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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.

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.

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.

The development of the insurance market in the Irkutsk region is of great importance, as it is promising, has competitive advantages over other regions and is subject to various threats. However, at present, insurance in the region is not developed properly, and there are many problems that need to be solved. The purpose of the article is to study the development of the insurance market in the Irkutsk region and determine its prospects. The research method was based on General scientific and dialectical methods of cognition. Irkutsk region occupies a stable 17th place among 85 regions of the Republic in terms of insurance premiums. At the same time, it does not show any special qualitative changes. As a result of the research, the author came to the conclusion that the region needs its own development concept based on the risk map. It should unite insurers who now work separately, pursue only their own goals and do not think about the interests of the region. They do not participate in social projects and do not pay taxes to the regional budget. Another problem is that no one takes into account the opportunities of the low-income population and does not offer them affordable insurance products. It is necessary to develop business risk insurance, because the number of entrepreneurs themselves is growing. Agricultural insurance, which is almost non-existent, needs to be revived. As a result of the emergency that occurred in the summer in the Irkutsk region, a large number of households and people were affected by the flood, but many of them did not have insurance. The losses were compensated from the Federal budget. Thus, the development of insurance in the region will reduce the financial burden on the budgets of regions, municipalities and the country. So far, the regional authorities have not taken measures to support insurance in the region. Each recipient of an insurance service thinks about their own insurance protection.

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.

The development challenges of addressing health problems in low- and middle-income countries are daunting but not insurmountable. There are now known and affordable interventions to deal with many aspects of the HIV/AIDS crisis as well as the continued challenge posed by malaria and other major infectious diseases. Three major development objectives of health insurance in low- and middle income countries are highlighted in this volume: securing sustainable financing for health care providers that serve the health needs of vulnerable populations; providing financial protection against the impoverishing cost of illness; and reducing social exclusion from organized health financing and delivery systems. Private health insurance schemes can address the needs of the poor and other vulnerable populations with appropriate combinations of subsidies, risk pooling, household savings, and user charges. The authors of this book argue in favor of a multipillar approach to health care financing in low- and middle-income countries that combines these instruments in addressing the underlying development objectives described above, while putting a strong emphasis on private voluntary health insurance. In this way, private means can make a significant contribution to public ends.