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The article discusses changes in the 2021 American Land Title Association's (ALTA) standard title insurance policy forms. Topics discussed include the clarification of certain covered risks, the addition of new language relating to remote online notarization in owner's and loan policies, and exclusions added with the 2021 Owner's and Loan Policy revisions.

There are numerous types of life insurance policies--seemingly something for every taste. But which is right for me? Among other considerations, there are issues of product dependability versus potential risk that expectations won't be met; flexibility of premiums versus required payment amounts and schedules; and overall compatibility with one's comfort and style of accumulating longterm assets for death benefit or retirement. [ABSTRACT FROM AUTHOR]

The article highlights the September 2022 Annual Report of the U.S. Federal Insurance Office (FIO) regarding cyber insurance, Terrorism Risk Insurance Program (TRIP) and industry efforts to address climate change. Topics include the climate-related insurance priorities presented by the FIO such as to assess climate-related insurance gaps and potential for disruptions of private coverage, and a separate annual report on TRIP effectiveness issued by the FIO on June 30, 2022.

We examine whether underwriters price up weakly demanded initial public offerings (IPOs) to prevent withdrawal. Our empirical strategy exploits a discontinuity in the distribution of IPO prices around the low boundary of the filing range. Offerings with a high ex ante withdrawal probability that are priced at this boundary are likely priced up to meet issuers' reservation prices. We compare the aftermarket returns of these IPOs to the returns of other weakly demanded offerings where issuers' reservation prices were likely not binding, and we identify a negative 8.4-percentage-point differential attributable to the aggressive pricing inherent in setting the price at the low boundary when withdrawal risk is high. [ABSTRACT FROM AUTHOR]

Many landlords do not carry liability insurance, which means that many residents have little chance of recovery after being harmed by dangerous housing conditions. More disabling injuries occur in homes than in workplaces and motor vehicles combined. These risks disproportionately affect low-income, minority tenants. Because state laws do not require landlords to carry liability insurance, property owners reap the financial benefits of the long-term rental housing market while passing the risk of injury and cost of harm to their tenants. In contrast, there is a growing trend among state and local jurisdictions to require hosts on platforms like Airbnb to assume the risk of harm and carry liability insurance as a prerequisite to participate in the short-term rental market. Incongruously, in many jurisdictions a temporary resident who stays in a property for twenty-nine days has greater protection than a long-term tenant who resides at the same property for more than a month. Analyzing racial bias in insurance regulations and juxtaposing statutory approaches to risk allocation, this Article posits that liability insurance coverage is properly understood as an access-to-justice issue that negatively affects the health of minority long-term renters. For long-term tenants who experience personal injury or property damage, prevailing in a case against a property owner often kickstarts the time-consuming and expensive process of attempting to collect on that judgment, and ultimately fails to provide relief. This Article argues that mandated liability coverage would align protections for long-term rental housing with those protections already in place for short-term rentals, affording permanent residents the same degree of protection as temporary visitors. [ABSTRACT FROM AUTHOR]

In this paper, we explore potential surplus modelling improvements by investigating how well the available models describe an insurance risk process. To this end, we obtain and analyse a real-life data set that is provided by an anonymous insurer. Based on our analysis, we discover that both the purchasing process and the corresponding claim process have seasonal fluctuations. Some special events, such as public holidays, also have impact on these processes. In the existing literature, the seasonality is often stressed in the claim process, while the cash inflow usually assumes simple forms. We further suggest a possible way of modelling the dependence between these two processes. A preliminary analysis of the impact of these patterns on the surplus process is also conducted. As a result, we propose a surplus process model which utilises a non-homogeneous Poisson process for premium counts and a Cox process for claim counts that reflect the specific features of the data. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop an approach to extract information about cyber risks from structured financial products. We consider decision makers that are interested in extracting information about the uncertainty of Cyber risks. The value of information can be evaluated using recently developed entropy approaches in Finance. The underlying idea is that what we call Arrow-Debreu Cyber Risk state prices can be extracted, provided the right structured products be 'created'. It is shown that different market-based approaches can be used to get a better idea of the shape of the loss distribution facing firms. This information is potentially of interest to evaluate the risk premiums of insurance products. Comparisons between extracted market expectations can also be informative for risk evaluation, notably the distribution of unexpected losses and the eventual shortfall calculations. Finally, recent information-theoretic approaches enable us to make the link between pricing and the value of information to investors. [ABSTRACT FROM AUTHOR]

Natural disasters, such as tornadoes, floods, and wildfire pose risks to life and property, requiring the intervention of insurance corporations. One of the most visible consequences of changing climate is an increase in the intensity and frequency of extreme weather events. The relative strengths of these disasters are far beyond the habitual seasonal maxima, often resulting in subsequent increases in property losses. Thus, insurance policies should be modified to endure increasingly volatile catastrophic weather events. We propose a Natural Disasters Index (NDI) for the property losses caused by natural disasters in the United States based on the "Storm Data" published by the National Oceanic and Atmospheric Administration. The proposed NDI is an attempt to construct a financial instrument for hedging the intrinsic risk. The NDI is intended to forecast the degree of future risk that could forewarn the insurers and corporations allowing them to transfer insurance risk to capital market investors. This index could also be modified to other regions and countries. [ABSTRACT FROM AUTHOR]

In this paper, I analyze the effectiveness of different capital regulations in mitigating the effects of moral hazard that exists only for systemically important banks. Leverage restrictions have the potential to reduce the fraction of banks that are systemically important but do not mitigate moral hazard for those that are. Risk adjusted requirements could mitigate moral hazard (of banks with low leverage) but do not affect (endogenous) systemic risk. A combination of both requirements as proposed by the Basel III framework can be successful, although only under restrictive conditions. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to investigate the effects of chief executive officer (CEO) international work experience, functional background and career concerns on managerially-distorted investment decisions. Design/methodology/approach: This paper focuses on S&P 500 publicly held US manufacturing companies during the period from 2009 to 2012. The data related to the CEOs' international experience and their functional background experience are manually collected from Business Week's Corporate Elite. Financial data is retrieved from COMPUSTAT database. The data for CEO tenure and age are retrieved from the ExecuComp database. Besides ordinary least squares regression, this paper conducts two-stage least squares regression analysis. Endogeneity and additional tests are also considered in this paper. Findings: The findings show that CEO international work experience may not reduce under-investment, but it may exacerbate over-investment. CEO throughput functional background may exacerbate under-investment, but it may not reduce over-investment. Furthermore, CEO career concerns are useful in reducing the inefficient investments caused by international work experience and throughput functional background. These results remain similar when potential self-selection bias, as well as alternative measures of career concerns and investment efficiency, are considered. Originality/value: This paper contributes to the existing literature in the following ways: first, while a significant amount of attention has been paid to how investment decisions are affected by financial reporting quality and material internal control weaknesses, there has been little evidence accumulated related to how managers' international experience, professional background and career concerns affect investment inefficiency. The authors attempt to fill this gap. Second, the authors manually collect the international experience and functional backgrounds of CEOs working for S&P 500 US manufacturing companies. This unique data set makes it possible to complement previous studies by investigating the effects of managerial international experience and functional background on investment behavior. Finally, previous theoretical studies have long recognized that managers' career concerns affect their corporate investment decisions. These studies suggest that young CEOs have a greater incentive to signal their abilities by adopting more active and possibly riskier investment strategies, thus raising the moral hazard problem with regard to firm investments. The authors enrich these studies by showing that work experience alleviates the moral hazard problem with respect to young CEOs' investment decisions. [ABSTRACT FROM AUTHOR]

We use the theory of cooperative games for the design of fair insurance contracts. An insurance contract needs to specify the premium to be paid and a possible participation in the benefit (or surplus) of the company. We suppose that a convex commonotonic premium functional is used to value the aggregated liability of the insurance company. It results from the analysis that when a contract is exposed to the default risk of the insurance company, ex‐ante equilibrium considerations require a certain participation in the benefit of the company to be specified in the contracts. The fair benefit participation of agents appears as an outcome of a game involving the residual risks induced by the default possibility and using fuzzy coalitions. [ABSTRACT FROM AUTHOR]

401(k) plans provide little guidance on turning accumulated assets into income. Insurance against the risk of outliving one's assets is available through immediate annuities, deferred annuities, and additional Social Security through delayed claiming. Under this Social Security bridge option, participants would tap their 401(k) for payments equal to their Social Security to delay claiming. This paper compares these three options in simulations against a baseline in which no assets are annuitized. In each option, assets not allocated to purchasing lifetime income are consumed following the required minimum distribution; robustness of results to optimal drawdown conditional on annuitization strategy is also assessed. The analysis finds that, when market and health shocks are included alongside longevity uncertainty, the Social Security bridge option is generally the best for households with median wealth. Wealthier households can benefit from combining the bridge option with a deferred annuity. [ABSTRACT FROM AUTHOR]

With the shift towards teleworking/working from home in recent years and accelerated by the COVID-19 pandemic, insurers are finding themselves relying on outsourcing as a way to cope with changes in business models and requirements. This has augmented the risk of cyberattacks and is ultimately considered a high risk for insurers of any size, not only because it subjects insurers to litigation concerning data breaches, but also because of the harm to the insurer's reputation when an attack happens, which is further magnified by resultant loss of system use. Clients already have the perception that insurers are too invasive when it comes to personal data (especially in the medical and life insurance fields), so they are blamed for not handling cyber risk meticulously regardless of whether it is the outsourcing provider's fault. Risk managers in insurance companies need to apply enterprise risk management (ERM) principles and identify cyber risks across the entire process to manage these risks. The paper proposes some potential policy solutions that would help insurers mitigate outsourcing cyber risks. Further research is required in this field, specifically into what strategies insurers are implementing to deal with the risks posed by the outsourcing provider's cyber risk and which of those strategies have fared better than others thus far. [ABSTRACT FROM AUTHOR]

In the fourth essay, I Hong Fu, Yuehua Zhang, Yinuo An, Li Zhou, Yanling Peng, Rong Kong i , and I Calum G. Turvey i consider how belief formation about risk can influence insurance markets. The original online version of this article was revised: Not all authors were listed correctly as authors of this paper and the footnote on the first page was missing. [Extracted from the article]

Probabilistic seismic demand model (PSDM) is one of the critical components of performance-based earthquake engineering frameworks. The aim of this study is to propose a procedure to generate PSDMs for a typical regular continuous-girder bridge subjected to far and near-fault ground motions (GMs) utilizing machine-learning methods. A series of nonlinear time history analyses (NTHAs) is carried out to calculate the damage caused by the far and near-fault GMs for four different site conditions, and 21 seismic intensity measures (IMs) are considered. Subsequently, PSDMs are established for the IMs and engineering demand parameters based on the existing NTHA data using machine-learning methods, which include linear regression, Bayesian regression (BR), and a tree-based model. The results indicated that random forest (RF) is the most suitable model to predict the longitudinal and transverse curvature at the bottom of the four piers from the coefficients of determination. More specifically, the relative importance of each parameter in the model is evaluated, and peak ground velocity (PGV), peak spectral velocity (PSV), Arias intensity (AI), and Fajfar intensity (FI) are found to be the critical factors for the RF-based PSDM. Finally, all of these parameters, except AI, are correlated with velocity. The research results explore a new method for establishing the seismic demand model of continuous-girder bridges, which can provide suggestions for seismic damage prediction and seismic insurance risk evaluation. [ABSTRACT FROM AUTHOR]

This article deals with the estimation of the risk‐insurance nexus. We specifically examined the effect of geopolitical risk on insurance premium in a panel of 18 countries, while controlling for the effect of real income. Second‐generation econometric methods were employed for this purpose, and the results provided strong evidence of a positive impact on insurance premiums by geopolitical risks. We specifically found that the impact of geopolitical risks on nonlife insurance premium is higher than the impact on life insurance premium. Real income was also found to have a significantly positive effect on insurance premiums, and the impact on nonlife insurance premium was similarly larger than the impact on life insurance premium. On the basis of income elasticity, we found that insurance has the semblance of a luxury good, and on the basis of the panel causality tests, we confirmed the feedback hypothesis. We therefore conclude that exposure to geopolitical risks raises insurance premiums either as a result of increased insurance demand to hedge against geopolitical uncertainty or as a result of uncertainty tax factored into insurance premiums in unstable environments. [ABSTRACT FROM AUTHOR]

Insurance risks have traditionally been borne in reinsurance markets. However, in the 1990s, after a series of huge natural disasters, and consequently massive insurance payments, the reinsurance markets reduced their capacity to bear risks. Insurance-linked securities, such as CAT (catastrophe) index futures contracts, were created to provide insurers with a way to transfer insurance risks to capital markets. However, two obstacles are preventing CAT index futures from being traded: the basis risk between insurers' risks and the futures payoff, and adverse selection between informed insurers and uninformed investors in capital markets. This study investigates the conditions under which CAT index futures, whose payoff is the average of insurers' losses, can be traded, and insurers choose CAT index futures rather than reinsurance to transfer their risks. The results show a trade-off: CAT index futures can be traded if the number of insurers in the index is large enough, since averaging multiple insurers' losses can mitigate adverse selection in the index futures' payoff. However, if the number of insurers in the index is too large, insurers prefer reinsurance to index futures due to the high basis risk in the futures' payoff. [ABSTRACT FROM AUTHOR]

CAT bonds may add value to insurers' risk management strategies and may therefore substitute for reinsurance. Physical climate risks associated with extreme weather events, such as tropical cyclones, heatwaves and floods, and slow-changing conditions, such as sea level rise and prolonged higher temperatures, are increasing due to climate change. This thematic issue of I The Geneva Papers i contributes to this understanding by addressing four important issues: the awareness of insurers of climate risks and opportunities, the role of insurance in improving disaster risk preparedness, optimal public-private insurance schemes to cover natural catastrophes, and finally the use of reinsurance and CAT bonds as natural catastrophe risk transfer tools. [Extracted from the article]

Artificial intelligence (AI) allows a computer program to supplement or, in many cases, replace the role of human decision-making or action. This often includes gathering and analyzing data to make more efficient and/or accurate decisions. While some AI is fairly simple, other AI applications rely on sophisticated machine learning (ML) that allow machines to learn and improve from experience without being continually reprogrammed by humans. [ABSTRACT FROM AUTHOR]

We study large and moderate deviations for an insurance portfolio, with the number of claims tending to infinity, without assuming identically distributed claims. The crucial assumption is that the centered claims are bounded and that variances are bounded below. From a general large deviations upper bound, we obtain an exponential bound for the probability of the average loss exceeding a threshold. A counterexample shows that a full large deviation principle, including also a lower bound, does not follow from our assumptions. We argue that our assumptions make sense, in particular, for life insurance portfolios and discuss how to apply our upper bound in this context. Finally, we use a moderate deviations result by Petrov (1954) to estimate the probability of exceeding a threshold that depends on portfolio size. In this asymptotic regime, the rate function that determines the asymptotic behavior is explicit and thus very easy to compute numerically without solving an optimization problem. [ABSTRACT FROM AUTHOR]

Here, we provide an ethical analysis of discrimination in private insurance to guide the application of non-discriminatory algorithms for risk prediction in the insurance context. This addresses the need for ethical guidance of data-science experts, business managers, and regulators, proposing a framework of moral reasoning behind the choice of fairness goals for prediction-based decisions in the insurance domain. The reference to private insurance as a business practice is essential in our approach, because the consequences of discrimination and predictive inaccuracy in underwriting are different from those of using predictive algorithms in other sectors (e.g., medical diagnosis, sentencing). Here we focus on the trade-off in the extent to which one can pursue indirect non-discrimination versus predictive accuracy. The moral assessment of this trade-off is related to the context of application—to the consequences of inaccurate risk predictions in the insurance domain. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the concept of Poissonian occupation times below level 0 of a spectrally negative Lévy process. In this case, occupation time is accumulated only when the process is observed to be negative at arrival epochs of an independent Poisson process. Our results extend some well known continuously observed quantities involving occupation times of spectrally negative Lévy processes. As an application, we establish a link between Poissonian occupation times and insurance risk models with Parisian implementation delays. [ABSTRACT FROM AUTHOR]

The results of previous Iranian studies on the protective effect of health insurance on catastrophic health expenditures (CHE) are inconsistent. Therefore, the aim of this meta‐analysis was to summarize all existent evidence. We searched international and Iranian scientific databases for relevant literature. Using a Mantel–Haenszel random‐effects model, the pooled odds ratios (OR) were calculated. Subgroup meta‐analyses were performed considering the type of insurance and study population. The pooled OR for the protective effect of health insurance risk on facing CHE was 0.93 (95% confidence interval [CI], 0.68–1.28). The protective effect of the two types of insurance was statistically insignificant. Health insurance does not effectively provide financial protection against CHE in Iran. Expanding the prepayment mechanism and integrating health insurance funds can be good strategies in protecting people from CHE. More attention should be paid to the design of health insurance benefit package to cover chronic diseases. [ABSTRACT FROM AUTHOR]

Previous literature have shown that warming temperatures due to climate change are likely to decrease mean crop yields and increase crop yield risk. However, there is limited understanding of how crop insurance participation can potentially affect the adverse crop yield impacts of warming (or extreme heat). This study specifically examines whether crop insurance participation influences the impact of extreme heat on yield risk (i.e. yield variance, skewness and kurtosis). We utilise a parametric moment-based method and county-level panel data to evaluate how crop insurance participation affects the relationship between warming temperatures and the moments of crop yield distributions. Our results indicate that the yield risk increasing effect of warming is further magnified under high levels of crop insurance participation. This result still holds even when allowing for long-run adaptation (although the crop insurance effect tends to be weaker in this case). In general, our results indicate that not only does crop insurance participation adversely impact mean yields under climate change, it also influences the extent by which warming affects yield variability over time. This supports the notion that crop insurance can serve as a disincentive for climate change adaptation in agriculture. [ABSTRACT FROM AUTHOR]

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As a developing country, China's insurance market is already the second largest insurance market in the world, and its development is inseparable from the comprehensive development of insurance companies' business. At present, insurance companies are engaged in both traditional and nontraditional insurance businesses. Thus, to avoid extreme financial events, the insurance market requires more risk management. Hence, examining systemic risk in the insurance market in China is an interesting research topic. This paper studies the comovement between all listed insurance companies and the insurance market in China by modeling the average and extreme dependence structure using different copula specifications. Furthermore, it analyzes both downside and upside risk spillover effects from insurance companies to the insurance market by quantifying the following three market risk measures: the value‐at‐risk (VaR), the conditional VaR (CoVaR) and the delta CoVaR (ΔCoVaR). Finally, we test the significance of risk spillover effects and provide a formal ranking of the listed insurance companies with respect to their contribution to both the downside and upside systemic risk of the insurance market. [ABSTRACT FROM AUTHOR]

Natural disasters have been occurring more frequently and with greater potency, creating a real and heightened financial and operational risk to businesses around the globe. This paper aims to enhance traditional business continuity techniques and strategies by discussing how risk management, insurance and claims knowledge can form a robust platform from which to minimise the impacts of natural disasters on business. To this end, the paper combines professional knowledge from the fields of risk management, disaster response and insurance claims recovery to offer best practices in the key phases of planning and response. [ABSTRACT FROM AUTHOR]

In risk analysis, sensitivity measures quantify the extent to which the probability distribution of a model output is affected by changes (stresses) in individual random input factors. For input factors that are statistically dependent, we argue that a stress on one input should also precipitate stresses in other input factors. We introduce a novel sensitivity measure, termed cascade sensitivity, defined as a derivative of a risk measure applied on the output, in the direction of an input factor. The derivative is taken after suitably transforming the random vector of inputs, thus explicitly capturing the direct impact of the stressed input factor, as well as indirect effects via other inputs. Furthermore, alternative representations of the cascade sensitivity measure are derived, allowing us to address practical issues, such as incomplete specification of the model and high computational costs. The applicability of the methodology is illustrated through the analysis of a commercially used insurance risk model. [ABSTRACT FROM AUTHOR]