scholarly journals GEOGRAPHICAL DIVERSIFICATION AND LONGEVITY RISK MITIGATION IN ANNUITY PORTFOLIOS

2021 ◽  
pp. 1-36
Author(s):  
Clemente De Rosa ◽  
Elisa Luciano ◽  
Luca Regis
Keyword(s):  
Interest Rates ◽  
Risk Mitigation ◽  
Longevity Risk ◽  
Insurance Company ◽  
International Expansion ◽  
Life Insurance Company ◽  
Continuous Time Model ◽  
Time Model ◽  
Risk Margin ◽  
Geographical Diversification

ABSTRACT This paper provides a method to assess the risk relief deriving from a foreign expansion by a life insurance company. We build a parsimonious continuous-time model for longevity risk that captures the dependence across different ages in domestic versus foreign populations. We calibrate the model to portray the case of a UK annuity portfolio expanding internationally toward Italian policyholders. The longevity risk diversification benefits of an international expansion are sizable, in particular when interest rates are low. The benefits are judged based on traditional measures, such as the Risk Margin or volatility reduction, and on a novel measure, the Diversification Index.

scholarly journals Solution of Ruin Probability for Continuous Time Model Based on Block Trigonometric Exponential Neural Network

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 876
Author(s):  
Yinghao Chen ◽  
Chun Yi ◽  
Xiaoliang Xie ◽  
Muzhou Hou ◽  
Yangjin Cheng
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Ruin Probability ◽  
Risk Model ◽  
Insurance Company ◽  
Classical Risk Model ◽  
Continuous Time Model ◽  
Time Model ◽  
Trial Solution ◽  
Premium Income

The ruin probability is used to determine the overall operating risk of an insurance company. Modeling risks through the characteristics of the historical data of an insurance business, such as premium income, dividends and reinvestments, can usually produce an integral differential equation that is satisfied by the ruin probability. However, the distribution function of the claim inter-arrival times is more complicated, which makes it difficult to find an analytical solution of the ruin probability. Therefore, based on the principles of artificial intelligence and machine learning, we propose a novel numerical method for solving the ruin probability equation. The initial asset u is used as the input vector and the ruin probability as the only output. A trigonometric exponential function is proposed as the projection mapping in the hidden layer, then a block trigonometric exponential neural network (BTENN) model with a symmetrical structure is established. Trial solution is set to meet the initial value condition, simultaneously, connection weights are optimized by solving a linear system using the extreme learning machine (ELM) algorithm. Three numerical experiments were carried out by Python. The results show that the BTENN model can obtain the approximate solution of the ruin probability under the classical risk model and the Erlang(2) risk model at any time point. Comparing with existing methods such as Legendre neural networks (LNN) and trigonometric neural networks (TNN), the proposed BTENN model has a higher stability and lower deviation, which proves that it is feasible and superior to use a BTENN model to estimate the ruin probability.

scholarly journals Optimal Claim Decisions for a Bonus-Malus System: a Continuous Approach

1979 ◽  
Vol 10 (2) ◽  
pp. 215-222 ◽  
Author(s):  
Nelson De Pril
Keyword(s):  
Risk Factors ◽  
Risk Group ◽  
A Priori ◽  
Risk Groups ◽  
Relevant Information ◽  
Insurance Company ◽  
Continuous Time Model ◽  
Time Model ◽  
Experience Rating ◽  
Risk Class

For the premium calculation the insurer will split up his collectivity of risks into risk groups which are homogeneous with respect to some directly observable risk factors. All risks of such a risk group will be charged the same base premium. But it is clear that by such an a priori classification not all determined factors can be taken into consideration, so that there will still remain accident proneness differentials within a risk group. Since these differentials will be reflected in the course of time by the claim experience of each risk, the insurer can come to a fair tarification by adjusting, each period, the base premium according to the individual claim experience of the risk. Such a system in which earlier neglected risk factors are taken into account a posteriori is an individual experience rating system. Our main interest goes to the following side-effect of experience rating: since an unfavourable claim experience results in a premium increase, an experience rated policyholder is stimulated to self-insure small damages. This phenomenon is well know in connection with bonus-malus systems in motor-car insurance, which explains why it is called “bonus-hunger”.In the present paper a continuous time model for the bonus-malus system is set up which takes into account this hunger for bonus. An insured causing an accident will decide according to a certain decision rule whether to file a claim with his insurance company. The relevant information that he needs to make this decision is: his current risk class, the number of claims he has already filed during that period and the moment at which the decision is to be made.

Discretization of deflated bond prices

2000 ◽  
Vol 32 (2) ◽  
pp. 540-563 ◽  
Author(s):  
Paul Glasserman ◽  
Hui Wang
Keyword(s):  
Interest Rates ◽  
Term Structure ◽  
Discrete Time ◽  
Continuous Time ◽  
Unit Interval ◽  
Continuous Time Model ◽  
Time Model ◽  
Numerical Work ◽  
Continuous Time Process ◽  
Continuous Time Processes

This paper proposes and analyzes discrete-time approximations to a class of diffusions, with an emphasis on preserving certain important features of the continuous-time processes in the approximations. We start with multivariate diffusions having three features in particular: they are martingales, each of their components evolves within the unit interval, and the components are almost surely ordered. In the models of the term structure of interest rates that motivate our investigation, these properties have the important implications that the model is arbitrage-free and that interest rates remain positive. In practice, numerical work with such models often requires Monte Carlo simulation and thus entails replacing the original continuous-time model with a discrete-time approximation. It is desirable that the approximating processes preserve the three features of the original model just noted, though standard discretization methods do not. We introduce new discretizations based on first applying nonlinear transformations from the unit interval to the real line (in particular, the inverse normal and inverse logit), then using an Euler discretization, and finally applying a small adjustment to the drift in the Euler scheme. We verify that these methods enforce important features in the discretization with no loss in the order of convergence (weak or strong). Numerical results suggest that these methods can also yield a better approximation to the law of the continuous-time process than does a more standard discretization.

International Expansion — A United Kingdom Perspective: A Discussion Paper

2000 ◽  
Vol 6 (1) ◽  
pp. 3-54 ◽  
Author(s):  
D.J. Grenham ◽  
D.C. Chakraborty ◽  
A. Chatterjee ◽  
P.J. Daelman ◽  
B. Heistermann ◽  
...  
Keyword(s):  
United Kingdom ◽  
Life Insurance ◽  
Insurance Markets ◽  
Insurance Company ◽  
International Expansion ◽  
Life Insurance Company ◽  
Discussion Paper ◽  
A Company ◽  
Overseas Market

ABSTRACTThis paper looks at the reasons why a UK life insurance company would wish to consider expanding into an overseas market, the factors it ought to bear in mind when deciding upon which country or countries to enter and the entry routes open to a company wishing to expand overseas.By way of examples of overseas life insurance markets, the paper provides a detailed description of the German and Indian life insurance markets.

Discretization of deflated bond prices

2000 ◽  
Vol 32 (02) ◽  
pp. 540-563 ◽  
Author(s):  
Paul Glasserman ◽  
Hui Wang
Keyword(s):  
Interest Rates ◽  
Term Structure ◽  
Discrete Time ◽  
Continuous Time ◽  
Unit Interval ◽  
Continuous Time Model ◽  
Time Model ◽  
Numerical Work ◽  
Continuous Time Process ◽  
Continuous Time Processes

This paper proposes and analyzes discrete-time approximations to a class of diffusions, with an emphasis on preserving certain important features of the continuous-time processes in the approximations. We start with multivariate diffusions having three features in particular: they are martingales, each of their components evolves within the unit interval, and the components are almost surely ordered. In the models of the term structure of interest rates that motivate our investigation, these properties have the important implications that the model is arbitrage-free and that interest rates remain positive. In practice, numerical work with such models often requires Monte Carlo simulation and thus entails replacing the original continuous-time model with a discrete-time approximation. It is desirable that the approximating processes preserve the three features of the original model just noted, though standard discretization methods do not. We introduce new discretizations based on first applying nonlinear transformations from the unit interval to the real line (in particular, the inverse normal and inverse logit), then using an Euler discretization, and finally applying a small adjustment to the drift in the Euler scheme. We verify that these methods enforce important features in the discretization with no loss in the order of convergence (weak or strong). Numerical results suggest that these methods can also yield a better approximation to the law of the continuous-time process than does a more standard discretization.

Tuesday Evening

PMLA ◽  
1935 ◽  
Vol 50 (4) ◽  
pp. 1357-1357
Keyword(s):  
Life Insurance ◽  
Insurance Company ◽  
Life Insurance Company ◽  
Local Committee ◽  
Tuesday Evening

On Tuesday evening the members of the Association, and attending members of their families, were entertained with a buffet supper at the Queen City Club at 7:30 p.m. at the invitation of Messrs. Joseph S. Graydon, John J. Rowe, and other Cincinnati friends of the Association. Following this supper an entertainment arranged by the Local Committee was presented in the Hall of the Western and Southern Life Insurance Company. Attendance: about 900.

Hr Practices And Hr Policies At Icici Prudential Life Insurance Company Ltd

Think India ◽  
2019 ◽  
Vol 22 (3) ◽  
pp. 348-354
Author(s):  
T. Krishna Veni ◽  
G. Kalyani
Keyword(s):  
Human Resources ◽  
Life Insurance ◽  
Insurance Company ◽  
Life Insurance Company ◽  
Hr Practices ◽  
Commercial Center

The job of Human Resources is changing as quick as innovation and the worldwide commercial center. Generally, the HR Department was seen as organization, kept individual documents and different records, dealt with the enlisting procedure, and gave other authoritative help to the business. Those circumstances are different. The positive consequence of these progressions is that HR experts have the chance to assume a progressively vital job in the business. The test for HR chiefs is to stay up with the latest with the most recent HR developments—mechanical, lawful, and something else.

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