Description: At the conclusion of this session attendees will be familiar with the status of the NAIC's GOES project and have a better understanding of the scenario sets under consideration and how they can be tested to assess the potential impact to principle-based reserve and capital levels.

Description: Understanding Asian Capital Regimes

Description: Analyze financial risk and explore the foundation for pricing, valuation and other functions served by actuaries in the modeling profession during this webcast. Expect a focus on the importance of understanding and preventing bias. Observe the different types of bias, how it can enter into models, how to identify it in models and best avoidance practices. Join our presenter who is pursuing a Masters in Economic Analytics at Clemson University as he incorporates his recent economic research into the webcast material.

Description: Electronic Health Records are here to stay. Take a deep dive into the world of electronic health records and how the industry is poised to utilize this new form of digital medical data to transform the way policies are underwritten and ultimately, transforming the client experience. Listen to industry experts speak about what they are doing to use this data most effectively and how this ultimately develops into ground-breaking solutions for the industry.

Description: In this session, we will discuss best practices in ALM and Strategic Asset Allocation (SAA) modeling approaches to account for the complex relationships between insurance liabilities and the portfolios backing them. We will highlight how robust modeling techniques not only result in optimal asset decisions from a long-term value perspective but can also result in better capital efficiency. At the conclusion of this session, attendees will be able to identify the key aspects of a successful ALM and SAA framework for liabilities subject to PBR.

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: Virtual - Session 8D: An Application of Clustering Approaches in Value-Based Care

Description: A comprehensive webcast designed to bring together industry practitioners to discuss the current state of Model Risk Management (MRM) frameworks. This event will delve into the advancements in MRM, the challenges faced by professionals in the field, and emerging trends such as machine learning model validation that are set to shape the future of MRM. Engage with experts, share knowledge, and explore innovative solutions to enhance the effectiveness of your MRM framework.

Description: "Can you answer the question 'what are the chances we will lose more than $1 million next year?' without saying 'it depends'? If you miss a projection, can you quantify the chances that the miss was due to random variation vs. an incorrect projection? ten in as presenters demonstrate how to answer these questions and others using total risk analysis. Total risk analysis includes quantifying both the random variation risk and the projection risk associated with actuarial functions like pricing and reserving. After attending this session, you will be able to describe total risk analysis, apply total risk analysis to many actuarial functions."

Description: In this presentation, actuaries and data scientists from Cleveland Clinic and Milliman discuss the development of a sepsis prediction model using machine learning. Presented with a unique challenge of handling massive amounts of data for near real-time risk scoring, the team took their model development to the cloud and delivered a product in less than a week through a unique virtual engagement.