After a three-month long crowd sourcing competition, three data scientists proved their data analytical prowess in Allstate's predictive modeling competition. The nation's largest publicly held insurer launched the "Claim Prediction Challenge" with Kaggle on July 13, 2011, offering $10,000 to number crunchers worldwide for the best models predicting bodily injury insurance claims based on vehicle characteristics.
Contestants continued to submit algorithms down to the competition's closing minutes on October 12. From 1,290 total submissions and 202 players, three winners emerged, with their models closest to predicting actual claims data. Taking home the first-place prize was Matthew Carle of Sydney, Australia, followed by Owen Zhang of Bolton, Conn., USA (second place) and Jason Tigg of London, U.K. (third).
Aside from monetary motivation, all three winners said they entered the competition to size up their skills against some of the best predictive modeling talents around. The public leader board on the competition site fueled continual model improvements and additional entries.
Want to continue reading?
Become a Free PropertyCasualty360 Digital Reader
Your access to unlimited PropertyCasualty360 content isn’t changing.
Once you are an ALM digital member, you’ll receive:
- All PropertyCasualty360.com news coverage, best practices, and in-depth analysis.
- Educational webcasts, resources from industry leaders, and informative newsletters.
- Other award-winning websites including BenefitsPRO.com and ThinkAdvisor.com.
Already have an account? Sign In
© 2024 ALM Global, LLC, All Rights Reserved. Request academic re-use from www.copyright.com. All other uses, submit a request to [email protected]. For more information visit Asset & Logo Licensing.
