Description: Healthcare costs have been rising faster than general inflation for many years. Early models that predicted this past pattern projected healthcare expenditure growth that continued to outpace total expenditure growth leading to the fallacious position that the whole of the US economy would ultimately be consumed by healthcare. The Society of Actuaries' Pension Section and Health Section Research teams commissioned Professor Thomas E. Getzen of Temple University to construct a resource model for the projection of long term healthcare cost trends that includes capacity constraints to ensure the long-term projection is rational. The motivation for creation of the model was driven by its potential usage as a resource for the estimation of reportable liabilities for retiree healthcare benefits as specified under FAS 106 and GASB 45 accounting statements. This is a zip file containing the following: 1. A background paper on the creation of the health trend model, 2. The model, programmed in Microsoft Excel [xls format], that projects per-person expenditures and growth rates through 2099 using baseline assumptions, but also permits the flexibility for user–inputted alternative assumptions, and 3. Technical documentation providing transparency and support for the ultimate results.

Description: This paper provides an overview of the employee benefit package, provides data and discusses issues with regard to cost variation, and shows how this data can be combined to provide an understanding of the variation for different employee benefit packages.

Description: The Society of Actuaries Product Development Section, the Modeling Section, the Reinsurance Section and the Financial Reporting Section announce the release of a new research report that introduces a novel framework for leveraging the "architecture" of an industry mortality table within a company's predictive analytics-based insured mortality analysis.

Description: Appendixes for the Evaluating ACO Efficiency: Risk Adjustment within Episodes study. The study aims to answer the question of how much of an episode’s cost and use of specific services can be attributed to the patient’s own health status, as opposed to being driven by other factors such as the care setting, patient preference, and provider practice patterns. In other words, do episode costs vary so widely because of patient characteristics, including health status, or are they related to other, nonclinical factors?

Description: This is the fourth Intercompany Study of Long–Term Care Insurance. This report combines and analyzes data received from 24 insurers that agreed to provide information to further the knowledge of long–term care insurance. Those insurers are listed in Appendix A of the report.

Description: The Society of Actuaries' Long-Term Care Insurance Experience Committee is soliciting information on long-term care policies for both incidence lapse mortality and claim terminations from January 1, 2000 through December 31, 2011.

Description: RMD file.

Description: The Individual Life Insurance Valuation Mortality Task Force of the Society of Actuaries has completed a new Valuation Basic Mortality Table for individual life insurance. This was updated April 2005 - Age Last Birthday tables added. This zipped file will decompress into 6 documents 2 Microsoft Word documents and 4 Microsoft Excel spreadsheets. ?Final Report.doc ?Appendix A.doc ?Ratio.xls ?Female.xls ?Male.xls ?ALB.xls

Description: The SOA's Committee on Finance Research is please to make available the results of this research project, jointly sponsored by the SOA and CAS, that explores economic series and provides and Excel based tool for generating future economic scenarios. This is an Excel Spreadsheet for Appendix C showing Simulated Financial Scenario Data of inflation rates and interest rates from this research project. Please see the SOA website for the full report and other related spreadsheets.

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.