ASTIN big data working party phase II: Predictive modeling

ASTIN big data working party phase II: Predictive modeling

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Speaker(s): Louise Francis (Francis Analytics and Actuarial Data Mining, Inc.), Axel Wolfstein (Verti)

The Phase 2 ASTIN Big Data Working party focused on introducing key Predictive Modeling methods used by actuaries. Phase 2 has a focus on hands-on applications.Because of the focus on applications, the working party work emphasizes applications and examples using publically available databases and downloadable code.The R open source software package was used in our examples.
The working party output is intended to be used as an educational tool in predictive modeling and machine learning by actuaries. Members of the Working Party identified an insurance database from a 2000 modeling competition.The data set was distributed and to all Working Party members for their modeling work.
The following are methods that the working party is introducing:

  • Unsupervised Learning (Principal Components and Clustering)
  • MARS (Multivariate Adaptive Regression Splines)
  • Trees
  • Ensemble models
  • In addition, deep learning neural networks, which were introduced by a separate ASTIN Working Party, is applied to the data for comparison to the other methods.

Phase 2 Current Members:

  • Louise Francis (champion for working party)
  • Syed Danish Ali
  • Fumihiro Endo
  • Mary Jo Kannon
  • Elana KulinskayaH
  • Hidemasa Oda
  • Axel Wolfstein

The working party results are comprised of four papers. We request one full break-out session.

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