Penalized Regression and Lasso Credibility

In this Akur8 Academy webinar, Thomas Holmes explores the power of penalized regression as an enhancement to traditional GLM (Generalized Linear Model) modeling. This session covers the theoretical and practical aspects of penalized regression, highlighting its deep connections to credibility theory. Additionally, Thomas introduces the concept of lasso credibility, demonstrating how penalized regression can be applied directly as a credibility procedure. By following the evolution from GLMs to lasso credibility, this webinar offers valuable insights and practical applications for actuaries and professionals in insurance modeling. If you missed this live session, request the full recording here!