Description: LTC insurers are beginning to implement population health programs to improve the lives of their policyholders before and during a claim. Measuring the financial impact of these programs can be difficult for a variety of reasons and multiple methodologies are used to evaluate treatments or programs. This article proposes two different methods of randomized control trials to evaluate the impact of these programs through a case study approach, along with additional potential considerations when evaluating effectiveness.

Description: Discussion of machine learning applications currently being used to augment traditional actuarial modeling in the life insurance industry. This includes data science techniques for: Quantifying and explaining differences between model versions or reporting periods Building proxy models for actuarial model output using machine learning One-class classification for data integrity checks Applications of unsupervised learning (e.g., clustering and principal components analysis) to reduce model run time

Description: We ask whether we can find support for the previously reported upper limit of the force of mortality of 0.7, i.e. about the probability of tossing a fair coin.

Description: This paper discusses the actuarial risk measures and uses a variety of estimation techniques such as nonparametric approach, parametric methods and robust procedures. From 39th Actuarial Research Conference, Iowa City, Iowa, August 5-7, 2004.

Description: Incorporating Pended Claims in Medical IBNR Estimates. Issue No. 45.

Description: We provide a possible solution to deal with the parameter estimation of mortality models when the population size is small, based on graduation methods.

Description: Exam study notes on credibility theory.

Description: By necessity, attributions of financial processes require approximations. Tools used for approximations include Aumann-Shapley, time step, step-through, average step-through, partial derivative, and average partial derivative. Significantly non-linear paths can cause problems during attribution. Time (theta) and market factors must be handled concurrently. Typically contractual factors can be handled separately. Average Step-Through, Aumann-Shapley and Aumann-Shapley-3 points perform the best given the same time period. Attribution should be done with fairly small time steps as opposed to using a lot of points in the Aumann-Shapley calculation, but using Aumann-Shapley-3 points as a last step has some advantages.

Description: Summary of the SOA research project on PBR Simplified Methods. Describes the multi-risk scenario generator, central estimate assumptions, assumption objectivity measures, and regulatory demonstrations per VM-20.

Description: Feature article about the use of approximations.