We model the mortality behavior of the general population in Mexico using data from 1990 to 2009 and compare it to the mortality assumed in the tables used in Mexico for insured lives. We fi a Lee-Carter model, a Renshaw-Haberman model and an Age-Period-Cohort model. The data used are drawn from...

We model the mortality behavior of the general population in Mexico using data from 1990 to 2009 and compare it to the mortality assumed in the tables used in Mexico for insured lives. We fi a Lee-Carter model, a Renshaw-Haberman model and an Age-Period-Cohort model. The data used are drawn from...

The aim of this paper is to estimate the longevity risk and its trend according to the age of the individual. We focus on individuals over 65. We use the value-at-risk to measure the longevity risk. We have proposed the use of an alternative methodology based on the estimation of the truncated...

This article focuses on business risk management in the insurance industry. A methodology for estimating the profit loss caused by each customer in the portfolio due to policy cancellation is proposed. Using data from a European insurance company, customer behaviour over time is analyzed in...

XGBoost is recognized as an algorithm with exceptional predictive capacity. Models for a binary response indicating the existence of accident claims versus no claims can be used to identify the determinants of traffic accidents. This study compared the relative performances of logistic...

We analyzed real telematics information for a sample of drivers with usage-based insurance policies. We examined the statistical distribution of distance driven above the posted speed limit—which presents a strong positive asymmetry-using quantile regression models. We found that, at different...

A new method to estimate longevity risk based on the kernel estimation of the extreme quantiles of truncated age-at-death distributions is proposed. Its theoretical properties are presented and a simulation study is reported. The flexible yet accurate estimation of extreme quantiles of...

Quantile regression provides a way to estimate a driver's risk of a traffic accident by means of predicting the percentile of observed distance driven above the legal speed limits over a one year time interval, conditional on some given characteristics such as total distance driven, age, gender,...