Description: En el seminario hablaremos sobre los nuevos flujos de tarificación, y nos enfocaremos en la inclusión del análisis geográfico en el proceso de modelado para optimizar la extracción del riesgo en modelos de Machine Learning.

Description: This session will cover everything you've wanted to know about GLMs but were too afraid to ask. How do these generalized models relate to the plain linear regression, and how can we be sure that the models we implement are appropriate for the task at hand?

Description: The insurance industry hinges on accurate actuarial assumptions. This session explores how insurers can leverage AI/machine learning (ML) to unlock greater accuracy and granularity in assumption setting, while effectively managing risks, implementing strong governance frameworks, and meeting validation expectations from regulators.

Description: The article explores a closed-form forecasting method that combines Exponentially Weighted Moving Average (EWMA), weighted linear regression, and ridge regression (L2 regularization). The approach addresses two key challenges in time-series forecasting: adapting to nonstationarity and mitigating overfitting due to multicollinearity. EWMA assigns more weight to recent observations, while ridge regression penalizes large coefficients to stabilize estimates. A cross-validation strategy across rolling time windows selects optimal hyperparameters: the EWMA decay factor (α) and the ridge penalty (λ). The method is tested using repeated regressions of stock returns, showing that most hyperparameter combinations outperform ordinary least squares (OLS) under the (λ=1, α=0) setting.

Description: This article helps actuaries who may have excellent business ideas to take the first step of starting a business

Description: "Risk adjustment is an important aspect of establishing appropriate capitation rates. When a set of services is carved out for specific management under a sub-capitation, establishing appropriate adjustments for varying levels of underlying risk is more complicated. Dive into analytical and operational challenges and resolutions as presenters share more about developing a risk adjustment model specific to the carve-out of behavioral health services through a real-life case study. You will further explore a definition of the use case, availability of historical data sets, selection of the modeling approach, learnings from the iterative modeling process, and the potential application of the results. After attending this session, you will be able to: Understand why a behavioral health specific-risk adjustment model has business value Understand the unique challenges related to developing risk adjustment on member and cost subsegments Understand the impact of trade-offs between model complexity and interpretability in the context of implementation Increase awareness of data nuances and requirements unique to this type of project Describe analytic techniques that can be investigated for use in projects of similar business objectives"

Description: As health insurance self-funding becomes more popular among smaller group sizes, risk is evolving for the MGUs, stop loss writers, and reinsurers that cover them. Assessing more small groups at lower attachment points means rethinking traditional stop loss underwriting techniques.

Description: Learn how modernization of data, models, and technology are influencing workflows. This webcast will address how workflows are changing in response to new regulatory requirements and the impacts the changes have on modeling and end-to-end future state operating models. Industry leading actuaries will discuss: How team collaboration can increase quality and speed of reporting to internal and external stakeholders How to strengthen controls and compliance frameworks across finance and actuarial departments How to modernize actuarial input/output for strategic analysis and insights How to attract and retain top talent by improving opportunities for actuaries There will also be dedicated time to ask questions of those who have made the transition.

Description: What is bias? How do you recognize it? What to do if you see it? This webcast will help respond to these questions and provide initial guidance on how to deal with these thorny issues. Please join us with your questions and we will have a nice conversation.

Description: Risk adjustment is widely used by public and private payers in value-based contracting and other risk-sharing arrangements aimed at addressing population health. Addressing social determinants of health (SDOH) and improving equitable outcomes is one of the aims of population health. Could SDOH be incorporated into risk adjustment? If so, how and how effectively? What implications might this have for market participants? In this session, Joan Barret, FSA, MAAA, from Axene Health Partners will begin by presenting background and findings from the 2022 SOA research report 'How Does Where you Live Impact Your Health?.' This is a question addressed through deep literature review and quantitative analysis, followed by an exploration of strategic approaches and barriers for payers and providers that wish to address SDOH inequities. Then, Rong Yi, FSA, MAAA, and Jeff Milton-Hall, FSA, MAAA, from Milliman will present their new SOA-sponsored analysis regarding integration of SDOH factors into Medicaid managed care risk adjustment. They will cover risk adjustment design considerations, policy and operational considerations for actuaries and states that wish to integrate SDOH into risk adjustment, simulated variation in financial outcomes for risk-bearing organizations when such integration occurs, and variation in the relationship of SDOH factors and morbidity to modeled risk across programs and populations. At the conclusion of the session, attendees will leave equipped to think critically and act effectively with respect to SDOH in their own work, from measurement and analysis design to actuarial interventions.