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mvClaim: an R package for multivariate general insurance claims severity modelling Annals of Actuarial Science Pub Date : 2021-04-05 Sen Hu, T. Brendan Murphy, Adrian O’Hagan
The mvClaim package in R provides flexible modelling frameworks for multivariate insurance claim severity modelling. The current version of the package implements a parsimonious mixture of experts (MoE) model family with bivariate gamma distributions, as introduced in Hu et al., and a finite mixture of copula regressions within the MoE framework as in Hu & O’Hagan. This paper presents the modelling
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LRMoE.jl: a software package for insurance loss modelling using mixture of experts regression model Annals of Actuarial Science Pub Date : 2021-03-18 Spark C. Tseung, Andrei L. Badescu, Tsz Chai Fung, X. Sheldon Lin
This paper introduces a new julia package, LRMoE, a statistical software tailor-made for actuarial applications, which allows actuarial researchers and practitioners to model and analyse insurance loss frequencies and severities using the Logit-weighted Reduced Mixture-of-Experts (LRMoE) model. LRMoE offers several new distinctive features which are motivated by various actuarial applications and mostly
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Tree-based models for variable annuity valuation: parameter tuning and empirical analysis Annals of Actuarial Science Pub Date : 2021-03-16 Zhiyu Quan, Guojun Gan, Emiliano Valdez
Variable annuities have become popular retirement and investment vehicles due to their attractive guarantee features. Nonetheless, managing the financial risks associated with the guarantees poses great challenges for insurers. One challenge is risk quantification, which involves frequent valuation of the guarantees. Insurers rely on the use of Monte Carlo simulation for valuation as the guarantees
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Valuation of long-term care options embedded in life annuities Annals of Actuarial Science Pub Date : 2021-03-15 An Chen, Michel Fuino, Thorsten Sehner, Joël Wagner
In most industrialised countries, one of the major societal challenges is the demographic change coming along with the ageing of the population. The increasing life expectancy observed over the last decades underlines the importance to find ways to appropriately cover the financial needs of the elderly. A particular issue arises in the area of health, where sufficient care must be provided to a growing
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Automatic analysis of insurance reports through deep neural networks to identify severe claims Annals of Actuarial Science Pub Date : 2021-03-09 Isaac Cohen Sabban, Olivier Lopez, Yann Mercuzot
In this paper, we develop a methodology to automatically classify claims using the information contained in text reports (redacted at their opening). From this automatic analysis, the aim is to predict if a claim is expected to be particularly severe or not. The difficulty is the rarity of such extreme claims in the database, and hence the difficulty, for classical prediction techniques like logistic
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Evaluation of equity-linked products in the presence of policyholder surrender option using risk-control strategies Annals of Actuarial Science Pub Date : 2021-03-08 Patrice Gaillardetz, Saeb Hachem, Mehran Moghtadai
Throughout the past couple of decades, the surge in the sale of equity-linked products has led to many discussions on the evaluation and risk management of surrender options embedded in these products. However, most studies treat such options as American/Bermudian style options. In this article, a different approach is presented where only a portion of the policyholders react optimally due to the belief
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Extracting information from textual descriptions for actuarial applications Annals of Actuarial Science Pub Date : 2021-03-02 Scott Manski, Kaixu Yang, Gee Y. Lee, Tapabrata Maiti
Initial insurance losses are often reported with a textual description of the claim. The claims manager must determine the adequate case reserve for each known claim. In this paper, we present a framework for predicting the amount of loss given a textual description of the claim using a large number of words found in the descriptions. Prior work has focused on classifying insurance claims based on
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Modelling random vectors of dependent risks with different elliptical components Annals of Actuarial Science Pub Date : 2021-02-22 Zinoviy Landsman, Tomer Shushi
In Finance and Actuarial Science, the multivariate elliptical family of distributions is a famous and well-used model for continuous risks. However, it has an essential shortcoming: all its univariate marginal distributions are the same, up to location and scale transformations. For example, all marginals of the multivariate Student’s t-distribution, an important member of the elliptical family, have
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Mortality models incorporating long memory for life table estimation: a comprehensive analysis Annals of Actuarial Science Pub Date : 2021-02-02 Hongxuan Yan, Gareth W. Peters, Jennifer Chan
Mortality projection and forecasting of life expectancy are two important aspects of the study of demography and life insurance modelling. We demonstrate in this work the existence of long memory in mortality data. Furthermore, models incorporating long memory structure provide a new approach to enhance mortality forecasts in terms of accuracy and reliability, which can improve the understanding of
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Using a stochastic economic scenario generator to analyse uncertain superannuation and retirement outcomes Annals of Actuarial Science Pub Date : 2020-12-10 Wen Chen, Bonsoo Koo, Yunxiao Wang, Colin O’Hare, Nicolas Langrené, Peter Toscas, Zili Zhu
The retirement systems in many developed countries have been increasingly moving from defined benefit towards defined contribution system. In defined contribution systems, financial and longevity risks are shifted from pension providers to retirees. In this paper, we use a probabilistic approach to analyse the uncertainty associated with superannuation accumulation and decumulation. We apply an economic
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A neural network model for solvency calculations in life insurance Annals of Actuarial Science Pub Date : 2020-12-01 Lucio Fernandez-Arjona
Insurance companies make extensive use of Monte Carlo simulations in their capital and solvency models. To overcome the computational problems associated with Monte Carlo simulations, most large life insurance companies use proxy models such as replicating portfolios (RPs). In this paper, we present an example based on a variable annuity guarantee, showing the main challenges faced by practitioners
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A spatial machine learning model for analysing customers’ lapse behaviour in life insurance Annals of Actuarial Science Pub Date : 2020-11-10 Sen Hu, Adrian O’Hagan, James Sweeney, Mohammadhossein Ghahramani
Spatial analysis ranges from simple univariate descriptive statistics to complex multivariate analyses and is typically used to investigate spatial patterns or to identify spatially linked consumer behaviours in insurance. This paper investigates if the incorporation of publicly available spatially linked demographic census data at population level is useful in modelling customers’ lapse behaviour
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Clustering driving styles via image processing Annals of Actuarial Science Pub Date : 2020-10-27 Rui Zhu, Mario V. Wüthrich
It has become of key interest in the insurance industry to understand and extract information from telematics car driving data. Telematics car driving data of individual car drivers can be summarised in so-called speed–acceleration heatmaps. The aim of this study is to cluster such speed–acceleration heatmaps to different categories by analysing similarities and differences in these heatmaps. Making
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Mortality forecasting using a Lexis-based state-space model Annals of Actuarial Science Pub Date : 2020-09-11 Patrik Andersson, Mathias Lindholm
A new method of forecasting mortality is introduced. The method is based on the continuous-time dynamics of the Lexis diagram, which given weak assumptions implies that the death count data are Poisson distributed. The underlying mortality rates are modelled with a hidden Markov model (HMM) which enables a fully likelihood-based inference. Likelihood inference is done by particle filter methods, which
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A review on Poisson, Cox, Hawkes, shot-noise Poisson and dynamic contagion process and their compound processes Annals of Actuarial Science Pub Date : 2020-09-09 Jiwook Jang, Rosy Oh
The Poisson process is an essential building block to move up to complicated counting processes, such as the Cox (“doubly stochastic Poisson”) process, the Hawkes (“self-exciting”) process, exponentially decaying shot-noise Poisson (simply “shot-noise Poisson”) process and the dynamic contagion process. The Cox process provides flexibility by letting the intensity not only depending on time but also
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AI in actuarial science – a review of recent advances – part 1 Annals of Actuarial Science Pub Date : 2020-08-26 Ronald Richman
Rapid advances in artificial intelligence (AI) and machine learning are creating products and services with the potential not only to change the environment in which actuaries operate but also to provide new opportunities within actuarial science. These advances are based on a modern approach to designing, fitting and applying neural networks, generally referred to as “Deep Learning.” This paper investigates
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AI in actuarial science – a review of recent advances – part 2 Annals of Actuarial Science Pub Date : 2020-08-26 Ronald Richman
Rapid advances in artificial intelligence (AI) and machine learning are creating products and services with the potential not only to change the environment in which actuaries operate, but also to provide new opportunities within actuarial science. These advances are based on a modern approach to designing, fitting and applying neural networks, generally referred to as “Deep Learning”. This paper investigates
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Using hierarchical Archimedean copulas for modelling mortality dependence and pricing mortality-linked securities Annals of Actuarial Science Pub Date : 2020-08-26 Jackie Li, Uditha Balasooriya, Jia Liu
In this article, we explore the use of multivariate Archimedean copulas in modelling the mortality dependence between different countries and pricing mortality bonds. We study the fitting performance of multi-dimensional, fully nested, and partially nested Archimedean copulas and test 11 types of generators and two skewed distributions. To evaluate their practical usefulness, we adopt the fitted models
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A practical support vector regression algorithm and kernel function for attritional general insurance loss estimation Annals of Actuarial Science Pub Date : 2020-08-24 Shadrack Kwasa, Daniel Jones
The aim of the paper is to derive a simple, implementable machine learning method for general insurance losses. An algorithm for learning a general insurance loss triangle is developed and justified. An argument is made for applying support vector regression (SVR) to this learning task (in order to facilitate transparency of the learning method as compared to more “black-box” methods such as deep neural
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Multifactorial disorders and polygenic risk scores: predicting common diseases and the possibility of adverse selection in life and protection insurance Annals of Actuarial Science Pub Date : 2020-08-14 Jessye M. Maxwell, Richard A. Russell, Hei Man Wu, Natasha Sharapova, Peter Banthorpe, Paul F O’Reilly, Cathryn M Lewis
During the past decade, genetics research has allowed scientists and clinicians to explore the human genome in detail and reveal many thousands of common genetic variants associated with disease. Genetic risk scores, known as polygenic risk scores (PRSs), aggregate risk information from the most important genetic variants into a single score that describes an individual’s genetic predisposition to
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Mortality data reliability in an internal model Annals of Actuarial Science Pub Date : 2020-08-03 Fabrice Balland, Alexandre Boumezoued, Laurent Devineau, Marine Habart, Tom Popa
Abstract In this paper, we discuss the impact of some mortality data anomalies on an internal model capturing longevity risk in the Solvency 2 framework. In particular, we are concerned with abnormal cohort effects such as those for generations 1919 and 1920, for which the period tables provided by the Human Mortality Database show particularly low and high mortality rates, respectively. To provide
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Longevity risk and capital markets: the 2018–19 update Annals of Actuarial Science Pub Date : 2020-07-29 David Blake, Andrew J. G. Cairns
This Special Issue of the Annals of Actuarial Science contains 12 contributions to the academic literature all dealing with longevity risk and capital markets. Draft versions of the papers were presented at Longevity 14: The Fourteenth International Longevity Risk and Capital Markets Solutions Conference that was held in Amsterdam on 20-21 September 2018. It was hosted by the Pensions Institute at
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On unbalanced data and common shock models in stochastic loss reserving Annals of Actuarial Science Pub Date : 2020-07-27 Benjamin Avanzi, Greg Taylor, Phuong Anh Vu, Bernard Wong
Introducing common shocks is a popular dependence modelling approach, with some recent applications in loss reserving. The main advantage of this approach is the ability to capture structural dependence coming from known relationships. In addition, it helps with the parsimonious construction of correlation matrices of large dimensions. However, complications arise in the presence of “unbalanced data”
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Fitting multi-population mortality models to socio-economic groups Annals of Actuarial Science Pub Date : 2020-07-14 Jie Wen, Andrew J.G. Cairns, Torsten Kleinow
We compare results for 12 multi-population mortality models fitted to 10 distinct socio-economic groups in England, subdivided using the Index of Multiple Deprivation. Using the Bayes Information Criterion to compare models, we find that a special case of the common age effect (CAE) model fits best in a variety of situations, achieving the best balance between goodness of fit and parsimony. We provide
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Optimal portfolio choice with tontines under systematic longevity risk Annals of Actuarial Science Pub Date : 2020-07-13 Irina Gemmo, Ralph Rogalla, Jan-Hendrik Weinert
Abstract We derive optimal portfolio choice patterns in retirement (ages 66–105) for a constant relative risk aversion utility maximising investor facing risky capital market returns, stochastic mortality risk, and income-reducing health shocks. Beyond the usual stocks and bonds, the individual can invest his assets in tontines. Tontines are cost-efficient financial contracts providing age-increasing
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Valuation of no-negative-equity guarantees with a lower reflecting barrier Annals of Actuarial Science Pub Date : 2020-07-10 R. Guy Thomas
If the general level of house prices falls a long way, policymakers may introduce new policies which seek to support prices. This paper considers the effect of such interventions on the valuation of no-negative-equity guarantees (NNEG) in equity release mortgages. I model interventions by a reflecting barrier expressed as a fraction of the current level of house prices. Reflection at the barrier is
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Home and Motor insurance joined at a household level using multivariate credibility Annals of Actuarial Science Pub Date : 2020-07-06 Florian Pechon, Michel Denuit, Julien Trufin
Actuarial ratemaking is usually performed at product and guarantee level, meaning that each product and guarantee is considered in isolation. Moreover, independence between policyholders is generally assumed. In this paper, we propose a multivariate Poisson mixture, with random effects correlated using a hierarchical structure, to accommodate for the dependence that may exist between unobserved risk
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CBDX: a workhorse mortality model from the Cairns–Blake–Dowd family Annals of Actuarial Science Pub Date : 2020-06-22 Kevin Dowd, Andrew J. G. Cairns, David Blake
Abstract The purpose of this paper is to identify a workhorse mortality model for the adult age range (i.e., excluding the accident hump and younger ages). It applies the “general procedure” (GP) of Hunt & Blake [(2014), North American Actuarial Journal, 18, 116–138] to identify an age-period model that fits the data well before adding in a cohort effect that captures the residual year-of-birth effects
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Multivariate Hawkes process for cyber insurance Annals of Actuarial Science Pub Date : 2020-06-17 Yannick Bessy-Roland, Alexandre Boumezoued, Caroline Hillairet
In this paper, we propose a multivariate Hawkes framework for modelling and predicting cyber attacks frequency. The inference is based on a public data set containing features of data breaches targeting the US industry. As a main output of this paper, we demonstrate the ability of Hawkes models to capture self-excitation and interactions of data breaches depending on their type and targets. In this
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On the use of Archimedean copulas for insurance modelling Annals of Actuarial Science Pub Date : 2020-06-17 Thilini Dulanjali Kularatne, Jackie Li, David Pitt
In this paper, we explore the use of an extensive list of Archimedean copulas in general and life insurance modelling. We consider not only the usual choices like the Clayton, Gumbel–Hougaard, and Frank copulas but also several others which have not drawn much attention in previous applications. First, we apply different copula functions to two general insurance data sets, co-modelling losses and allocated
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Identifiability in age/period/cohort mortality models Annals of Actuarial Science Pub Date : 2020-06-04 Andrew Hunt, David Blake
Abstract The addition of a set of cohort parameters to a mortality model can generate complex identifiability issues due to the collinearity between the dimensions of age, period and cohort. These issues can lead to robustness problems and difficulties making projections of future mortality rates. Since many modern mortality models incorporate cohort parameters, we believe that a comprehensive analysis
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Identifiability in age/period mortality models Annals of Actuarial Science Pub Date : 2020-06-02 Andrew Hunt, David Blake
Abstract As the field of modelling mortality has grown in recent years, the number and importance of identifiability issues within mortality models has grown in parallel. This has led both to robustness problems and to difficulties in making projections of future mortality rates. In this paper, we present a comprehensive analysis of the identifiability issues in age/period mortality models in order
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Longevity trend risk over limited time horizons Annals of Actuarial Science Pub Date : 2020-05-21 Stephen J. Richards, Iain D. Currie, Torsten Kleinow, Gavin P. Ritchie
Abstract We consider various aspects of longevity trend risk viewed through the prism of a finite time window. We show the broad equivalence of value-at-risk (VaR) capital requirements at a p-value of 99.5% to conditional tail expectations (CTEs) at 99%. We also show how deferred annuities have higher risk, which can require double the solvency capital of equivalently aged immediate anuities. However