Description: Four appendices are attached to the monograph: a letter requesting information, two letters requesting participation, and a set of general database specifications. From Group Medical Insurance Large Claims Database Collections and Analysis, M-HB97-1.

Description: Open source programming languages have become a common part of the actuarial toolkit over the years. Using tools like R and Python, highly technical actuaries can automate onerous processes, easily work with massive amounts of data, create models and generate reports. Although these tools excel at turbo-charging analysts, it can be difficult for benefits to inure to the rest of the organization given the learning curve (“Can’t you just put this in Excel?”), control risks (“So your entire process could break overnight if some random person in Nebraska changes something?”), and internal IT environments. Listen in on a panel discussion where presenters share their personal stories of working with open source in a production setting. Hear about real world business problems, how open source tools were used, what risks were present, how they were overcome and the final business result.

Description: Join in and learn to describe the changes in provider contracting that are emerging in the post-COVID marketplace. Examples include: - Carrier transparency files - Increase sophistication of provider negotiators - Additional sources of data - Market issues increasing urgency - Demanding new contracting models

Description: Toward a Predictive Analytics Framework files

Description: In this session, we will delve into the powerful capabilities of two essential algorithms in the field of data science and machine learning: Generalized Additive Models (GAM) and CatBoost. These algorithms can play a crucial role in conducting experience studies for insurance.