Description: How well can we predict ACA HHS Risk Adjustment Data Validation (HRADV) results? Put another way, how susceptible is the current HRADV process to small sample volatility? What potential remedies are there to the current model's shortcomings? Every plan, regardless of how many members they have above the 1000 minimum, count equally if they qualify for an HRADV with how the result is interpreted, and the subsequent HRADV risk transfer ($330M in 2023).

Description: With the unprecedented proliferation in the size and complexity of data over the past decade, actuaries have invested considerable time and energy in the development of new skills and expertise in order to be able to understand and use “big data” to its fullest potential in the development of actuarial work product.

Description: Cover a variety of topics centered around the unsupervised learning technique called 'clustering'. The presenters will take you through a wide array of topics that range from 'What is Clustering?' to 'How can I use this technique to solve problems I didn't even know existed?' In the health care industry, everyone is looking for an edge in reducing total spend-cluster analysis finds the unambiguous in an ambiguous framework of results.

Description: Similar to how states had made adjustments to their capitation rates to reflect acuity adjustments caused by the onset of the pandemic, states will need to modify the rates to reflect the unwinding since utilization patterns and average acuity per enrolled member will change. When the continuous coverage requirements set forth by the COVID-19 Public Health Emergency (PHE) ended, Medicaid-managed care programs across the country adopted various approaches to phasing out maintenance of effort (MOE) as a result of changes to the PHE-era continuous eligibility requirements. Phasing out the MOE requirement will ultimately result in members who no longer meet eligibility requirements losing their Medicaid coverage. Further, states are facing a wide variety of circumstances and are implementing diverse approaches to the MOE phase-out. This topic will be of significant interest to all actuaries and stakeholders of the capitation rate development process for Medicaid-managed care programs. Join us as we discuss the operationalization of the PHE unwind while referencing the SOA's research project which models the effects of the unwinding on Medicaid eligibility and population costs. You will learn about the various approaches that different states have adopted to manage the unwinding process, which will be instrumental for accurately pricing managed care rates.

Description: One of the most effective ways to convey quantitative results is via data visualization. However, many times actuaries have been ineffective in doing this. In this session, you will see a demonstration of certain dataviz choices that make communicating results more effective in terms of graph type choice, graph element styles, colors and more. All examples will be in Excel-and doesn't require Visual Basic for Applications (VBA)! Nothing too fancy! I want to distribute working files to attendees before the session so they can follow along with how to build the graphs, make changes, etc. Graph choices will include line graph, tile grid map and jitter graph.

Description: Amid the growing adoption of AI/ML models for underwriting and pricing, Life and Annuity carriers are facing increasing regulation in North America on Model Risk Management (MRM) and the use of AI. Colorado has set a precedent in the US by requiring reporting in June 2024, with other states looking to follow suit. To ensure compliance, Chief Risk Officers and Heads of MRM, working with their business partners, will need to evolve their MRM and AI risk frameworks, enhance model validation capabilities, and strengthen governance. This session will present: - Key trends and challenges faced by carriers amid increasing model landscape complexity and regulatory expectations - Regulatory outlook and implications for carriers' MRM and AI risk programs - An approach to enhance MRM and AI risk frameworks, including specific model validation program updates to address the unique risks of AI/ML models - Opportunities to enhance both MRM validation effectiveness and efficiency through the adoption of more risk-based approaches, smart sourcing, and automation - Case studies of how leading carriers are evolving their MRM and AI risk programs Upon attending the session, the attendees will develop a good understanding of increasing regulatory expectations, the required MRM and AI risk framework enhancements, and approaches to design and execute an effective MRM validation program in a cost-efficient manner.

Description: Driver-based forecasting is a powerful tool to predict and estimate future outcomes. In recent years, driver-based forecasting has gained significant attention as a technique for actuaries to forecast the financial performance of insurance companies. Often there can be frustration around the ability to use forecasts to manage the business. However the objective of a driver-based forecast is to break down historic and projected movement based on the key drivers which impact the results. The key is to understand what the key drivers are on forecasts and what is the relative level of impact and influence we have on the drivers. Listen in on a discussion on the core principles of driver-based forecasting, including how to identify key drivers, collect accurate data, and leverage the latest technology to generate forecasts that traditional models can't match. Explore with us the various driver-based models and how actuaries can leverage them to enhance their decision-making capabilities. Then join the conversation about the challenges actuaries face when implementing this technique and how to mitigate these problems.

Description: As data continues to become more robust and readily available, there has been a push in the actuarial field to transition away from Excel to SQL and Python native cloud-based platforms. While these platforms are widely used and powerful, they present challenges for the actuarial industry: Requiring processes to be production-ready from the onset, technical expertise for integration and robust documentation. Low-code tools provide a unique alternative solution, which works when the organization's operating model allows for actuarial and IT to work together, giving actuaries the flexibility they need while maintaining a level of control followed by the organization In this session, you will watch demonstrations that showcase low-code tools and their use case in the actuarial space. See how these low-barrier-to-entry tools can be leveraged to create robust processes. We will discuss solutions such as Alteryx and Dataiku and how low-code tools can integrate with coding languages such as Python to create more robust processes.

Description: The COVID-19 pandemic has been an acute reminder of the material impacts that pandemics can have on Life (re)insurance and society at large. Learn to describe the journey of a Life reinsurance practitioner to model and operationalize pandemic and infectious disease risk, why this is of importance to actuaries, and their risk management. It will consider how such models have been used, developments over time, and challenges in using and calibrating these models. The session will also provide perspectives from a pandemic model provider who will describe the fundamental metrics for pandemic loss distributions and how learnings from the COVID-19 pandemic can be used to quantify the potential impact of the next pandemic. Finally, dive into an outline of how biological principles can be applied to anticipating plausible pathogens causing the next pandemic.

Description: The upcoming VM-22 standard promises significant changes for the non-VA life insurance industry, impacting regulatory compliance, risk management, and financial reporting. This presentation equips insurance companies to navigate this crucial transition. We'll delve into key considerations from capital, modeling, and hedging perspectives, providing actionable insights for optimizing your VM-22 implementation strategy.