skyblu.ai

Address-level risk scoring for P&C insurers

Underwriting & Risk Startup

Overview

Skyblu.ai is a risk-scoring platform for P&C insurers, turning individual street addresses into address-level risk features for motor and household lines. The approach replaces coarser postcode-level risk aggregation with data tied to the specific property or driving location.

The platform combines geoinformatics, climate science, hydrology, and actuarial modeling to produce peril scores for flood, hail, wind gust, landslide, wildfire, and (in France) subsidence, along with driving-behavior signals for motor insurance. Insurers use these features in pricing, underwriting, and risk-model precision workflows.

Founded in 2018 and based in Warsaw, Poland, the company is live in Poland, France, and Spain, with stated plans to expand into additional European markets. Founder and CEO Kinga Kita-Wojciechowska is an actuary with about ten years of insurance pricing experience across six countries; the rest of the core team includes specialists in meteorology, hydrology, geoinformatics, and data science.

Products & Services

Motor Insurance Risk Features

Address-level data describing driving patterns and behavioral risk, used to improve motor pricing accuracy beyond postcode-based models.

Target Users: P&C insurers underwriting motor policies

Household Insurance Climate Risk Scores

Peril scores for flood, hail, wind gust, landslide, and wildfire, plus subsidence risk for the French market, built from climate science and hydrology modeling combined with satellite imagery analysis.

Target Users: P&C insurers underwriting household and home policies