Impact Forecasting has developed a catastrophe flood model for Czechia to estimate insurance losses. The model is built on a dataset of 12,066 years of daily rainfall and temperature data for the European area, representing the current climate (LAERT...
This paper proposes a novel methodology, based on machine learning and statistical models, for predicting hurricane-related losses to specific assets. Our approach uses three critical storm parameters typically tracked by meteorological agencies: max...
This study examines the geographical spillover of the state-level average homeowners insurance cost for 48 US contiguous states. We estimate a panel spatial Durbin model with state and year fixed effect for data between 2001 and 2018. We found a sign...
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...
The Danish fire loss dataset records commercial fire losses under three insurance coverages: building, contents, and profits. Existing research has primarily focused on the heavy-tail behaviour of the losses but ignored the relationship among differe...
The development of quality control and risk management systems is a priority for any industry and especially for the corporate insurance industry. Defective product and work incidents represent 14% of the total number of insurance claims, serving as...
Our four-year interdisciplinary behavioral weight loss program is fully covered by public health insurance for patients with a body mass index of ≥35 kg/m2. We evaluated the real-world outcomes of anthropometric, metabolic and psychologic paramete...
The purpose of this study was mathematical model development for assessing the cost of losses from risks in the maritime transportation of goods that are dynamic in nature, and developing a methodical approach to the dynamic costs assessment for each...
Background: Patients with symptomatic abdominal tissue excess following massive weight loss (MWL) often experience skin affections associated with hygiene challenges, functional impairments, and psychological distress, all of which significantly impa...
In this paper, we examine the question of how to devise an optimal insurance claim settlement scheme under the constraint of a cap on the amount of the claim payment. We establish objective functions to maximize the net benefit due to exaggerated cla...
This paper analyzes how the agricultural insurance market is adapting to climate change, particularly as extreme weather events become more frequent and severe. We focus on the optimal decision faced by a risk-averse farmer who wants to insure their...
This study delves into a critical examination of the Size of Loss distribution patterns in the context of auto insurance during pre- and post-pandemics, emphasizing their profound influence on insurance pricing and regulatory frameworks. Through a co...
Occurrence of extreme natural events raises the need for a quick and accurate estimation of losses on the insured residential property in order to support timely recovery of the area. Although various models are now available to estimate the amount o...
We propose several numerical algorithms to compute the distribution of gross loss in a positively dependent catastrophe insurance portfolio. Hierarchical risk aggregation is performed using bivariate copula trees. Six common parametric copula familie...
Insurers typically argue that regulatory limits on their ability to use genetic tests will induce ‘adverse selection’; they say that this has disadvantages not just for insurers, but also for society as a whole. I argue that, even on its own terms, t...
Wind-induced loss modeling plays a key role in insurance risk management. Hence, a flexible vulnerability framework is to be developed for residential and commercial buildings. This model predicts the losses induced by hurricane wind pressure, wind-b...
This paper develops and implements an equilibrium model of systemic risk. The model derives a systemic risk measure, loss beta, in characterizing all too-big-to-fail banks using a capital insurance equilibrium. By constructing each bank’s loss portfo...
This article presents the Exponential–Generalized Inverse Gaussian regression model with varying dispersion and shape. The EGIG is a general distribution family which, under the adopted modelling framework, can provide the appropriate level of...
Bridges are important infrastructures for urban growth and the economic development of a country, because bridges allow a large volume of logistics and transportation by connecting rivers, canyons, islands and lands. As such, massive resources includ...
Actuaries are interested in modeling actuarial data using loss models that can be adopted to describe risk exposure. This paper introduces a new flexible extension of the log-logistic distribution, called the extended log-logistic (Ex-LL) distributio...
Despite the potential importance of crime rates in investments, there are no indices dedicated to evaluating the financial impact of crime in the United States. As such, this paper presents an index-based insurance portfolio for crime in the United S...
Energy resiliency has been thrust to the forefront by recent severe weather events and natural disasters. Billions of dollars are lost each year due to power outages. This article highlights the unique value renewable energy hybrid systems (REHS), co...
We compare two types of reinsurance: excess of loss (EOL) and largest claim reinsurance (LCR), each of which transfers the payment of part, or all, of one or more large claims from the primary insurance company (the cedant) to a reinsurer. The primar...
Given the highly visible nature, transportation infrastructure construction projects are often exposed to numerous unexpected events, compared to other types of construction projects. Despite the importance of predicting financial losses caused by ri...
Climate change poses significant risks to natural and economic environments, particularly through its interaction with air pollution. As agriculture is vital for national production, and crop insurance supports social security, it is crucial to exami...
Several distributions and families of distributions are proposed to model skewed data, e.g., with skew-normal and related distributions. Lambert W random variables offer an alternative approach in which, instead of constructing a new distribution, a...
In this paper we analyze insurance demand when the utility function depends both upon final wealth and the level of losses or gains relative to a reference point. Besides some comparative statics results, we discuss the links with first-order risk av...
We developed a methodology for the neural network boosting of logistic regression aimed at learning an additional model structure from the data. In particular, we constructed two classes of neural network-based models: shallow–dense neural netw...
The aggregation of individual risks into total risk using a weighting variable multiplied by two ratio variables representing incidence and intensity is an important task for risk professionals. For example, expected loss (EL) of a loan is the produc...
The hazard components of National Flood Insurance Program (NFIP) claims data in Florida were systematically analyzed and revised in the current study. The provided fields in NFIP claims data are not always complete or accurate and are often missing....
Stop-loss reinsurance is a risk management tool that allows an insurance company to transfer part of their risk to a reinsurance company. Ruin probabilities allow us to measure the effect of stop-loss reinsurance on the solvency of the primary insure...
17 March 2020
Whether exposure to air pollution is associated with developing sensorineural hearing loss (SHL) remains controversial. Using data from the National Health Insurance Research Database, we recruited a total of 75,767 subjects aged older than 20 years...
Due to the recent introduction of innovative construction methods and technologies, construction projects increasingly require sustainability in their high degrees of specialization and complex work processes. This is due to a wide variety of new ris...
The estimation of age-to-age development factors is fundamental to loss reserving, with direct implications for risk management and regulatory compliance in the auto insurance sector. The precise and robust estimation of these factors underpins the c...
This study addresses key challenges in auto insurance territory risk analysis by examining the complexities of spatial loss data and the evolving landscape of territorial risks before and during the COVID-19 pandemic. Traditional approaches, such as...
Agricultural crop insurance is an important component for mitigating farm risk, particularly given the potential for unexpected climatic events. Using a 2.8 million nationwide insurance claim dataset from the United States Department of Agriculture (...
Climate change increases extreme whether events such as floods, hailstorms, or storms, which can affect agriculture, causing damages and economic loss within the agro-food sector. Optical remote sensing data have been successfully used in damage dete...
In the presence of reinsurance, an insurer may effectively reduce its (aggregated) loss by partially ceding such a loss to a reinsurer. Stop-loss and quota-share reinsurance contracts are commonly agreed between these two parties. In this paper, we a...
This work presents a practical approach to improve risk quantification for heavy-tailed insurance claims through model averaging and grid map visualization, addressing the drawbacks of traditional single “best” model selection commonly us...
This paper investigates an optimal reinsurance policy using a risk model with dependent claim and insurance premium by assuming that the insurance premium is random. Their dependence structure is modeled using Sarmanov’s bivariate exponential d...
In this paper, we study the problem of misrepresentation under heavy-tailed regression models with the presence of both misrepresented and correctly-measured risk factors. Misrepresentation is a type of fraud when a policy applicant gives a false sta...
This paper discusses different classes of loss models in non-life insurance settings. It then overviews the class of Tukey transform loss models that have not yet been widely considered in non-life insurance modelling, but offer opportunities to prod...
The scope of this topic stems from the change in insurance companies and the subsequent transition to IFRS 17. The new code came into force on 1 January 2023. Therefore, the purpose of this article is to compare the two standards in terms of methodol...
Statistical models are crucial in analyzing insurance loss and claims data, offering insights into various risk elements. The prevailing statistical notion that “all models are wrong, but some are useful” can wield significant influence,...
Insurance pricing is the process of determining the premiums that policyholders pay in exchange for insurance coverage. In order to estimate premiums, actuaries use statistical based methods, assessing various factors such as the probability of certa...
To address the problems of traditional insurance compensation methods for flood losses, such as difficulty in determining losses, poor timeliness, a complicated compensation process and moral hazard, an urban flood index insurance tiered compensation...
This study explores the insurance pricing domain in the motor insurance industry, focusing on the creation of “technical models” which are essentially obtained after combining the frequency model (the expected number of claims per unit of...
This work estimates yield losses due to drought events in the mountain grasslands in north-eastern Italy, laying the groundwork for index-based insurance. Given the high correlation between the leaf area index (LAI) and grassland yield, we exploit th...
This study analyzes insurance claim data from an 11-county area in the Florida Panhandle following the landfall of Hurricane Michael. The data includes 1467 non-mobile home structures, with 902 (61.5%) storm-damaged structures in Bay County. The anal...
This systematic literature review (SLR) explores the role of community-based catastrophe insurance (CBCI) as a tool for sustainable economic loss risk mitigation. Utilizing bibliometric analysis and a literature review, this study aims to reveal the...
of 10