Hong-Jie Li , Xing-Gang Luo , Zhong-Liang Zhang , Shen-Wei Huang , Wei Jiang
{"title":"A usage-based insurance (UBI) pricing model considering customer retention","authors":"Hong-Jie Li , Xing-Gang Luo , Zhong-Liang Zhang , Shen-Wei Huang , Wei Jiang","doi":"10.1016/j.insmatheco.2025.103132","DOIUrl":"10.1016/j.insmatheco.2025.103132","url":null,"abstract":"<div><div>Usage-based insurance (UBI) charges drivers differently through telematics-based driving risk assessments. While current UBI pricing models differentiate driving risks, their overly discriminative prices may expel risky drivers, whose driving behaviors could have been modified, thereby incurring insurers' losses in profits. We propose a new UBI pricing model to address this problem by incorporating customer retention into the conventional UBI framework. Specifically, our model offers targeted discounts based on drivers' price sensitivity to retain those who may terminate the insurance contract, as well as provides concrete suggestions to help them modify unsafe driving behaviors. Using empirical data from a major Chinese auto insurer, we confirm that our model yields higher profits for insurers over the UBI pricing model that does not account for customer retention, and exemplify how suggestions for drivers can be drawn from driving profiles.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"124 ","pages":"Article 103132"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580676","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}
{"title":"The principle of a single big jump from the perspective of tail moment risk measure","authors":"Jinzhu Li","doi":"10.1016/j.insmatheco.2025.103118","DOIUrl":"10.1016/j.insmatheco.2025.103118","url":null,"abstract":"<div><div>Consider a financial or insurance system with a finite number of individual components. The famous principle of a single big jump (PSBJ) says that a system crisis occurs mainly due to a single but unusually large loss from some individual component. Most of literatures modeled the PSBJ through the tail probabilities of the largest risk and the total risk of the system. Different from the existing works, this paper is devoted to explore the PSBJ from a new perspective. We aim to establish the PSBJ based on a kind of risk measure defined via the tail moments of the related risks. Our study is mainly conducted under a widely used framework, in which the individual risks are pairwise asymptotically independent and have the distributions from the Fréchet or Gumbel max-domain of attraction. The asymptotic behavior of the tail mixed moments is also discussed in detail. The results obtained are applied to an optimal capital allocation problem based on a tail mean-variance model. A numerical study is given to illustrate the accuracy of our main asymptotic results. We also give a thorough discussion on some interesting theoretical properties regarding the PSBJ.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"124 ","pages":"Article 103118"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195362","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}
{"title":"Care-dependent target benefit pension plan with minimum liability gap","authors":"Ruotian Ti , Ximin Rong , Cheng Tao , Hui Zhao","doi":"10.1016/j.insmatheco.2025.103127","DOIUrl":"10.1016/j.insmatheco.2025.103127","url":null,"abstract":"<div><div>With the progressive aging of populations, the significance of long-term care (LTC) services in aging societies is growing. In this paper, we integrate LTC services with pensions, studying a stochastic model for a care-dependent target benefit pension (TBP) plan. The plan members' target benefit rates are set according to the care cost for three different health states, i.e., healthy, mildly disabled and severely disabled states. The pension liability evaluation is defined as the potential compensation to all active and retired members, under the assumption of the pension fund default. The objective of minimizing the benefit gap and liability gap is achieved by addressing a stochastic optimal control problem. Then, we derive analytic solutions for optimal investment and benefit payment strategies by employing the corresponding Hamilton-Jacobi-Bellman (HJB) equation. Numerical results show that under a fixed aggregate contribution of the care-dependent TBP, a slight decrease in the target benefit for healthy retirees leads to a significant increase for retirees in both mildly and severely disabled states, thereby improving equity for disabled retirees. Furthermore, we compare the care-dependent TBP with a traditional TBP and a care-dependent tontine in terms of risk sharing, financial stability, and intergenerational equity, highlighting the advantages of the care-dependent TBP.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"124 ","pages":"Article 103127"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144491368","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}
{"title":"As-if-Markov reserves for reserve-dependent payments","authors":"Marcus C. Christiansen , Boualem Djehiche","doi":"10.1016/j.insmatheco.2025.103129","DOIUrl":"10.1016/j.insmatheco.2025.103129","url":null,"abstract":"<div><div>In multistate life insurance, prospective reserves are commonly calculated as expectations conditioned only on the current state of the individual policy, rather than on the full observed past history, which is well motivated in Markov models, but is often done even when the empirical data does not show the Markov property. The resulting as-if-Markov prospective reserves then represent partially portfolio averaged values rather than individual values. This averaging effect is particularly relevant when individual policies are lapsed or modified, where it is common practice to credit the individual reserve to the policyholder, making the cashflow reserve-dependent. Such reserve dependence is normally avoided by applying the Cantelli theorem, but this does not work for as-if-Markov reserves without the Markov property. We show that, under mild technical assumptions, the as-if-Markov prospective reserves are still well defined despite the circularity in their definition, and we explain how they can be computed numerically by fixed-point iteration.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"124 ","pages":"Article 103129"},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470924","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}
{"title":"Efficient hedging of life insurance portfolio for loss-averse insurers","authors":"Edouard Motte, Donatien Hainaut","doi":"10.1016/j.insmatheco.2025.103116","DOIUrl":"10.1016/j.insmatheco.2025.103116","url":null,"abstract":"<div><div>This paper investigates the hedging of equity-linked life insurance portfolio for loss-averse insurers. We consider a general arbitrage-free financial market and an actuarial market composed of <em>n</em>-independent policyholders. As the combined market is incomplete, perfect hedging of any actuarial-financial payoff is not possible. Instead, we study the efficient hedging of <em>n</em>-size equity-linked life insurance portfolio for insurers who are only concerned with their losses. To this end, we consider stochastic control problems (under the real-world measure) in order to determine the optimal hedging strategies that either maximize the probability of successful hedge (called quantile hedging) or minimize the expectation for a class of shortfall loss functions (called shortfall hedging). Based on the super-replication theory and a duality approach, we show that the optimal strategies depend both on actuarial and financial risks. Moreover, these strategies adapt not only to the size of the insurance portfolio but also to the risk-aversion of the insurer. The numerical results show that, for loss-averse insurers, the strategies outperform the mean-variance hedging strategy, demonstrating the relevance of adopting the right strategy according to the insurers' risk aversion and portfolio size.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"123 ","pages":"Article 103116"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138149","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}
{"title":"Approximations of multi-period liability values by simple formulas","authors":"Nils Engler, Filip Lindskog","doi":"10.1016/j.insmatheco.2025.103112","DOIUrl":"10.1016/j.insmatheco.2025.103112","url":null,"abstract":"<div><div>This paper is motivated by computational challenges arising in multi-period valuation in insurance. Aggregate insurance liability cashflows typically correspond to stochastic payments several years into the future. However, insurance regulation requires that capital requirements are computed for a one-year horizon, by considering cashflows during the year and end-of-year liability values. This implies that liability values must be computed recursively, backwards in time, starting from the year of the most distant liability payments. Solving such backward recursions with paper and pen is rarely possible, and numerical solutions give rise to major computational challenges.</div><div>The aim of this paper is to provide explicit and easily computable expressions for multi-period valuations that appear as limit objects for a sequence of multi-period models that converge in terms of conditional weak convergence. Such convergence appears naturally if we consider large insurance portfolios such that the liability cashflows, appropriately centered and scaled, converge weakly as the size of the portfolio tends to infinity.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"123 ","pages":"Article 103112"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855891","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}
{"title":"Improving detections of serial dynamics for longitudinal actuarial data with underwriting-controlled testing","authors":"Tsz Chai Fung","doi":"10.1016/j.insmatheco.2025.103111","DOIUrl":"10.1016/j.insmatheco.2025.103111","url":null,"abstract":"<div><div>Longitudinal actuarial data, where policyholders' claims are recorded over multiple years, offer valuable insights for pricing and reserving. However, standard modeling approaches typically assume no serial dynamics in conditional claim distributions over time. Such an assumption is difficult to validate given that most non-life insurance products are short-term, yielding data from only a few years. Recent diagnostic methods can detect serial dynamics but do not distinguish between changes induced by endogenous underwriting standards (e.g., renewal and pricing policies favoring low-risk policyholders) and genuine, exogenous temporal shifts (e.g., evolving socioeconomic environment). In this paper, we develop underwriting-controlled serial dynamic tests for longitudinal actuarial data. By applying an inverse-probability-weighted estimation approach, we adjust for underwriting effects and thus detect the true underlying serial dynamics. We propose tests based on three metrics, parameter difference, prediction bias, and prediction loss, enabling both statistical and economic interpretations of dynamic changes. Simulation studies show that our tests avoid false detections caused by underwriting effects. An analysis using European automobile insurance data illustrates how our approach offers deeper insights into when and why serial dynamics emerge.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"123 ","pages":"Article 103111"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855796","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}
{"title":"Learning from COVID-19: A catastrophe mortality bond solution in the post-pandemic era","authors":"Ze Chen , Hong Li , Yu Mao , Kenneth Q. Zhou","doi":"10.1016/j.insmatheco.2025.103113","DOIUrl":"10.1016/j.insmatheco.2025.103113","url":null,"abstract":"<div><div>The development of robust financial instruments to mitigate pandemic-induced mortality risks has become increasingly critical, particularly for the insurance sector, in the aftermath of COVID-19. This paper introduces a novel pandemic bond designed to alleviate the financial burden on life insurers and reinsurers exposed to pandemic-related mortality risks. The bond's payouts are linked to publicly available pandemic data, enhancing transparency, ensuring timely payments, and mitigating the risks of information asymmetry and moral hazard. A stochastic Susceptible-Infected-Recovered-Deceased (SIRD) model is developed to evaluate the pricing and hedging performance of the PAN bond. Numerical analysis based on U.S. COVID-19 data illustrates the proposed SIRD model's effectiveness in generating reliable probabilistic forecasts of excess mortality and demonstrates the bond's potential as an effective hedge against pandemic-induced mortality risks.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"123 ","pages":"Article 103113"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168028","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}
{"title":"Pricing and hedging of variable annuities with path-dependent guarantee in Wishart stochastic volatility models","authors":"José Da Fonseca , Patrick Wong","doi":"10.1016/j.insmatheco.2025.103114","DOIUrl":"10.1016/j.insmatheco.2025.103114","url":null,"abstract":"<div><div>This paper presents the pricing of a path-dependent guaranteed minimum maturity benefit in the Wishart multidimensional stochastic volatility model and the Wishart affine stochastic correlation model. We derive a closed-form solution for the option price in these two models, requiring only the computation of a one-dimensional integration. Thanks to the remarkable analytical properties of these models, we also compute all sensitivities of the option price to the model parameters. An implementation illustrates the results, confirms that pricing is fast and accurate, and provides a framework for pricing and risk management of this product in Wishart stochastic volatility models.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"123 ","pages":"Article 103114"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144123750","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}
{"title":"Portfolio benchmarks in defined contribution pension plan management","authors":"Daxin Huang , Yang Liu","doi":"10.1016/j.insmatheco.2025.04.002","DOIUrl":"10.1016/j.insmatheco.2025.04.002","url":null,"abstract":"<div><div>In financial practice, a portfolio benchmark is of importance as it characterizes the fluctuation of the market and better evaluates the performance of the fund manager. We study the optimal investment problem of Defined Contribution (DC) pension plan management with portfolio benchmarks. As such, three technical difficulties arise, and we overcome them accordingly. First, the classic Legendre transformation cannot handle the stochastic nature of the portfolio benchmark. We introduce a parameterized Legendre transformation technique and conduct it to obtain closed-form optimal control strategies. Second, we discover that the optimal solution is not unique when the drift parameter of the benchmark is exactly Merton's constant. We employ a risk management criterion minimizing the liquidation probability to further select a “best” control strategy among the optimums. Third, the Lagrange multiplier cannot be directly solved from the budget constraint. We propose a new numerical technique called the Monte Carlo bisection method to solve it. Therefore, we can analyze the optimal strategies with asymptotic analysis and demonstrate financial insights. We find that when the benchmark is deterministic or its drift is low, the optimal investment aligns with the literature, while the high-drift benchmarks lead to an opposite risk behavior. Finally, empirical validation using the US and Chinese market data shows that our strategy is more effective in a lower risk-premium market.</div></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"123 ","pages":"Article 103110"},"PeriodicalIF":1.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834319","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}