This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus.

Mortality improvements, uncertainty in future mortality trends and the relevant impact on life annuities and pension plans constitute important topics in the field of actuarial mathematics and life insurance techniques. In particular, actuarial calculations concerning pensions, life annuities and other living benefits (provided, for example, by long-term care insurance products and whole life sickness covers) are based on survival probabilities which necessarily extend over a long time horizon. In order to avoid underestimation of the related liabilities, the insurance company (or the pension plan) must adopt an appropriate forecast of future mortality.
Great attention is currently being devoted to the management of life annuity portfolios, both from a theoretical and a practical point of view, because of the growing importance of annuity benefits paid by private pension schemes. In particular, the progressive shift from defined benefit to defined contribution pension schemes has increased the interest in life annuities with a guaranteed annual amount.
This book provides a comprehensive and detailed description of methods for projecting mortality, and an extensive introduction to some important issues concerning longevity risk in the area of life annuities and pension benefits. It relies on research work carried out by the authors, as well as on a wide teaching experience and in CPD (Continuing Professional Development) initiatives. The following topics are dealt with: life annuities in the framework of post-retirement income strategies; the basic mortality model; recent mortality trends that have been experienced; general features of projection models; discussion of stochastic projection models, with numerical illustrations; measuring and managing longevity risk.

This book encourages insurance companies and regulators to explore offering Islamic insurance to boost the insurance industry in India. The distinctive features of Takaful also make it appealing even to non-Muslims. According to the 2012 World Takaful Report, India has immense potential for Takaful is based on the size of its Muslim population and the growth of its economy. However, it is surprising that Takaful has yet to be introduced in India since it has been offered in non-majority Muslim countries, such as Singapore, Thailand, and Sri Lanka. When the concept and practice of Takaful are examined, it is free from interest, uncertainty, and gambling. These are the main elements prohibited in Islam. However, it has been evidenced that these elements are also banned in teaching other religions believed by the Indians. Given this landscape, this book fills the gap in research on the viability of Takaful in India, focusing on its empirical aspects by examining the perception of Indian insurance operators toward Takaful.

Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science, and finance. The book builds on students' existing knowledge of probability and statistics by establishing a solid and thorough understanding of these methods. It also emphasizes the wide variety of practical situations in insurance and actuarial science where these techniques may be used.

Although some chapters are linked, several can be studied independently from the others. The first chapter introduces claims reserving via the deterministic chain ladder technique. The next few chapters survey loss distributions, risk models in a fixed period of time, and surplus processes, followed by an examination of credibility theory in which collateral and sample information are brought together to provide reasonable methods of estimation. In the subsequent chapter, experience rating via no claim discount schemes for motor insurance provides an interesting application of Markov chain methods. The final chapters discuss generalized linear models and decision and game theory.

Developed by an author with many years of teaching experience, this text presents an accessible, sound foundation in both the theory and applications of actuarial science. It encourages students to use the statistical software package R to check examples and solve problems.

This book sets out in a clear and concise manner the central principles of insurance law in the Caribbean, guiding students through the complexities of the subject. This book features, among several other key themes, extensive coverage of: insurance regulation; life insurance; property insurance; contract formation; intermediaries; the claims procedure; and analysis of the substantive laws of several jurisdictions. Commonwealth Caribbean Insurance Law is essential reading for LLB students in Caribbean universities, students in CAPE Law courses, and practitioners.

This book, the second one of three volumes, gives practical examples by a number of use cases showing how to take first steps in the digital journey of banks and insurance companies. The angle shifts over the volumes from a business-driven approach in "Disruption and DNA" to a strong technical focus in "Data Storage, Processing and Analysis", leaving "Digitalization and Machine Learning Applications" with the business and technical aspects in-between. This second volume mainly emphasizes use cases as well as the methods and technologies applied to drive digital transformation (such as processes, leveraging computational power and machine learning models).

The market is like the sea: it gives, and it takes away. That became apparent once again when the economy and society went into "lockdown" due to the coronavirus outbreak. Organizations will either sink or swim, and only the pros will be able to keep their heads above water. This is a self-help book for managers, supervisors and administrators who see themselves as skippers at the helm of an organization in times of turbulence, uncertainty and complexity. It provides a number of the latest handy management models, such as the Three-Phase Model, Governance Model and Management Matrix, which help leaders and managers arrive at well thought-out risk management decisions. In addition, the practical cases and discussion questions in each chapter help readers implement these models in their organizations. The book is an English translation of the Dutch book 'Varen in de mist', which was nominated for the Dutch Management Book of the Year.

This book begins with the fundamental large sample theory, estimating ruin probability, and ends by dealing with the latest issues of estimating the Gerber-Shiu function. This book is the first to introduce the recent development of statistical methodologies in risk theory (ruin theory) as well as their mathematical validities. Asymptotic theory of parametric and nonparametric inference for the ruin-related quantities is discussed under the setting of not only classical compound Poisson risk processes (Cramer-Lundberg model) but also more general Levy insurance risk processes. The recent development of risk theory can deal with many kinds of ruin-related quantities: the probability of ruin as well as Gerber-Shiu's discounted penalty function, both of which are useful in insurance risk management and in financial credit risk analysis. In those areas, the common stochastic models are used in the context of the structural approach of companies' default. So far, the probabilistic point of view has been the main concern for academic researchers. However, this book emphasizes the statistical point of view because identifying the risk model is always necessary and is crucial in the final step of practical risk management.

Why do people buy health insurance? Conventional theory holds that people purchase insurance because they prefer the certainty of paying a small premium to the risk of getting sick and paying a large medical bill. Conventional theory also holds that any additional health care that consumers purchase because they have insurance is not worth the cost of producing it. Therefore, economists have promoted policies--copayments and managed care--to reduce consumption of this additional, seemingly low-value care.
This book presents a new theory of consumer demand for health insurance. It holds that people purchase insurance to obtain additional income when they become ill. In effect, insurance companies act to transfer insurance premiums from those who remain healthy to those who become ill. This additional income generates purchases of additional high-value care, often allowing sick persons to obtain life-saving care that they could not otherwise afford.
Regarding risk, the new theory relies on empirical studies showing that consumers actually prefer the risk of a large loss to incurring a smaller loss with certainty. Therefore, if consumers purchase insurance, it is not because they desire to avoid risk. Instead, the new theory suggests consumers simply pay a premium when healthy in exchange for a claim on additional income (effected when insurance pays for the medical care) if they become ill.
Health insurance is substantially more valuable to the consumer under the new theory. The new theory moreover implies that copayments and managed care--central health policies of the last 30 years--were directed at solving problems that largely did not exist. Because these policies either reduced the amount of income transferred to ill persons or limited access to valuable health care, they may have done more harm than good. The new theory also provides a solid theoretical justification for insuring the uninsured and for implementing national health insurance.

A New York Times bestseller/Washington Post Notable Book of 2017/NPR Best Books of 2017/Wall Street Journal Best Books of 2017 "This book will serve as the definitive guide to the past and future of health care in America."-Siddhartha Mukherjee, Pulitzer Prize-winning author of The Emperor of All Maladies and The Gene At a moment of drastic political upheaval, An American Sickness is a shocking investigation into our dysfunctional healthcare system - and offers practical solutions to its myriad problems. In these troubled times, perhaps no institution has unraveled more quickly and more completely than American medicine. In only a few decades, the medical system has been overrun by organizations seeking to exploit for profit the trust that vulnerable and sick Americans place in their healthcare. Our politicians have proven themselves either unwilling or incapable of reining in the increasingly outrageous costs faced by patients, and market-based solutions only seem to funnel larger and larger sums of our money into the hands of corporations. Impossibly high insurance premiums and inexplicably large bills have become facts of life; fatalism has set in. Very quickly Americans have been made to accept paying more for less. How did things get so bad so fast? Breaking down this monolithic business into the individual industries-the hospitals, doctors, insurance companies, and drug manufacturers-that together constitute our healthcare system, Rosenthal exposes the recent evolution of American medicine as never before. How did healthcare, the caring endeavor, become healthcare, the highly profitable industry? Hospital systems, which are managed by business executives, behave like predatory lenders, hounding patients and seizing their homes. Research charities are in bed with big pharmaceutical companies, which surreptitiously profit from the donations made by working people. Patients receive bills in code, from entrepreneurial doctors they never even saw. The system is in tatters, but we can fight back. Dr. Elisabeth Rosenthal doesn't just explain the symptoms, she diagnoses and treats the disease itself. In clear and practical terms, she spells out exactly how to decode medical doublespeak, avoid the pitfalls of the pharmaceuticals racket, and get the care you and your family deserve. She takes you inside the doctor-patient relationship and to hospital C-suites, explaining step-by-step the workings of a system badly lacking transparency. This is about what we can do, as individual patients, both to navigate the maze that is American healthcare and also to demand far-reaching reform. An American Sickness is the frontline defense against a healthcare system that no longer has our well-being at heart.

Insurance Economics brings together the economic analysis of decision making under risk, risk management and demand for insurance among individuals and corporations, objectives pursued and management tools used by insurance companies, the regulation of insurance, and the division of labor between private and social insurance. Appropriate both for advanced undergraduate and graduate students of economics, management, and finance, this text provides the background required to understand current research. Predictions derived from theoretical arguments are not merely stated, but also related to empirical evidence. Throughout the book, conclusions summarize key results, helping readers to check their knowledge and comprehension. Issues discussed include paradoxes in decision making under risk and attempts at their resolution, moral hazard and adverse selection including the possibility of a "death spiral", and future challenges to both private and social insurance such as globalization and the availability of genetic information. This second edition has been extensively revised. Most importantly, substantial content has been added to represent the evolution of risk-related research. A new chapter, Insurance Demand II: Nontraditional Approaches, provides a timely addition in view of recent developments in risk theory and insurance. Previous discussions of Enterprise Risk Management, long-term care insurance, adverse selection, and moral hazard have all been updated. In an effort to expand the global reach of the text, evidence and research from the U.S. and China have also been added.

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.

This open access book collects expert contributions on actuarial modelling and related topics, from machine learning to legal aspects, and reflects on possible insurance designs during an epidemic/pandemic. Starting by considering the impulse given by COVID-19 to the insurance industry and to actuarial research, the text covers compartment models, mortality changes during a pandemic, risk-sharing in the presence of low probability events, group testing, compositional data analysis for detecting data inconsistencies, behaviouristic aspects in fighting a pandemic, and insurers' legal problems, amongst others. Concluding with an essay by a practicing actuary on the applicability of the methods proposed, this interdisciplinary book is aimed at actuaries as well as readers with a background in mathematics, economics, statistics, finance, epidemiology, or sociology.

This book presents a consistent and complete framework for studying the risk management of a pension fund. It gives the reader the opportunity to understand, replicate and widen the analysis. To this aim, the book provides all the tools for computing the optimal asset allocation in a dynamic framework where the financial horizon is stochastic (longevity risk) and the investor's wealth is not self-financed. This tutorial enables the reader to replicate all the results presented. The R codes are provided alongside the presentation of the theoretical framework. The book explains and discusses the problem of hedging longevity risk even in an incomplete market, though strong theoretical results about an incomplete framework are still lacking and the problem is still being discussed in most recent literature.

This Volume of the AIDA Europe Research Series on Insurance Law and Regulation focuses on transparency as the guiding principle of modern insurance law. It consists of chapters written by leaders in the respective field, who address transparency in a range of civil and common law jurisdictions, along with overview chapters. Each chapter reviews the transparency principles applicable in the jurisdiction discussed. Whether expressly or impliedly, all jurisdictions recognize a duty on the part of the insured to make a fair presentation of the risk when submitting a proposal for cover to the insurers, although there is little consensus on the scope of that duty. Disputed matters in this regard include: whether it is satisfied by honest answers to express questions, or whether there is a spontaneous duty of disclosure; whether facts relating to the insured's character, as opposed to the nature of the risk itself, are to be presented to the insurers; the role of insurance intermediaries in the placement process; and the remedy for breach of duty. Transparency is, however, a much wider concept. Potential policyholders are in principle entitled to be made aware of the key terms of coverage and to be warned of hidden traps (such as conditions precedent, average clauses and excess provisions), but there are a range of different approaches. Some jurisdictions have adopted a "soft law" approach, using codes of practice for pre-contract disclosure, while other jurisdictions employ the rather nebulous duty of (utmost) good faith. Leaving aside placement, transparency is also demanded after the policy has been incepted. The insured is required to be transparent during the claims process. There is less consistency in national legislation regarding the implementation of transparency by insurers in the context of handling claims.

Modern risk management as practiced today faces significant obstacles-we argue-primarily due to the fundamental premise of the concept itself. It asserts that we are mainly dealing with measurable, quantifiable risks and that we can manage the uncontrollable by relying on formal control-based systems, which has produced a general view that (enterprise) risk management is a technical-scientific discipline. Strategic Risk Leadership offers a critique of the status quo, and encourages leaders, executives, and chief risk officers to find fresh approaches that can help them deal more proactively with what the future may hold. The book provides an overview of the history of risk management and current risk governance approaches as prescribed by leading risk management standards, such as COSO and ISO31000. This enables practitioners to challenge the frameworks and improve their adoption in practice introducing sustainable resilience as a (more) meaningful response to uncertain and unknowable conditions. The book shows how traditional thinking downplays the significance of human behavior and judgmental biases as key elements of major organizational exposures illustrated and explained through numerous case examples and studies. This book is essential reading for strategic risk managers to understand the requirements for effective risk governance practices in the contemporary and rapidly changing global risk landscape. Indeed, it is a valuable resource for all risk executives, leaders, and chief risk officers, as well as advanced students of risk management.

This book is devoted to the mathematical methods of metamodeling that can be used to speed up the valuation of large portfolios of variable annuities. It is suitable for advanced undergraduate students, graduate students, and practitioners. It is the goal of this book to describe the computational problems and present the metamodeling approaches in a way that can be accessible to advanced undergraduate students and practitioners. To that end, the book will not only describe the theory of these mathematical approaches, but also present the implementations.

The increasing complexity of insurance and reinsurance products has seen a growing interest amongst actuaries in the modelling of dependent risks. For efficient risk management, actuaries need to be able to answer fundamental questions such as: Is the correlation structure dangerous? And, if yes, to what extent? Therefore tools to quantify, compare, and model the strength of dependence between different risks are vital. Combining coverage of stochastic order and risk measure theories with the basics of risk management and stochastic dependence, this book provides an essential guide to managing modern financial risk.
* Describes how to model risks in incomplete markets, emphasising insurance risks.
* Explains how to measure and compare the danger of risks, model their interactions, and measure the strength of their association.
* Examines the type of dependence induced by GLM-based credibility models, the bounds on functions of dependent risks, and probabilistic distances between actuarial models.
* Detailed presentation of risk measures, stochastic orderings, copula models, dependence concepts and dependence orderings.
* Includes numerous exercises allowing a cementing of the concepts by all levels of readers.
* Solutions to tasks as well as further examples and exercises can be found on a supporting website.
An invaluable reference for both academics and practitioners alike, Actuarial Theory for Dependent Risks will appeal to all those eager to master the up-to-date modelling tools for dependent risks. The inclusion of exercises and practical examples makes the book suitable for advanced courses on risk management in incomplete markets. Traders looking for practical advice on insurance markets will also find much of interest.

This textbook provides a broad overview of the present state of insurance mathematics and some related topics in risk management, financial mathematics and probability. Both non-life and life aspects are covered. The emphasis is on probability and modeling rather than statistics and practical implementation. Aimed at the graduate level, pointing in part to current research topics, it can potentially replace other textbooks on basic non-life insurance mathematics and advanced risk management methods in non-life insurance. Based on chapters selected according to the particular topics in mind, the book may serve as a source for introductory courses to insurance mathematics for non-specialists, advanced courses for actuarial students, or courses on probabilistic aspects of risk. It will also be useful for practitioners and students/researchers in related areas such as finance and statistics who wish to get an overview of the general area of mathematical modeling and analysis in insurance.

This book introduces ALM in the context of banks and insurance companies. Although this strategy has a core of fundamental frameworks, models may vary between banks and insurance companies because of the different risks and goals involved. The authors compare and contrast these methodologies to draw parallels between the commonalities and divergences of these two services and thereby provide a deeper understanding of ALM in general.

In this concise yet comprehensive guide to the mathematics of modern portfolio theory the authors discuss mean-variance analysis, factor models, utility theory, stochastic dominance, very long term investing, the capital asset pricing model, risk measures including VAR, coherence, market efficiency, rationality and the modelling of actuarial liabilities. Each topic is clearly explained with assumptions, mathematics, limitations, problems and solutions presented in turn. Joshi's trademark style of clarity and practicality is here brought to classical financial mathematics. The book is suitable for mathematically trained students in actuarial studies, business and economics as well as mathematics and finance, and it can be used for both self-study and as a course text. The authors' experience as both academics and practitioners brings clarity and relevance to the book, whilst ensuring that the limitations of models are highlighted.

Unassuming but formidable, American maritime insurers used their position at the pinnacle of global trade to shape the new nation. The international information they gathered and the capital they generated enabled them to play central roles in state building and economic development. During the Revolution, they helped the U.S. negotiate foreign loans, sell state debts, and establish a single national bank. Afterward, they increased their influence by lending money to the federal government and to its citizens. Even as federal and state governments began to encroach on their domain, maritime insurers adapted, preserving their autonomy and authority through extensive involvement in the formation of commercial law. Leveraging their claims to unmatched expertise, they operated free from government interference while simultaneously embedding themselves into the nation's institutional fabric. By the early nineteenth century, insurers were no longer just risk assessors. They were nation builders and market makers. Deeply and imaginatively researched, Underwriters of the United States uses marine insurers to reveal a startlingly original story of risk, money, and power in the founding era.

This book summarizes the state of the art in tree-based methods for insurance: regression trees, random forests and boosting methods. It also exhibits the tools which make it possible to assess the predictive performance of tree-based models. Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and numerical illustrations or case studies. All numerical illustrations are performed with the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. In particular, master's students in actuarial sciences and actuaries wishing to update their skills in machine learning will find the book useful. This is the second of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance.

This is a comprehensive and accessible reference source that documents the theoretical and practical aspects of all the key deterministic and stochastic reserving methods that have been developed for use in general insurance. Worked examples and mathematical details are included, along with many of the broader topics associated with reserving in practice. The key features of reserving in a range of different contexts in the UK and elsewhere are also covered. The book contains material that will appeal to anyone with an interest in claims reserving. It can be used as a learning resource for actuarial students who are studying the relevant parts of their professional bodies' examinations, as well as by others who are new to the subject. More experienced insurance and other professionals can use the book to refresh or expand their knowledge in any of the wide range of reserving topics covered in the book.