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 ...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.展开更多
The paper presents an innovative approach towards agricultural insurance underwriting and risk pricing through the development of an Extreme Machine Learning (ELM) Actuarial Intelligent Model. This model integrates di...The paper presents an innovative approach towards agricultural insurance underwriting and risk pricing through the development of an Extreme Machine Learning (ELM) Actuarial Intelligent Model. This model integrates diverse datasets, including climate change scenarios, crop types, farm sizes, and various risk factors, to automate underwriting decisions and estimate loss reserves in agricultural insurance. The study conducts extensive exploratory data analysis, model building, feature engineering, and validation to demonstrate the effectiveness of the proposed approach. Additionally, the paper discusses the application of robust tests, stress tests, and scenario tests to assess the model’s resilience and adaptability to changing market conditions. Overall, the research contributes to advancing actuarial science in agricultural insurance by leveraging advanced machine learning techniques for enhanced risk management and decision-making.展开更多
This study proposes a novel approach for estimating automobile insurance loss reserves utilizing Artificial Neural Network (ANN) techniques integrated with actuarial data intelligence. The model aims to address the ch...This study proposes a novel approach for estimating automobile insurance loss reserves utilizing Artificial Neural Network (ANN) techniques integrated with actuarial data intelligence. The model aims to address the challenges of accurately predicting insurance claim frequencies, severities, and overall loss reserves while accounting for inflation adjustments. Through comprehensive data analysis and model development, this research explores the effectiveness of ANN methodologies in capturing complex nonlinear relationships within insurance data. The study leverages a data set comprising automobile insurance policyholder information, claim history, and economic indicators to train and validate the ANN-based reserving model. Key aspects of the methodology include data preprocessing techniques such as one-hot encoding and scaling, followed by the construction of frequency, severity, and overall loss reserving models using ANN architectures. Moreover, the model incorporates inflation adjustment factors to ensure the accurate estimation of future loss reserves in real terms. Results from the study demonstrate the superior predictive performance of the ANN-based reserving model compared to traditional actuarial methods, with substantial improvements in accuracy and robustness. Furthermore, the model’s ability to adapt to changing market conditions and regulatory requirements, such as IFRS17, highlights its practical relevance in the insurance industry. The findings of this research contribute to the advancement of actuarial science and provide valuable insights for insurance companies seeking more accurate and efficient loss reserving techniques. The proposed ANN-based approach offers a promising avenue for enhancing risk management practices and optimizing financial decision-making processes in the automobile insurance sector.展开更多
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 ...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.展开更多
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 considere...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.展开更多
Using actuarial techniques, the study estimates the fired gap of pooling account and individual account respectively on on enterprise worker＇ s basic endowment insurance in Hebei province. And based on the estimation...Using actuarial techniques, the study estimates the fired gap of pooling account and individual account respectively on on enterprise worker＇ s basic endowment insurance in Hebei province. And based on the estimation, the study puts forward four policy suggestions： expand the coverage of the pension scheme; revised the number of months oft he annuities; increase the level of interest; improve financial support.展开更多
AIM: To investigate the outcome of living donor liver transplantation (LDLT) recipients transplanted with small-for-size grafts (SFSGs). METHODS: Between November 2001 and December 2010, 196 patients underwent LDLT wi...AIM: To investigate the outcome of living donor liver transplantation (LDLT) recipients transplanted with small-for-size grafts (SFSGs). METHODS: Between November 2001 and December 2010, 196 patients underwent LDLT with right lobe liver grafts at our center. Recipients were divided into 2 treatment groups: group A with an actuarial graft-to-recipient weight ratio (aGRWR) < 0.8% (n = 45) and group B with an aGRWR = 0.8% (n = 151). We evaluated serum liver function markers within 4 wk after transplantation. We also retrospectively evaluated the outcomes of these patients for potential effects related to the recipients, the donors and the transplantation procedures based upon a review of their medical records. RESULTS: Small-for-size syndrome (SFSS) developed in 7 of 45 patients (15.56%) in group A and 9 of 151 patients (5.96%) in group B (P = 0.080). The levels of alanine aminotransferase and aspartate aminotransferase in group A were higher than those in group B during early period after transplantation, albeit not sig-nificantly. The cumulative 1-, 3-and 5-year liver graft survival rates were 82.22%, 71.11% and 71.11% for group A and 81.46%, 76.82%, and 75.50% for group B patients, respectively (P = 0.623). However, univariate analysis of risk factors associated with graft survival in group A demonstrated that the occurrence of SFSS after LDLT was the only significant risk factor affecting graft survival (P < 0.001). Furthermore, multivariate analysis of our data did not identify any additional significant risk factors accounting for poor graft survival. CONCLUSION: Our study suggests that LDLT recipients with an aGRWR < 0.8% may have liver graft outcomes comparable to those who received larger size grafts. Further studies are required to ascertain the safety of using SFSGs. (c) 2014 Baishideng Publishing Group Co., Limited. All rights reserved.展开更多
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 ...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.展开更多
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 ...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.展开更多
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 proc...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.展开更多
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 ...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.展开更多
Based on the reality that 29 Chinese provinces have already implemented the policy allowing a couple to raise a second child if either parent is an only child, this paper provides an empirical study on the effect of t...Based on the reality that 29 Chinese provinces have already implemented the policy allowing a couple to raise a second child if either parent is an only child, this paper provides an empirical study on the effect of this policy on the financial status of the social pooling fund of basic pension insurance for urban employees. Our study suggests the followings. First, under the previous unchanged family planning policy, current deficits and cumulative deficits will occur in the social pooling fund in the year 2047 and 2063 respectively. Second, if lO% to 50% of qualified couples choose to raise a second child, the financial status of the social pooling fund will improve; relative to the previous unchanged family planning policy, the contribution ratio can decrease from 20% to the range between 18.06% and 19.57% without causing any changes to the original financial status of income and expenditure. Third, if the percentage of couples choosing to raise a second child rises to 60% to 100%, the contribution ratio can even decrease to the range between 16.55% and 17. 7% without causing any changes to the financial status as under the previous unchanged family planning policy. The above conclusions have all passed the sensitivity test. Therefore, the ＂two-child policy＂ for qualified couples is favorable to alleviating the payment pressures of pension insurance but the policy effectiveness is subject to fertility desire and the intensity of government implementation.展开更多
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 ...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.展开更多
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 catastroph...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.展开更多
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 approa...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.展开更多
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 susta...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.展开更多
文摘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.
文摘The paper presents an innovative approach towards agricultural insurance underwriting and risk pricing through the development of an Extreme Machine Learning (ELM) Actuarial Intelligent Model. This model integrates diverse datasets, including climate change scenarios, crop types, farm sizes, and various risk factors, to automate underwriting decisions and estimate loss reserves in agricultural insurance. The study conducts extensive exploratory data analysis, model building, feature engineering, and validation to demonstrate the effectiveness of the proposed approach. Additionally, the paper discusses the application of robust tests, stress tests, and scenario tests to assess the model’s resilience and adaptability to changing market conditions. Overall, the research contributes to advancing actuarial science in agricultural insurance by leveraging advanced machine learning techniques for enhanced risk management and decision-making.
文摘This study proposes a novel approach for estimating automobile insurance loss reserves utilizing Artificial Neural Network (ANN) techniques integrated with actuarial data intelligence. The model aims to address the challenges of accurately predicting insurance claim frequencies, severities, and overall loss reserves while accounting for inflation adjustments. Through comprehensive data analysis and model development, this research explores the effectiveness of ANN methodologies in capturing complex nonlinear relationships within insurance data. The study leverages a data set comprising automobile insurance policyholder information, claim history, and economic indicators to train and validate the ANN-based reserving model. Key aspects of the methodology include data preprocessing techniques such as one-hot encoding and scaling, followed by the construction of frequency, severity, and overall loss reserving models using ANN architectures. Moreover, the model incorporates inflation adjustment factors to ensure the accurate estimation of future loss reserves in real terms. Results from the study demonstrate the superior predictive performance of the ANN-based reserving model compared to traditional actuarial methods, with substantial improvements in accuracy and robustness. Furthermore, the model’s ability to adapt to changing market conditions and regulatory requirements, such as IFRS17, highlights its practical relevance in the insurance industry. The findings of this research contribute to the advancement of actuarial science and provide valuable insights for insurance companies seeking more accurate and efficient loss reserving techniques. The proposed ANN-based approach offers a promising avenue for enhancing risk management practices and optimizing financial decision-making processes in the automobile insurance sector.
文摘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.
基金funded by the Deanship Scientific Research(DSR),King Abdulaziz University,Jeddah,under the GrantNo.KEP-PhD:21-130-1443.
文摘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.
文摘Using actuarial techniques, the study estimates the fired gap of pooling account and individual account respectively on on enterprise worker＇ s basic endowment insurance in Hebei province. And based on the estimation, the study puts forward four policy suggestions： expand the coverage of the pension scheme; revised the number of months oft he annuities; increase the level of interest; improve financial support.
基金Supported by National Science and Technology Major Project of China,No.2008ZX10002-025 and No.2008ZX10002-026
文摘AIM: To investigate the outcome of living donor liver transplantation (LDLT) recipients transplanted with small-for-size grafts (SFSGs). METHODS: Between November 2001 and December 2010, 196 patients underwent LDLT with right lobe liver grafts at our center. Recipients were divided into 2 treatment groups: group A with an actuarial graft-to-recipient weight ratio (aGRWR) < 0.8% (n = 45) and group B with an aGRWR = 0.8% (n = 151). We evaluated serum liver function markers within 4 wk after transplantation. We also retrospectively evaluated the outcomes of these patients for potential effects related to the recipients, the donors and the transplantation procedures based upon a review of their medical records. RESULTS: Small-for-size syndrome (SFSS) developed in 7 of 45 patients (15.56%) in group A and 9 of 151 patients (5.96%) in group B (P = 0.080). The levels of alanine aminotransferase and aspartate aminotransferase in group A were higher than those in group B during early period after transplantation, albeit not sig-nificantly. The cumulative 1-, 3-and 5-year liver graft survival rates were 82.22%, 71.11% and 71.11% for group A and 81.46%, 76.82%, and 75.50% for group B patients, respectively (P = 0.623). However, univariate analysis of risk factors associated with graft survival in group A demonstrated that the occurrence of SFSS after LDLT was the only significant risk factor affecting graft survival (P < 0.001). Furthermore, multivariate analysis of our data did not identify any additional significant risk factors accounting for poor graft survival. CONCLUSION: Our study suggests that LDLT recipients with an aGRWR < 0.8% may have liver graft outcomes comparable to those who received larger size grafts. Further studies are required to ascertain the safety of using SFSGs. (c) 2014 Baishideng Publishing Group Co., Limited. All rights reserved.
文摘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.
文摘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.
文摘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.
文摘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.
基金sponsored by the National Social Sciences Foundation Program,An Evaluation of the Impact of China’s Family Planning Policy Adjustment on the Sustainability of the Social Security Fund and A Study of the Relevant Countermeasures(Grant No.15XRK005,chaired by:Zeng Yi)
文摘Based on the reality that 29 Chinese provinces have already implemented the policy allowing a couple to raise a second child if either parent is an only child, this paper provides an empirical study on the effect of this policy on the financial status of the social pooling fund of basic pension insurance for urban employees. Our study suggests the followings. First, under the previous unchanged family planning policy, current deficits and cumulative deficits will occur in the social pooling fund in the year 2047 and 2063 respectively. Second, if lO% to 50% of qualified couples choose to raise a second child, the financial status of the social pooling fund will improve; relative to the previous unchanged family planning policy, the contribution ratio can decrease from 20% to the range between 18.06% and 19.57% without causing any changes to the original financial status of income and expenditure. Third, if the percentage of couples choosing to raise a second child rises to 60% to 100%, the contribution ratio can even decrease to the range between 16.55% and 17. 7% without causing any changes to the financial status as under the previous unchanged family planning policy. The above conclusions have all passed the sensitivity test. Therefore, the ＂two-child policy＂ for qualified couples is favorable to alleviating the payment pressures of pension insurance but the policy effectiveness is subject to fertility desire and the intensity of government implementation.
基金The authors's research is part of the ANR project DREAMeS(ANR-21-CE46-0002)The research of Sarah Kaakai is Funded by the European Union(ERC,SINGER,101054787)。
文摘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.
基金This work was supported by the Science and Technology Project of State Grid Corporation of China under Grant(5100-201999546A-0-0-00).
文摘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.
基金Supported by the National Natural Science Foundation of China(No.11571365,11171349)
文摘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.
基金National Social Science Foundation[13&ZD164]National Natural Science Foundation[71173230].
文摘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.
