Thu, 06 May 2021

OAKLAND, CA / ACCESSWIRE / April 20, 2021 / today announced new findings on the efficacy of the company's Z-FIREmodel, which was used as the focus of a recent research paper by Sheri Scott, a principal with Milliman, a leading global actuarial consulting firm. The new white paper, the second in their research series ‘Understanding Wildfire Risk in California', studied the efficacy of's Z-FIRE™ model for assessing risk to homes covered by the California Fair Access to Insurance Requirements (FAIR) Plan, which as the state's insurer of last resort insures the properties in California which are most vulnerable to wildfire. This ongoing research was done independently and was not commissioned by or the FAIR Plan. The intention of the research was not to endorse any one model or product.

The paper found Z-FIRE™ to deliver a significant lift in risk prediction. The lift is a measure of the predictive power of the model to differentiate the best from the worst risks and improve the FAIR Plan's ability to price wildfire risk.

'We firmly believe that next generation AI-based climate risk models like Z-FIRE™ that incorporate unique property level characteristics are central to accurately assessing the climate risk of each property. Such individualized risk assessment provides insurers, asset managers, consumers, businesses and government all the data to efficiently insure and mitigate the impacts of catastrophic events.,' said Kumar Dhuvur, Founder and Head of Product at 'Z-FIRE™ allows carriers to confidently offer risk-adjusted premiums to properties they would previously consider uninsurable, which gets us closer to achieving an equitable and resilient insurance market for all.'

Z-FIRE™ has been trained on more than 1200 wildfire events across 20+ years of wildfire history whereas traditional models take only limited risk factors into account and do not make use of historical loss data. Through machine learning and the use of modern satellite technology, accounts for the property-level factors that contribute to wildfire risk which produces insights with 10,000 times higher resolution than the simple statistical models currently used by the industry. Data on building materials, topography, historical weather data, and critically, factors extracted from aerial imagery like vegetation which can be affected by mitigation efforts contribute to the model's modern view of property risk. Z- FIRE™ combines these details to derive a predictive risk score.

To access the full white paper please visit risk-score-model and for more information on Z-FIRE™ and's other climate risk models please visit

About Us

Increasingly frequent natural disasters have impacted communities and drove $2.2 Trillion in economic losses over the past decade. uses 200Bn data points, including aerial imagery, and artificial intelligence to assess the impact of climate change one building at a time. has partnered with leading insurance companies and property owners to help them protect homes, businesses and support thriving communities. was named Top 100 Most Innovative AI Company in the world by CB Insights in 2020, and Gartner Cool Vendor in Insurance by Gartner Research in 2019. For more information visit:




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