Insurance Mathematics & Economics最新文献_第7页

Life care reverse mortgages: Monitoring the net cashflows of a new hybrid insurance product 寿险反向抵押贷款：监测一种新型混合保险产品的净现金流

IF 2.2 2区经济学

Insurance Mathematics & Economics Pub Date : 2025-11-01 Epub Date: 2025-11-02 DOI: 10.1016/j.insmatheco.2025.103170

Giovanna Apicella , Emilia Di Lorenzo , Giulia Magni , Marilena Sibillo

{"title":"Life care reverse mortgages: Monitoring the net cashflows of a new hybrid insurance product","authors":"Giovanna Apicella , Emilia Di Lorenzo , Giulia Magni , Marilena Sibillo","doi":"10.1016/j.insmatheco.2025.103170","DOIUrl":"10.1016/j.insmatheco.2025.103170","url":null,"abstract":"<div><div>Combining retirement income and long-term disability protection is a well-established concept in the literature. We present a new connection between the lifetime annuity provided by a Reverse Mortgage and long-term care (LTC) insurance, jointly managed in a unique bundled product. Indeed, we define the RM (considered as a source of lifetime income) and LTC as two different regimes of a jointly managed insurance product, which we call the “Life Care Reverse Mortgage” (LCRM). From an actuarial perspective, we design the underlying structure of the LCRM and the inherent framework for the ex-ante estimation of a time-dependent profit/loss function, that provides a measure of the expected annual net cashflows for a life insurer holding a portfolio of LCRMs. We perform a numerical application to illustrate the regime-switching mechanism on which the proposed LCRM insurance contracts are based and to quantify over time the lender’s return for a pool of LCRM contracts through the designed time-dependent profit/loss function. Furthermore, we analyse the sensitivity of the portfolio profit/loss function to two sources of uncertainty: health patterns over time and house price dynamics.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"125 ","pages":"Article 103170"},"PeriodicalIF":2.2,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transformers-based least square Monte Carlo for solvency calculation in life insurance 基于变压器的寿险偿付能力最小二乘蒙特卡罗计算

IF 2.2 2区经济学

Insurance Mathematics & Economics Pub Date : 2025-11-01 Epub Date: 2025-09-29 DOI: 10.1016/j.insmatheco.2025.103163

Francesca Perla , Salvatore Scognamiglio , Andrea Spadaro , Paolo Zanetti

{"title":"Transformers-based least square Monte Carlo for solvency calculation in life insurance","authors":"Francesca Perla , Salvatore Scognamiglio , Andrea Spadaro , Paolo Zanetti","doi":"10.1016/j.insmatheco.2025.103163","DOIUrl":"10.1016/j.insmatheco.2025.103163","url":null,"abstract":"<div><div>The Solvency Capital Requirement (SCR), mandated by Solvency II, represents the capital insurers must hold to ensure solvency, calculated as the Value-at-Risk of the Net Asset Value at a 99.5% confidence level over a one-year period. While Nested Monte Carlo simulations are the gold standard for SCR calculation, they are highly resource-intensive. The Least Squares Monte Carlo (LSMC) method provides a more efficient alternative but faces challenges with high-dimensional data due to the curse of dimensionality. We introduce a novel extension of LSMC, incorporating advanced deep learning models, specifically Transformer models, which enhance traditional machine learning methods. This approach significantly improves the accuracy of approximating the complex relationship between insurance liabilities and risk factors, leading to a more accurate SCR calculation. Our extensive experiments on two insurance portfolios demonstrate the effectiveness of this transformer-based LSMC approach. Additionally, we show that Shapley values can be applied to achieve model explainability, which is crucial for regulatory compliance and for fostering the adoption of deep learning in the highly regulated insurance sector.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"125 ","pages":"Article 103163"},"PeriodicalIF":2.2,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Equilibrium investment strategies for a defined contribution pension plan with random risk aversion 随机风险规避下固定缴款养老金计划的均衡投资策略

IF 2.2 2区经济学

Insurance Mathematics & Economics Pub Date : 2025-11-01 Epub Date: 2025-08-07 DOI: 10.1016/j.insmatheco.2025.103140

Ling Wang , Bowen Jia

引用次数: 0

Ordering higher risks in Yaari's dual theory 在Yaari的二元理论中，排序风险更高

IF 2.2 2区经济学

Insurance Mathematics & Economics Pub Date : 2025-11-01 Epub Date: 2025-09-01 DOI: 10.1016/j.insmatheco.2025.103150

A. Castaño-Martínez, G. Pigueiras, C.D. Ramos, M.A. Sordo

{"title":"Ordering higher risks in Yaari's dual theory","authors":"A. Castaño-Martínez, G. Pigueiras, C.D. Ramos, M.A. Sordo","doi":"10.1016/j.insmatheco.2025.103150","DOIUrl":"10.1016/j.insmatheco.2025.103150","url":null,"abstract":"<div><div>In <span><span>Yaari</span></span>'s (<span><span>1987</span></span>) dual theory of choice under risk, risk preferences are based on a functional that incorporates a subjective distortion function. In the context of <span><span>Wang</span></span>'s (<span><span>1996</span></span>) premium principle, <span><span>Wang and Young (1998)</span></span> introduce a sequence of partial ordering classes for risk distributions which characterize the preferences of groups of risk-averse agents making decisions based on this functional. Under this framework, if one distribution is perceived as less risky than another, its mean is smaller than or equal to the latter's, which can make certain risk distributions non-comparable. In this paper, we investigate a sequence of partial orders for risk distributions, grounded in comparisons of successive integrals of TVaR curves, that capture the preferences of agents primarily concerned with large risks that exceed their expected values. The normative properties of these orders are explored through the <em>n</em>th-degree coefficient of dual risk aversion, which serves as the dual analog of the index of absolute risk aversion introduced by <span><span>Caballé and Pomansky (1996)</span></span> within the expected utility model.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"125 ","pages":"Article 103150"},"PeriodicalIF":2.2,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144931738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic investment-driven insurance pricing and optimal regulation 动态投资驱动的保险定价与最优监管

IF 2.2 2区经济学

Insurance Mathematics & Economics Pub Date : 2025-11-01 Epub Date: 2025-09-29 DOI: 10.1016/j.insmatheco.2025.103160

Bingzheng Chen , Zongxia Liang , Shunzhi Pang

引用次数: 0

Individual survivor fund account: The impact of bequest motives on tontine participation 个人遗属基金账户：遗赠动机对长期参与的影响

IF 2.2 2区经济学

Insurance Mathematics & Economics Pub Date : 2025-11-01 Epub Date: 2025-10-01 DOI: 10.1016/j.insmatheco.2025.103161

Tak Wa Ng, Thai Nguyen

引用次数: 0

Pitfalls in machine learning interpretability: Manipulating partial dependence plots to hide discrimination 机器学习可解释性的陷阱：操纵部分依赖图来隐藏歧视

IF 2.2 2区经济学

Insurance Mathematics & Economics Pub Date : 2025-11-01 Epub Date: 2025-07-30 DOI: 10.1016/j.insmatheco.2025.103135

Xi Xin , Giles Hooker , Fei Huang

{"title":"Pitfalls in machine learning interpretability: Manipulating partial dependence plots to hide discrimination","authors":"Xi Xin , Giles Hooker , Fei Huang","doi":"10.1016/j.insmatheco.2025.103135","DOIUrl":"10.1016/j.insmatheco.2025.103135","url":null,"abstract":"<div><div>The adoption of artificial intelligence (AI) across industries has led to the widespread use of complex black-box models and interpretation tools for decision making. This paper proposes an adversarial framework to uncover the vulnerability of permutation-based interpretation methods for machine learning tasks, with a particular focus on partial dependence (PD) plots. This adversarial framework modifies the original black box model to manipulate its predictions for instances in the extrapolation domain. As a result, it produces deceptive PD plots that can conceal discriminatory behaviors while preserving most of the original model's predictions. This framework can produce multiple fooled PD plots via a single model. By using real-world datasets including an auto insurance claims dataset and COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) dataset, our results show that it is possible to intentionally hide the discriminatory behavior of a predictor and make the black-box model appear neutral through interpretation tools like PD plots while retaining almost all the predictions of the original black-box model. Managerial insights for regulators and practitioners are provided based on the findings.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"125 ","pages":"Article 103135"},"PeriodicalIF":2.2,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Censored and extreme losses: Functional convergence and applications to tail goodness-of-fit 删减损失和极端损失：函数收敛和尾部拟合优度的应用

IF 2.2 2区经济学

Insurance Mathematics & Economics Pub Date : 2025-11-01 Epub Date: 2025-09-15 DOI: 10.1016/j.insmatheco.2025.103157

Martin Bladt, Christoffer Øhlenschlæger

引用次数: 0

Diversification effect in multivariate optimal risk transfer 多元最优风险转移中的分散效应

IF 2.2 2区经济学

Insurance Mathematics & Economics Pub Date : 2025-11-01 Epub Date: 2025-09-12 DOI: 10.1016/j.insmatheco.2025.103156

Vali Asimit , Tsz Chai Fung , Liang Peng , Fang Yang

{"title":"Diversification effect in multivariate optimal risk transfer","authors":"Vali Asimit , Tsz Chai Fung , Liang Peng , Fang Yang","doi":"10.1016/j.insmatheco.2025.103156","DOIUrl":"10.1016/j.insmatheco.2025.103156","url":null,"abstract":"<div><div>There are two main practical questions in the context of multivariate risk transfers. First, non-intragroup risk transfers raise the question of whether to purchase (re)insurance coverage for the aggregate risk or separately for each risk. Second, intragroup risk transfers are always challenged by regulators on whether there is a commercial purpose in such transactions, and therefore, insurance buyers must commercially validate their decisions. This paper investigates the diversification effect from the buyer's and the seller's perspectives. Our analysis for insurance buyers is based on the ratio between the optimal reinsurance risk margin cost for the total sum of losses and the sum of the individual optimal risk margin costs for each loss type. Because analytical comparison is infeasible, we develop a statistical inference method for this ratio and evaluate its finite sample performance through simulation. The seller's perspective is modeled via a new measure to assess the relative profitability of offering joint versus separate risk transfer contracts. The combined use of these measures enables both buyers and sellers to identify optimal risk transfer decisions that are commercially viable for both parties. Finally, we apply the proposed inference methods to the widely studied Danish fire loss dataset, illustrating the practical implications of our findings that equally apply to an intragroup or non-intragroup risk transfer.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"125 ","pages":"Article 103156"},"PeriodicalIF":2.2,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Portfolio selection and risk sharing via risk budgeting 通过风险预算进行投资组合选择和风险分担

IF 2.2 2区经济学

Insurance Mathematics & Economics Pub Date : 2025-11-01 Epub Date: 2025-07-31 DOI: 10.1016/j.insmatheco.2025.103139

Vali Asimit , Wing Fung Chong , Radu Tunaru , Feng Zhou

引用次数: 0