Description: This paper attempts to broaden the actuary's understanding of decrement rate estimation and to clear up some of the more common misconceptions which have been promoted.

Description: The purpose of this paper is to illustrate the use of a new approximation to determine contingency reserves against adverse mortality experience for a portfolio of life annuity contracts.

Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

Description: This paper presents simple Bayesian graduation models that substantially ease the prior elicitation burden, and also describes a Monte Carlo integration approach that greatly reduces the computational load.

Description: Presented at Living to 100 symposium, January 2011. This paper presents a method for using death records to infer exposure on non-extinguished cohorts, thereby allowing the development of a credible table for high ages.

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: This paper introduces a conjecture as to a method for estimating how much has to be added to the probability of ruin by n claims to obtain the probability of ultimate ruin. From the Actuarial Research Clearing House 1994 Vol. 2 .

Description: This paper discusses a class of asymmetric distributions arising in a random summation scheme. Members of the class are called asymmetric Laplace distributions as the standard Laplace distributions, which are symmetric, constitute a proper subclass. Among distributions which are limits in random summation schemes, asymmetric Laplace distributions play an analogous role to that of normal distributions among distributional limits of non-random sums. Asymmetric LaPlace laws are more 'peaky' and have heavier tails than normal laws. They have stability properties and are convenient in applications, as their densities have explicit forms and estimation procedures are easily implemented. Anticipating increasing interest in this class of distributions, the authors present statistical tools which can be utilized in practice, including algorithms for simulation and estimation. They also discuss more general classes of distributions, where asymmetric Laplace distributions appear as special cases.

Description: Presents a theoretical basis for a computerized methodology for estimating biological age - a measure of time to death.

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