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'Catastrophe Risk Financing in Developing Countries' provides a detailed analysis of the imperfections and inefficiencies that impede the emergence of competitive catastrophe risk markets in developing countries. The book demonstrates how donors and international financial institutions can assist governments in middle- and low-income countries in promoting effective and affordable catastrophe risk financing solutions. The authors present guiding principles on how and when governments, with assistance from donors and international financial institutions, should intervene in catastrophe insurance markets. They also identify key activities to be undertaken by donors and institutions that would allow middle- and low-income countries to develop competitive and cost-effective catastrophe risk financing strategies at both the macro (government) and micro (household) levels. These principles and activities are expected to inform good practices and ensure desirable results in catastrophe insurance projects. 'Catastrophe Risk Financing in Developing Countries' offers valuable advice and guidelines to policy makers and insurance practitioners involved in the development of catastrophe insurance programs in developing countries.

Specialist groups have often advised health ministers and other decision makers in developing countries on the use of social health insurance (SHI) as a way of mobilizing revenue for health, reforming health sector performance, and providing universal coverage. This book reviews the specific design and implementation challenges facing SHI in low- and middle-income countries and presents case studies on Ghana, Kenya, Philippines, Colombia, and Thailand.

Type of the article: Theoretical Article AbstractThe functioning of insurance markets during prolonged military conflict remains insufficiently explored in contemporary insurance and risk management literature. The purpose of this study is to develop and apply the Insurance Market Wartime Resilience Index (IMWRI) for assessing insurance market resilience under conditions of military conflict. The empirical calibration combines indicators from both the non-life and life insurance segments; however, the dominant contribution comes from non-life insurance data. Consequently, the resulting IMWRI should be interpreted as a market-wide resilience measure with a stronger sensitivity to developments in the non-life segment. The proposed IMWRI integrates five dimensions of wartime insurance market functioning: premium resilience, claims functionality, reinsurance support, solvency and financial stability, and market structure adaptation. The empirical results demonstrate that the Ukrainian insurance market produces an approximate IMWRI value of 67.9%. The largest contributions are generated by premium resilience (0.2625) and solvency and financial stability (0.2325), followed by market structure and concentration (0.0893) and claims functionality (0.0780). The smallest contribution is provided by reinsurance support (0.0165). This distribution suggests that wartime insurance resilience in Ukraine is driven primarily by internal market capacity and financial stability rather than by external risk-transfer mechanisms. The proposed IMWRI confirms that resilience is generated through a combination of financial stability, premium continuity, institutional adaptation, and selective risk transfer. Therefore, the future development of wartime insurance systems depends not only on strengthening insurers themselves but also on building integrated public-private risk-sharing mechanisms capable of narrowing the gap between market resilience and protection needs.

Private voluntary health insurance already plays an important role in the health sector of many low and middle income countries.The book reviews the context under which private insurance could contribute to an improvement in the financial sustainability of the health sector, financial protection against the costs of illness, household income.

Health care expenditures can be financed through a mix of public resources and private spending. Private spending is a much larger share of total health spending in low- and middle-income countries than in higher income countries. Moreover, a significant percentage of private spending in those countries is out-of-pocket direct payments for health care services by individuals. Out of pocket expenditures account for more than 60 percent of the total health care spending in low-income countries and 40 percent of total health care spending in middle-income countries. A growing number of low- and middle-income governments are considering private health insurance as a way of both reducing the risk that individuals will have a catastrophic financial burden and achieving other public health care goals. Among these goals are reducing the financial burden on overstretched public health financing, achieving more equitable access to health care, and improving quality and efficiency in the delivery of health care services. An important component of a successful private health insurance market, however, is its legal framework. As discussed in detail later in this book, countries regulate insurance companies to counter systemic market failures that lead to an inefficient and inequitable market. In particular, insurance laws are designed to prevent insurers from becoming insolvent and from engaging in unfair practices and discriminatory behavior. When private health insurance serves as a significant source of financing in a nation's health care system, usually insurance laws also include a range of consumer protection laws that enhance both access to the services covered by private health insurers and the adequacy of the benefits provided by the insurer. This chapter provides a general overview of private health insurance. It begins with a discussion of the definition of private health insurance and the potential roles of private health insurance as part of a nation's health care financing system. In addition, the chapter reviews the variety of entities that sell private health insurance

The article applies a scientific-methodical approach to the taxation of insurers' incomes in order to achieve an optimal balance between the revenue base of the budget and the minimization of budget risks. Empirical measurement of relationships between the financial results of insurers and tax regulation of their activities using economic models and mathematical apparatus made it possible to develop the latest financial decision-making tools based on the Census II method. These tools contribute to the formation of the tax base (income after insurance activities) from the point of view of minimizing the impact of budgetary risks on the level of state budget revenues. The foundation of the developed scientific-methodological approach is the algorithm of actions for determining the actual deviation of the tax base from the calculated trend cycle. This allows us to minimize the risk of not receiving budget revenues and create multiple scenarios of resilience to the influence of external factors.The proposed approach makes it possible to produce alternative financial decisions regarding the choice of the taxation mechanism of domestic insurers in order to minimize budgetary risks. The practical significance of the obtained results is revealed in the developing theoretical and methodological provisions and outlined methodological approaches in practical activities, which justify the optimal choice of the tax base of insurance companies with the lowest level of variability, taking into account the influence of exogenous processes in a dynamic market background. This will form prerogatives to minimize the risk of not receiving budget revenues. It has been empirically proven that the specified scientific-methodical approach will contribute to the optimization of the insurance business taxation process, ensuring a balance between the interests of the state and all participants in this market.

Introduction/Main Objectives: This study explores the application of machine-learning techniques to risk-based premium calculations for insurance guarantee schemes within the Indonesian insurance market. This study aims to develop a risk-based premium calculation model using machine-learning techniques in the Indonesian context. Background Problems: A gap exists in determining risk-based premiums for both the life and non-life insurance sectors within the Indonesian insurance market. Identifying and understanding the key variables that significantly influence risk-based capital (RBC) is important, and this research addresses this need. Novelty: This paper is the first to apply machine learning to calculate risk-based premiums in the context of the Indonesian insurance market. The distinction between the life and non-life insurance sectors in terms of the importance of its variables and itsselection of an optimal model further enrich its unique approach. Research Methods: We employed gradient-boosted and decision-tree models to identify key factors impacting risk-based capital. Furthermore, we leveraged clustering techniques to categorize companies into distinct risk tiers, aiming to enable more precise risk-based premium rate calculations. Finding/Results: The findings reveal significant differences between the life and non-life insurance sectors in terms of key variables that impact their risk-based capital. These insights lead to the categorization of insurance companies into distinct risk tiers whichhelps to more accurately calculate risk-based premiums. Conclusion: Machine learning can serve as a powerful tool in refining insurance risk management practices, ultimately benefiting insurers, policyholders, and regulators alike.

Most analyses of insurance market failures have been implemented in a one-period (static) setting, with considerably less attention devoted to problems arising in a multi-period (dynamic) context. In a dynamic framework, risk-averse individuals benefit not only from period-by-period \"event\" insurance, but also from insurance against becoming a bad risk and begin reclassified into a higher-risk group with a concomitant increase in premiums. We refer to this latter possibility as \"reclassification risk.\" This article examines the private market for long-term care insurance in the US and present empirical evidence suggesting that it does not provide full insurance against reclassification risk.

Objective: The objective of the article is to examine the relationship between insurance market share and the financial results of insurance companies. We formulated the following research question: Is an insurance com- pany’s market position (market share) influenced by its financial results? If so, which ones?Research Design Methods: The scope of research covers insurance companies operating in the insurance markets of the EU-15 countries. We surveyed the insurance companies with the largest market share. The research period covered the years 2012-2021. We compiled the data on the insurance markets of the EU-15 countries based on the OECD Statistics database and the financial data characterising the insurance companies selected for the study – based on the ORBIS Database. We used STATISTICA 13 and GRETL software to compile the survey results. We used the method of analysis of scientific literature – domestic and foreign, statistical and econometric methods and own observations.Findings: The research has made it possible to answer the research questions. Financial results influence the market position of an insurance company. This means that financial performance was one of the determinants of an insurance company’s market position. This is indicated both by the analysis of the literature on the subject, where some studies confirm the existence of a relation between market position, measured by insurance market share, and the financial results of insurance companies and by our research covering the EU-15 insurance market. Implications Recommendations: The research conducted will serve insurance companies and insurance market institutions – in financial management strategies, as well as by policyholders and beneficiaries of in- surance contracts, i.e. consumers – in consumer decision-making.Contribution Value Added: The study fills a research gap in the determinants of the efficiency of insurance companies and, in particular, the issue of the relation between the market share of a single operator and its financial results. They also contribute to the development of research in insurance finance falling within the discipline of economics and finance. The study of a homogeneous group of insurance companies – with the largest share in a given national market – as well as the study of the insurance market of the EU-15 countries, which should be considered stable with an established market structure, should be regarded as innovative.