Informed underwriting decisions

A variety of factors influence a property’s wildfire exposure risk score. Vegetative features, such as fuel load, type, and alignment, and regional considerations, including topography, climate, and fire history, all contribute to the risk profile of an insured property. WDSrisk was created to utilize these wildfire risk elements to provide users with an easily-understood score. The proprietary WDSrisk algorithm is focused solely on interpreting wildfire risk - a unique approach when compared to big-data models that dominate the insurance industry - integrating location vulnerability with wildfire hazard potential to identify the probability of loss during a wildfire event. This probability is then associated with deviation categories for the state to better inform policy underwriting decisions.

Key Benefits:

  • Outputs make policy writing decisions easy
  • Immediate point analysis via web interface and/or API to aid potential policy decision-making
  • Easily interpreted scoring, identifying loss probability and categories specific the state
  • DOI acceptance in several Western states, confirming use to impact policy pricing and decision making

WDSrisk Key Elements

Outputs make policy writing decisions easy

Immediate point analysis via web interface and/or API to aid potential policy decision-making

Easily interpreted scoring, identifying loss probability and categories specific the state

DOI acceptance in several Western states, confirming use to impact policy pricing and decision making

WDSrisk Solutions

Spatially Weighted Modeling: Algorithms incorporate the best aspects of industry standard models without the challenges

Multiple weighted layers: Weaves into risk, analyzing many layers and accurately appropriating the influence of distance for each.

Granularity

WDSrisk score provides finer granularity; increasing pricing options and removes boundary pricing.

Each layer’s output is combined

Algorithm weights the influence of each layer on overall threat.

A single, easy to use output is produced.

Output score can be transposed automatically to correspond to the Insurer’s current risk scale.

Many outputs that the insurer may already be using can be isolated from the WDSrisk model E.g. Ember Zone