The problem. Banks are expected to quantify physical climate risk across their lending books, in Israel under Bank of Israel Directive 345 and in the EU under ECB and EBA expectations. Commercial flood scores describe an area, not a street, and they exclude the drainage network that decides urban rainfall flooding. In Europe, borrower-level insurance data is often out of reach for banks under privacy law.
 

What we provide. Flood depth and arrival time for each property, by API or file, ready to feed collateral valuation, PD and LGD models and stress tests. The data describes the physical network and terrain, so it does not depend on borrower records. It can also run beside your current provider as an independent second opinion.

Layer: 4 · Risk Data.

The problem. Flat flood pricing produces adverse selection: premiums are too low on high-risk streets and too high on safe ones. When a loss may be recoverable from a third party, subrogation teams need engineering-grade evidence.

​

What we provide. A building-level flood index for underwriting. A backtest on a storm you already know: the model's prediction set against your actual claims. Flood depth and timing as evidence for claims and subrogation review. Later, warnings to policyholders ahead of a storm (Roadmap).

​

Layers: 4 · Risk Data, and 1 · Calibrated Model for the backtest.

The problem. A score does not tell an owner whether to acquire, upgrade or sell, and it does not price the fix. Underground parking, plant rooms and basements carry the exposure, and investors expect asset-level physical-risk assessment, for example in GRESB reporting.

What we provide. A site report with flood depth and timing at your building and its access routes. On top of it, a CAPEX Pack: the tested measure, such as detention volume, a drainage connection or a blue roof, and its estimated cost, so the decision is priced before acquisition or works.

Layers: 4 · Risk Data and 2 · CAPEX Packs.