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Predictive Analytics in Life Insurance: How to Get Real Results

RGA shares basic steps insurers can take to prevent overfitting for more accurate predictive models.


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: Predictive Analytics in Life Insurance: How to Get Real Results


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

The Presenter

  • Rosmery Cruz
    Senior Data Scientist
    Global Research and Data Analytics
    RGA

Summary

Contact RGA's research team to learn more about data science, predictive analytics and insurance.  

Click here to view a presentation on this subject from the 2018 SOA Predictive Analytics Symposium.

https://player.vimeo.com/video/333412931
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