Description: This tool created graphs of Google's mobility Data. This version of the tool contains global, country-level data through July 31, 2020

Description: The July 2013 issue of the SOA’s Forecasting & Futurism section’s newsletter, Forecasting & Futurism.

Description: Transcript of the Q&A period from Session 6A: Projection and Statistical Modeling of Mortality at Late Age

Description: Authored by a MIB Solutions team of Tom Rhodes, Stuart Klugman, Marianne Purushotham and Stacy Gill, the report summarizes the results of a study on the application and adoption of credibility theory within the life insurance and annuity industry. In addition to the report, numerical examples related to the application of credibility to company mortality and lapse data are provided in the four Excel files. This excel spreadsheet is a numerical example relating to the application of Credibility for lapses by policy for limited fluctuation. Please see the SOA website research section for the full report on Credibility Theory Practices.

Description: Hear about some applications using quantile regression-derived individual and group claim distributions and how they may be used in various traditional health care modeling situations. The session will not focus on the technical use of quantile regression to obtain estimates of claim distributions, but more so is intended to focus on the uses of the distributions in actuarial modeling and the additive framework in assessing claims distributions. Presenters will show how actuaries can better assess risks by focusing on the individual- and group-specific claims distributions as opposed to traditional point-estimate-centric models.

Description: Health care has changed rapidly over the past couple of years. The pandemic has shifted consumer behavior in how and where they receive health care as well as consumer attitudes toward health care. Payers continue to design innovative solutions in responses to their patient’s needs and expectations. These changes in consumer behaviors and the responses by payers are expected to impact both health care cost and utilization. Discuss changes in health care that have emerged due to the pandemic and how they are expected to influence actuarial assumptions. Explore epidemiological models commonly used in the industry, the considerations when using these models, as well as the challenges with regards to gathering and interpreting relevant experience data. By attending this session, you will be able to: Identify shifts in consumer behavior that have emerged from the pandemic and describe how payers are responding to new patient expectations. Discuss how these post-pandemic changes by consumers and payers influence medical spending. Determine which actuarial assumptions are impacted and how and if the impact is expected to be temporary or permanent. Discuss considerations taken by actuaries and challenges faced when modelling actuarial assumptions post pandemic.

Description: As effective dates for major changes in insurance accounting are rapidly approaching, insurers find themselves at various stages of their implementation programs. Driven by the need for compliance and desire for operational excellence, companies are transforming by reimagining their processes, leveraging technology enablers, redefining roles and responsibilities, and enhancing risk management, governance, and controls. Companies that proactively include risk and control elements in their accounting change implementation programs benefit from improved outcomes, enhanced investment returns, early identification, and mitigating of risk. Focus on risk and controls considerations around accounting change programs and how strategic partnerships with internal audit and ERM groups can benefit these significant transformation programs. By attending the session, you will: Be able to articulate key considerations around risk and controls for accounting change implementation programs.

Description: What is a vitagion? Is there such thing as catastrophic longevity? What does a 1 in 200 year mortality loss event look like? How might actuaries use mortality scenarios in their practice? Explore how to move beyond simplistic stress testing with singular percentage shocks to building a robust set of information, derived from stochastically generated scenarios for longevity and excess mortality outcomes. This data can inform assumption setting, longevity swaps, capital levels, and risk management. These concepts apply to life insurers, pension actuaries, and reinsurers. By attending the session, you will: - Understand what is a loss exceedance curve is and how it may be useful to quantify tail risks. - Comprehend how to incorporate stochastic variability into longevity and excess mortality assumptions. - Find out what elements go into a stochastic prediction of extreme mortality events using nested models. - Learn how to add more depth to youractuarial assumptions.

Description: Table of Contents

Description: Health Watch, Issue 79, December 2015, Health Watch