Investing in Life considers the creation and expansion of the American life insurance industry from its early origins in the 1810s through the 1860s and examines how its growth paralleled and influenced the emergence of the middle class. Using the economic instability of the period as her backdrop, Sharon Ann Murphy also analyzes changing roles for women; the attempts to adapt slavery to an urban, industrialized setting; the rise of statistical thinking; and efforts to regulate the business environment. Her research directly challenges the conclusions of previous scholars who have dismissed the importance of the earliest industry innovators while exaggerating clerical opposition to life insurance. Murphy examines insurance as both a business and a social phenomenon. She looks at how insurance companies positioned themselves within the marketplace, calculated risks associated with disease, intemperance, occupational hazard, and war, and battled fraud, murder, and suicide. She also discusses the role of consumers-their reasons for purchasing life insurance, their perceptions of the industry, and how their desires and demands shaped the ultimate product.

The challenges of the current financial environment have revealed the need for a new generation of professionals who combine training in traditional finance disciplines with an understanding of sophisticated quantitative and analytical tools. Risk Management and Simulation shows how simulation modeling and analysis can help you solve risk management problems related to market, credit, operational, business, and strategic risk. Simulation models and methodologies offer an effective way to address many of these problems and are easy for finance professionals to understand and use. Drawing on the author s extensive teaching experience, this accessible book walks you through the concepts, models, and computational techniques.

How Simulation Models Can Help You Manage Risk More Effectively

Organized into four parts, the book begins with the concepts and framework for risk management. It then introduces the modeling and computational techniques for solving risk management problems, from model development, verification, and validation to designing simulation experiments and conducting appropriate output analysis. The third part of the book delves into specific issues of risk management in a range of risk types. These include market risk, equity risk, interest rate risk, commodity risk, currency risk, credit risk, liquidity risk, and strategic, business, and operational risks. The author also examines insurance as a mechanism for risk management and risk transfer. The final part of the book explores advanced concepts and techniques. The book contains extensive review questions and detailed quantitative or computational exercises in all chapters. Use of MATLAB(r) mathematical software is encouraged and suggestions for MATLAB functions are provided throughout.

Learn Step by Step, from Basic Concepts to More Complex Models

Packed with applied examples and exercises, this book builds from elementary models for risk to more sophisticated, dynamic models for risks that evolve over time. A comprehensive introduction to simulation modeling and analysis for risk management, it gives you the tools to better assess and manage the impact of risk in your organizations. The book can also serve as a support reference for readers preparing for CFA exams, GARP FRM exams, PRMIA PRM exams, and actuarial exams.

An incisive framework for companies seeking to increase their resilience In The Black Swan Problem: Risk Management Strategies for a World of Wild Uncertainty, renowned risk and finance expert Hakan Jankensgard delivers an extraordinary and startling discussion of how firms should navigate a world of uncertainty and unexpected events. It examines three fundamental, high-level strategies for creating resilience in the face of "black swan" risks, highly unlikely but devastating events: insurance, buffering, and flexibility: The author also presents: Detailed case studies, stories, and examples of major firms that failed to anticipate Black Swan Problems and, as a result, were either wiped out or experienced a major strategy disruption Extending the usual academic focus on individual biases to analyze Swans from an organizational perspective and prime organizations to proactive rather than reactive action Practical applications and tactics to mitigate Black Swan risks and protect corporate strategies against catastrophic losses and the collateral damage that they cause Strategies and tools for turning Black Swan events into opportunities, reflecting the fact that resilience can be used for strategic advantage An expert blueprint for companies seeking to anticipate, mitigate, and process tail risks, The Black Swan Problem is a must-read for students and practitioners of risk management, executives, founders, managers, and other business leaders.

In recent years, the damage caused by natural disasters has increased worldwide; this trend will only continue with the impact of climate change. Despite this, the role for the most common mechanism for managing risk - insurance - has received little attention. This book considers the contribution that insurance arrangements can make to society's management of the risks of natural hazards in a changing climate. It also looks at the potential impacts of climate change on the insurance sector, and insurers' responses to climate change. The author combines theory with evidence from the rich experiences of the Netherlands together with examples from around the world. He recognises the role of the individual in preparing for disasters, as well as the difficulties individuals have in understanding and dealing with infrequent risks. Written in plain language, this book will appeal to researchers and policy-makers alike.

Predictive modeling involves the use of data to forecast future events. It relies on capturing relationships between explanatory variables and the predicted variables from past occurrences and exploiting this to predict future outcomes. Forecasting future financial events is a core actuarial skill actuaries routinely apply predictive-modeling techniques in insurance and other risk-management applications. This book is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples of predictive modeling. The book also addresses the needs of more seasoned practicing analysts who would like an overview of advanced statistical topics that are particularly relevant in actuarial practice. Predictive Modeling Applications in Actuarial Science emphasizes life-long learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used by analysts to gain a competitive advantage in situations with complex data."

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.

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.

In recent years, the damage caused by natural disasters has increased worldwide; this trend will only continue with the impact of climate change. Despite this, the role for the most common mechanism for managing risk - insurance - has received little attention. This book considers the contribution that insurance arrangements can make to society's management of the risks of natural hazards in a changing climate. It also looks at the potential impacts of climate change on the insurance sector, and insurers' responses to climate change. The author combines theory with evidence from the rich experiences of the Netherlands together with examples from around the world. He recognises the role of the individual in preparing for disasters, as well as the difficulties individuals have in understanding and dealing with infrequent risks. Written in plain language, this book will appeal to researchers and policy-makers alike.

Insurance is an extraordinarily useful tool to manage risk. When it works as intended, it provides financial protection to individuals and a profitable business model for insurance firms and their investors. But it is broadly misunderstood by consumers, regulators, and insurance executives. This book looks at the behavior of individuals at risk, insurance industry decision makers, and policy makers at the local, state, and federal level involved in the selling, buying, and regulating of insurance. It compares their actions to those predicted by benchmark models of choice derived from classical economic theory. When actual choices stray from predictions, the behavior is considered to be anomalous. With considerable sums of money at stake, both in consumer premiums and insurance company payouts, it is important to understand the reasons for anomalous behavior. Howard Kunreuther, Mark Pauly, and Stacey McMorrow examine these anomalies through the lens of behavioral economics, which takes into account emotions, biases, and simplified decision rules. The authors then consider if and how such behavioral anomalies could be modified to improve individual and social welfare. This book is neither a defense of the insurance industry nor an attack on it. Neither is it a consumer guide to purchasing insurance, although the authors believe that consumers will benefit from the insights it contains. Rather, this book describes situations in which both public policy and the insurance industry s collective posture need to change. This may require incentives, rules, and institutions to help reduce both inefficient and anomalous behavior, thereby encouraging behavior that will improve individual and social welfare."

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.

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.

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).

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.

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.

Der Band stellt einerseits Vorgeschichte, Verlauf und Auswirkungen eines der spektakularsten Zusammenbruche eines Versicherungskonzerns im 20. Jahrhundert dar und bietet daruber hinaus eine am Beispiel demonstrierte, systematische Analyse der Verflechtung von Misswirtschaft mit Medien, Staat und Gesellschaft. Die Phoenix Lebensversicherung, mit Sitz in Wien und Kunden in 22 Landern, wurde im Jahr 1936 zahlungsunfahig. Sie hatte riesige Verluste aufgeturmt, Bilanzen gefalscht und Schlusselpersonen hofiert. Ihr Sturz drohte eine europaweite Finanzkrise auszuloesen und wurde mit diktatorischen Massnahmen aufgefangen. Das Buch schildert die wirtschaftliche wie politische Rolle des Versicherers vor 1918, wahrend der Weimarer Republik und ab 1933.

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.

This 2006 book introduces and develops the basic actuarial models and underlying pricing of life-contingent pension annuities and life insurance from a unique financial perspective. The ideas and techniques are then applied to the real-world problem of generating sustainable retirement income towards the end of the human life-cycle. The role of lifetime income, longevity insurance, and systematic withdrawal plans are investigated in a parsimonious framework. The underlying technology and terminology of the book are based on continuous-time financial economics by merging analytic laws of mortality with the dynamics of equity markets and interest rates. Nonetheless, the book requires a minimal background in mathematics and emphasizes applications and examples more than proofs and theorems. It can serve as an ideal textbook for an applied course on wealth management and retirement planning in addition to being a reference for quantitatively-inclined financial planners.

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 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.

A Hands-On Approach to Understanding and Using Actuarial Models Computational Actuarial Science with R provides an introduction to the computational aspects of actuarial science. Using simple R code, the book helps you understand the algorithms involved in actuarial computations. It also covers more advanced topics, such as parallel computing and C/C++ embedded codes. After an introduction to the R language, the book is divided into four parts. The first one addresses methodology and statistical modeling issues. The second part discusses the computational facets of life insurance, including life contingencies calculations and prospective life tables. Focusing on finance from an actuarial perspective, the next part presents techniques for modeling stock prices, nonlinear time series, yield curves, interest rates, and portfolio optimization. The last part explains how to use R to deal with computational issues of nonlife insurance. Taking a do-it-yourself approach to understanding algorithms, this book demystifies the computational aspects of actuarial science. It shows that even complex computations can usually be done without too much trouble. Datasets used in the text are available in an R package (CASdatasets).

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.