Regression models still rule in P&C Insurance | Jim Weiss | Data Science Hangout

ADD THE DATA SCIENCE HANGOUT TO YOUR CALENDAR HERE: https://pos.it/dsh - All are welcome! We'd love to see you! This week's guest was Jim Weiss, Chief Risk Officer, commercial and executive at Crum and Forster! Some topics covered in this week's Hangout were the use of regression modeling (have you ever heard of the Tweedie distribution?) in property and casualty insurance, handling changing model results and communicating them to business stakeholders, using GenAI and "co-opetition" to identify and prevent fraudulent claims, and identifying and managing bias or confounding effects in pricing models. Resources mentioned in the video and chat: 🔗 The Once and Future C&F → https://www.cfins.com/the-once-and-future-cf-landing/ 🔗 Tweedie distribution → https://en.wikipedia.org/wiki/Tweedie_distribution 🔗 Statistical Rethinking Lectures Playlist → https://www.youtube.com/playlist?list=PLDcUM9US4XdNOlqSyhe38US8mFgmqzI14 🔗 Considerations for Managing Potential Bias in Pricing Models → https://eforum.casact.org/article/91188-considerations-for-managing-potential-bias-in-pricing-models 🔗 Pointblank for data validation (Python) → https://posit-dev.github.io/pointblank/ 🔗 Pointblank (R) → https://rstudio.github.io/pointblank/ ► Subscribe to Our Channel Here: https://bit.ly/2TzgcOu Follow Us Here: Website: https://www.posit.co Hangout: https://pos.it/dsh The Lab: https://pos.it/dslab LinkedIn: https://www.linkedin.com/company/posit-software Bluesky: https://bsky.app/profile/posit.co Thanks for hanging out with us! 💛 Timestamps 00:00 Introduction 02:16 "Who is Crum and Forster? What do you do? What types of problems does your team help them solve?" 04:14 "What kind of data types would you see in your day to day or your team would see in your day to day? And what is an example of a problem that you feel like you've solved lately or that you've been working on lately?" 10:14 "What types of regression do you use?" 13:35 "In your insurance modeling career, what is the most unusual or unexpected variable that has contributed to one of your models?" 18:48 "How do you handle it when you see that the results are significantly different across models?" 21:45 "Are you Team Bayesian or Team Frequentist when it comes to your statistics?" 27:13 "My health care organization is interested in identifying fraudulent claims. Currently, they're looking at Excel spreadsheets, same time, different person. Do you have any advice on a better way to guide them to automation?" 30:51 "What software do you use to do your job?" 35:40 "Do you ever use instrumental variables in your models?" 47:47 "Do you have any career advice for us? Is there something you wish that you had known when you were first entering the industry?" 50:38 "How much do you and your team use AI to help you along?" 52:56 "How does your team span expertise in such varied fields?"