Identify the chronic flood risk for every property by using our proprietary high-resolution risk model, capturing flood exposure at a resolution of 1 x 1 meter.

Unique Data and Machine Learning for Damage Prediction:

• A unique dataset developed through multiple years of R&D collaboration with Fremtind Insurance, activating data from more than one million pluvial flood policies.

• The 7Analytics machine learning model is built upon more than 600 physical parameters per property and has been trained on a vast database of flood claims data.

• This enables the model to output superior damage predictions with applications in risk discrimination and pricing.

Proactive and Dynamic Modeling:

• Unlike traditional flood models based on historical events, we have reverse-engineered flood risk modeling by using a proactive modeling approach which is not biased towards the occurrence of historical flood events.

• Using a first-principles, physical model and fluid dynamics techniques, the model works reliably in any topography where geospatial data is available (land-use and terrain data).

• The model is fully dynamic, adopting changes in the landscape and built-environment with live urbanization tracking, which is crucial to a thorough understanding of flood risk over time.