调查:谁把Actuary翻译为“精算师”?

1998年12月,笔者曾提出：是谁首先把Actuarial Science翻译成＂精算学＂？至今,整整16年过去了,笔者仍然没有获得确切答案,但有一点可以确定的是,这一中文译名出自台湾。无论对于中国大陆精算界,还是对于台湾精算界,探求这个问题的答案都是十分有意义的一件事情,就像每个人都要知道自己的出身背景一样重要。基于这一共识,笔者决定联手继续调查这个问题。这个问题的答案固然极有价值,但更为重要、更有意义的是调查工作的过程。它从一个非常特殊的角度。

Artificial Intelligence-Based Automated Actuarial Pricing and Underwriting Model for the General Insurance Sector

The Automated Actuarial Pricing and Underwriting Model has been enhanced and expanded through the implementation of Artificial Intelligence to automate three distinct actuarial functions: loss reserving, pricing, and underwriting. This model utilizes data analytics based on Artificial Intelligence to merge microfinance and car insurance services. Introducing and applying a no-claims bonus rate system, comprising base rates, variable rates, and final rates, to three key policyholder categories significantly reduces the occurrence and impact of claims while encouraging increased premium payments. We have enhanced frequency-severity models with eight machine learning algorithms and adjusted the Automated Actuarial Pricing and Underwriting Model for inflation, resulting in outstanding performance. Among the machine learning models utilized, the Random Forest (RANGER) achieved the highest Total Aggregate Comprehensive Automated Actuarial Loss Reserve Risk Pricing Balance (ACAALRRPB), establishing itself as the preferred model for developing Automated Actuarial Underwriting models tailored to specific policyholder categories.

Automated Actuarial Data Analytics-Based Inflation Adjusted Frequency Severity Loss Reserving Model

In this paper, the Automated Actuarial Loss Reserving Model is developed and extended using machine learning. The traditional actuarial reserving techniques are no longer compatible with the increase in technological advancement currently at hand. As a result, the development of the alternative Artificial Intelligence Based Automated Actuarial Loss Reserving Methodology which captures diverse risk profiles for various policyholders through augmenting the Micro Finance services, Auto Insurance Services and Both Services lines of business on the same platform through the computation of the Comprehensive Automated Actuarial Loss Reserves (CAALR) has been implemented in this paper. The introduction of the four further types of actuarial loss reserves to those existing in the actuarial literature seems to significantly reduce lapse rates, reduce the reinsurance costs as well as expenses and outgo. As a matter of consequence, this helps to bring together a combination of new and existing policyholders in the insurance company. The frequency severity models have been extended in this paper using ten machine learning algorithms which ultimately leads to the derivation of the proposed machine learning-based actuarial loss reserving model which remarkably performed well when compared to the traditional chain ladder actuarial reserving method using simulated data.

On a Novel Extended Lomax Distribution with Asymmetric Properties and Its Statistical Applications

In this article,we highlight a new three-parameter heavy-tailed lifetime distribution that aims to extend the modeling possibilities of the Lomax distribution.It is called the extended Lomax distribution.The considered distribution naturally appears as the distribution of a transformation of a random variable following the logweighted power distribution recently introduced for percentage or proportion data analysis purposes.As a result,its cumulative distribution has the same functional basis as that of the Lomax distribution,but with a novel special logarithmic term depending on several parameters.The modulation of this logarithmic term reveals new types of asymetrical shapes,implying a modeling horizon beyond that of the Lomax distribution.In the first part,we examine several of its mathematical properties,such as the shapes of the related probability and hazard rate functions;stochastic comparisons;manageable expansions for various moments;and quantile properties.In particular,based on the quantile functions,various actuarial measures are discussed.In the second part,the distribution’s applicability is investigated with the use of themaximumlikelihood estimationmethod.The behavior of the obtained parameter estimates is validated by a simulation work.Insurance claim data are analyzed.We show that the proposed distribution outperforms eight well-known distributions,including the Lomax distribution and several extended Lomax distributions.In addition,we demonstrate that it gives preferable inferences from these competitor distributions in terms of risk measures.

A Research on Whole Life Insurance

The formulas of premiums and premium reserves of a kind of mixed whole life insurance were obtained by the methods of actuarial science. Then we take a typical policy of whole life insurance in present Chinese market as an example to analyze its expense design and predict its market prospects.

Modelling Insurance Losses with a New Family of Heavy-Tailed Distributions

The actuaries always look for heavy-tailed distributions to model data relevant to business and actuarial risk issues.In this article,we introduce a new class of heavy-tailed distributions useful for modeling data in financial sciences.A specific sub-model form of our suggested family,named as a new extended heavy-tailed Weibull distribution is examined in detail.Some basic characterizations,including quantile function and raw moments have been derived.The estimates of the unknown parameters of the new model are obtained via the maximum likelihood estimation method.To judge the performance of the maximum likelihood estimators,a simulation analysis is performed in detail.Furthermore,some important actuarial measures such as value at risk and tail value at risk are also computed.A simulation study based on these actuarial measures is conducted to exhibit empirically that the proposed model is heavy-tailed.The usefulness of the proposed family is illustrated by means of an application to a heavy-tailed insurance loss data set.The practical application shows that the proposed model is more flexible and efficient than the other six competing models including(i)the two-parameter models Weibull,Lomax and Burr-XII distributions(ii)the three-parameter distributions Marshall-Olkin Weibull and exponentiated Weibull distributions,and(iii)a well-known four-parameter Kumaraswamy Weibull distribution.

Some Actuarial Formula of Life Insurance for Fuzzy Markets

This paper presents an actuarial model of life insurance for fuzzy markets based on Liu process. At first, some researches about an actuarial model of life insurance for stochastic market and concepts about fuzzy process have been reviewed. Then, an actuarial model of life insurance for fuzzy process is formulated.

Best Bounds on Measures of Risk and Probability of Ruin for Alpha Unimodal Random Variables When There Is Limited Moment Information

This paper presents explicit formulae giving tight upper and lower bounds on the expectations of alpha-unimodal random variables having a known range and given set of moments. Such bounds can be useful in ordering of random variables in terms of risk and in PERT analysis where there is only incomplete stochastic information concerning the variables under investigation. Explicit closed form solutions are also given involving alpha-unimodal random variables having a known mean for two particularly important measures of risk—the squared distance or variance, and the absolute deviation. In addition, optimal tight bounds are given for the probability of ruin in the collective risk model when the severity distribution has an alpha-unimodal distribution with known moments.

Time-consistent pension policy with minimum guarantee and sustainability constraint

This paper proposes and investigates an optimal pair investment/pension policy for a pay-as-you-go(PAYG)pension scheme.The social planner can invest in a buffer fund in order to guarantee a minimal pension amount.The model aims at taking into account complex dynamic phenomena such as the demographic risk and its evolution over time,the time and age dependence of agents preferences,and financial risks.The preference criterion of the social planner is modeled by a consistent dynamic utility defined on a stochastic domain,which incorporates the heterogeneity of overlapping generations and its evolution over time.The preference criterion and the optimization problem also incorporate sustainability,adequacy and fairness constraints.The paper designs and solves the social planner's dynamic decision criterion,and computes the optimal investment/pension policy in a general framework.A detailed analysis for the case of dynamic power utilities is provided.

Catastrophe Risk Management for Electric Power Distribution Systems:An Insurance Approach

High-impact,low-probability catastrophes may cause equipment damage,customer outages and serious economic losses to an aging power distribution infrastructure with low redundancy and automation.To cope with catastrophe risks faced by distribution systems(DSs),insurance is proposed as a supplement to existing resilience enhancement measures,which can provide financial aid in recovery after disasters,as well as incentives to make DSs more resilient to potential hazards.This calls for a quantitative assessment for insurance pricing that can not only predict potential losses caused by future catastrophes but also evaluate the effect of risk management measures.In this paper,a four-module actuarial framework,including hazard,vulnerability,resilience,and insurance modules,is developed to assess the catastrophe risks of DSs.Based on Monte Carlo simulation(MCS)and mixed integer linear programming(MILP),the dynamic characteristics of disasters,random failures of equipment,control measures including fault isolation,load transfer,line patrolling,manual switching,and fault repair,are comprehensively incorporated in the premium determination of catastrophe insurance.Numerical simulations are performed on the modified IEEE 33-bus test systems to illustrate the validity of the proposed catastrophe insurance schemes.

中国健康保险精算的现状、问题和对策

本文阐明了健康保险精算在商业健康保险业务发展和社会医疗保险制度建立过程中的重要作用 ,分析了中国健康保险精算的现状及其存在的主要问题 ,通过与发达国家的对比 ,提出了加快中国健康保险精算事业发展的对策和建议。

An Actuarial Approach to Reload Option Valuation for a Non-tradable Risk Assets under Jump-diffusion Process and Stochastic Interest Rate

We use an actuarial approach to estimate the valuation of the reload option for a non-tradable risk asset under the jump-diffusion processes and Hull-White interest rate. We verify the validity of the actuarial approach to the European vanilla option for non-tradable assets. The formulas of the actuarial approach to the reload option are derived from the fair premium principle and the obtained results are arbitrage. Numerical experiments are conducted to analyze the effects of different parameters on the results of valuation as well as their differences from those obtained by the no-arbitrage approach. Finally, we give the valuations of the reload options under different parameters.

Raising the retirement age:the impact on the individual and actuarial balance for Chinese urban workers’basic pensions

Rapid population ageing and increasing longevity are raising concerns about the sustainability of the basic pension systems in China.Raising the retirement age,as an important way to maintain long-term financial sustainability,has become the main policy choice for China.Some studies show that postponing retirement can solve the financial pressures of pension systems effectively.However,if the pension benefits increase with the pensionable age,this may offset some effects and even have a negative impact on the financial balance.This paper builds cohort models and period actuarial balance models for Chinese urban workers’basic pension system to measure the cohort and period effects of postponing retirement,with the aim of analysing the change in the individual pension net wealth and the long-term actuarial balance of the system with population ageing and increasing life expectancy.The result shows that raising the retirement age,which is linked to life expectancy,will lead to an increase in the pension benefits,individual net pension wealth and then pension fund expenditure.It may benefit the individual and short-term actuarial balance but have a small effect on the long-term actuarial balance of the system.