Gauge

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Take more educated risks.

Assessing weather risk for underwriting can be difficult and tedious. Gauge allows insurers to strengthen their business portfolio by providing enhanced analysis of weather risk for multiple perils in an easy-to-use online application.

Risk Analysis and Asset Management

This risk analysis and portfolio management tool enables users to evaluate the geospatial risk of hail, tornadoes, straight-line winds, heavy rainfall, winter storms and ice storms. GAUGE groups together areas of similar risk by peril, allowing underwriters and managers to overlay their portfolio of business and streamline decision making for future risk allocation. Through statistical analysis of at least 37 years of historical weather data, underwriters can more intelligently and efficiently make weather-related risk decisions.

Risk Scoring

Weather Analytics scores each peril based on the level of risk exposure, calculating statistical risk indices on a 15x15 km (9x9 mile) grid cell for simplified but accurate analysis. Gauge groups and color codes areas of similar risk into zones, allowing the user to quickly identify areas of higher risk versus lower risk. Each zone provides detailed risk statistics based on time-of-year and severity (such as risk based on various hail sizes).

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Portfolio Management

Gauge can take a user’s book of business to evaluate current, to-date weather risk susceptibility and view where insured assets lie with respect to various risk zones. Underwriters can evaluate the value of assets across risk zones, allowing for smarter risk taking decisions when writing new business.

Use Case

Historical convective storm data can be prone to biases and errors, and Weather Analytics goes to great lengths to ensure our data is the most accurate. For example, when computing hail risk, human-reported hail observations are normalized to account for the bias related to population density, improving the accuracy of the pure atmospheric-based risk assessment. Historical human observations are also blended with high resolution radar-based data, improving the geographical resolution of risk, and reducing the errors related to human reporting and population density variations.