Estimate the underwriting profit impact of adopting Z-FLOOD across high-risk counties, using the combined-ratio method. Every assumption is shown and adjustable.
Housing units (Census) and home value (Zillow) pre-fill from public data and can be overridden. The flood-risk share (*) is an illustrative assumption. Assumptions below carry illustrative defaults you can change.
This model estimates the underwriting profit impact of adopting Z-FLOOD in a given county. It uses the combined ratio, the core profitability metric in insurance, which adds the loss ratio (claims paid as a share of premium) to the expense ratio (acquisition and admin cost as a share of premium). A combined ratio under 100% means the book is profitable before investment income.
We start from the county's housing units and the share in flood-risk zones to size the addressable market. Applying the uptake rate gives the number of policies, and the premium rate applied to average home value gives the premium per policy. Together these produce total written premium.
The profit uplift comes from one lever: Z-FLOOD's improvement to the loss ratio. Better flood risk selection means fewer claim dollars per premium dollar, which drops straight to underwriting profit. We apply that improvement to written premium, then adjust for two real-world frictions: how fast the product can be filed and approved, and how ready the carrier's systems are to integrate it. Slower filing and weaker integration discount the realized return.
Every assumption above is shown on screen and can be changed. The defaults are illustrative starting points, not Z-FLOOD performance figures. Adjust them to your own book and the results update live.