Field notes.
Research, analysis, and lessons learned from building wildfire models, underwriting AI, and geospatial analytics.
Why Should Insurers Look at La Niña Differently?
Between 1955 and 2019, over 350,000 hail events occurred in the US. La Niña increases hail frequency by ~50%. We dug into the geographic and temporal patterns insurers need to understand.
UrbanStat Classified 80% of Structures Burned in Dixie Fire as High or Worse Risk
Dixie Fire, the 2nd largest wildfire in California history, burned almost 1 million acres and destroyed ~1,300 structures. UrbanStat's AI model classified 80% of affected structures as High or worse risk.
UrbanStat Classified Over 95% of Areas Burned in Dixie Fire as High or Worse Risk
As California's Dixie Fire exploded in size, we analyzed our model's performance. Over 95% of burned areas were classified as High or worse risk by UrbanStat's pre-season wildfire risk map.
UrbanStat Adds Parcel and Permit Data to Its Analytics Platform
We've added parcel and permit data covering all 50 states — over 30 new variables including construction date, building value, and permits. UrbanStat now has hundreds of data points per address.
UrbanStat Expands Wildfire Risk Coverage to New Geographies
Our proprietary wildfire risk map now covers California, Nevada, Arizona, Washington, and Oregon. The model has predicted over 90% of areas burned by the most destructive fires as High or worse risk.
Using ZIP Codes Costs You, and Here Is Why
ZIP codes were invented to deliver mail, not to underwrite insurance. We analyzed the opportunity cost of using ZIP codes for moratoriums and found insurers are leaving significant premium on the table.
UrbanStat Predicted Over 85% of Burned Areas in 2020 Before Wildfire Season Started
2020 was a record-breaking year with over 4 million acres burned. Our model classified over 85% of burned areas as High or worse risk — and over 90% for the top 10 most destructive fires.
Is Machine Learning the Silver Bullet in Underwriting?
Machine learning for insurance underwriting isn't straightforward. From imbalanced datasets to regulatory constraints, here's what we've learned building ML models for property insurance over 3 years.
The Wildfires Won't Stop Miraculously, What's Next?
Over 30 wildfires sparked in California within days, burning 3.1 million acres in 2020. As an industry, we need better risk models that focus on causation, not just correlation.
UrbanStat Adds Over 30 Countries in Europe to Its Data Collection
UrbanStat expanded data coverage from 3 to over 35 countries. European carriers can now access 25+ data points per address including earthquake, storm, flood, wildfire, and crime data.
Four Major Lessons We Learned About Wildfires in California
After 2 years of wildfire research, we found that commonly used variables like fuel and slope aren't enough. Power infrastructure, climate patterns, and human factors matter far more than the industry realizes.