Description: This article discusses the reliance the banking industry placed on sophisticated mathematical models.

Description: This abstract describes a paper that investigates model uncertainty arising from different ways of treating the operational loss data collection threshold.

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: This abstract describes a paper that proposes a multi-population Global Vector Autoregression (GVAR) mortality model, in which the joint mortality dynamics of all populations are formulated in a large vector autoregression model with a set of contemporaneous global mortality factors.

Description: This is an Excel workbook that can be used as a tool for health insurance companies to model their potential risk exposure from an influenza pandemic. It is based on a model developed for a Society of Actuaries study examining the potential implications of a pandemic on the U.S. health insurance industry. The spreadsheet is saved with many of the same assumptions used in this research and reproduces the results of the exhibits contained in the June 2010 report, 'Potential Impact of Pandemic Influenza on the U.S. Health Insurance Industry.'

Description: An overview of bias and fairness in machine learning models, as they apply to use cases in life insurance.

Description: Employers, health plans, stop-loss insurers and reinsurers are all affected by the high cost of treating cancer. In recent years, cutting-edge pharmaceuticals, bone marrow transplants and CAR-T cell therapies have driven very high cost trends for cancer, with more emerging therapies on the horizon. In this session, we will review these new treatments, showcase models that aid in understanding the range of likely financial effects of the current, expanded, and likely-to-be approved indications for cell therapies that will treat certain patients affected by lymphoma, leukemia, and multiple myeloma. This session will explain important considerations for modeling Medicare, Medicaid versus commercial populations, key risk concerns caused by the size of enrollee pools, and important differences between the various therapies that affect modeling. We will also discuss averted cost, health outcomes, pricing levels, and risks caused by provider billing practices.

Description: The Individual Life Experience Committee is holding a competition encouraging actuaries and other interested parties to predict 2017 industry mortality based on a data set containg 2009 - 2016 data. The competition is not only about predicting mortality, but also about explaining and presenting the results.

Description: The topics of ESG (Environmental, Social & Corporate Governance) and sustainability are an increasing area of focus for insurance companies, and thus actuaries. This webcast provides a primer on these topics along with considerations for US valuation actuaries and their evolution in European insurance markets.

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.