Description: Expert discussion of three previous papers: Makeham-Type Mortality Models Mumpar-Victoria, An Extreme Value Analysis of Advanced Age Mortality Data Robertson, and Living to 100 and Beyond: An Extreme Value Study Han. From 2005 Living to 100 and Beyond Monograph, M-LI05-1.

Description: Abstract for the 2008 ERM Monograph paper, “Estimating Mortality Risk Using Predictive Modeling”

Description: Discussion on Living to 100 Session 4A. Papers presented: Inference for Logistic-type models for the Force of Mortality and, Predictive Modeling for Advanced Age Mortality

Description: As a life reinsurer, understanding mortality risk is mission critical. Superior models of mortality risk lead to more competitive pricing in profitable market segments and more efficient use of capital. Surprisingly, modern statistical tools such as predictive modeling have not previously been used to model mortality data to gain this edge. In this paper, we present the use of a predictive modeling technique called projection pursuit regression PPR to model mortality data. We first describe the process of creating a PPR model using inter-company mortality data collected by the Individual Life Experience Committee of the Society of Actuaries, and present the resulting model. We then discuss the process of using this model as a starting point for creating a more detailed PPR model of internal company mortality data.

Description: Experts' discussion of mortality laws and models. From 2005 Living to 100 and Beyond Monograph, M-LI05-1.

Description: These are the discussant comments from Session 1A: Data Sources and Analysis from the January 4-6 2017 Living to 100 Symposium in Orlando.

Description: This paper demonstrates the calculation of the moments of the distribution of aggregate life insurance claims from seriatim inforce data, assuming that each record represents an independent Bernoulli trial with its own known probability of a claim, q. Continuous distributions matching the first three or four moments are identified.