Convective Storms and the Insurance Industry: Challenges and Opportunities

Convective storms affect countries worldwide, with billions in losses and dozens of fatalities every year. They are now the key insured loss driver in the United States, even after considering the losses sustained by tropical cyclones in 2017. Since 2008, total insured losses from convective storms have exceeded $10 billion per year. Additionally, these losses continue to increase year over year. Key loss drivers include increased population, buildings, vehicles, and property values. However, other loss drivers relate to construction materials and practices, as well as building code adoption and enforcement. The increasing loss trends pose a number of challenges for the insurance industry and broader society. These challenges are discussed, and some recommendations are presented.

SUBROGATION IN INSURANCE CONTRACT

Subrogation is a legal right characteristically reserved by property insurers. Subrogation occurs in property insurance and in some particular cases of liability insurance. The doctrine of subrogation operates to ensure protection of certain specific principles relevant to the property insurance including the principle of indemnification whereby the compensation received is no more and no less than a full indemnity for the insured loss or damage suffered by the insured due to loss occurrence, the principle of non-cumulation in terms of claims under the same insurance contract and the principle which excludes claiming indemnity from the person who is legally responsible for causing the loss, because otherwise the insurance contract may be an unjustified source of profit for the insured as the insured would get double recovery or paid out twice for the same claim.With the payment of the reimbursement from an insurance agreement on the insurer, all rights that the insured has towards the persons responsible for the damage up to the amount of the paid compensation are transferred. With the subrogation, the insurer takes up the legal position of the insured person and exercises his right to subrogation from the rights of the insured (derivative acquisition of the right), so that the insurer exceeds the claims in scope and amount as the insured had towards the perpetrator.Subrogation is the right of the insurer, it is not his obligation. The insurer is not obliged to use this right to transfer the rights to the responsible person.The notion of subrogation is often associated with the concept of insurance regression. But there is a difference between these two terms: recourse is the right of the insurer to claim the amount of compensation that he has paid to the insured (injured parties) from the harmful person, while subrogation is the transfer of the right (the claim for damages to the responsible person) from the insured to the insurer up to the amount of the compensation paid on the basis of an insurance contract. The right to recourse is a consequence of the existence of subrogation, i.e. transfer of the rights of the insured person to the responsible person, and which is reached by the law itself.Тhe subrogation doctrine also operates to ensure that the defendant or the person who is legally responsible for the loss shall not be absolved of liability under the civil law. Namely, the perpetrator should bear the consequences of his liability for the caused damage, and therefore the legislator of the insurer (as one of the contractual parties in insurance contract) has recognized the right what he has paid the injured party (as the contractual party in the insurance contract called the insured) to calm from the perpetrator.Furthermore, subrogation doctrine operates to ensure profit for the insurance companies whereby the reimbursement funds the claims or sum insured are covered from additionally grow; therefore, this doctrine is of great importance to the insurers.

Exploring inter-organizational paradoxes: Methodological lessons from a study of a grand challenge

In this article, we outline a methodological framework for studying the inter-organizational aspects of paradoxes and specify this in relation to grand challenges. Grand challenges are large-scale, complex, enduring problems that affect large populations, have a strong social component and appear intractable. Our methodological insights draw from our study of the insurance protection gap, a grand challenge that arises when economic losses from large-scale disaster significantly exceed the insured loss, leading to economic and social hardship for the affected communities. We provide insights into collecting data to uncover the paradoxical elements inherent in grand challenges and then propose three analytical techniques for studying inter-organizational paradoxes: zooming in and out, tracking problematization and tracking boundaries and boundary organizations. These techniques can be used to identify and follow how contradictions and interdependences emerge and dynamically persist within inter-organizational interactions and how these shape and are shaped by the unfolding dynamics of the grand challenge. Our techniques and associated research design help advance paradox theorizing by moving it to the inter-organizational and systemic level. This article also illustrates paradox as a powerful lens through which to further our understanding of grand challenges.

Tornado Damage Mitigation: Benefit–Cost Analysis of Enhanced Building Codes in Oklahoma

In April 2014, the city of Moore, Oklahoma, adopted enhanced building codes designed for wind-resistant construction. This action came after Moore suffered three violent tornadoes in 14 yr. Insured loss data and a rigorous approach to estimating how much future damage can be mitigated is used to conduct a benefit–cost analysis of the Moore standards applied to the entire state of Oklahoma. The results show that the new codes easily pass the benefit–cost test for the state of Oklahoma by a factor of 3 to 1. Additionally, a sensitivity analysis is conducted on each of the five input variables to identify the threshold where each variable causes the benefit–cost test to fail. Variables include the estimate of future losses, percent of damage that can be reduced, added cost, residential share of overall losses, and the discount rate.

Predicting the Texas Windstorm Insurance Association claim payout of commercial buildings from Hurricane Ike

Following growing public awareness of the danger from hurricanes and tremendous demands for analysis of loss, many researchers have conducted studies to develop hurricane damage analysis methods. Although researchers have identified the significant indicators, there currently is no comprehensive research for identifying the relationship among the vulnerabilities, natural disasters, and economic losses associated with individual buildings. To address this lack of research, this study will identify vulnerabilities and hurricane indicators, develop metrics to measure the influence of economic losses from hurricanes, and visualize the spatial distribution of vulnerability to evaluate overall hurricane damage. This paper has utilized the Geographic Information System to facilitate collecting and managing data, and has combined vulnerability factors to assess the financial losses suffered by Texas coastal counties. A multiple linear regression method has been applied to develop hurricane economic damage predicting models. To reflect the pecuniary loss, insured loss payment was used as the dependent variable to predict the actual financial damage. Geographical vulnerability indicators, built environment vulnerability indicators, and hurricane indicators were all used as independent variables. Accordingly, the models and findings may possibly provide vital references for government agencies, emergency planners, and insurance companies hoping to predict hurricane damage.

The Australian Great Flood of 1954: Estimating the Cost of a Similar Event in 2011

As in many other parts of the globe, migration to the coast and rapid regional development in Australia is resulting in large concentrations of population and insured assets. One of the most rapidly growing regions is southeastern Queensland and northern New South Wales, an area prone to flooding. This study reexamines the Great Flood of 1954 and develops a deterministic methodology to estimate the likely cost if a similar event had occurred in 2011. This cost is estimated using council flood maps, census information, historical observations, and Risk Frontiers' proprietary flood vulnerability functions. The 1954 flood arose from heavy rainfall caused by the passage of a tropical cyclone that made landfall on 20 February near the Queensland–New South Wales border, before heading south. Responsible for some of the largest floods on record for many northern New South Wales' river catchments, it occurred prior to the availability of reliable insurance statistics and the recent escalation in property values. The lower-bound estimate of the insurance loss using current exposure and assuming 100% insurance penetration for residential buildings and contents is AU$3.5 billion, a cost that would make it the third-highest ranked insured loss due to an extreme weather event since 1967. The corresponding normalized economic loss is AU$7.6 billion but the uncertainty about this figure is high. The magnitude of these losses reflects the accumulation of exposure on the floodplains. Risk-informed land-use planning practices and improved building regulations hold the key to reducing future losses.

Major Growth in Some Business-Related Uses of Climate Information

Uses of climate information have grown considerably in the past 15 years as a wide variety of weather-sensitive businesses sought to deal effectively with their financial losses and manage risks associated with various weather and climate conditions. Availability of both long-term quality climate data and new technologies has facilitated development of climate-related products by private-sector atmospheric scientists and decision makers. Weather derivatives, now widely used in the energy sector, allow companies to select a financially critical seasonal weather threshold, and, for a price paid to a provider, to obtain financial reparation if this threshold is exceeded. Another new product primarily used by the insurance industry is weather-risk models, which define the potential risks of severe-weather losses across a region where few historical insured loss data exist. Firms develop weather-risk models based on historical storm information combined with a target region’s societal, economic, and physical conditions. Examples of the derivatives and weather-risk models and their uses are presented. Atmospheric scientists who want to participate in the development and use of these new risk-management products will need to broaden their educational experience and develop knowledge and skills in fields such as finance, geography, economics, statistics, and information technology.