Description: This mortality study is based on results of calendar year 1994 from 17 companies. Experience for issues ages over 70 is reported with differentiation by sex, issue age, policy year, amount, smoking status, underwriting status, reinsurance status, plan of insurance, and level of retention.

Description: Improve your financial reporting knowledge with this SOA e-course. It will help you understand financial statements and regulatory capital requirements.

Description: Dive into this review on Artificial Intelligence and Machine Learning (AIML) techniques for actuarial modeling for life & annuities. Presenters will showcase learnings from the recent SOA research paper "Predictive Analytics and Machine Learning – Practical Applications for Actuarial Modeling" (Nested Stochastic). The researchers will go over models and methodologies used to develop high-fidelity proxy models for various life & annuity applications.

Description: CMS has required hospitals to publish their chargemaster rates, cash discounts and negotiated rates as of January 1, 2021. Our panel is comprised of a data strategist, an executive from a large hospital system and an actuary.

Description: An Excel spreadsheet to aid the reader in interpreting the information contained in the report, which provides exposure information by lapse factor and data cell. Please see the SOA website experience studies for the full report.

Description: Analysis of Profits Before and After 90% Modco at beg. of 2nd year.

Description: Data needed to run the Hack-a-Thon that was held at the 2019 PAS.

Description: Excel file to be attached to cover sheet on this same 2005-2007 individual life persistency study. Contains the actual persistency experience data from the study.

Description: This is a presentation on computing tight bounds for insurance payments with nonlinear risk. Semi-definite Programming is defined, some examples are presented, and non-linear applications are presented. From Actuarial Research Clearing House, 2012, Vol.1.

Description: This paper shows that credibilty theory and Parametric Empirical Bayes [PEB] theory are closely related and applies PEB theory to credibility applications for normal and other familiar probability distributions.