Journal of Risk and Insurance最新文献

Risk sharing has been practiced in various forms in the financial industry. This paper is the first to study both dynamic and static risk-sharing mechanisms for a group of participants over multiple periods. The design of risk-sharing strategies is based on the Pareto optimization of quadratic utilities of participants' reserves. Such a framework builds a connection between portfolio optimization in the finance literature and that for risk sharing in the insurance literature. Building on the most common form of reinsurance—pro rata treaties, we propose a peer-to-peer (P2P) network for risk sharing. Assuming independent multivariate losses over time, we find that the optimal risk-sharing allocation exhibits a three-component structure with the long-term limit and two correction terms. This allows us to show convergence of the risk-sharing solution and the ratios of long-term reserves. Furthermore, we study the impact of actuarial fairness on various risk-sharing strategies and their long-term limits.

A “seat belt defense” allows a defendant in a third-party auto liability event to present evidence of seat belt nonuse to reduce a plaintiff's recovery. When successfully applied, the defense has a direct effect on reducing liability payouts by insurers for accidents. Our analysis reveals that seat belt defense laws are associated with a 10% reduction in auto claims costs, which equates to a reduction in loss costs of approximately $14 per insured vehicle. We find little evidence that the defense reduces accident frequency and no evidence that the defense affects seat belt usage. The lack of a deterrent effect on driving behavior suggests that the availability of the defense is not salient to drivers. The reduction in loss costs supports the notion that defense lawyers are aware of the defense and make use of it. The resulting effect of lowering insurance payouts may alleviate increasing auto insurance costs.

Life span uncertainty (longevity risk) impacts several economic decisions. Individuals can form and revise their survival beliefs making use of behavioral heuristics. We propose a model of sentiment, in which individuals are assumed to switch between optimistic and pessimistic expectations of their health. When optimism is persistent in the face of health shocks, or when individuals are more likely to change their sentiment from pessimistic to optimistic than otherwise, our model predicts survival underestimation at young ages and overestimation at old ages. An empirical analysis based on the longitudinal data from Survey of Health, Ageing and Retirement in Europe validates our model.

We investigate whether individuals correctly assess the risk of default of annuity providers and incorporate this information into their decision-making when purchasing an annuity. To do so, we analyze actual retirement product choices from a large administrative data set from Chile and exploit an exogenous change that decreased the coverage of government guarantees against annuity provider default. If individuals are rational and properly incorporate default risk into their decision process then, before this change, individuals should choose riskier providers that give higher annuity payments. However, we find that individuals' decisions are not influenced by changes in their protection against the risk of provider default. It seems that individuals have been unnecessarily reducing their annuity payments by not incorporating crucial information about their actual risk exposure to default when selecting annuities at retirement.

The Affordable Care Act (ACA) substantially altered regulations in the nongroup and small group health insurance markets and those markets continue to receive significant policy attention. To understand how those markets have functioned in recent years and how they would be impacted by policy changes, we estimated enrollment and spending by age and sex using claims data covering enrollment in ACA risk-adjusted plans in 2017–2019 and compared spending to a federal default age-rating curve for premiums. Our results suggest that women aged 55–64 helped stabilize the nongroup market through high enrollment and relatively low spending. Men enrolled in the marketplace also subsidized other nongroup enrollees but to a lesser extent than expected. In fact, men aged25–50 enrolled in nongroup plans spent 18% more than their counterparts enrolled through a small employer. These unique spending patterns have interesting policy implications, including that lowering the Medicare eligibility age would likely increase premiums in the nongroup market.

We study the effect of weather index insurance (WII) uptake on social capital. We measure individual social capital using experimental and survey-based measures and relate it to the actual purchase of WII. We use propensity score matching (PSM) and an instrumental variable (IV) to address endogeneity concerns. Our descriptive and PSM estimates show that WII uptake negatively and significantly affects social capital. We find that insured households contribute less to the public good than uninsured households. We also find qualitatively and quantitatively similar results using our IV approach, yet insufficient power renders most of our IV estimates insignificant. We however report robust significant effects of instrumented WII uptake on sociopsychological outcomes—WII uptake increases perceptions of self-sufficiency and free-riding behavior: these are potential channels through which a negative effect on social capital comes about. Although far from conclusive, our paper provides several pieces of evidence that suggest WII uptake negatively affects social capital.

Identifying insurance fraud is a difficult task due to the complex nature of the fraud itself, the diversity of techniques employed, the rarity of fraud cases observed in data sets, and the relatively limited allocation of human, financial, and time resources to carry out investigations. The aim of this paper is to provide a clean and well structured study on modeling fraud on home insurance contracts, using real French data from 2013 to 2017. Several methods are developed to identify risk factors and unusual customer behaviors. Traditional econometric models as well as new machine-learning algorithms with good predictive performance and high operational efficiency are tested, while maintaining method interpretability. Each methodology is evaluated on the basis of adequate performance measures and the issue of imbalanced databases is also addressed. Finally, specific methods are applied to interpret the results of the machine-learning methods.

We find that there are fewer disclosures of risk factors when customers for life insurance are screened by financial advisors, compared with when similar profile customers are screened directly by the insurer's telephone operators. The lower rate of disclosure is systematic across all medical and lifestyle risks and has a sizeable economic impact on customer premiums. As a result, customers screened by advisors enjoy unfairly cheaper and more favorable policies. We identify the key drivers of lower customer disclosures to be conflicted incentives and lower scrutiny. We assert that the fewer disclosures from customers screened by advisors may translate into noncaptured risk that could be cross-subsidized by customers who provide more complete disclosures through the insurer's telephone operators. On reviewing our findings, the participating insurer in the study calculated that removing advisors from the screening process could allow certain insurance products to be heavily discounted while maintaining profitability.

Based on classical contagion models we introduce an artificial cyber lab: the digital twin of a complex cyber system in which possible cyber resilience measures may be implemented and tested. Using the lab, in numerical case studies, we identify two classes of measures to control systemic cyber risks: security- and topology-based interventions. We discuss the implications of our findings on selected real-world cybersecurity measures currently applied in the insurance and regulation practice or under discussion for future cyber risk control. To this end, we provide a brief overview of the current cybersecurity regulation and emphasize the role of insurance companies as private regulators. Moreover, from an insurance point of view, we provide first attempts to design systemic cyber risk obligations and to measure the systemic risk contribution of individual policyholders.