Risk Prediction Initiative
Hurricane Landfall Forecasting Competition
Source: Bernews
RPI2.0 announced its third round of Seasonal US Hurricane Landfall Forecasting competition, citing the potential predictive skill of ‘crowd-intelligence’
RPI2.0 Announces Round 2 of its 2013 Seasonal Forecast Competition
In a nod to the value of crowdsourcing as an effective forecasting method RPI2.0 announces round 2 of its seasonal forecast competition, in which participants can win $1,250 by submitting forecasts by March 1
Read MoreRPI2.0 Announces Crowdsourcing Experiment; Seasonal Forecast Competition
Source: Bernews
HAMILTON, Bermuda, Nov. 20, 2012 / Market Watch: In a nod to the value of crowdsourcing as an effective forecasting method, the RPI2.0 announces the start of its seasonal forecast competition, in which participants can win up to $5000
Hurricane Wind Speed Can Predict Economic Losses
Using more than a century of data, Rick Murnane, Risk Prediction Institute (RPI) Project Manager and Senior Research Scientist at BIOS, and his co-author uncovered a simple—but surprisingly robust—method of estimating losses
Read More(Re)Insurance Companies Use RPI2.0 Workshop Proceedings as Industry Reference
In March of this year, the newly christened Risk Prediction Initiative (RPI) 2.0 hosted a workshop on the medium-term outlook for the frequency of hurricane landfalls in the RMS v11.0 risk model. According to this model, the computed risk for hurricanes over the medium-term (next 5 years) increased more than 100% in some regions, which forces insurance companies to hold more capital
Read MoreRisk Prediction Initiative 2.0 Hosts RMS Conference
Over the past 16 years, RPI has formed an extensive network of world-renowned climate scientists who have used their expertise in areas such as climate change, ocean currents, and ocean-atmosphere interactions to more accurately estimate the frequency and intensity of natural catastrophes. Combined with more than a decade of experience regarding the needs of the (re)insurance industry, RPI stands as one of the major players in science-based risk prediction for the (re)insurance industry
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