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Life insurance --- Corporations --- Taxation

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This paper provides an analysis of ex post facto effects after the entry of foreign companies into the Vietnamese insurance market and argues that foreign competition has positively impacted the insurance industry based on evidence from Vietnam. Based on 16 years of data, the paper presents the main observations on the impact of international competition on the insurance market after Vietnam opened up to foreign investors. The results show that in Vietnam: after foreign penetration, local companies do not lose market share rapidly as liberation takes time; foreign insurers may dominate the domestic market, but if insurance penetration is low, this impact does not endanger the financial security of the country; the dominance of foreign insurers in the life sector could change the traditional insurance trajectory in emerging economies , which are traditionally oriented mostly on developing compulsory third-party liability insurance; foreign insurers make long-term contributions to the local economy if they invest in local capital markets. Thus, the paper argues that foreign competition has positively impacted the insurance industry based on evidence from Vietnam.

Access to Markets --- Competition --- Finance and Development --- Finance and Financial Sector Development --- Financial Development --- Foreign Ownership --- Insurance and Risk Mitigation --- Life Insurance

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"Loaded Dice: Race & Risk in the United States presents the historical relationship between statistical risk assessment and race in the United States. It illustrates how, through a reliance on the variable of race, actuarial science transformed the nature of racism and, in turn, helped usher racial disparities in wealth, incarceration, and housing from the nineteenth century into the twentieth. The monograph begins by investigating the development of statistical risk assessment explicitly based on race in the late-nineteenth-century life insurance industry. It then traces how such risk assessment migrated from industry to government, becoming a guiding force in sentencing and parole decisions and in federal housing policy. Finally, it concludes with an analysis of "proxies" for race-statistical variables that correlate significantly with race--in order to demonstrate the persistent presence of race in risk assessment even after the anti-discrimination regulations won by the Civil Rights Movement. Offering readers a new perspective on the historical importance of actuarial science in structural racism, Loaded Dice is a particularly timely contribution as Big Data and algorithmic decision making increasingly pervade American life"--

African Americans --- Risk assessment --- Race discrimination --- Actuarial science --- Life insurance --- African American criminals. --- Sentences (Criminal procedure) --- Noirs américains --- Évaluation du risque --- Discrimination raciale --- Relations interethniques --- Actuariat --- Assurance-vie --- Criminels noirs américains. --- Sentences (procédure pénale) --- Social conditions --- Economic conditions. --- Housing. --- Conditions sociales --- Conditions économiques. --- Logement. --- United States --- Race relations. --- United State --- African Americans - Social conditions - 1975 --- -African Americans - Economic conditions. --- Risk assessment - United States. --- Race discrimination - United States. --- Actuarial science - United States. --- African Americans - Housing. --- Life insurance - United States. --- Sentences (Criminal procedure) - United States. --- United State - Race relations.

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This book examines the challenges for the life insurance sector in Europe arising from new technologies, socio-cultural and demographic trends, and the financial crisis. It presents theoretical and applied research in all areas related to life insurance products and markets, and explores future determinants of the insurance industry’s development by highlighting novel solutions in insurance supervision and trends in consumer protection. Drawing on their academic and practical expertise, the contributors identify problems relating to risk analysis and evaluation, demographic challenges, consumer protection, product distribution, mortality risk modeling, applications of life insurance in contemporary pension systems, financial stability and solvency of life insurers. They also examine the impact of population aging on life insurance markets and the role of digitalization. Lastly, based on an analysis of early experiences with the implementation of the Solvency II system, the book provides policy recommendations for the development of life insurance in Europe.

Insurance. --- Macroeconomics. --- Actuarial science. --- Personal finance. --- Pension plans. --- Demography. --- Economic policy. --- Macroeconomics/Monetary Economics//Financial Economics. --- Actuarial Sciences. --- Personal Finance/Wealth Management/Pension Planning. --- Economic Policy. --- Economic nationalism --- Economic planning --- National planning --- State planning --- Economics --- Planning --- National security --- Social policy --- Historical demography --- Social sciences --- Population --- Vital statistics --- Finance, Personal --- Financial management, Personal --- Financial planning, Personal --- Personal finance --- Personal financial management --- Personal financial planning --- Finance --- Financial literacy --- Statistics --- Insurance --- Assurance (Insurance) --- Coverage, Insurance --- Indemnity insurance --- Insurance coverage --- Insurance industry --- Insurance protection --- Mutual insurance --- Underwriting --- Mathematics --- Life insurance --- Marketing. --- Insurance, Life --- Viatical settlements

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Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries’ “preferred methods” were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure.

History of engineering & technology --- deposit insurance --- implied volatility --- static arbitrage --- parameterization --- machine learning --- calibration --- dichotomous response --- predictive model --- tree boosting --- GLM --- validation --- generalised linear modelling --- zero-inflated poisson model --- telematics --- benchmark --- cross-validation --- prediction --- stock return volatility --- long-term forecasts --- overlapping returns --- autocorrelation --- chain ladder --- Bornhuetter–Ferguson --- maximum likelihood --- exponential families --- canonical parameters --- prior knowledge --- accelerated failure time model --- chain-ladder method --- local linear kernel estimation --- non-life reserving --- operational time --- zero-inflation --- overdispersion --- automobile insurance --- risk classification --- risk selection --- least-squares monte carlo method --- proxy modeling --- life insurance --- Solvency II --- claims prediction --- export credit insurance --- semiparametric modeling --- VaR estimation --- analyzing financial data --- n/a --- Bornhuetter-Ferguson