Insurance and actuarial studies Books

Book SynopsisDrawing on examples ranging from military history to the business world, a retired four-star general in the U.S. Army offers a battle-tested system for detecting and responding to risk, showing that there are in fact ten dimensions of control we can adjust at any given time.

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Book SynopsisPresents an overview of financial risk modeling, with a focus on practical applications, empirical reality, and historical perspective. Covering the mean-variance analysis and the capital asset pricing model, this title offers an account of factor models, which are the key to successful risk analysis in every economic climate.Trade Review"Thorough and well-cited, this is a comprehensive treatment of techniques for portfolio risk management. It provides a unique perspective, from the fundamentals to practical applications. There are few books that cover this material in this particular way."—Christopher L. Culp, author of Structured Finance and Insurance"The range of topics is wide and the coverage is deep. An impressive book."—Peter Christoffersen, McGill University"The conceptual framework of this book is presented in a lucid and clear manner. The treatment is mathematically rigorous where it matters, without ever becoming pedantic and without cutting corners."—Riccardo Rebonato, Royal Bank of Scotland"This book takes major steps forward in the crucially important area of portfolio risk measurement, making significant strides toward incorporating industry and country risk, as well as macroeconomic, FX, credit, transactions cost, and liquidity risks. It will be an essential reference text for academics, central bankers, and others in the financial services industry."—Francis X. Diebold, University of PennsylvaniaTable of ContentsAcknowledgments xi Introduction xiii Key Notation xix Chapter 1: Measures of Risk and Return 1 1.1 Measuring Return 1 1.2 The Key Portfolio Risk Measures 6 1.3 Risk-Return Preferences and Portfolio Optimization 12 1.4 The Capital Asset Pricing Model and Its Applications to Risk Analysis 23 1.5 The Objectives and Limitations of Portfolio Risk Analysis 31 Chapter 2: Unstructured Covariance Matrices 36 2.1 Estimating Return Covariance Matrices 36 2.2 The Error-Maximization Problem 47 2.3 Portfolio Choice as Decision Making under Uncertainty 54 Chapter 3: Industry and Country Risk 61 3.1 Industry-Country Component Models 61 3.2 Empirical Evidence on the Relative Magnitudes of Country and Industry Risks 73 3.3 Sector-Currency Models of Corporate Bond Returns 77 Chapter 4: Statistical Factor Analysis 79 4.1 Types of Factor Models 79 4.2 Approximate Factor Models 82 4.3 The Arbitrage Pricing Theory 86 4.4 Small-n Estimation Methods 88 4.5 Large-n Estimation Methods 93 4.6 Number of Factors 98 Chapter 5: The Macroeconomy and Portfolio Risk 101 5.1 Estimating Macroeconomic Factor Models 101 5.2 Event Studies of Macroeconomic Announcements 110 5.3 Macroeconomic Policy Endogeneity 112 5.4 Business Cycle Betas 115 5.5 Empirical Fit and the Relative Value of Macroeconomic Factor Models 116 Chapter 6: Security Characteristics and Pervasive Risk Factors 117 6.1 Equity and Fixed-Income Characteristics 117 6.2 Characteristic-Based Factor Models of Equities 122 6.3 The Fama-French Model and Extensions 130 6.4 The Semiparametric Approach to Characteristic-Based Factor Models 132 Chapter 7: Measuring and Hedging Foreign Exchange Risk 134 7.1 Definitions of Foreign Exchange Risk 134 7.2 Optimal Currency Hedging 142 7.3 Currency Covariances with Stock and Bond Returns 149 7.4 Macroeconomic Influences on Currency Returns 151 Chapter 8: Integrated Risk Models 155 8.1 Global and Regional Integration Trends 155 8.2 Risk Integration across Asset Classes 158 8.3 Segmented Asset Allocation and Security Selection 159 8.4 Integrated Risk Models 162 Chapter 9: Dynamic Volatilities and Correlations 167 9.1 GARCH Models 167 9.2 Stochastic Volatility Models 178 9.3 Time Aggregation 180 9.4 Downside Correlation 181 9.5 Option-Implied Volatility 184 9.6 The Volatility Term Structure at Long Horizons 187 9.7 Time-Varying Cross-Sectional Dispersion 188 Chapter 10: Portfolio Return Distributions 191 10.1 Characterizing Return Distributions 191 10.2 Estimating Return Distributions 196 10.3 Tail Risk 203 10.4 Nonlinear Dependence between Asset Returns 207 Chapter 11: Credit Risk 212 11.1 Agency Ratings and Factor Models of Spread Risk 213 11.2 Rating Transitions and Default 217 11.3 Credit Instruments 218 11.4 Conceptual Approaches to Credit Risk 220 11.5 Recovery at Default 232 11.6 Portfolio Credit Models 232 11.7 The 2007-8 Credit-Liquidity Crisis 238 Chapter 12: Transaction Costs and Liquidity Risk 241 12.1 Some Basic Terminology 241 12.2 Measuring Transactions Cost 246 12.3 Statistical Properties of Liquidity 261 12.4 Optimal Trading Strategies and Transaction Costs 266 Chapter 13: Alternative Asset Classes 271 13.1 Nonsynchronous Pricing and Smoothed Returns 271 13.2 Time-Varying Risk, Nonlinear Payoff, and Style Drift 284 13.3 Selection and Survivorship Biases 291 13.4 Collectibles: Measuring Return and Risk with Infrequent and Error-Prone Observations 295 13.5 Summary 298 Chapter 14: Performance Measurement 299 14.1 Return-Based Performance Measurement 299 14.2 Holdings-Based Performance Measurement and Attribution 303 14.3 Volatility Forecast Evaluation 309 14.4 Value-at-Risk Hit Rates 316 14.5 Forecast and Realized Return Densities 317 Chapter 15: Conclusion 319 15.1 Some Key Messages 319 15.2 Questions for Future Research 320 References 323 Index 345

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Book SynopsisInforming American Health Care Policy provides a critical perspective on the National Medical ExpAnditure Surveys (NMES) and how these surveys have responded to the sometimes conflicting challenges of policy and research.Trade Review"... Informing American Health Care Policy is a useful, evenentertaining book for anyone who uses health data or who wants tounderstand the history and evolution of expAnditure surveys."(Health Affairs May/June 2000) "In this important book, the lead researchers associated with NMESdescribe the development of this rich data source and, in a seriesof well-crafted papers, illustrate the use of these data ininforming major areas of health policy. It is a must-read foranyone interested in American health policy-especially for youngerprofessionals entering this growing field." (Uwe E. Reinhardt,James Madison Professor of Political Economy, PrincetonUniversity) "National health expenditure surveys have provided policymakerswith the information they need to make informed decisions. Thisvolume tells us about the evolution and contributions of thefederal government's most ambitious health care survey. I recommAndit for those interested in improving the quality of data availableto those who formulate policy." (John K. Iglehart, founding editor,Health Affairs) "I enjoyed reading this book. Thanks to the major investment inhealth expAnditure and insurance surveys and the increasinglysophisticated analytic capacity described in this volume, policyofficials now have a much more precise and up-to-date understandingof the implications of policy choices." (Karen Davis, president,The Commonwealth Fund; developed President Carter's 1977 nationalhealth reform proposal) "Thoughtful and informed reflections on the lessons learned byNMES. Provides sound guidance and procedures required to addressthe Anduring policy questions of Who's covered? Who pays?, and Howmuch? in the emerging U.S. health care environment of the future."(Lu Ann Aday, professor of behavioral sciences and management andpolicy sciences, the University of Texas School of Public Health;and author, Designing and Conducting Health Surveys, FourthEdition)Table of ContentsForeword. Preface and Acknowledgments. The Editors. The Contributors. Introduction (A. Monheit & R. Wilson). PAST CHALLLENGES AND CURRENT ISSUES. National Medical ExpAnditure Surveys: Genesis and Rationale (R.Andersen & O. Anderson). Modeling Consumer and Provider Behavior: The First NationalExpenditure Study (G. Wilensky). The Provider System and the Changing Locus of Expenditure Data:Survey Strategies from Fee-for-Service to Managed Care (J. Cohen& A. Taylor). SOURCES OF PAYMENT AND THE STRUCTURE OF HEALTH INSURANCE. Examining Health Insurance Differences: Issues of Public Equity andCost Efficiency (P. Short). Health Insurance, Employment, and the Labor Market (A.Monheit). VULNERABLE POPULATIONS: HEALTH CARE AND MEASURES OF ACCESS. The National ExpAnditure Surveys and Studies of Access to Care byVulnerable Populations (M. Berk). Evaluating Medicare and Medicaid: The Yield in Information from theNational Medical Expenditure Surveys (J. Kasper). SURVEY METHODS, BUDGET CONSTRAINTS, AND OPERATIONAL ISSUES. Better Estimates of Populations at Risk and More EfficientSampling: Changing Survey Design Strategies over Time (S.Cohen). Continuity Versus Change: Challenges in Designing a SuccessorSurvey (D. Walden). Survey Integration and End-of-Century Constraints (R.Arnett). THE ROLE OF NATIONAL DATA IN POLICY FORMULATION. Health System Reform Debates and Medical Expenditure Surveys (L.Nichols). Name Index. Subject Index.

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Book SynopsisIn addition, this detailed industry case study helps explain information technology's so-called productivity paradox, showing that firms took roughly two decades to achieve the initial computerization and process integration that the industry set as objectives in the 1950s.Trade ReviewStructuring the Information Age makes educating reading and is an important contribution to our understanding of the connection between past and present in the transformation of socio-economic systems. -- Asaf Darr Administrative Science Quarterly 2006 Brilliant volume... Yate's study of the adaptation of information-processing resources in insurance has greatly widened the horizons of our understanding of the dynamics of technological development in a business setting. Business History Review 2006 Yates has contributed another original study to the history of information technology. -- Kenneth Lipartito Technology and Culture 2006 A welcome addition to a growing body of literature on the history of the use of computers by businesses, and a good model for other scholars to use. -- James W. Cortada American Historical Review 2006 Structuring the Information Age examines the history of information technology in the United States by shifting focus away from the producers of that technology and toward a kind of end user that has heretofore received little attention-large-scale corporations, which easily rank among the leading information-technology (it) consumers. -- Timothy Alborn Journal of Interdisciplinary History 2007 This timely and important work is the first scholarly history devoted to the use of information technology within a single American industry. -- Thomas Haigh EH.Net 2007 This valuable addition to the historiography of the computer looks at new technologies from a user's viewpoint. Here the user is the life insurance business, which is an appropriate choice because it has always been an information-intense business. IEEE History Center Newsletter 2007 Structuring the Information Age will interest two types of readers: those who are concerned with the development, adoption, and impact of technology and those who are concerned with the growth, strategies, and economic influence of business organizations. -- Daphne A. Jameson Journal of Business and Technical Communication 2006Table of ContentsAcknowledgmentsIntroductionPart I: Life Insurance in the Tabulator Era1. Insurance at the Turn of the Twentieth Century2. First Impressions of Tabulating, 1890–19103. The Push toward Printing, 1910–19244. Insurance Associations and the Flowering of the Tabulator EraPart II: Life Insurance Enters the Computer Era5. Early Engagement between Insurance and Computing6. Insurance Adoption and Use of Early Computers7. Incremental Migration during the 1960s and 1970s8. Case Studies in Insurance Computing: New England Mutual Life and Aetna LifeConclusionNotesSelected BibliographyIndex

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Book SynopsisIn addition, this detailed industry case study helps explain information technology's so-called productivity paradox, showing that firms took roughly two decades to achieve the initial computerization and process integration that the industry set as objectives in the 1950s.Trade ReviewStructuring the Information Age makes educating reading and is an important contribution to our understanding of the connection between past and present in the transformation of socio-economic systems. -- Asaf Darr Administrative Science Quarterly 2006 Brilliant volume... Yate's study of the adaptation of information-processing resources in insurance has greatly widened the horizons of our understanding of the dynamics of technological development in a business setting. Business History Review 2006 Yates has contributed another original study to the history of information technology. -- Kenneth Lipartito Technology and Culture 2006 A welcome addition to a growing body of literature on the history of the use of computers by businesses, and a good model for other scholars to use. -- James W. Cortada American Historical Review 2006 Structuring the Information Age examines the history of information technology in the United States by shifting focus away from the producers of that technology and toward a kind of end user that has heretofore received little attention-large-scale corporations, which easily rank among the leading information-technology (it) consumers. -- Timothy Alborn Journal of Interdisciplinary History 2007 This timely and important work is the first scholarly history devoted to the use of information technology within a single American industry. -- Thomas Haigh EH.Net 2007 This valuable addition to the historiography of the computer looks at new technologies from a user's viewpoint. Here the user is the life insurance business, which is an appropriate choice because it has always been an information-intense business. IEEE History Center Newsletter 2007 Structuring the Information Age will interest two types of readers: those who are concerned with the development, adoption, and impact of technology and those who are concerned with the growth, strategies, and economic influence of business organizations. -- Daphne A. Jameson Journal of Business and Technical Communication 2006Table of ContentsAcknowledgmentsIntroductionPart I: Life Insurance in the Tabulator Era1. Insurance at the Turn of the Twentieth Century2. First Impressions of Tabulating, 1890–19103. The Push toward Printing, 1910–19244. Insurance Associations and the Flowering of the Tabulator EraPart II: Life Insurance Enters the Computer Era5. Early Engagement between Insurance and Computing6. Insurance Adoption and Use of Early Computers7. Incremental Migration during the 1960s and 1970s8. Case Studies in Insurance Computing: New England Mutual Life and Aetna LifeConclusionNotesSelected BibliographyIndex

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Book SynopsisThis study explores the policy options a provincial government might consider in extending health care coverage to the purchase of prescription drugs and dental care. It examines the major public policy objectives involved, such as spreading risk, redistributing wealth, and reducing the barriers to care, and evaluates alternative programs in terms of their costs and efficiency as well as their realization of the basic social objectives of health care. Using varied statistics, some drawn from schemes in other provinces, it estimates what different packages of pharmacare and denticare would have cost in Ontario in 1975. The results indicate that universal coverage may be one of the most costly and least effective options. Based on current modes of service delivery, a universal pharmacare and denticare program would transfer wealth to upper income groups without significantly improving the utilization of health care services.A study of drug manufacturing and retailing systems in

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Book SynopsisWhether man-made or naturally occurring, large-scale disasters can cause fatalities and injuries, devastate property and communities, savage the environment, impose significant financial burdens on individuals and firms, and test political leadership. Moreover, global challenges such as climate change and terrorism reveal the interdependent and interconnected nature of our current moment: what occurs in one nation or geographical region is likely to have effects across the globe. Our information age creates new and more integrated forms of communication that incur risks that are difficult to evaluate, let alone anticipate. All of this makes clear that innovative approaches to assessing and managing risk are urgently required.When catastrophic risk management was in its inception thirty years ago, scientists and engineers would provide estimates of the probability of specific types of accidents and their potential consequences. Economists would then propose risk management poliTrade Review"Extraordinarily thoughtful and insightful, the authors of The Future of Risk Management provide students and professionals in the field of risk management new pathways for approaches and solutions to our myriad areas of risk. Moreover, anyone interested in understanding the risks our societies face should study these essays." * Franklin W. Nutter, President, Reinsurance Association of America *"The field of risk management has exploded in recent decades as natural disasters, financial meltdowns, pandemics, and other damaging events have wreaked havoc across borders. The Future of Risk Management brings together essays from leading thinkers on ways to reduce risk so that today's threats do not turn into tomorrow's catastrophes. Aimed at policy leaders seeking strategies to reduce future harm, this volume deserves a close read and a spot on the bookshelf of all forward-thinking decision-makers." * Alice Hill, The Hoover Institution, Stanford University *"The Future of Risk Management engages in a critical discussion on how we as a nation and the world as a whole should better prepare for and reduce the costs of future disasters. The authors correctly recognize that our current disaster preparedness and response paradigm is fundamentally broken-plagued by inconsistencies, short-sightedness, and a lack of integration. Instead, we need to take a holistic, long-term approach to disaster response and risk management and allocate resources based on the best objective data available." * Jason M. Tuber, U.S. Congressional Staffer *"This comprehensive, critical, and lucid survey demonstrates convincingly that effectively managing climate change and other major threats requires understanding how the average person reacts to risk. It's a story about lessons learned and lessons forgotten, about logic and bias, about positive incentives and perverse incentives-and serves as a warning that we have a long, long way to go before we manage risk effectively." * Michael Oppenheimer, Princeton University *Table of ContentsIntroduction —Howard Kunreuther, Robert J. Meyer, and Erwann O. Michel-Kerjan PART I. BEHAVIORAL FACTORS INFLUENCING DECISION-MAKING UNDER RISK AND UNCERTAINTY Chapter 1. The Arithmetic of Compassion and the Future of Risk Management —Paul Slovic and Daniel Västfjäll Chapter 2. "Risk as Feelings" and "Perception Matters": Psychological Contributions on Risk, Risk-Taking, and Risk Management —Elke U. Weber Chapter 3. Risk-Based Thinking —Baruch Fischhoff Chapter 4. Structured Empirical Analysis of Decisions Under Natural Hazard Risk —Craig E. Landry, Gregory Colson, and Mona Ahmadiani Chapter 5. Mixing Rationality and Irrationality in Insurance Demand and Supply —Mark Pauly Chapter 6. The Disaster Cycle: What We Do Not Learn from Experience —Robert J. Meyer PART II. IMPROVING RISK ASSESSMENT Chapter 7. Using Models to Set a Baseline and Measure Progress in Reducing Disaster Casualties —Robert Muir-Wood Chapter 8. Learning from All Types of Near-Misses —Robin Dillon Chapter 9. Managing Systemic Industry Risk: The Need for Collective Leadership —Paul J. H. Schoemaker Chapter 10. Measuring Economic Resilience: Recent Advances and Future Priorities —Adam Rose PART III. DEVELOPING BETTER RISK COMMUNICATION STRATEGIES Chapter 11. Improving Stakeholder Engagement for Upstream Risks —Robin Gregory and Nate Dieckmann Chapter 12. Improving the Accuracy of Geopolitical Risk Assessments —Barbara A. Mellers, Philip E. Tetlock, Joshua D. Baker, Jeffrey A. Friedman, and Richard Zeckhauser Chapter 13. Efficient Warnings, Not "Wolf or Puppy" Warnings —Lisa A. Robinson, W. Kip Viscusi, and Richard Zeckhauser PART IV. ROLE OF RISK MITIGATION, RISK-SHARING, AND INSURANCE Chapter 14. Threats to Insurability —Carolyn Kousky Chapter 15. The Role of Insurance in Risk Management for Natural Disasters: Back to the Future —Howard Kunreuther Chapter 16. Improving Individual Flood Preparedness Through Insurance Incentives —W. J. Wouter Botzen Chapter 17. Strong and Well-Enforced Building Codes as an Effective Disaster Risk Reduction Tool: An Evaluation —Jeffrey Czajkowski PART V. GOVERNMENT AND RISK MANAGEMENT Chapter 18. Getting the Blend Right: Public-Private Partnerships in Risk Management —Cary Coglianese Chapter 19. The Regulation of Insurance Markets Subject to Catastrophic Risks —Robert W. Klein Chapter 20. Rethinking Government Disaster Relief in the United States: Evidence and a Way Forward —Erwann O. Michel-Kerjan List of Contributors Index

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Book SynopsisTrade Review"Extraordinarily thoughtful and insightful, the authors of The Future of Risk Management provide students and professionals in the field of risk management new pathways for approaches and solutions to our myriad areas of risk. Moreover, anyone interested in understanding the risks our societies face should study these essays." * Franklin W. Nutter, President, Reinsurance Association of America *"The field of risk management has exploded in recent decades as natural disasters, financial meltdowns, pandemics, and other damaging events have wreaked havoc across borders. The Future of Risk Management brings together essays from leading thinkers on ways to reduce risk so that today's threats do not turn into tomorrow's catastrophes. Aimed at policy leaders seeking strategies to reduce future harm, this volume deserves a close read and a spot on the bookshelf of all forward-thinking decision-makers." * Alice Hill, The Hoover Institution, Stanford University *"The Future of Risk Management engages in a critical discussion on how we as a nation and the world as a whole should better prepare for and reduce the costs of future disasters. The authors correctly recognize that our current disaster preparedness and response paradigm is fundamentally broken-plagued by inconsistencies, short-sightedness, and a lack of integration. Instead, we need to take a holistic, long-term approach to disaster response and risk management and allocate resources based on the best objective data available." * Jason M. Tuber, U.S. Congressional Staffer *"This comprehensive, critical, and lucid survey demonstrates convincingly that effectively managing climate change and other major threats requires understanding how the average person reacts to risk. It's a story about lessons learned and lessons forgotten, about logic and bias, about positive incentives and perverse incentives-and serves as a warning that we have a long, long way to go before we manage risk effectively." * Michael Oppenheimer, Princeton University *Table of ContentsIntroduction —Howard Kunreuther, Robert J. Meyer, and Erwann O. Michel-Kerjan PART I. BEHAVIORAL FACTORS INFLUENCING DECISION-MAKING UNDER RISK AND UNCERTAINTY Chapter 1. The Arithmetic of Compassion and the Future of Risk Management —Paul Slovic and Daniel Västfjäll Chapter 2. "Risk as Feelings" and "Perception Matters": Psychological Contributions on Risk, Risk-Taking, and Risk Management —Elke U. Weber Chapter 3. Risk-Based Thinking —Baruch Fischhoff Chapter 4. Structured Empirical Analysis of Decisions Under Natural Hazard Risk —Craig E. Landry, Gregory Colson, and Mona Ahmadiani Chapter 5. Mixing Rationality and Irrationality in Insurance Demand and Supply —Mark Pauly Chapter 6. The Disaster Cycle: What We Do Not Learn from Experience —Robert J. Meyer PART II. IMPROVING RISK ASSESSMENT Chapter 7. Using Models to Set a Baseline and Measure Progress in Reducing Disaster Casualties —Robert Muir-Wood Chapter 8. Learning from All Types of Near-Misses —Robin Dillon Chapter 9. Managing Systemic Industry Risk: The Need for Collective Leadership —Paul J. H. Schoemaker Chapter 10. Measuring Economic Resilience: Recent Advances and Future Priorities —Adam Rose PART III. DEVELOPING BETTER RISK COMMUNICATION STRATEGIES Chapter 11. Improving Stakeholder Engagement for Upstream Risks —Robin Gregory and Nate Dieckmann Chapter 12. Improving the Accuracy of Geopolitical Risk Assessments —Barbara A. Mellers, Philip E. Tetlock, Joshua D. Baker, Jeffrey A. Friedman, and Richard Zeckhauser Chapter 13. Efficient Warnings, Not "Wolf or Puppy" Warnings —Lisa A. Robinson, W. Kip Viscusi, and Richard Zeckhauser PART IV. ROLE OF RISK MITIGATION, RISK-SHARING, AND INSURANCE Chapter 14. Threats to Insurability —Carolyn Kousky Chapter 15. The Role of Insurance in Risk Management for Natural Disasters: Back to the Future —Howard Kunreuther Chapter 16. Improving Individual Flood Preparedness Through Insurance Incentives —W. J. Wouter Botzen Chapter 17. Strong and Well-Enforced Building Codes as an Effective Disaster Risk Reduction Tool: An Evaluation —Jeffrey Czajkowski PART V. GOVERNMENT AND RISK MANAGEMENT Chapter 18. Getting the Blend Right: Public-Private Partnerships in Risk Management —Cary Coglianese Chapter 19. The Regulation of Insurance Markets Subject to Catastrophic Risks —Robert W. Klein Chapter 20. Rethinking Government Disaster Relief in the United States: Evidence and a Way Forward —Erwann O. Michel-Kerjan List of Contributors Index

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Book SynopsisSet at a health insurance company dubbed Acme, this book chronicles how the privatization of the health care system in Puerto Rico transformed the experience of accessing and providing care on the island. Through interviews and participant observation, it explores the everyday contexts in which market reforms were enacted.Trade ReviewA persuasive account and `insiders view of how Managed Care really works. Managed Care, Jessica Mulligan argues, is really `ungovernable care. The assumption that `rational consumers can exercise `choice ignores the way ordinary people understand and deal with their health care issues. `Consumers see themselves as retired workers, mothers, or those who have chronic diseases like diabetes. `Choice is bewildering or limited. `Satisfaction boils down to surveys that code statements like `I cant complain and omit narratives about struggles to get better care. Mulligan argues we need to diagnose these ills that characterize neoliberal models of healthcare reform before we can work to change them. -- Louise Lamphere,Distinguished Professor of Anthropology Emerita, University of New MexicoA telling ethnography of the privatization of health care in Puerto Rico. Written from within the system of managed care, Mulligans impressive understanding of historical, cultural, economic, entrepreneurial, and moral aspects of reform paints a troubling picture of what is wrong with market approaches to care. Clear, timely, and insightful, Unmanageable Care contributes importantly to the medical anthropology of health care. It also goes beyond that to illustrate the limits and failures of market approaches to manage caregiving that are regularly overlooked by health policy experts with unfortunate results. An important book! -- Arthur Kleinman, M.D.,Esther and Sidney Rabb Professor of Anthropology, Harvard UniversityMulligan does an excellent job of, as she puts it, & tak[ing] seriously the potential of market-based solutions to reducing healthcare costs.While methodologically appealing to anthropologists, this book also has broader implications for those seeking healthcare solutions for disadvantaged populations in resource-constrained settings. * American Anthropologist *Table of ContentsContents Acknowledgments ix Introduction: Learning to Manage 1 Part I: Elements of a System 1. A History of Reform: Colonialism, Public Health, and Privatized Care 312. Regulating a Runaway Train: Everyone Is Replaceable 61 3. New Consumer Citizens: Life Histories 89 Part II: The Business of Care: Market Values and Management Strategies 4. Quality: Managing by Numbers 125 5. Complaints: The Wrong Glucometer ... Again! 151 6. Market Values: Partnering and Choice 179 Conclusion: Ungovernability as Market Rule 209 Appendix 1: A Methodological Appendix 231 Appendix 2: Interview Descriptions 241 Notes 253 Works Cited 277 Index 295 About the Author 299

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Book SynopsisThe insurance industry is among the most highly regulated industries today, and literature on the field is a complex thicket of sources. This valuable, one-of-a-kind resource is a comprehensive guide to locating and using information resources about the insurance industry.Trade Review”A small but detailed reference work, this paperback could function as the one insurance, risk management, and actuarial science resource for academic libraries with smaller collections or for public libraries with a strong business focus. For larger institutions, this text would provide a handy quick guide in a reference collection.""— ARBATable of ContentsPreface Chapter 1: Introductory Guides to Insurance: Consumer Information Sources, Guides, and Popular Works Chapter 2: Textbooks: Insurance, Actuarial Science, Risk Management, and Related Topics Chapter 3: The Insurance Industry: Almanacs, Fact Books, and Statistics; Databases; Dictionaries and Encyclopedias; Directories; Handbooks; and Associations Chapter 4: The History of Insurance Chapter 5: Insurance Law Chapter 6: International Insurance Chapter 7: Actuarial Science Chapter 8: Risk Management Chapter 9: Health Care Reform and Health Insurance Chapter 10: Annuities and Life Insurance Chapter 11: Property/Casualty Insurance, Catastrophe Insurance, and Liability Insurance Chapter 12: Employment and Related Insurance: Disability, Employment Benefits, and Workers’ Compensation; Social Insurance and Social Security; and Employee Benefits and Retirement Plans Chapter 13: Bank and Financial Insurance: Bank and Credit Insurance and Risk Management; Economics and Insurance; and Finance and Investment Advisory Sources Chapter 14: Careers in Insurance and Insurance Education Chapter 15: Miscellaneous Insurance and Related Topics Appendix A: Abbreviations and Acronyms Appendix B: Insurance, Risk Management, and Actuarial Associations and Agencies Appendix C: Selected Insurance, Risk Management, and Actuarial Studies Journals Appendix D: Insurance, Actuarial Science, and Risk Management Schools and University Departments Appendix E: Selected Major Business and Insurance Libraries Index.

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Book SynopsisThis timely two-volume collection successfully combines economically-oriented legal scholarship on insurance with policy-relevant economics scholarship on insurance.Trade Review‘Often considered quite diverse, law and economics impact on the insurance industry in almost equal measure, which means that this copiously footnoted two-volume work, with its extensive bibliographies, will offer perspectives on the economic implications of the law which will be useful to insurance lawyers, economists, academics and graduate students alike.’ -- Phillip Taylor MBE and Elizabeth Taylor, The Barrister MagazineTable of ContentsContents: Acknowledgements Introduction Daniel Schwarcz PART I INFORMATION ASYMMETRIES IN THE LAW AND ECONOMICS OF INSURANCE A. Adverse Selection 1. Amy Finkelstein and James Poterba (2002), ‘Selection Effects in the United Kingdom Individual Annuities Market’ 2. Peter Siegelman (2004), ‘Adverse Selection in Insurance Markets: An Exaggerated Threat’ B. Moral Hazard 3. Alma Cohen and Rajeev Dehejia (2004), ‘The Effect of Automobile Insurance and Accident Liability Laws on Traffic Fatalities’ 4. Tom Baker (1996), ‘On the Genealogy of Moral Hazard’ PART II INTERPRETING, REGULATING AND ENFORCING INSURANCE POLICIES A. Interpreting and Construing Insurance Policies 5. Kenneth S. Abraham (1996), ‘A Theory of Insurance Policy Interpretation’ 6. Michelle E. Boardman (2006), ‘Contra Proferentem: Allure of Ambiguous Boilerplate’ B. Regulating the Content of Insurance Policies 7. Russell Korobkin (1999), ‘The Efficiency of Managed Care “Patient Protection” Laws: Incomplete Contracts, Bounded Rationality, and Market Failure’ 8. Daniel Schwarcz (2007), ‘A Products Liability Theory for the Judicial Regulation of Insurance Policies’ C. Bad Faith Breach of Contract 9. Alan O. Sykes (1996), ‘”Bad Faith” Breach of Contract by First Party Insurers’ PART III LIABILITY INSURANCE A. The Desirability of Liability Insurance 10. Steven Shavell (1982), ‘On Liability and Insurance’ 11. George L. Priest (1989), ‘Insurability and Punitive Damages’ B. The Duty to Settle 12. Kent D. Syverud (1990), ‘The Duty to Settle’ 13. Alan O. Sykes (1994), ‘Judicial Limitations on the Discretion of Liability Insurers to Settle or Litigate: An Economic Critique’ C. The Impact of Liability Insurance 14. Tom Baker and Sean J. Griffith (2007), ‘The Missing Monitor in Corporate Governance: The Directors' & Officers' Liability Insurer’ 15. Kathryn Zeiler, Charles Silver, Bernard Black, David Hyman and William M. Sage (2007), ‘Physicians’ Insurance Limits and Malpractice Payments: Evidence From Texas Closed Claims, 1990–2003’ Volume II: Acknowledgements Introduction An introduction by the editor appears in Volume I PART I REGULATING INSURANCE MARKETS A. The Structure of Insurance Regulation 1. Jonathan R. Macey and Geoffrey P. Miller (1993), ‘The McCarran-Ferguson Act of 1945: Reconceiving the Federal Role in Insurance Regulation’ 2. Martin F. Grace and Richard D. Phillips (2007), ‘The Allocation of Governmental Regulatory Authority: Federalism and the Case of Insurance Regulation’ B. Solvency Regulation 3. J. David Cummins, Scott E. Harrington and Robert Klein (1995), ‘Insolvency Experience, Risk-Based Capital, and Prompt Corrective Action in Property-Liability Insurance’ 4. Scott E. Harrington (2005), ‘Capital Adequacy in Insurance and Reinsurance’ C. Regulation and Risk Classification 5. Kenneth S. Abraham (1985), ‘Efficiency and Fairness in Insurance Risk Classification’ 6. Michael Hoy and Michael Ruse (2005), ‘Regulating Genetic Information in Insurance Markets’ D. Price Regulation in Insurance Markets 7. Henry Grabowski, W. Kip Viscusi and William N. Evans (1989), ‘Price and Availability Tradeoffs of Automobile Insurance Regulation’ 8. Mary A. Weiss, Sharon Tennyson and Laureen Regan (2010), ‘The Effects of Regulated Premium Subsidies on Insurance Costs: An Empirical Analysis of Automobile Insurance’ 9. Dwight M. Jaffee and Thomas Russell (2002), ‘Regulation of Automobile Insurance in California’ E. Regulation and Insurance Policy Renewal 10. Mark V. Pauly, Howard Kunreuther and Richard Hirth (1995), ‘Guaranteed Renewability in Insurance’ 11. Ronen Avraham and K.A.D. Camara (2007), ‘The Tragedy of the Human Commons’ F. Regulating Insurance Demand 12. Kyle D. Logue (2001), ‘The Current Life Insurance Crisis: How the Law Should Respond’ 13. Daniel Schwarcz (2010), ‘Regulating Consumer Demand in Insurance Markets’ PART II PUBLIC VS. PRIVATE INSURANCE MARKETS A. Tort Law as Insurance 14. Richard A. Epstein (1985), ‘Products Liability as an Insurance Market’ 15. Jon D. Hanson and Kyle D. Logue (1990), ‘The First-Party Insurance Externality: An Economic Justification for Enterprise Liability’ 16. Kenneth S. Reinker and David Rosenberg (2007), ‘Unlimited Subrogation: Improving Medical Malpractice Liability by Allowing Insurers to Take Charge’ B. Government Role in Catastrophe Insurance 17. Dwight M. Jaffee and Thomas Russell (1997), ‘Catastrophe Insurance, Capital Markets, and Uninsurable Risks’ 18. J. David Cummins (2006), ‘Should the Government Provide Insurance for Catastrophes?’ 19. Howard Kunruether and Mark Pauly (2006), ‘Rules Rather than Discretion: Lessons from Hurricane Katrina’

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Book SynopsisPresents various legal, political, historical, and financial arguments about the two types of auto insurance.Table of ContentsSeries Editor's PrefaceRita J. SimonThe Case for Automobile Tort Liability Jerry J. Phillips The Case for No-Fault Insurance Stephen Chippendale ResponsesRejoinder-Jerry J. PhillipsRejoinder-Stephen Chippendale Index

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Book SynopsisSustainable Life Insurance: Managing Risk Appetite for Insurance Savings and Retirement Products gives an overview of all relevant aspects of traditional and non-traditional savings and retirement products from both insurers' and policyholders' respective risk appetites. Examples of such products include general accounts, whole life, annuities (variable, fixed and fixed indexed, structured), index-linked products, CPPI-based products, etc.The book contains technical details associated with both practice and theory, specifically related to modelling, product design, investments and risk management challenges and solutions, tailored to both insurers' and policyholders' perspectives.Features The book offers not only theoretical background but also concrete, cutting-edge quick wins across strategic and operational business axes. It will be an asset for professionals in the insurance industry, and a great teachinTable of ContentsIntroduction. 1. The transformation of the Risk Appetite for Sustainable Savings and Retirement. 1.1. The transformation of the insurance business since the past decade. 1.2. Securing long-term sustainable business growth: from Governance to effective risk management. 2. Products Risk Appetite for Sustainable Savings and Retirement. 2.1. The increasingly selective customer’ Risk Appetite across the four axes: yields/flexibility/financial guarantees/cost. 2.2. Meeting both shareholders and policyholders Appetites through sustainable Capital-light products? 3. Measuring Risk Appetite for Sustainable Savings and Retirement. 3.1. Considerations on Risk-neutral vs. Real-world pricing framework. 3.2. Hybrid Financial Risks Modelling for Sustainable Savings and Retirement. 3.3. Computational challenges and opportunities: accelerating the computational Run Time by Speeding up the convergence of Monte Carlo simulations. 4. Designing Products aligned with Risk Appetite for Sustainable Savings and Retirement. 4.1. Screening sustainable opportunities balancing shareholders vs. customers’ interests within persistent low rates and growing regulatory constraints. 4.2 Sustainable Liabilities designs enhancements. 4.3 Sustainable Investment Assets designs. 5. Hedging Risks aligned with Risk Appetite for Sustainable Savings and Retirement. 5.1. Hedging principles, processes and PandL attribution. 5.2. From Dynamic hedging to Semi-static hedging. 5.3. Managing hedging liquidity constraints. Bibliography.

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Book SynopsisThis is the first book to focus on the legal question of the incorporation of arbitration clauses, even though this issue constitutes a common problem that arises frequently in practice. Arbitration Clauses and Third Parties compares different branches of law, namely shipping, reinsurance, and construction, where the legal notion of incorporation is often implemented. It evaluates how the differences and peculiarities of the said branches of law impact the outcome of the incorporation of arbitration clauses and therefore why a âone size fits allâ approach should be avoided. The book provides both an in-depth legal analysis of the incorporation of arbitration clauses as well as the legal position of the third parties regarding arbitration agreements and a detailed evaluation of the relevant case law. It further offers a unique comparative analysis of English law and Singapore law with regards to the incorporation of arbitration clauses and features recent case law on Table of ContentsTable of Cases, Preface, Part I Muddying the Water: Incorporation of Arbitration Clauses in Shipping, Reinsurance, and Construction Chain Contracts, Chapter 1 The Foundations of Incorporation and Arbitration Clauses, Chapter 2 Incorporation of Charterparty Arbitration Clauses into Bills of Lading, Chapter 3 Incorporation of Arbitration Clauses into Reinsurance Contracts, Chapter 4 Construction Contracts and the Incorporation of Arbitration Clauses, Chapter 5 Singapore Law and Incorporation of Arbitration Clauses, PART II Not Incorporation – but a Close Analogy: Arbitration Clauses Binding Third Parties, Chapter 6 Arbitration Agreements and Third Parties, Index

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Book SynopsisRisk Analysis in Finance and Insurance, Third Edition presents an accessible yet comprehensive introduction to the main concepts and methods that transform risk management into a quantitative science. Considering the interdisciplinary nature of risk analysis, the author discusses many important ideas from stochastic analysis, mathematical finance and actuarial science in a simplified manner. He explores the interconnections among these disciplines and encourages readers toward further study of the subject. This edition continues to study risks associated with financial and insurance contracts, using an approach that estimates the value of future payments based on current financial, insurance, and other information.Features of the third editionâ 12 chapters instead of 8 of the 2nd edition. Two new chapters on Wiener process as a base for financial market modeling. Option pricing in the Bachelier model, the model of Black and Scholes, the Gram-Charlier model. American options and their pricing in the Black-Scholes modelâ Several new notions, topics and results that are not reflected yet in other textbooks, and even in monographs (Binomial model with constraints, detailed exposition of quantile hedging technique, Conditional Value at Risk, Range of Value at Risk, applications to equity-linked life insurance)â Can be regarded as a self-contained issue of courses on Mathematical Finance, Actuarial Science and Risk Managementâ Replete with new exercises, problems, hints and solutions

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Book SynopsisTrade Review‘Richard Liskov has performed a valuable service in condensing and simplifying insurance regulation for those who have little familiarity with the subject. His book is essential reading for any lawyer with a client who is in the U.S. insurance marketplace or wants to be, any law student with an interest in how financial services are regulated in the U.S., and any insurance professional whose company is, or someday may be, under U.S. regulation.’ -- James Corcoran, Former Superintendent of Insurance for the State of New York, US‘This book provides a comprehensive overview of insurance regulation in the US. It should be required reading for all US insurance regulatory attorneys (and US insurance regulators as well). Equally important, it will prove to be a valuable resource for EU and UK attorneys who have insurance clients doing business, or who want to do business, in the US.’ -- Frederic M. Garsson, Saul Ewing LLP, US‘Insurance touches each of us in our daily lives. Having served as New York’s Attorney General for fifteen years, I know that Richard Liskov’s book is a valuable guide for lawyers, law students and those engaged in the insurance business in the United States – or indeed anyone interested in how insurance is regulated. It should be on everyone’s bookshelf.’ -- Robert Abrams, Former Attorney General of New York, USTable of ContentsContents: 1 An overview of U.S. insurance regulation and some key definitions 2 The respective roles of state and federal governments in U.S. insurance regulation 3 How state insurance departments are organized and operate 4 How states define what “insurance” is and who is an insurer, and how states license insurance companies and insurance professionals 5 How states monitor the financial condition of licensed insurance companies 6 How U.S. state insurance regulators deal with financially troubled insurance companies 7 How state insurance regulators supervise the market conduct of insurance companies and insurance professionals 8 How the U.S. federal government and state insurance regulators supervise health insurance 9 U.S. insurance regulation heading into the global technological future Index

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Book SynopsisA one-stop guide for the theories, applications, and statistical methodologies essential to operational risk Providing a complete overview of operational risk modeling and relevant insurance analytics, Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk offers a systematic approach that covers the wide range of topics in this area. Written by a team of leading experts in the field, the handbook presents detailed coverage of the theories, applications, and models inherent in any discussion of the fundamentals of operational risk, with a primary focus on Basel II/III regulation, modeling dependence, estimation of risk models, and modeling the data elements. Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk begins with coverage on the four data elements used in operational risk framework as well as processing risk taxonomy. The book then goes further Table of ContentsPreface xvii Acronyms xix List of Distributions xxi 1 OpRisk in Perspective 1 1.1 Brief History 1 1.2 Risk-Based Capital Ratios for Banks 5 1.3 The Basic Indicator and Standardized Approaches for OpRisk 9 1.4 The Advanced Measurement Approach 10 1.4.1 Internal Measurement Approach 11 1.4.2 Score Card Approach 11 1.4.3 Loss Distribution Approach 12 1.4.4 Requirements for AMA 13 1.5 General Remarks and Book Structure 16 2 OpRisk Data and Governance 17 2.1 Introduction 17 2.2 OpRisk Taxonomy 17 2.2.1 Execution, Delivery, and Process Management 19 2.2.2 Clients, Products, and Business Practices 21 2.2.3 Business Disruption and System Failures 22 2.2.4 External Frauds 23 2.2.5 Internal Fraud 23 2.2.6 Employment Practices and Workplace Safety 24 2.2.7 Damage to Physical Assets 25 2.3 The Elements of the OpRisk Framework 25 2.3.1 Internal Loss Data 26 2.3.2 Setting a Collection Threshold and Possible Impacts 26 2.3.3 Completeness of Database (Under-reporting Events) 27 2.3.4 Recoveries and Near Misses 27 2.3.5 Time Period for Resolution of Operational Losses 28 2.3.6 Adding Costs to Losses 28 2.3.7 Provisioning Treatment of Expected Operational Losses 28 2.4 Business Environment and Internal Control Environment Factors (BEICFs) 29 2.4.1 Risk Control Self-Assessment (RCSA) 29 2.4.2 Key Risk Indicators 31 2.5 External Databases 33 2.6 Scenario Analysis 34 2.7 OpRisk Profile in Different Financial Sectors 37 2.7.1 Trading and Sales 37 2.7.2 Corporate Finance 38 2.7.3 Retail Banking 38 2.7.4 Insurance 39 2.7.5 Asset Management 40 2.7.6 Retail Brokerage 42 2.8 Risk Organization and Governance 43 2.8.1 Organization of Risk Departments 44 2.8.2 Structuring a Firm Wide Policy: Example of an OpRisk Policy 46 2.8.3 Governance 47 3 Using OpRisk Data for Business Analysis 48 3.1 Cost Reduction Programs in Financial Firms 49 3.2 Using OpRisk Data to Perform Business Analysis 53 3.2.1 The Risk of Losing Key Talents: OpRisk in Human Resources 53 3.2.2 OpRisk in Systems Development and Transaction Processing 54 3.3 Conclusions 58 4 Stress-Testing OpRisk Capital and the Comprehensive Capital Analysis and Review (CCAR) 59 4.1 The Need for Stressing OpRisk Capital Even Beyond 99.9% 59 4.2 Comprehensive Capital Review and Analysis (CCAR) 60 4.3 OpRisk and Stress Tests 68 4.4 OpRisk in CCAR in Practice 70 4.5 Reverse Stress Test 75 4.6 Stressing OpRisk Multivariate Models—Understanding the Relationship Among Internal Control Factors and Their Impact on Operational Losses 76 5 Basic Probability Concepts in Loss Distribution Approach 79 5.1 Loss Distribution Approach 79 5.2 Quantiles and Moments 85 5.3 Frequency Distributions 88 5.4 Severity Distributions 89 5.4.1 Simple Parametric Distributions 90 5.4.2 Truncated Distributions 92 5.4.3 Mixture and Spliced Distributions 93 5.5 Convolutions and Characteristic Functions 94 5.6 Extreme Value Theory 97 5.6.1 EVT—Block Maxima 98 5.6.2 EVT—Random Number of Losses 99 5.6.3 EVT—Threshold Exceedances 100 6 Risk Measures and Capital Allocation 102 6.1 Development of Capital Accords Base I, II and III 103 6.2 Measures of Risk 106 6.2.1 Coherent and Convex Risk Measures 107 6.2.2 Comonotonic Additive Risk Measures 109 6.2.3 Value-at-Risk 109 6.2.4 Expected Shortfall 114 6.2.5 Spectral Risk Measure 120 6.2.6 Higher-Order Risk Measures 122 6.2.7 Distortion Risk Measures 125 6.2.8 Elicitable Risk Measures 126 6.2.9 Risk Measure Accounting for Parameter Uncertainty 130 6.3 Capital Allocation 133 6.3.1 Coherent Capital Allocation 134 6.3.2 Euler Allocation 136 6.3.3 Standard Deviation 138 6.3.4 Expected Shortfall 139 6.3.5 Value-at-Risk 140 6.3.6 Allocation by Marginal Contributions 142 6.3.7 Numerical Example 143 7 Estimation of Frequency and Severity Models 146 7.1 Frequentist Estimation 146 7.1.1 Parameteric Maximum Likelihood Method 149 7.1.2 Maximum Likelihood Method for Truncated and Censored Data 151 7.1.3 Expectation Maximization and Parameter Estimation 152 7.1.4 Bootstrap for Estimation of Parameter Accuracy 156 7.1.5 Indirect Inference–Based Likelihood Estimation 157 7.2 Bayesian Inference Approach 159 7.2.1 Conjugate Prior Distributions 161 7.2.2 Gaussian Approximation for Posterior (Laplace Type) 161 7.2.3 Posterior Point Estimators 162 7.2.4 Restricted Parameters 163 7.2.5 Noninformative Prior 163 7.3 Mean Square Error of Prediction 164 7.4 Standard Markov Chain Monte Carlo (MCMC) Methods 166 7.4.1 Motivation for Markov Chain Methods 167 7.4.2 Metropolis–Hastings Algorithm 177 7.4.3 Gibbs Sampler 178 7.4.4 Random Walk Metropolis–Hastings within Gibbs 179 7.5 Standard MCMC Guidelines for Implementation 180 7.5.1 Tuning, Burn-in, and Sampling Stages 180 7.5.2 Numerical Error 185 7.5.3 MCMC Extensions: Reducing Sample Autocorrelation 187 7.6 Advanced MCMC Methods 188 7.6.1 Auxiliary Variable MCMC Methods: Slice Sampling 189 7.6.2 Generic Univariate Auxiliary Variable Gibbs Sampler: Slice Sampler 189 7.6.3 Adaptive MCMC 192 7.6.4 Riemann–Manifold Hamiltonian Monte Carlo Sampler (Automated Local Adaption) 196 7.7 Sequential Monte Carlo (SMC) Samplers and Importance Sampling 201 7.7.1 Motivating OpRisk Applications for SMC Samplers 202 7.7.2 SMC Sampler Methodology and Components 210 7.7.3 Incorporating Partial Rejection Control into SMC Samplers 216 7.7.4 Finite Sample (Nonasymptotic) Accuracy for Particle Integration 219 7.8 Approximate Bayesian Computation (ABC) Methods 220 7.9 OpRisk Estimation and Modeling for Truncated Data 223 7.9.1 Constant Threshold - Poisson Process 224 7.9.2 Negative Binomial and Binomial Frequencies 227 7.9.3 Ignoring Data Truncation 228 7.9.4 Threshold Varying in Time 232 7.9.5 Unknown and Stochastic Truncation Level 236 8 Model Selection and Goodness-of-Fit Testing for Frequency and Severity Models 238 8.1 Qualitative Model Diagnostic Tools 238 8.2 Tail Diagnostics 240 8.3 Information Criterion for Model Selection 242 8.3.1 Akaike Information Criterion for LDA Model Selection 242 8.3.2 Deviance Information Criterion 245 8.4 Goodness-of-Fit Testing for Model Choice (How to Account for Heavy Tails!) 246 8.4.1 Convergence Results of the Empirical Process for GOF Testing 247 8.4.2 Overview of Generic GOF Tests—Omnibus Distributional Tests 256 8.4.3 Kolmogorov–Smirnov Goodness-of-Fit Test and Weighted Variants: Testing in the Presence of Heavy Tails 260 8.4.4 Cramer-von-Mises Goodness-of-Fit Tests and Weighted Variants: Testing in the Presence of Heavy Tails 271 8.5 Bayesian Model Selection 283 8.5.1 Reciprocal Importance Sampling Estimator 284 8.5.2 Chib Estimator for Model Evidence 285 8.6 SMC Sampler Estimators of Model Evidence 286 8.7 Multiple Risk Dependence Structure Model Selection: Copula Choice 287 8.7.1 Approaches to Goodness-of-Fit Testing for Dependence Structures 293 8.7.2 Double Parameteric Bootstrap for Copula GOF 297 9 Flexible Parametric Severity Models: Basics 300 9.1 Motivation for Flexible Parametric Severity Loss Models 300 9.2 Context of Flexible Heavy-Tailed Loss Models in OpRisk and Insurance LDA Models 301 9.3 Empirical Analysis Justifying Heavy-Tailed Loss Models in OpRisk 303 9.4 Quantile Function Heavy-Tailed Severity Models 305 9.4.1 g-and-h Severity Model Family in OpRisk 311 9.4.2 Tail Properties of the g-and-h, g, h, and h–h Severity in OpRisk 321 9.4.3 Parameter Estimation for the g-and-h Severity in OpRisk 324 9.4.4 Bayesian Models for the g-and-h Severity in OpRisk 328 9.5 Generalized Beta Family of Heavy-Tailed Severity Models 333 9.5.1 Generalized Beta Family Type II Severity Models in OpRisk 333 9.5.2 Sub families of the Generalized Beta Family Type II Severity Models 336 9.5.3 Mixture Representations of the Generalized Beta Family Type II Severity Models 337 9.5.4 Estimation in the Generalized Beta Family Type II Severity Models 339 9.6 Generalized Hyperbolic Families of Heavy-Tailed Severity Models 340 9.6.1 Tail Properties and Infinite Divisibility of the Generalized Hyperbolic Severity Models 342 9.6.2 Subfamilies of the Generalized Hyperbolic Severity Models 344 9.6.3 Normal Inverse Gaussian Family of Heavy-Tailed Severity Models 346 9.7 Halphen Family of Flexible Severity Models: GIG and Hyperbolic 350 9.7.1 Halphen Type A: Generalized Inverse Gaussian Family of Flexible Severity Models 355 9.7.2 Halphen Type B and IB Families of Flexible Severity Models 361 10 Dependence Concepts 365 10.1 Introduction to Concepts in Dependence for OpRisk and Insurance 365 10.2 Dependence Modeling Within and Between LDA Model Structures 366 10.2.1 Where Can One Introduce Dependence Between LDA Model Structures? 368 10.2.2 Understanding Basic Impacts of Dependence Modeling Between LDA Components in Multiple Risks 369 10.3 General Notions of Dependence 372 10.4 Dependence Measures 387 10.4.1 Linear Correlation 390 10.4.2 Rank Correlation Measures 393 10.5 Tail Dependence Parameters, Functions, and Tail Order Functions 398 10.5.1 Tail Dependence Coefficients 398 10.5.2 Tail Dependence Functions and Orders 407 10.5.3 A Link Between Orthant Extreme Dependence and Spectral Measures: Tail Dependence 410 11 Dependence Models 414 11.1 Introduction to Parametric Dependence Modeling Through a Copula 414 11.2 Copula Model Families for OpRisk 422 11.2.1 Gaussian Copula 428 11.2.2 t-Copula 430 11.2.3 Archimedean Copulas 435 11.2.4 Archimedean Copula Generators and the Laplace Transform of a Non-Negative Random Variable 439 11.2.5 Archimedean Copula Generators, l1-Norm Symmetric Distributions and the Williamson Transform 441 11.2.6 Hierarchical and Nested Archimedean Copulae 452 11.2.7 Mixtures of Archimedean Copulae 454 11.2.8 Multivariate Archimedean Copula Tail Dependence 456 11.3 Copula Parameter Estimation in Two Stages: Inference for the Margins 457 11.3.1 MPLE: Copula Parameter Estimation 458 11.3.2 Inference Functions for Margins (IFM): Copula Parameter Estimation 459 12 Examples of LDA Dependence Models 462 12.1 Multiple Risk LDA Compound Poisson Processes and Lévy Copula 462 12.2 Multiple Risk LDA: Dependence Between Frequencies via Copula 468 12.3 Multiple Risk LDA: Dependence Between the k-th Event Times/Losses 468 12.3.1 Common Shock Processes 469 12.3.2 Max-Stable and Self-Chaining Copula Models 470 12.4 Multiple Risk LDA: Dependence Between Aggregated Losses via Copula 474 12.5 Multiple Risk LDA: Structural Model with Common Factors 477 12.6 Multiple Risk LDA: Stochastic and Dependent Risk Profiles 478 12.7 Multiple Risk LDA: Dependence and Combining Different Data Sources 482 12.7.1 Bayesian Inference Using MCMC 484 12.7.2 Numerical Example 485 12.7.3 Predictive Distribution 487 12.8 A Note on Negative Diversification and Dependence Modeling 489 13 Loss Aggregation 492 13.1 Analytic Solution 492 13.1.1 Analytic Solution via Convolutions 493 13.1.2 Analytic Solution via Characteristic Functions 494 13.1.3 Moments of Compound Distribution 496 13.1.4 Value-at-Risk and Expected Shortfall 499 13.2 Monte Carlo Method 499 13.2.1 Quantile Estimate 500 13.2.2 Expected Shortfall Estimate 502 13.3 Panjer Recursion 503 13.4 Panjer Extensions 509 13.5 Fast Fourier Transform 511 13.6 Closed-Form Approximation 514 13.7 Capital Charge Under Parameter Uncertainty 519 13.7.1 Predictive Distributions 520 13.7.2 Calculation of Predictive Distributions 521 13.8 Special Advanced Topics on Loss Aggregation 523 13.8.1 Discretisation Errors and Extrapolation Methods 524 13.8.2 Classes of Discrete Distributions: Discrete Infinite Divisibility and Discrete Heavy Tails 527 13.8.3 Recursions for Convolutions (Partial Sums) with Discretised Severity Distributions (Fixed n) 535 13.8.4 Alternatives to Panjer Recursions: Recursions for Compound Distributions with Discretised Severity Distributions 543 13.8.5 Higher Order Recursions for Discretised Severity Distributions in Compound LDA Models 545 13.8.6 Recursions for Discretised Severity Distributions in Compound Mixed Poisson LDA Models 547 13.8.7 Continuous Versions of the Panjer Recursion 550 14 Scenario Analysis 556 14.1 Introduction 556 14.2 Examples of Expert Judgments 559 14.3 Pure Bayesian Approach (Estimating Prior) 561 14.4 Expert Distribution and Scenario Elicitation: Learning from Bayesian Methods 563 14.5 Building Models for Elicited Opinions: Hierarchical Dirichlet Models 566 14.6 Worst-Case Scenario Framework 568 14.7 Stress Test Scenario Analysis 571 14.8 Bow-Tie Diagram 574 14.9 Bayesian Networks 576 14.9.1 Definition and Examples 577 14.9.2 Constructing and Simulating a Bayesian Net 580 14.9.3 Combining Expert Opinion and Data in a Bayesian Net 581 14.9.4 Bayesian Net and Operational Risk 582 14.10 Discussion 584 15 Combining Different Data Sources 585 15.1 Minimum Variance Principle 586 15.2 Bayesian Method to Combine Two Data Sources 588 15.2.1 Estimating Prior: Pure Bayesian Approach 590 15.2.2 Estimating Prior: Empirical Bayesian Approach 592 15.2.3 Poisson Frequency 593 15.2.4 The LogNormal Severity 597 15.2.5 Pareto Severity 601 15.3 Estimation of the Prior Using Data 606 15.3.1 The Maximum Likelihood Estimator 606 15.3.2 Poisson Frequencies 607 15.4 Combining Expert Opinions with External and Internal Data 609 15.4.1 Conjugate Prior Extension 610 15.4.2 Modeling Frequency: Poisson Model 611 15.4.3 LogNormal Model for Severities 618 15.4.4 Pareto Model 620 15.5 Combining Data Sources Using Credibility Theory 625 15.5.1 Bühlmann–Straub Model 626 15.5.2 Modeling Frequency 628 15.5.3 Modeling Severity 631 15.5.4 Numerical Example 633 15.5.5 Remarks and Interpretation 634 15.6 Nonparametric Bayesian Approach via Dirichlet Process 635 15.7 Combining Using Dempster–Shafer Structures and p-Boxes 638 15.7.1 Dempster–Shafer Structures and p-Boxes 639 15.7.2 Dempster’s Rule 641 15.7.3 Intersection Method 643 15.7.4 Envelope Method 644 15.7.5 Bounds for the Empirical Data Distribution 645 15.8 General Remarks 647 16 Multifactor Modeling and Regression for Loss Processes 649 16.1 Generalized Linear Model Regressions and the Exponential Family 649 16.1.1 Basic Components of a Generalized Linear Model Regression in the Exponential Family 650 16.1.2 Basis Function Regression 654 16.2 Maximum Likelihood Estimation for Generalized Linear Models 655 16.2.1 Iterated Weighted Least Squares Maximum Likelihood for Generalised Linear Models 655 16.2.2 Model Selection via the Deviance in a GLM Regression 657 16.3 Bayesian Generalized Linear Model Regressions and Regularization Priors 659 16.3.1 Bayesian Model Selection for Regularlized GLM Regression 665 16.4 Bayesian Estimation and Model Selection via SMC Samplers 666 16.4.1 Proposed SMC Sampler Solution 667 16.5 Illustrations of SMC Samplers Model Estimation and Selection for Bayesian GLM Regressions 668 16.5.1 Normal Regression Model 668 16.5.2 Poisson Regression Model 669 16.6 Introduction to Quantile Regression Methods for OpRisk 672 16.6.1 Nonparametric Quantile Regression Models 674 16.6.2 Parametric Quantile Regression Models 675 16.7 Factor Modeling for Industry Data 681 16.8 Multifactor Modeling under EVT Approach 683 17 Insurance and Risk Transfer: Products and Modeling 685 17.1 Motivation for Insurance and Risk Transfer in OpRisk 685 17.2 Fundamentals of Insurance Product Structures for OpRisk 688 17.3 Single Peril Policy Products for OpRisk 692 17.4 Generic Insurance Product Structures for OpRisk 694 17.4.1 Generic Deterministic Policy Structures 694 17.4.2 Generic Stochastic Policy Structures: Accounting for Coverage Uncertainty 700 17.5 Closed-Form LDA Models with Insurance Mitigations 705 17.5.1 Insurance Mitigation Under the Poisson-Inverse-Gaussian Closed-Form LDA Models 705 17.5.2 Insurance Mitigation and Poisson-α-Stable Closed-Form LDA Models 712 17.5.3 Large Claim Number Loss Processes: Generic Closed-Form LDA Models with Insurance Mitigation 719 17.5.4 Generic Closed-Form Approximations for Insured LDA Models 734 18 Insurance and Risk Transfer: Pricing Insurance-Linked Derivatives, Reinsurance, and CAT Bonds for OpRisk 750 18.1 Insurance-Linked Securities and CAT Bonds for OpRisk 751 18.1.1 Background on Insurance-Linked Derivatives and CAT Bonds for Extreme Risk Transfer 755 18.1.2 Triggers for CAT Bonds and Their Impact on Risk Transfer 760 18.1.3 Recent Trends in CAT Bonds 763 18.1.4 Management Strategies for Utilization of Insurance-Linked Derivatives and CAT Bonds in OpRisk 763 18.2 Basics of Valuation of ILS and CAT Bonds for OpRisk 765 18.2.1 Probabilistic Pricing Frameworks: Complete and Incomplete Markets, Real-World Pricing, Benchmark Approach, and Actuarial Valuation 771 18.2.2 Risk Assessment for Reinsurance: ILS and CAT Bonds 794 18.3 Applications of Pricing ILS and CAT Bonds 796 18.3.1 Probabilistic Framework for CAT Bond Market 796 18.3.2 Framework 1: Assuming Complete Market and Arbitrage-Free Pricing 798 18.3.3 Framework 2: Assuming Incomplete Arbitrage-Free Pricing 809 18.4 Sidecars, Multiple Peril Baskets, and Umbrellas for OpRisk 815 18.4.1 Umbrella Insurance 816 18.4.2 OpRisk Loss Processes Comprised of Multiple Perils 817 18.5 Optimal Insurance Purchase Strategies for OpRisk Insurance via Multiple Optimal Stopping Times 823 18.5.1 Examples of Basic Insurance Policies 826 18.5.2 Objective Functions for Rational and Boundedly Rational Insurees 828 18.5.3 Closed-Form Multiple Optimal Stopping Rules for Multiple Insurance Purchase Decisions 830 18.5.4 Aski-Polynomial Orthogonal Series Approximations 835 A Miscellaneous Definitions and List of Distributions 842 A.1 Indicator Function 842 A.2 Gamma Function 842 A.3 Discrete Distributions 842 A.3.1 Poisson Distribution 842 A.3.2 Binomial Distribution 843 A.3.3 Negative Binomial Distribution 843 A.3.4 Doubly Stochastic Poisson Process (Cox Process) 844 A.4 Continuous Distributions 844 A.4.1 Uniform Distribution 844 A.4.2 Normal (Gaussian) Distribution 844 A.4.3 Inverse Gaussian Distribution 845 A.4.4 LogNormal Distribution 845 A.4.5 Student’s t Distribution 846 A.4.6 Gamma Distribution 846 A.4.7 Weibull Distribution 846 A.4.8 Inverse Chi-Squared Distribution 847 A.4.9 Pareto Distribution (One-Parameter) 847 A.4.10 Pareto Distribution (Two-Parameter) 847 A.4.11 Generalized Pareto Distribution 848 A.4.12 Beta Distribution 848 A.4.13 Generalized Inverse Gaussian Distribution 849 A.4.14 d-variate Normal Distribution 849 A.4.15 d-variate t-Distribution 850 Bibliography 851 Index 892

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Book SynopsisReal case studies on insurance fraud written by real fraud examiners Insurance Fraud Casebook is a one-of-a-kind collection consisting of actual cases written by fraud examiners out in the field. These cases were hand selected from hundreds of submissions and together form a comprehensive picture of the many types of insurance fraudhow they are investigated, across industries and throughout the world. Entertaining and enlightening, the cases cover every type of insurance fraud, from medical fraud to counterfeiting. Each case outlines how the fraud was engineered, how it was investigated, and how perpetrators were brought to justice Written for fraud examiners, auditors, and insurance auditors Other titles by Wells: Fraud Fighter and Corporate Fraud Handbook, Third Edition Edited by Dr. Joseph T. Wells, the founder and Chairman of the Association of Certified Fraud Examiners (ACFE), the world''s leading anti-frTable of ContentsPreface ix Insurance Fraud Classification System xiii Chapter 1 Needles in a Paystack 1Charles Piper Chapter 2 The Good Doctor and Insurance Consultant 11Michael King Chapter 3 Greasing the Wheels in the Oil Business 21Abdulrazaq Al-Morjan Chapter 4 Living the Dream, Keeping Up the Lie 31Andries J. Brummer Chapter 5 Extinguishing an Arson Fraud 39Barry Zalma Chapter 6 Weakest Link in the Chain 47Angela Bisasor Chapter 7 Everyone Gets Hurt: A Study in Workers’ Compensation Fraud 57Michael Sputo Chapter 8 The Hazards of Doing Business with Friends 67Bill Maloney Chapter 9 There’s Gold in Them Thar Malls! 75Carl Knudson Chapter 10 Damsel in Diamonds 83Michael Skrypek Chapter 11 Operation Give and Go 93Edward P. Buttimore Chapter 12 An Inspection Is Worth a Thousand Photos 103Ed Madge Chapter 13 The Danger of Trusting Too Much 113Joe Bonk Chapter 14 The Twin Cities Machine 121Bob Weir Chapter 15 With Friends Like These . . . 131John Fifarek Chapter 16 All the Buzz 139Dalene Bartholomew Chapter 17 Getting Rich from the Elderly 149John R. Holley Chapter 18 Transparent Greed 159Joseph Licandro Chapter 19 Fault of Fortune 169Jyoti Khetarpal Chapter 20 Going Blind to Fraud 179Karen Wright Chapter 21 Going Against the Cartel 191Loftin C. Woodiel Chapter 22 Falling Prey to Online Charms 199Tina Hancock Chapter 23 Big Bills in Little Cuba 209Mark Starinsky Chapter 24 Rushing an Insurance Claim 217Peter Parillo Chapter 25 Ignorance Is Bliss, While It Lasts 229Rebecca Busch Chapter 26 The Name Game 239William D. Meader Chapter 27 Woo, Wed, Insure, Murder 249William P. Hight Chapter 28 Mystery Shopping for Fraud 259Stephen Pedneault Index 269

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Book SynopsisThe future of the insurance regulation begins now For those involved with the insurance industry, from investment professionals to policy makers, and regulators to legislators, tremendous change is coming. With insurance premiums constituting an ever-growing portion of annual U.S.Table of ContentsPreface Acknowledgments Chapter 2: Life Insurance’s Importance to American Families and Industry’s Concern about Regulation (Dirk Kempthorne) Chapter 3: Why Insurance Needs a Federal Regulator Option (Roger W. Ferguson, Jr.) Chapter 4: Observations on Insurance Regulation – Uniformity, Efficiency, and Financial Stability (Therese M. Vaughan) Chapter 5: Lessons Learned from AIG for Modernizing Insurance Regulation (Eric R. Dinallo) Chapter 6: Assessing the Vulnerability of the U.S. Life Insurance Industry (Anna Paulson, Thanases Plestis, Richard Rosen, Robert McMenamin and Zain Mohey-Dean) Appendix 6A: Details on Estimating Asset Risk Chapter 7: Systemic Risk and Regulation of the U.S. Insurance Industry (J. David Cummins and Mary A. Weiss) Chapter 8: Designation and Supervision of Insurance SIFIs (Scott E. Harrington and Alan B. Miller) Chapter 9: Is the Insurance Industry Systemically Risky? (Viral V Acharya and Matthew Richardson1) Chapter 10: Modernizing the Safety Net for Insurance Companies (John H. Biggs) Chapter 11: Policyholder Protection in the Wake of the Financial Crisis (Peter G. Gallanis) Appendix 11A: The Critical Role of “Prompt Corrective Action” Appendix 11B: Table of Relevant Guaranty Association Coverage Levels by State As of September 19, 2013 (Subject to Change) Chapter 12: Comparative Regulation of Market Intermediaries: Insights from the Indian Life Insurance Market (Santosh Anagol (Wharton), Shawn Cole (Harvard Business School), and Shayak Sarkar (Harvard University)) About the Authors About the Website Index

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Book SynopsisA value management framework designed specifically for banking and insurance The Value Management Handbook is a comprehensive, practical reference written specifically for bank and insurance valuation and value management. Spelling out how the finance and risk functions add value in their respective spheres, this book presents a framework for measuring and more importantly, influencing the value of the firm from the position of the CFO and CRO. Case studies illustrating value-enhancing initiatives are designed to help Heads of Strategy offer CEOs concrete ideas toward creating more value, and discussion of hard and soft skills put CFOs and CROs in a position to better influence strategy and operations. The challenge of financial services valuation is addressed in terms of the roles of risk and capital, and business-specific value trees demonstrate the source of successful value enhancement initiatives. While most value management resources fail to adequately Table of ContentsList of Abbreviations xiii Preface xvii Acknowledgments xix About the Author xxiii Part One Introduction 1 Chapter 1 Why is Value Management Important? 3 Better Information 3 Better Insights 6 Better Decisions 8 Why Shareholder Value? 12 Chapter 2 How do CFOs and CROs Add Value? 15 The Evolution of the Corporate Center as “Shareholder Surrogate” 15 The Implications for the CFO 20 The Implications for the CRO 24 Part Two Better Information – Measuring Value 29 Chapter 3 RAPMs – The Industry Standard 31 What Makes Financial Services Unique? 31 What do RAPMs do and How? 34 The RAPM (R)evolution 37 Three RAPMs for Three Distinct Purposes 41 Linking Directly to Shareholder Value 46 Insurance Example 49 Banking Example 50 Chapter 4 Two Challenges in Using RAPMs 51 Do RAPMs Influence Strategy? 51 Do RAPMs Give the Right Signals? 55 Chapter 5 Valuing Financial Services – The Theory 71 What Determines Share Value? Market Multiples, RoE and Growth 71 But What Determines Market Multiples? 73 Why a Market-Consistent Approach? 77 Value: Where it Comes from and How to Create More of it 80 Chapter 6 Valuing Financial Services – The Evidence 85 Evidence from the Insurance Industry 85 Evidence from Banking 96 Is it Just me or are Others Thinking the Same Thing? 98 Chapter 7 Market-Consistent Valuation for Insurers 101 Introduction to Fair Valuation for Insurers 101 Calculating Traditional Embedded Value 104 European Embedded Value 106 Market Consistent Embedded Value (MCEV) 109 How is MCEV Calculated in Practice? 115 From MCEV to MVBS 120 Final Comments: Whither MCEV? 122 Part Three Better Insights – Managing Value 125 Chapter 8 Property and Casualty Insurance 127 History and Economic Rationale 127 From Principles to Rules of the Game 133 From Rules to the Valuation of PC Businesses 135 PC KPIs: Understanding and Managing Value 140 Chapter 9 Life and Health Insurance 151 History and Economic Rationale 151 From Principles to “Rules of the Game” 163 LH Valuation 167 Understanding Value Creation: Capital Intensity and Financial Risk Taking 171 Chapter 10 Banking 189 History 189 Products 195 Economic Rationale 197 From Principles to “Rules of the Game” 199 From “Rules” to Value 201 Chapter 11 Achieving Profitable Growth 211 Rules of the Game and KPIs 211 Management Actions – Three Horizons of Growth 217 Horizon 1 – Increasing Sales Productivity 218 Horizon 1 – Going Multi-channel 221 Horizon 1 – Getting More out of Existing Customers; cross sell, big data and customer loyalty 224 Horizon 1 – Managing the Customer Portfolio Skew 228 Horizon 2 – Anticipating Mega-trends 230 Horizon 2 – Exploiting Adjacencies 232 Horizon 2 – Transformational and Bolt-on Acquisitions 234 Horizon 3 – Creative Disruptions 238 Chapter 12 Achieving Operating Efficiency 241 The Importance of Operating Efficiency 242 Rules of the Game 248 Pay Less: Optimize Procurement 249 Pay Less: From Business Process Redesign to Outsourcing 250 Use Less, But More Effectively: Digitize and Automate 253 Use Less, But More Effectively: Re-engineer the Product Portfolio 254 Use Less, But More Effectively: Managing Acquisition Expenses 257 Part Four Better Decisions – Capital, Balance Sheet and Risk Management 261 Chapter 13 Corporate Strategy and Capital Allocation 263 Corporate Strategy, Capital Allocation and Performance Management 263 Capital Allocation: The Capital Budget, from Sources to Uses of Capital 265 Capital Allocation: Optimizing the Corporate Portfolio 273 Capital Allocation: Aligning Financial Resources within Constraints 278 Chapter 14 Strategic Planning and Performance Management 285 What is Strategic Planning? 285 Why does Strategic Planning Fail and What can be done About it? 295 Corporate Strategy 302 Chapter 15 Balance Sheet Management 311 Balance Sheet Management Activities 311 The Asset/Liability Committee (ALCO) Mandate and Agenda 314 The Asset/Liability Management (ALM) Unit 323 The Insurer ALM-Investment Value Chain 330 The Treasury Function 339 Chapter 16 The Economics of Asset/Liability Management 345 The Role of ALM Earnings 345 The Risks: Some Spectacular ALM Failures 349 The Returns: Are Shareholders Willing to Pay a Premium or a Discount? 361 Chapter 17 The Practical Aspects of Asset/Liability Management 371 ALM Performance and Risk Measures 372 Calculating Funds Transfer Prices (FTPs) 385 Measuring Alpha 406 Chapter 18 Cash and Liquidity Management 413 Managing Funding Liquidity Risk 413 What Happens if it Goes Wrong? 416 Measuring Funding Liquidity Risk 420 Chapter 19 Managing the Capital and Funding Structure 431 Capital Funding Management 431 Determining the Optimal Capital Structure 436 The Empirical Reality: What Determines Capital Structure? 446 Chapter 20 Risk Management 451 Enterprise Risk Management 451 Taking the Right Decisions 460 The Role of Culture 463 Chapter 21 Risk Governance and Organization 477 Risk Governance Principles 477 Role of the Board and Management 478 Three-Line-of-Defense Model 480 The Risk Function 484 Chapter 22 Risk Identification and Evaluation 491 From Risk Identification to Evaluation 491 Data-Driven Approaches 497 Evaluation-Based Approaches 499 Building a Resilient Organization 507 Chapter 23 Risk Underwriting – Strategy and Governance 513 Underwriting Context 513 Underwriting Strategy 518 Underwriting Governance 522 Chapter 24 Risk Underwriting – Technical Tools 527 Retail Segment: “Scoring” Models 527 Commercial Lines: Leveraging Expert Judgment 535 Underwriting Structured Solutions 541 Underwriting Controls, Validation and Learning 542 Chapter 25 Risk Underwriting – From Technical Pricing to Value Maximization 549 Technical Production Cost: RAPM Pricing 549 From Technical Pricing to Optimal Price 558 Chapter 26 Managing Operational and Reputational Risks 571 Defining Operational Risk 571 Managing Operational Risk 581 Chapter 27 Risk and Limit Controlling 589 Risk Reporting 589 An Effective Risk Limit Framework 601 Final Thoughts on Risk and Limit Reporting 606 Appendices Appendix A: Market Multiple Approaches 609 Appendix B: Derivation of Steady-State Valuation Multiples 613 Appendix C: Valuing Banks and Insurers: The Link Between Value and New Business and Investment RAPM 621 Appendix D: Beyond Debt and Equity 629 Glossary 641 References 653 Index 675

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Book SynopsisThe definitive and timeless guide to the principles of banking and finance, addressing and meeting the challenges of competition, strategy, regulation and the digital age.Table of ContentsForeword xvii Paul Fisher Foreword xxi Professor Alexander Lipton Foreword xxiii Rundheersing Bheenick Preface xxv Acknowledgments xxxi About the Author xxxix List of Extract Book Titles xli Part I Principles Of Banking, Finance And Financial Products 3 Chapter 1 A Primer on Banking, Finance and Financial Instruments 5 Chapter 2 Derivative Instruments and Hedging 121 Chapter 3 The Yield Curve 273 Chapter 4 Eurobonds, Securitisation and Structured Finance 345 Part II Bank Regulatory Capital and Risk Management 407 Chapter 5 Banks and Risk Management 409 Chapter 6 Banks and Credit Risk 465 Chapter 7 Understanding and Managing Operational Risk 523 Chapter 8 Regulatory Capital and the Capital Adequacy Assessment Process 541 Chapter 9 Financial Statements, Ratio Analysis, and Credit Analysis 617 Part III Bank Treasury and Strategic Asset–Liability Management 653 Chapter 10 The Bank Treasury Operating Model and ALCO Governance Process Best-Practice 655 Chapter 11 Bank Asset–Liability Management (ALM) and “Strategic ALM” 697 Chapter 12 Liquidity and Funding: Policy, Management, and Risk Management 795 Chapter 13 Market Risk and Non-Traded Market Risk (Interest-Rate Risk in the Banking Book) 971 Chapter 14 The Future of Bank Treasury and Balance Sheet Risk Management 1033 Chapter 15 Regulatory Reporting and Principles of Policy Documentation 1055 Part IV The Future of Banking: Strategy, Governance and Culture 1087 Chapter 16 Strategy Setting: Principles for Sustained Bank Viability 1091 Chapter 17 Present and Future Principles of Governance and Culture 1147 Chapter 18 Present and Future Principles of Banking: Business Model and Customer Service 1187 Part V Case Studies: Analysis, Coherent Advice and Problem Solving 1211 Chapter 19 Case Studies: Analysis, Coherent Advice and Problem Solving 1213 Chapter 20 Guide to the Website 1245 Afterword 1251 Index 1253

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Book SynopsisThe business guide to Big Data in insurance, with practical application insight Big Data and Analytics for Insurers is the industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. Written from a non-IT perspective, this book focusses less on the architecture and technical details, instead providing practical guidance on translating analytics into target delivery. The discussion examines implementation, interpretation, and application to show you what Big Data can do for your business, with insights and examples targeted specifically to the insurance industry. From fraud analytics in claims management, to customer analytics, to risk analytics in Solvency 2, comprehensive coverage presented in accessible language makes this guide an invaluable resource for any insurance professional. The insurance industry is heavily dependent on data, and the advent of Big Data and analytics represents a major advancTrade Review"..essential reading for insurance management of all levels and specialities, for students, and for IT suppliers to the insurance industry." (Only Strategic, December 2016)Table of ContentsPreface xi Acknowledgements xiii About the Author xv CHAPTER 1 Introduction – The New ‘Real Business’ 1 1.1 On the Point of Transformation 2 1.1.1 Big Data Defined by Its Characteristics 3 1.1.2 The Hierarchy of Analytics, and how Value is Obtained from Data 6 1.1.3 Next Generation Analytics 7 1.1.4 Between the Data and the Analytics 9 1.2 Big Data and Analytics for All Insurers 10 1.2.1 Three Key Imperatives 10 1.2.2 The Role of Intermediaries 13 1.2.3 Geographical Perspectives 14 1.2.4 Analytics and the Internet of Things 15 1.2.5 Scale Benefit – or Size Disadvantage? 15 1.3 How Do Analytics Actually Work? 17 1.3.1 Business Intelligence 18 1.3.2 Predictive Analytics 20 1.3.3 Prescriptive Analytics 22 1.3.4 Cognitive Computing 23 Notes 24 CHAPTER 2 Analytics and the Office of Finance 25 2.1 The Challenges of Finance 26 2.2 Performance Management and Integrated Decision-making 27 2.3 Finance and Insurance 27 2.4 Reporting and Regulatory Disclosure 29 2.5 GAAP and IFRS 29 2.6 Mergers, Acquisitions, and Divestments 30 2.7 Transparency, Misrepresentation, The Securities Act and ‘SOX’ 31 2.8 Social Media and Financial Analytics 32 2.9 Sales Management and Distribution Channels 33 2.9.1 Agents and Producers 34 2.9.2 Distribution Management 35 Notes 36 CHAPTER 3 Managing Financial Risk across the Insurance Enterprise 37 3.1 Solvency II 37 3.2 Solvency II, Cloud Computing and Shared Services 40 3.3 ‘Sweating the Assets’ 40 3.4 Solvency II and IFRS 41 3.5 The Changing Role of the CRO 42 3.6 CRO as the Customer Advocate 45 3.7 Analytics and the Challenge of Unpredictability 45 3.8 The Importance of Reinsurance 46 3.9 Risk Adjusted Decision-Making 46 Notes 49 CHAPTER 4 Underwriting 51 4.1 Underwriting and Big Data 52 4.2 Underwriting for Specialist Lines 54 4.3 Telematics and User-Based Insurance as an Underwriting Tool 55 4.4 Underwriting for Fraud Avoidance 56 4.5 Analytics and Building Information Management (BIM) 57 Notes 58 CHAPTER 5 Claims and the ‘Moment of Truth’ 61 5.1 ‘Indemnity’ and the Contractual Entitlement 61 5.2 Claims Fraud 62 5.2.1 Opportunistic Fraud 63 5.2.2 Organized Fraud 64 5.3 Property Repairs and Supply Chain Management 66 5.4 Auto Repairs 71 5.5 Transforming the Handling of Complex Domestic Claims 73 5.5.1 The Digital Investigator 73 5.5.2 Potential Changes in the Claims Process 75 5.5.3 Reinvention of the Supplier Ecosystem 76 5.6 Levels of Inspection 77 5.6.1 Reserving 78 5.6.2 Business Interruption 79 5.6.3 Subrogation 80 5.7 Motor Assessing and Loss Adjusting 81 5.7.1 Motor Assessing 82 5.7.2 Loss Adjusting 83 5.7.3 Property Claims Networks 84 5.7.4 Adjustment of Cybersecurity Claims 87 5.7.5 The Demographic Time Bomb in Adjusting 87 Notes 88 CHAPTER 6 Analytics and Marketing 91 6.1 Customer Acquisition and Retention 93 6.2 Social Media Analytics 96 6.3 Demography and How Population Matters 97 6.4 Segmentation 98 6.5 Promotion Strategy 100 6.6 Branding and Pricing 100 6.7 Pricing Optimization 101 6.8 The Impact of Service Delivery on Marketing Success 102 6.9 Agile Development of New Products 103 6.10 The Challenge of ‘Agility’ 104 6.11 Agile vs Greater Risk? 105 6.12 The Digital Customer, Multi- and Omni-Channel 105 6.13 The Importance of the Claims Service in Marketing 106 Notes 107 CHAPTER 7 Property Insurance 109 7.1 Flood 109 7.1.1 Predicting the Cost and Likelihood of Flood Damage 110 7.1.2 Analytics and the Drying Process 111 7.2 Fire 112 7.2.1 Predicting Fraud in Fire Claims 113 7.3 Subsidence 115 7.3.1 Prediction of Subsidence 116 7.4 Hail 119 7.4.1 Prediction of Hail Storms 120 7.5 Hurricane 121 7.5.1 Prediction of Hurricane Damage 121 7.6 Terrorism 122 7.6.1 Predicting Terrorism Damage 123 7.7 Claims Process and the ‘Digital Customer’ 124 Notes 125 CHAPTER 8 Liability Insurance and Analytics 127 8.1 Employers’ Liability and Workers Compensation 127 8.1.1 Fraud in Workers Compensation Claims 128 8.1.2 Employers’ Liability Cover 130 8.1.3 Effective Triaging of EL Claims 130 8.2 Public Liability 131 8.3 Product Liability 132 8.4 Directors and Officers Liability 133 Notes 134 CHAPTER 9 Life and Pensions 135 9.1 How Life Insurance Differs from General Insurance 136 9.2 Basis of Life Insurance 137 9.3 Issues of Mortality 138 9.4 The Role of Big Data in Mortality Rates 139 9.5 Purchasing Life Insurance in a Volatile Economy 140 9.6 How Life Insurers Can Engage with the Young 141 9.7 Life and Pensions for the Older Demographic 142 9.8 Life and Pension Benefits in the Digital Era 143 9.9 Life Insurance and Bancassurers 145 Notes 147 CHAPTER 10 The Importance of Location 149 10.1 Location Analytics 149 10.1.1 The New Role of the Geo-Location Expert 149 10.1.2 Sharing Location Information 150 10.1.3 Geocoding 150 10.1.4 Location Analytics in Fraud Investigation 151 10.1.5 Location Analytics in Terrorism Risk 152 10.1.6 Location Analytics and Flooding 152 10.1.7 Location Analytics, Cargo and Theft 154 10.2 Telematics and User-Based Insurance (‘UBI’) 155 10.2.1 History of Telematics 155 10.2.2 Telematics in Fraud Detection 157 10.2.3 What is the Impact on Motor Insurers? 157 10.2.4 Telematics and Vehicle Dashboard Design 158 10.2.5 Telematics and Regulation 159 10.2.6 Telematics – More than Technology 160 10.2.7 User-Based Insurance in Other Areas 161 10.2.8 Telematics in Commercial Insurances 162 Notes 164 CHAPTER 11 Analytics and Insurance People 167 11.1 Talent Management 167 11.1.1 The Need for New Competences 168 11.1.2 Essential Qualities and Capabilities 169 11.2 Talent, Employment and the Future of Insurance 173 11.2.1 Talent Analytics and the Challenge for Human Resources 173 11.3 Learning and Knowledge Transfer 174 11.3.1 Reading Materials 175 11.3.2 Formal Qualifications and Structured Learning 175 11.3.3 Face-to-Face Training 176 11.3.4 Social Media and Technology 177 11.4 Leadership and Insurance Analytics 178 11.4.1 Knowledge and Power 179 11.4.2 Leadership and Influence 179 11.4.3 Analytics and the Impact on Employees 181 11.4.4 Understanding Employee Resistance 182 Notes 184 CHAPTER 12 Implementation 185 12.1 Culture and Organization 188 12.1.1 Communication and Evangelism 192 12.1.2 Stakeholders’ Vision of the Future 193 12.2 Creating a Strategy 193 12.2.1 Program Sponsorship 194 12.2.2 Building a Project Program 195 12.2.3 Stakeholder Management 197 12.2.4 Recognizing Analytics as a Tool of Empowerment 198 12.2.5 Creation of Open and Trusting Relationships 199 12.2.6 Developing a Roadmap 200 12.2.7 Implementation Flowcharts 202 12.3 Managing the Data 202 12.3.1 Master Data Management 203 12.3.2 Data Governance 203 12.3.3 Data Quality 204 12.3.4 Data Standardization 204 12.3.5 Storing and Managing Data 205 12.3.6 Security 207 12.4 Tooling and Skillsets 207 12.4.1 Certification and Qualifications 208 12.4.2 Competences 208 Notes 209 CHAPTER 13 Visions of the Future? 211 13.1 Auto 2025 211 13.2 The Digital Home in 2025 – ‘Property Telematics’ 214 13.3 Commercial Insurance – Analytically Transformed 218 13.4 Specialist Risks and Deeper Insight 220 13.5 2025: Transformation of the Life and Pensions Industry 221 13.6 Outsourcing and the Move Away from Non-Core Activities 223 13.7 The Rise of the Super Supplier 224 Notes 225 CHAPTER 14 Conclusions and Reflections 227 14.1 The Breadth of the Challenge 229 14.2 Final Thoughts 230 Notes 231 APPENDIX A Recommended Reading 233 APPENDIX B Data Summary of Expectancy of Reaching 100 235 APPENDIX C Implementation Flowcharts 239 APPENDIX D Suggested Insurance Websites 265 APPENDIX E Professional Insurance Organizations 267 Index 269

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