Description: Nathan Pohle and Darryl Wagner believe actuaries can benefit from new technologies in predictive analytics and life insurance.

Description: Stochastic modeling requirements are resulting in more 'run time' and less 'analysis time'. An expensive solution is leveraging cloud infrastructures and robust computing grids. The presenters will explore the use of cluster modeling and present case studies showcasing this automatable and robust technique, which could allow actuaries to recover the time lost to 'run time'. Developing automatable and clustered models requires robust governance practices to ensure credibility of results.

Description: Data science, predictive analytics and AI are certainly the buzzwords these days. They are heavily used and developed in underwriting and marketing but for most actuaries, they might/may as well be science fiction. The presenters will demonstrate how a normal actuary can utilize data science techniques in their daily job function without forming an official data science team within a company. It can be done in a gradual fashion so that normal business is not disrupted and improvements are made over time. The usage of data science techniques will include demonstrations of the following areas: - Regression analysis - Economic scenario generator - Experience study - Data quality checks - Inforce compression for explicit hedging

Description: Discuss various analytics and use cases using payer published reimbursement contract data under federal mandate of Transparency in Coverage. These contract rates are publicly available in machine readable format (MRF) starting July 1, 2022, and refreshed monthly. By attending the session, you will have a better understanding of the state-of-art development and analytics using MRF data, including the technologies used to extract and analyze huge MRF files, validation and limitations of published rates, and their use cases.

Description: The COVID-19 pandemic has disrupted the global economy at a level never imagined. The economic fallout has been catastrophic. Record high unemployment, staggering revenue loss, bankruptcy and an uncertain future have businesses—and consumers—searching for a beacon of hope. In the quest for a lifeline, actuarial teams are quickly being thrust into the spotlight

Description: As the insurance industry continues to evolve due to a pandemic and rapidly changing economic and regulatory conditions, the role of data scientists and actuaries has become increasingly important. In an interview with the Atidot data science and actuarial team, we discuss what it is like to work at an InsurTech, how data scientists and actuaries can collaborate, and look at some concrete technical examples of where the innovation is having an impact. This article explores what collaboration can look like and how the role of data science and actuary may evolve in the InsurTech industry in the future.

Description: This article delves into the transformative realm of Business Intelligence (BI) tools. We explore the fundamental functionality and structure of these tools, and through case studies illustrate how they offer valuable insights into carrier experience and underwriting dynamics. From real-time data visualization to in-depth data analysis, discover the essential features that empower businesses to make better informed decisions.

Description: We all know how important data is, right? But the most challenging question we face is how we transform raw data into meaningful insights to help make better business decisions. How should we communicate this vast amount of data into digestible pieces that enable end users to perform on-demand analytics and become self-sufficient? This is where data visualization tools stand out. The field of data visualization combines both art and [data] science. While data visualizations can be creative and pleasing to the eyes, they can also be highly functional in uncovering a point of view or unlocking insights unseen before. Dive into Power BI, Streamlit, and Tableau, and work through an actual business use case utilizing these tools. Find out more about data gathering and connections, processing, and analysis leading up to an interactive dashboard. At the end of the session, you will be able to: - Understand general data issues and how to clean and transform raw data for visualizations. - Differentiate between many visualization tools, and analyze pros and cons to determine the right toolkit for the use-case on hand - Learn practical tips on how to use visualization tools to build meaningful visualizations and dashboards. - Interpret results and patterns from the visualizations and make impactful business decisions.