Actuarial
  • Videos
  • August 2019

How to Get Real Results in Predictive Analytics

In Brief

Contact 69É«ÇéƬ's research team to learn more about data science, predictive analytics, and insurance.  

Ever-increasing computing power allows analysts to manipulate data and build models from both small and large datasets more quickly and more effectively than ever before. Yet these enhanced capabilities also come with a greater number of choices and greater exposure to building models that overfit the data.

Tasked with determining an applicant’s mortality risk years into the future, life insurers must be acutely aware of the potential pitfalls of overfitting, take steps to accurately validate every predictive model they develop, and work continuously to update and improve models as new forms of data become available.

See also: 


If you would like to discuss this webcast further, please e-mail us at: CMSTeam@rgare.comContact 69É«ÇéƬ's research team to learn more about post-term lapsecustomer engagement, and insurance. 


More Like This...

Meet the Authors & Experts

ROSEMARY CRUZ
Expert
Rosmery Cruz
Executive Director, Behavioral Data Science Risk and Behavioral Science, 69É«ÇéƬ