Services
Datum provides several levels of Big Data analysis services that seamlessly integrate with existing underwriting and pricing workflows. We work with existing software and existing processes to help our clients better understand Expected Loss through data. We do the heavy lifting for you, no software integration or training is required. We work with each client to define specific analysis goals and we deliver practical, actionable results. Each of our Big Data analytical services is offered on a subscription basis at a fraction of the cost of legacy catastrophe models. Learn more.
Datum provides several levels of Big Data analysis services that seamlessly integrate with existing underwriting and pricing workflows. We work with existing software and existing processes to help our clients better understand Expected Loss through data. We do the heavy lifting for you, no software integration or training is required. We work with each client to define specific analysis goals and we deliver practical, actionable results. Each of our Big Data analytical services is offered on a subscription basis at a fraction of the cost of legacy catastrophe models. Learn more.
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Eurus Wind
Event Probabilities
We run exposure data through our machine learning platform Eurus® to provide a numerical analysis of event probabilities giving you an enhanced view of event risk enabling your firm to create numerically driven EP curves and calculate PML estimates.
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Eurus Plus
Unmodeled Loss
As our weather data set is global and comprehensive we are able to provide insights beyond traditional modeled perils to include Tornado, Winter Storm, and Severe Thunderstorm event risk in a variety of regions over various periods of time in the future. Eurus Plus delivers the power of Eurus Wind as well as additional peril analysis capabilities.
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Eurus Insights
Big Data Insights
We are able to put our Big Data modeling platform to work on massive data sets beyond windstorm property catastrophe. We work with clients to better understand portfolio Expected Loss through data across a range of perils, regions and lines of business beyond traditional property catastrophe.
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