Description: This paper reports on the findings of a working group established in 1999 by the SOA's Finance Practice Area to look at how the insurance industry measures and monitors risk through risk position reporting. Also the working group established industry standard practices in risk position reporting and reported on a number of areas for possible improvement in such reporting.

Description: This paper addresses the fuzziness in regression models. The goal is to present a test procedure to explicitly examine whether an independent variable has a clear functional relationship with the dependent variable in a specific regression model, or whether their relationship is fuzzy. To this end, the authors interpret the spread of the regression coefficients as a statistic measuring the fuzziness of the relationship between the corresponding independent variable and the dependent variable. They then derive test distributions based on the null hypothesis that such spreads could have been obtained with data generated by a classical regression model with random errors. The analysis is presented in conceptual rather than technical terms.

Description: The theme of this paper relates to solving portfolio selection problems using linear programming. The authors extend the linear optimization framework for Conditional Value-at-Risk-based portfolio selection problems to optimization over a more general class of risk measure known as the class of Coherent Distortion Risk Measure. From Actuarial Research Clearing House, 2012 Vol. 1.

Description: In this paper, we propose measures of the risk that the value of the liabilities becomes larger than the value of the assets, and this especially for insurance companies. We study probabilities of mismatching and a degree of mismatching in unsegmented and multidimensional models of the balance, in which we stress the influence of interest rates on the active and passive side of the balance.

Description: The results obtained during the last one-third of the research project and the project at whole are presented. The report only contains brief descriptions of the results which are placed in addendums and which are in reality copies of papers and a chapter of a book submitted for publication. Some theoretical and applied problems induced by the research are discussed.

Description: These files shows the Schelling Segregation model. It accompanies the report Complexity Science - an introduction and invitation for actuaries, and supports the material in Chapter six: Cellular automata.

Description: 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. 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 model, programmed in Microsoft Excel [xlsx format], projects per-person expenditures and growth rates through 2099 using a set of equations and assumptions developed by Professor Getzen with assistance from the Society of Actuaries Project Oversight Group appointed to oversee the effort. The model includes baseline assumptions as well as flexibility for user–inputted alternative assumptions.

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 report explores AI bias in insurance and health data, highlighting the ethical role of actuaries and offering cross-disciplinary guidance for fairer decision-making systems.

Description: In today’s business world, many financial decisions undergo considerable analysis before the decision is made and the decision-maker is often held accountable for the outcomes. The purpose of this research is to introduce the concept of total risk analysis (TRA), which is designed to help the decision-maker answer key questions at the time the decision is made. This paper will focus on a specific example of a typical healthcare decision: setting a budget for claims in the upcoming year. In addition to explaining TRA and providing a case study, this paper presents quantitative research regarding cost distributions for health care costs.