Journals

Journal of Risk and Insurance

The Journal of Risk and Insurance (JRI) publishes theoretical and empirical research on the topics of insurance economics and risk management. Research in the JRI informs practice, policy-making, and regulation in insurance markets as well as corporate and household risk management. It is currently indexed by the American Economic Association’s Economic Literature Index, RePEc, the Social Sciences Citation Index, and others. Issues of the JRI, from volume one to volume 82 (2015), are available online through JSTOR. Recent issues of the JRI are available through Wiley Online Library. A subscription to the Journal of Risk and Insurance is one of the many benefits of ARIA Membership.

Journal of Risk and Insurance

Early View

An examination of life insurance policy surrender and loan activity

Extant literature has explored policyowner decision‐making as it relates to both life insurance policy surrender and borrowing activity. However, researchers have not yet examined why individuals may select one option over the other. In this study, we investigate common hypotheses related to policy surrender and loan activity using approaches which allow us to examine the two options jointly while also accounting for the multidimensional nature of the decision‐making process. We offer evidence consistent with the emergency fund, alternative funds, and policy replacement hypotheses as they relate to the decision to either surrender a policy or take out a policy loan and find that differential effects exist between the two options. In particular, our findings suggest that households tend to surrender their cash value policies when longer‐term financial needs arise while temporary needs are more likely addressed with loans which keep the policy in force, each consistent with rational household decision‐making.

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Journal of Risk and Insurance

Early View

The efficiency of voluntary risk classification in insurance markets

It has been established that categorical discrimination based on observable characteristics such as gender, age, or ethnicity enhances efficiency. We consider a different form of risk classification when there exists a costless yet imperfectly informative test of risk type, with the test outcome unknown to the agents ex ante. We show that a voluntary risk classification in which agents are given the option to take the test always increases efficiency compared with no risk classification. Moreover, voluntary risk classification also Pareto dominates a regime of compulsory risk classification in which all agents are required to take the test.

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Journal of Risk and Insurance

Early View

Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policies

Changing climate and technology can often lead to nonstationary losses across both time and space for a variety of insurance lines including property, catastrophe, health, and life. As a result, naive estimation of premium rates using past losses will tend to be biased. We present three successively flexible data‐driven methodologies to nonparametrically smooth across both space and time simultaneously, thereby appropriately incorporating possibly nonidentically distributed data into the rating process. We apply these methodologies in estimating U.S. crop insurance premium rates. Crop insurance, with global premiums totaling $4.1 trillion in 2018, is an interesting application as losses exhibit both temporal and spatial nonstationarity. We find significant borrowing of information across both time and space. We also find all three methodologies improve both the stability and accuracy of crop insurance premium rates. The proposed methods may be of relevance for other lines of insurance characterized by spatial and/or temporal nonstationary losses.

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Risk Management & Insurance Review

Risk Management and Insurance Review publishes high-quality applied research, well-reasoned opinion and discussion in the field of risk and insurance. Additionally, the Review provides a repository of high-caliber model lectures in risk and insurance, along with articles discussing and evaluating instructional techniques. A subscription to the Risk Management and Insurance Review is one of the many benefits of ARIA Membership.

Risk Management & Insurance Review

Volume 23, Issue 4

A framework for the evaluation of InsurTech

In recent years, the insurance industry has known rapid development and application of new technologies, leading to the emergence of a large number of innovative products. This constitutes a challenge for stakeholders ranging from consumers, management, investors, and on to regulators, who need to evaluate these so‐called InsurTech innovations. This study applies a modified Delphi method in combination with the Analytical Hierarchy Process of Saaty evaluate potential innovations on three main dimensions, (i) management and operations, (ii) level of technology, and (iii) user experience. The authors propose a transparent way of evaluating InsurTech innovations that also may provide guidance for their future development.

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Risk Management & Insurance Review

Volume 23, Issue 4

Government insurance for business interruption losses from pandemics: An evaluation of its feasibility and possible frameworks

Many businesses have suffered severe economic losses due to the COVID‐19 pandemic. Because property business interruption (BI) policies generally do not cover losses caused by a virus, this has led to proposals for some form of government program that would provide this coverage. This paper explains why private BI pandemic insurance on a broad scale is infeasible. It considers the goals of a government BI pandemic insurance program and the challenges it would face with respect to its design and implementation and how they could be addressed and concludes that creating such a program requires thorough and careful consideration of its features and the tradeoffs involved with its structure.

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Risk Management & Insurance Review

Upcoming

Pandemic risk: Impact, modeling, and transfer

COVID‐19 has proven that pandemic risk deems to the type of catastrophe risk that needs to be treated seriously, by both society and the insurance industry. A key element to measure, manage, and transfer pandemic risk is the modeling capability. This paper first reviews the insured loss from COVID‐19 and the impact on the insurance industry. Then, current pandemic risk modeling capabilities and how insurance industry uses these models are evaluated. Some suggestions are made in terms of how these models can be improved in the future and how they can assist in insuring the pandemic risk. Finally, the nonmodeling elements of pandemic risk transfer and the government’s role are discussed.

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