Casualty Insurance Research Articles

Comprehensive Analysis of Credit Risk Determinants in the Egyptian Property and Casualty Insurance Sector: Exploring Macroeconomic, Industrial, and Company Specific Factors

Comprehensive Analysis of Credit Risk Determinants in the Egyptian Property and Casualty Insurance Sector: Exploring Macroeconomic, Industrial, and Company Specific Factors

Enhanced gradient boosting for zero-inflated insurance claims and comparative analysis of CatBoost, XGBoost, and LightGBM

The property and casualty (P&C) insurance industry faces challenges in developing claim predictive models due to the highly right-skewed distribution of positive claims with excess zeros. To address this, actuarial science researchers have employed ‘zero-inflated’ models that combine a traditional count model and a binary model. This paper investigates the use of boosting algorithms to process insurance claim data, including zero-inflated telematics data, to construct claim frequency models. Three popular gradient boosting libraries - XGBoost, LightGBM, and CatBoost -- are evaluated and compared to determine the most suitable library for training insurance claim data and fitting actuarial frequency models. Through a comprehensive analysis of two distinct datasets, it is determined that CatBoost is the best for developing auto claim frequency models based on predictive performance. Furthermore, we propose a new zero-inflated Poisson boosted tree model, with variation in the assumption about the relationship between inflation probability p and distribution mean μ, and find that it outperforms others depending on the characteristics of the data. This model enables us to take advantage of particular CatBoost tools, which makes it easier and more convenient to investigate the effects and interactions of various risk features on the frequency model when using telematics data.

Impact of Hofstede’s cultural dimensions on insurance demand

Factors determining the demand for different types of insurance and consumer behaviours have been the subject of many studies. The analysed factors included cultural dimensions, i.e. certain aspects of culture that could be measured, which allows determining the position of a given culture in relation to others. However, the research results were very diverse, which motivated the authors to conduct their own research. The aim of the study discussed in the article was to verify the relationship between Hofstede’s cultural dimensions and insurance demand in selected European countries. It covered various types of insurance: life insurance, property and casualty insurance, motor insurance, general liability insurance and health insurance, as well as all types of insurance in total. The study used secondary data relating to 27 countries and the years 2004–2020 presented on the Insurance Europe and Geert Hofstede websites. Six Hofstede’s cultural dimension indices: the power distance index, individualism vs. collectivism, masculinity vs. femininity, the uncertainty avoidance index, longterm normative orientation vs. short-term normative orientation and indulgence vs. restraint, as well as insurance density (total premiums per inhabitant) were used as variables in the models. The research confirmed the lack of or a very weak relationship between most Hofstede’s cultural dimensions and the demand for insurance, except the indulgence dimension. The relationship between this factor and insurance demand proved significant, which is important not only from a methodological point of view (little interest devoted to this indicator in the literature), but also from a business perspective (e.g. from a marketing communication perspective).

Claim Reserves Estimation Using Chain Ladder Method in Casualty Insurance for the Period 2010 - 2019

In a work environment, the presence of risk or unforeseeable events is inevitable, as employees certainly seek to get a sense of security in doing work. Therefore, insurance is responsibility to provide sense of security to employees by providing protection in the form of claim payments to employees who get accidents. To meet the claim payment, insurance companies need to prepare funds. With the chain ladder method, insurance companies can estimate how much funds must be prepared to make claim payments. This study used the secondary data from general insurance companies in the United States published by the National Association of Insurance Commissioners under the title "Statistical Compilation of Annual Statement Information for Property/Casualty Insurance Companies in 2019". Data in the form of cumulative run-off triangle with accident period 2010-2019. Through this calculation, claim reserves that must be prepared by insurance companies for 2020 amounted to USD 1,553,906.

상해보험에서 인과관계와 증명책임

The ruling deals with a case in which a dead person is diagnosed with spinal disorders and dementia at a hospital after a fall, and the airway is blocked during a meal. He usually suffered from myocardial infarction. In this case, it became an issue that the evaluation of impairment of various hospitals conducted to judge the causal relation between the accident and the result of the disability and death of the insured in the casualty insurance contract joined by the plaintiff. In order to judge the disability caused by the disaster, the court of first instance designated one hospital and applied for a fact inquiry. The causal relation between the fall accident and the disability of the deceased was denied because of the result of the fact inquiry of the hospital and the dead person’s previous symptoms. The Court of Appeals and the Supreme Court accepted the judgment of the Court of First Instance. However, it is difficult to understand the judgment of the court that there is no causal relation between the fall accident and the disability without various evidence collection procedures. On the other hand, the first court and the appellate court ruled that there is a direct connection between the suffocation and death of the dead man, while the Supreme Court denied it and ordered the reversal. The opinions of the hospital and the National Forensic Service, which judged the cause of death of the deceased, were contradictory. In addition, the results of the fact-finding of two hospitals conducted during the proceedings were also contradictory. Nevertheless, the decision to conclude that the cause of death was suffocation in the lower court trial is not convincing. In this way, despite the fact that the results of fact-finding of various hospitals in relation to the disability and death of the deceased are incompatible with each other, it is beyond the limit of free evaluation of evidence that the court ruled without observing the empirical or logical laws and ignoring the evidence trial. Therefore, I am in favor of the Supreme Court's order of reversal on the death caused by the disaster of the lower court, but I am opposed to the acceptation of the lower court's decision on the claim for disability.

Measuring Systemic Risk: A Financial Statement-Based Approach for Insurance Firms and Banks

One of the important limitations of the SRISK measure of systemic risk, proposed by Brownlees and Engle and Acharya, Engle and Richardson, is its reliance on stock market data without much validation against the institutions’ fundamentals based on its financial statements. We propose a financial statement based approach to estimating the vulnerability of an institution to a systemic event (labeled CRISK). We illustrate our approach for three business models: a life insurer (Prudential), a property and casualty insurer (Chubb) and an investment bank (J.P. Morgan Chase). We also validate CRISK using AIG’s capital shortfall during the 2008 financial crisis. Our approach reveals that SRISK is likely to (i) overstate (misstate) capital requirements for life insurers (PC and (ii) to overstate capital requirements for banks heavily reliant on FDIC insured deposits. We recommend using the market based SRISK measure as a first cut filter to identify systemically important institutions. The analyst can refine the list and validate the expected capital shortfall number using CRISK or a detailed financial statement analysis of the kind we advocate in this paper.

US Property Casualty Insurers’ Responses to Mega Natural Disasters

US Property Casualty Insurers’ Responses to Mega Natural Disasters

Rank-Based Multivariate Sarmanov for Modeling Dependence between Loss Reserves

The interdependence between multiple lines of business has an important impact on determining loss reserves and risk capital, which are crucial for the solvency of a property and casualty (P&C) insurance company. In this work, we introduce the two-stage inference method using the Sarmanov family of multivariate distributions to the actuarial literature. In fact, we study rank-based methods using the Sarmanov distribution to adequately estimate the loss reserves and properly capture the dependence between lines of business. An inadequate choice of the dependence structure may negatively impact the estimation of the marginals and, hence, the reserve. Thus, we propose a two-stage inference strategy in this research to address this, while taking advantage of the flexibility of the Sarmanov distribution. We show that this strategy leads to a more robust estimation, and better captures the dependence between the risks. We also show that it generates smaller risk capital and a better diversification benefit. We extend the model to the multivariate case with more than two lines of business. To illustrate and validate our methods, we use three different sets of real data from both a major US property–casualty insurer and a large Canadian insurance company.

Foreign Ownership, Investor Attention and the Risk-Taking Behavior of Property and Casualty Insurance Firms: Evidence From Vietnam

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.

Measuring Interest Rate Risk Management by Financial Institutions

Financial intermediaries manage myriad interest rate risk exposures. We propose a new method to measure financial intermediaries' residual interest rate risk using high-frequency financial market data. Our method exploits all available high-frequency information and is valid under extremely weak assumptions. Applying the method to U.S. life insurers, we find their interest rate risk management strategies are generally effective. However, life insurers are more sensitive to changes in long-term interest rates than property and casualty insurers. We show that the term premium helps to explain the difference in sensitivities between the two types of insurer.

ESG, Taxes, and Profitability of Insurers

The growing concerns about sustainability urge insurance companies to implement Environmental, Social, and Governance (ESG) policies in order to remain competitive. All the three dimensions of corporate sustainability involve taxation; therefore, it is important to establish if this association reflects on financial performance. Our analysis of worldwide property and casualty (P&C) insurers during 2013–2022 reveals that high ESG insurers pay more taxes, while they are less profitable compared to low ESG insurers. This pattern is confirmed using instrumental variable regressions and simultaneous equations systems. We argue that sustainable insurers are less tempted to avoid taxes and do not shift their tax burdens onto policyholders and investors. However, the interplay between taxes and sustainability seems to harm insurers’ profitability, potentially having negative effects on investment and economic growth. This is an important insight for tax authorities and insurance managers.

Dependence Between Report Lag and Claim Amounts in Property and Casualty Insurance

Dependence Between Report Lag and Claim Amounts in Property and Casualty Insurance

Effects from ESG Scores on P&C Insurance Companies

Insurers act as institutional investors and underwriters of risk. Therefore, improving their environmental, social, and governance (ESG) performance is important for the transmission of ESG values to all economic sectors. We analyze ESG scores of worldwide Property and Casualty (P&C) insurers during 2013–2022 and show that more sustainable insurers have high operating leverage despite appearing to be financially stable from their combined ratios and z-scores. Additional results for the US subsample illustrate that stocks issued by sustainable insurers deliver positive excess returns. Overall, these findings suggest that there is a significant association between sustainable practices and the ability of insurers to execute business and create value. This is important for insurance managers, investors, and policy makers, as insurers play a prominent role in promoting economic growth and stability.

Storm CAT Bond: Modeling and Valuation

The frequency and intensity of weather-related catastrophes, such as storms and floods, have been increasing due to climate change. This leads to rising storm catastrophe risks to the property–casualty insurance and reinsurance sector. In this article, we propose an index-based storm catastrophe (CAT) bond for reinsurers to hedge catastrophe risks related to storm losses. Storm loss data have a large portion of zero values and a continuous positive right-skewed distribution, together with high-dimensional spatial dependence. We address these unique properties by proposing a general two-part autoregressive (2PAR) distribution as the marginal model and a semicontinuous spatiotemporal vine copula as the dependence model. We investigate the CAT bond market equilibrium and endogenously solve for the optimal market price of risk and coupon rates. Our empirical results using historical loss data at the county level in Florida show that the proposed CAT bond can stabilize the reinsurer’s cash flows and create attractive returns to investors by offering high coupon rates. Our framework can be generalized to design and price other catastrophe financing facilities.

Analyst coverage, executive compensation and corporate risk‐taking: Evidence from property–casualty insurance firms

AbstractUsing an exogenous drop in analyst coverage introduced by broker closures and mergers, we test for the causal impact of analyst coverage on corporate risk‐taking, in an opaque industry. We document an increase in risk using several book‐based and market‐based risk measures, including tail and default risk measures. Results are driven by firms with stronger managerial risk‐taking compensation incentives. The increase in risk is stronger in more opaque firms, and firms with weaker policyholder monitoring. Firm risk increases through at least one risk‐taking action, such as investing firm assets in higher‐risk bonds. Our study highlights the importance of stock analysts in affecting corporate risk‐taking, especially in the presence of stronger managerial, compensation risk‐taking incentives.

Improving the Accuracy and Performance of Deep Learning Model by Applying Hybrid Grey Wolf Whale Optimizer to P&C Insurance Data

The insurance industry is based on risk calculations, high profits, and detailed information. The predictive models that insurance companies utilize allow insurance companies to make accurate decisions about the insurance sector. This research focuses on improving the accuracy of predicting customers of Property and Casualty (P&C) insurance. In this study, a reliable quantitative analytical big data method has been developed, and the Hybrid Grey Wolf and Whale Optimization (HGWWO) is utilized with Deep Learning Model for evaluating customer behavior of the customers of P&C insurance. The research discussed the Hybrid Gray Wolf-Whale Optimization algorithm and the steps involved in the optimization process. This paper has presented the details of how to create a Grey Wolf Optimizer, Whale Optimizer and then combining both for initialization, evaluation, and optimization of the relevant P&C insurance dataset to improve the prediction accuracy. We have also compared the performance of the Deep Learning model with a few traditional machine learning models.

Underwriting Cycles in Property-Casualty Insurance: The Impact of Catastrophic Events

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.

Impact of Reinsurance Agreements on Assets and Liabilities Management of Property and Casualty Insurance Companies Applied in the Egyptian Insurance Market

Impact of Reinsurance Agreements on Assets and Liabilities Management of Property and Casualty Insurance Companies Applied in the Egyptian Insurance Market

Environmental Pollution Liability Insurance Pricing and the Solvency of Insurance Companies in China: Based on the Black-Scholes Model.

Environmental pollution liability insurance is becoming increasingly important for China to achieve its emission reduction targets. Insurance pricing is a crucial factor restricting the market share of environment pollution liability insurance, from the perspective of the Black-Scholes pricing model, which in turn has influenced the solvency of insurance companies in China. Firstly, this study analyzes the problems existing in compulsory liability insurance for environmental pollution in China. It proceeds with analyzing the price of compulsory environmental pollution liability insurance using the Black-Scholes pricing model, and derives a high premium insurance rate of 2.44%. Moreover, it performs a multivariate regression analysis using the asset and liability data, taken from the annual report, to identify three key factors affecting the solvency adequacy ratio, namely, capital debt ratio, reflecting the company asset structure; net interest rate on assets, reflecting the asset scale with actual solvency; and claim ratio, reflecting the business quality. Based on the results of regression analysis and robustness test for the China Insurance Clauses (CIC) company, People's Insurance Company of China (PICC), and Asia-Pacific Property & Casualty Insurance (API) company, it is shown that the effect of total asset, total debt, capital debt ratio, claim ratio, and net interest rate on assets on the solvency adequacy ratio is significant, with respect to the size of the coefficients. Based on the Black-Scholes pricing model found in the previous cycle of liability insurance, and keeping in view the existing problems of environmental pollution liability insurance expenditure, this paper presents suggestions that are conducive to improving the solvency of insurance companies in China.

Insuring a Sustainable Future: How Property and Casualty Insurers are Adapting to Net Zero

Insuring a Sustainable Future: How Property and Casualty Insurers are Adapting to Net Zero