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Climate change poses a serious risk for insurance firms, threatening their sustainability from numerous channels of impact. Assessing this impact, however, is not straightforward. We assess and distinguish between insurance firms by impact and response to climate change and relate the firms' financial characteristics to climate risk exposure. A text mining approach using climate change sub-dictionaries on risk exposure, impact, and response, and a nested feature extraction method is developed to define and classify insurance firms' adaptation levels to climate change. These features reveal that casualty insurance firms are most susceptible to acute climate risk, while life insurance firms are more prone to chronic climate risk. Insurance firms with the highest exposure to climate change present a high level of adaptation to pecuniary impact of the risk. Nevertheless, many firms with exposure remain inadequately prepared for climate change and firms with high exposure show relatively higher financial weakness. [ABSTRACT FROM AUTHOR]

We study how professional investors capitalize flood risk in commercial real estate (CRE) markets after hurricane Sandy. We show that New York CRE exposed to flood risk trades at a large, persistent discount. CRE in Boston, which mostly escaped direct hurricane‐related damage, also exhibits persistent price penalties. These price effects are driven by asset‐level capitalization rates, not building occupancy. Results from a placebo test using real estate prices in Chicago show that our inferences are not driven by coincidental, unrelated price trends for waterfront real estate assets. Our results are consistent with professional investors responding to a persistent shift in the salience of flood risk post‐Sandy, even in locations spared by the disaster. [ABSTRACT FROM AUTHOR]

We examine how uncertainty about a firm's future cash flows influences the quality of its accounting information. As uncertainty increases, information asymmetry between managers and stakeholders will almost certainly increase, amplifying the potential influence of uncertainty. We focus on a specific setting where severe levels of uncertainty can influence financial reporting, the property‐casualty (P&C) insurance industry and use catastrophes as a shock to the level of uncertainty regarding P&C insurer's future cash flows. We use P&C firms' claim loss estimation errors as a proxy for accounting information quality. Results suggest that, in times of heightened uncertainty, managers respond by increasing accounting information quality. Moreover, managerial claim loss forecasts are more accurate for publicly traded P&C firms relative to privately—or mutually—owned P&C firms as catastrophe exposure increases. Additionally, claim loss estimates are incrementally more accurate in times of heightened uncertainty for public P&C firms with higher institutional ownership or analyst following. These results corroborate the conjecture that managers' decisions to provide more accurate forecasts in times of heightened uncertainty are attributable to an increased demand for better information by external stakeholders. [ABSTRACT FROM AUTHOR]

During the last three decades, the Kafue flats floodplain fishery on the Kafue River in Zambia has been increasingly exploited due to more individuals settling in the area and seasonal travellers gaining access to the fishery during flood season. Despite successful governance arrangements that effectively regulated access to fish stocks for many generations, evidence shows that these arrangements are not working as new entrants continue to gain access and overexploit remaining fish stocks. Managing new entrants is a crucial factor in achieving sustainable use. Our objective was to gain an understanding of fisheries governance on the Kafue floodplain fishery, particularly in Shimungalu and Nyimba fishing villages, where different levels of government support for co‐management structures produced different outcomes. Our research approach was qualitative, by utilising the snowball sampling technique and incorporating interviews and documentary analysis. Our aim was to investigate discrepancies in the efficacy of resource access and utilisation in the two fishing camps, and to offer recommendations on how governance systems for the fishery could be refined to improve their efficacy. This comparative analysis of the two fishing communities, which share numerous characteristics with various small‐scale fisheries in Africa, provides an opportunity to understand how polycentric governance offers a solution by enabling other organisations to fill capacity gaps faced by relevant authorities. The lessons derived from this analysis offer valuable insights into enhancing fisheries governance and future research directions in Zambia, and Africa at large. [ABSTRACT FROM AUTHOR]

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This study extends current knowledge on competition and corporate defense by investigating how firms transfer risk in response to their firm-specific multimarket and structural competitive conditions. Drawing on the theory of multimarket competition, we propose an inverted U–shaped relationship between multimarket competition and risk transfer. We also propose that, for the sake of gaining a competitive edge, the extent to which a firm manages risk will tend to be opposite to that of its competitors. Last, we propose that egocentric industry concentration will moderate the relationship between multimarket competition and risk transfer besides its direct effect. Analysis of reinsurance usage in the US property and casualty insurance industry strongly supports our model and shows that firm-specific competitive conditions are salient to a firm's risk transfer level. [ABSTRACT FROM AUTHOR]

This article discusses the recent changes in states' statutes of limitations for civil actions related to child sexual abuse. It focuses on New York's Child Victims Act (CVA) as an example, which allows victims to bring civil claims even after the statute of limitations has expired. Many other states have implemented similar laws, resulting in numerous sexual abuse victims pursuing claims against institutions like the Boy Scouts of America and Catholic dioceses. The article also addresses the challenges and strategies involved in proving the existence and terms of lost insurance policies in these cases. It suggests methods such as finding similar policies issued to similar entities during the relevant period and using standard insurance forms as references. The burden of disproving coverage lies with the insurer, who must provide all relevant documents and proofs of coverage. The article provides an overview of the legal and evidentiary standards governing recovery under lost policies and offers guidance for policyholders and insurance companies in resolving claims related to sexual abuse. [Extracted from the article]

In this paper, we introduce and employ a multi-agent model of entry to analyze barriers to entry in the U.S. property casualty insurance industry. Our estimations are conducted at the market-year level, enabling a detailed exploration of the relative importance of barriers across three dimensions: geography, product, and time. Our findings reveal that entry barriers are both prevalent and significant in the U.S. property casualty insurance industry, with de novo entrants encountering the most challenges from product barriers across all markets. We observe that expanding across product lines is more costly than expanding across states. Particularly, New York and California exhibit the strongest state barriers. Among various product lines, our research identifies that insurance expertise in mortgage guaranty and medical professional liability insurance presents the most substantial barriers to entry. This study contributes valuable insights into the dynamics of entry barriers in the U.S. property casualty insurance industry, highlighting the importance of considering geographic and product-specific knowledge, as well as temporal factors, in the context of market entry. Through analyses across these dimensions, we enhance the understanding of the challenges faced by new entrants and shed light on the specific market conditions shaping entry barriers. [ABSTRACT FROM AUTHOR]

While flooding is the costliest natural disaster risk, public‐sector investments provide incomplete protection. Moreover, individuals are in general reluctant to voluntarily invest in measures which limit damage costs from natural disasters. The moral hazard hypothesis argues that insured individuals take fewer other preparedness measures based on their assumption that their losses will be covered anyway. Conversely, the advantageous selection hypothesis argues that individuals view insurance and other risk reduction measures as complements. This study offers a comprehensive assessment of factors related to the separate uptake of natural disaster insurance and the flood‐proofing of homes as well as why people may take both of these measures together. We use data from a survey conducted in Paris, France, in 2018, after several flood events, for a representative sample of 2976 residents facing different levels of flood risk. We perform both main effects regressions and interaction analyses to reveal that home adaptation to flooding is positively associated with comprehensive insurance coverage, which includes financial protection against natural disasters. Furthermore, actual and perceived risks, as well as awareness of official information on flood risk, are found to explain some of the relationship between home adaptation and comprehensive insurance purchase. We suggest several recommendations to policymakers based on these insights which aim to address insurance coverage gaps and the failure to take disaster risk reduction measures. In particular, groups in socially vulnerable situations may benefit from subsidized insurance, low interest loans, and decision aids to implement costly adaptation measures. [ABSTRACT FROM AUTHOR]

In a world of rising long-term risks and their ensuing syndromes, the mitigation and financing of long-term risks are therefore arguably some of the most critical issues facing society. However, long-term thinking involving future generations draws limited attention in current political and social systems. Private insurance has received increased attention due to its expert role in risk management and its risk transfer mechanisms, and it has played an important role in dealing with some types of long-term risk, such as floods and earthquakes. Increasingly, insurance also contributes to disaster mitigation through regulating the conduct of policyholders by creating incentives for policyholders to counter short-termism and invest in reduction measures regarding long-term risks. In addition, it has been shown that supply-side problems and behavioural anomalies make it difficult to insure against long-term risks. Innovative long-term insurance solutions and a combination of public and private partnerships are proposed to overcome these restrictions. [ABSTRACT FROM AUTHOR]

Empirical evidence suggests that insurance groups allocate capital to members with better performance or growth prospects and use internal capital markets (ICMs) to protect the franchise value of less capitalized members. We propose and test an additional motivation for the use of ICMs—to manage regulatory scrutiny risk. We show that almost 50% of insurers at risk of facing additional regulatory scrutiny due to failing four Insurance Regulatory Information System (IRIS) ratios received sufficient internal capital to avoid enhanced regulation. Moreover, the likelihood and extent of internal capital allocation are related to regulatory scrutiny risk and the amount of capital allocated is typically just enough to avoid regulatory scrutiny. Time series evidence indicates that groups manage regulatory scrutiny risk by allocating capital toward affiliates when their pre‐capital contribution IRIS ratio failures exceed three, and away from affiliates when they are no longer at risk of additional regulatory scrutiny. [ABSTRACT FROM AUTHOR]

This study enriches the current literature because it is the first to examine how foreign ownership and Investor attention affect the risk-taking behaviors of property and casualty insurance companies in Vietnam. This study is unique because it tests whether foreign ownership moderates the relationship between investor attention and the risk-taking behavior of insurance firms or vice versa. This study employs the Random Effect Models, Generalized Least Squares, Johnson-Neyman test, and simple slope analyses to analyze 28 property and casualty insurance companies from 2010 to 2022. The findings indicate that foreign ownership and investor attention increases the risk-taking behaviors of insurance firms. Moreover, the findings indicate that foreign ownership moderates the relationship between investor attention and the risk-taking behavior of insurance firms in Vietnam. The findings align with agency theory, stakeholder theory, limited attention theory, and prior literature. This study supports managers and policymakers in developing the insurance sector sustainably, especially in emerging markets. [ABSTRACT FROM AUTHOR]

First, within a product line, deductible options are vertically differentiated (i.e., if all deductible options were offered at the same price, everyone would choose the lower deductible). It's a pleasure to discuss this article, which estimates risk preferences from observational data while accommodating heterogeneity across three dimensions of choice: consideration sets, risk preference types (whether a consumer maximizes expected utility or not), and within-type preferences for risk. This brings us back to the information from the National Association of Insurance Commissioners that the average size of a collision claim is more than three times the size of the average comprehensive claim (and, perhaps relatedly, collision claims are 3.5 times more likely to be filed), and the admonishment from Bankrate that if you can't afford to cover your deductible, it's not useful to buy insurance in the first place. An insurance "context" is a line or type of insurance, such as collision insurance or comprehensive insurance. [Extracted from the article]

This paper investigates the impact of flood management policies on airport investment and the resulting financial constraints. Specifically, it examines the effects of flood insurance, building codes, and public adaptation investment on the investment decisions of 100 United States airports located in flood-prone areas. The paper estimated the financial loss from extreme precipitations and flooding using novel data from the United States Federal Emergency Management Agency, and a differences-in-differences framework leveraging the introduction of the 2012 Biggert–Waters reform of the National Flood Insurance Program. The findings reveal that while flood insurance costs negatively influence overall airport investment, they do not significantly affect investment–cash sensitivity. On the other hand, the introduction of stricter building codes and public adaptation investment leads to increased cash usage for investment purposes, particularly among airports exposed to extreme precipitation and flood risks. Furthermore, the analysis suggests that the observed increase in financial constraints resulting from stricter building codes and public adaptation investment is likely driven by the asymmetry of information rather than the materiality of flood risk. In other words, public investment in flood risk reduction appears to signal to investors that the airport is exposed to flood risk, potentially leading to increased financial constraints. This finding highlights the importance of considering information asymmetry when assessing the impact of flood management policies on financial constraints. Understanding the underlying drivers of these effects is crucial for supporting resilient infrastructure development and informing effective decision-making in flood-prone areas. [ABSTRACT FROM AUTHOR]

The United States' National Flood Insurance Program (NFIP) has accumulated over $20 billion in debt to the US Treasury since 2005, partly due to discounted premiums on homes in flood‐prone areas. To address this issue, FEMA introduced Risk Rating 2.0 in October 2021, which is able to assess and charge more accurate and equitable rates to homeowners. However, rates must be continually updated to account for increasing flood damage caused by sea level rise and more intense hurricanes due to climate change. This study proposes a strategy to adopt updated premium rates that account for climate change effects and address affordability and risk mitigation issues with a means‐tested voucher program. The strategy is tested in a coastal community, Ortley Beach, NJ, by projecting its future flood risk under sea level rise and storm intensification. Compared with using static rates for all the properties in Ortley Beach, the proposed strategy is shown to reduce the NFIP's potential losses to the community from 2020 to 2050 by half (from $4.6 million to $2.3 million), improve the community's flood resistance, and address affordability concerns. Sensitivity analysis of varying incomes, loan interest rates, and conditions for a voucher indicates that the strategy is feasible and effective under a wide range of scenarios. Thus, the proposed strategy can be applied to various communities along the US coastline as an effective way of updating risk‐based premiums while addressing affordability and resilience concerns. [ABSTRACT FROM AUTHOR]

Purpose: The survivorship of firms under extreme weather poses an essential question about the local economy's health. Over 90% of agricultural banks are categorized as community banks, which are important financial institutions promoting local growth. While previous studies suggest that climate change and weather shocks adversely impact community banks' resiliency, studies on whether these institutions engage in risk-reducing management strategies have been limited. In this study, the authors examine strategic choices of local community banks when facing flood events which include (1) safety net increase, (2) portfolio diversification, and (3) branch opening. These strategic choices are the coping mechanisms banks can take to survive while affecting the local competitive lending market. Design/methodology/approach: The authors use panel-fixed effect regressions based on the storm data from National Oceanic and Atmospheric Administration (NOAA)'s National Weather Service (NWS) and the call reports from the Federal Deposit Insurance Corporation (FDIC). The authors focus on community banks' account variable characteristics and the number of offices to examine whether community banks take an active role in managing flood risk. Findings: Results suggest that community banks do employ the selected strategic choices to a certain degree, as it is found that there is an increase in the core capital that absorbs shocks and portfolio diversification. However, the magnitudes of these activities are rather small and not large enough to fully mitigate the climate risk. Also, the authors do not find any evidence of branch expansion associated with local floods. Originality/value: This study contributes to the literature by examining different strategic choices of community banks in the face of natural uncertainty. Even though concerns of climate risk have been raised in the regulatory setting, a lack of guidance or assessment tools could contribute to the passive action of these community banks, even though climate risks can have a significant economic impact. Thus, the evidence documented from this study calls for further guidelines and the importance of highlighting climate risks on community banks so that they can actively engage in risk-reducing strategies. [ABSTRACT FROM AUTHOR]

In this paper, we developed a Shiny-based application called AutoReserve. This application serves as a tool used for a variety of types of loss reserving. The primary target audience of the app is personal auto actuaries, who are professionals in the insurance industry specializing in assessing risks and determining insurance premiums for personal vehicles. However, the app is not limited exclusively to actuaries. Other individuals or entities, such as insurance companies, researchers, or analysts, who have access to the necessary data and require insights or analysis related to personal auto insurance, can also benefit from using the app. It is the first web-based application of its kind that is free to use and deployable from the personal computer or mobile device. AutoReserve is a software solution that caters to the needs of insurance professionals where only a few existing web-based applications are available. The application is divided into three parts: a summary of the loss data, a classical loss reserving tool, and a machine learning loss reserving tool. Each component of the application functions differently and allows for inputs from the user to analyze the provided loss data. The user, in other words, individuals or entities who utilize the Auto Reserve application, can then use the outputs for these three sections to improve his or her risk management or loss reserving process. AutoReserve is unique compared to other loss reserving tools because of its ability to employ both traditional, spreadsheet-based and modern, machine-learning-based loss reserving tools. AutoReserve is accessible on the web. The app is currently usable and is still undergoing frequent updates with new features and bug fixes. [ABSTRACT FROM AUTHOR]

This paper challenges the question of existence and predictability of underwriting cycles in the U.S. property and casualty insurance industry. Using an approach in the frequency domain, we demonstrate the existence of a hidden periodic component in annual aggregated loss ratios. The data support an underwriting cycle length of 8–9 years. Going beyond previous research and studying almost 30 years of quarterly underwriting data, we can improve forecasting performance by (dis)connecting cycles and catastrophic events. Superior out-of-sample forecast results from models with intervention variables flagging the time point of catastrophic outbreaks is achieved in terms of mean squared/absolute forecast errors. We evaluate model confidence sets containing the most accurate model with a certain confidence level. The analysis suggests that reliable forecasts can be achieved net of the irregular major peaks in loss distributions that arise from natural catastrophes as well as unusual "black swan" events. [ABSTRACT FROM AUTHOR]

With the advent of the "big" data era, large-sample properties of a statistical learning method are becoming more and more important in an actuary's daily work. For a fixed sample size, regardless of how large it is, the variance of an estimator can be larger than a pre-assigned level to an arbitrary extent. In this paper, we propose a nonparametric sequential learning procedure for estimating the pure premium. Our method not only provides an accurate estimate of the pure premium but also guarantees that the mean of our random sample sizes is close to the unobservable optimal fixed sample size and the variance of our estimator is close to all small pre-determined levels. In addition, our method is nonparametric and applicable to any claims distribution; hence it avoids potential issues associated with a parametric model such as model misspecification risk and the effect of selection. [ABSTRACT FROM AUTHOR]

In this paper, we developed a Shiny-based application called AutoReserve. This application serves as a tool used for a variety of types of loss reserving. The primary target audience of the app is personal auto actuaries, who are professionals in the insurance industry specializing in assessing risks and determining insurance premiums for personal vehicles. However, the app is not limited exclusively to actuaries. Other individuals or entities, such as insurance companies, researchers, or analysts, who have access to the necessary data and require insights or analysis related to personal auto insurance, can also benefit from using the app. It is the first web-based application of its kind that is free to use and deployable from the personal computer or mobile device. AutoReserve is a software solution that caters to the needs of insurance professionals where only a few existing web-based applications are available. The application is divided into three parts: a summary of the loss data, a classical loss reserving tool, and a machine learning loss reserving tool. Each component of the application functions differently and allows for inputs from the user to analyze the provided loss data. The user, in other words, individuals or entities who utilize the Auto Reserve application, can then use the outputs for these three sections to improve his or her risk management or loss reserving process. AutoReserve is unique compared to other loss reserving tools because of its ability to employ both traditional, spreadsheet-based and modern, machine-learning-based loss reserving tools. AutoReserve is accessible on the web. The app is currently usable and is still undergoing frequent updates with new features and bug fixes.