types being structured.