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The International Series on Actuarial Science, published by Cambridge University Press in conjunction with the Institute and Faculty of Actuaries, contains textbooks for students taking courses in or related to actuarial science, as well as more advanced works designed for continuing professional development or for describing and synthesizing research. The series is a vehicle for publishing books that reflect changes and developments in the curriculum, that encourage the introduction of courses on actuarial science in universities, and that show how actuarial science can be used in all areas where there is long-term financial risk.

  • Editorial Boards: Christopher Daykin, Independent Consultant and Actuary, Angus Macdonald, Heriot-Watt University

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19 results in International Series on Actuarial Science

Nonlife Actuarial Models
  • Theory, Methods and Evaluation
  • 2nd edition
  • Yiu-Kuen Tse
  • Published online:
    07 July 2023
    Print publication:
    25 May 2023
  • Actuaries must pass exams, but more than that: they must put knowledge into practice. This coherent book supports the Society of Actuaries' short-term actuarial mathematics syllabus while emphasizing the concepts and practical application of nonlife actuarial models. A class-tested textbook for undergraduate courses in actuarial science, it is also ideal for those approaching their professional exams. Key topics covered include loss modelling, risk and ruin theory, credibility theory and applications, and empirical implementation of loss models. Revised and updated to reflect curriculum changes, this second edition includes two brand new chapters on loss reserving and ratemaking. R replaces Excel as the computation tool used throughout – the featured R code is available on the book's webpage, as are lecture slides. Numerous examples and exercises are provided, with many questions adapted from past Society of Actuaries exams.

Quantitative Enterprise Risk Management
  • Mary R. Hardy, David Saunders
  • Published online:
    28 July 2022
    Print publication:
    05 May 2022
  • This well-balanced introduction to enterprise risk management integrates quantitative and qualitative approaches and motivates key mathematical and statistical methods with abundant real-world cases - both successes and failures. Worked examples and end-of-chapter exercises support readers in consolidating what they learn. The mathematical level, which is suitable for graduate and senior undergraduate students in quantitative programs, is pitched to give readers a solid understanding of the concepts and principles involved, without diving too deeply into more complex theory. To reveal the connections between different topics, and their relevance to the real world, the presentation has a coherent narrative flow, from risk governance, through risk identification, risk modelling, and risk mitigation, capped off with holistic topics - regulation, behavioural biases, and crisis management - that influence the whole structure of ERM. The result is a text and reference that is ideal for graduate and senior undergraduate students, risk managers in industry, and anyone preparing for ERM actuarial exams.

Actuarial Mathematics for Life Contingent Risks
  • 3rd edition
  • David C. M. Dickson, Mary R. Hardy, Howard R. Waters
  • Published online:
    30 April 2020
    Print publication:
    19 December 2019
  • The substantially updated third edition of the popular Actuarial Mathematics for Life Contingent Risks is suitable for advanced undergraduate and graduate students of actuarial science, for trainee actuaries preparing for professional actuarial examinations, and for life insurance practitioners who wish to increase or update their technical knowledge. The authors provide intuitive explanations alongside mathematical theory, equipping readers to understand the material in sufficient depth to apply it in real-world situations and to adapt their results in a changing insurance environment. Topics include modern actuarial paradigms, such as multiple state models, cash-flow projection methods and option theory, all of which are required for managing the increasingly complex range of contemporary long-term insurance products. Numerous exam-style questions allow readers to prepare for traditional professional actuarial exams, and extensive use of Excel ensures that readers are ready for modern, Excel-based exams and for the actuarial work environment. The Solutions Manual (ISBN 9781108747615), available for separate purchase, provides detailed solutions to the text's exercises.

Modelling Mortality with Actuarial Applications
  • Angus S. Macdonald, Stephen J. Richards, Iain D. Currie
  • Published online:
    28 April 2018
    Print publication:
    03 May 2018
  • Actuaries have access to a wealth of individual data in pension and insurance portfolios, but rarely use its full potential. This book will pave the way, from methods using aggregate counts to modern developments in survival analysis. Based on the fundamental concept of the hazard rate, Part I shows how and why to build statistical models, based on data at the level of the individual persons in a pension scheme or life insurance portfolio. Extensive use is made of the R statistics package. Smooth models, including regression and spline models in one and two dimensions, are covered in depth in Part II. Finally, Part III uses multiple-state models to extend survival models beyond the simple life/death setting, and includes a brief introduction to the modern counting process approach. Practising actuaries will find this book indispensable, and students will find it helpful when preparing for their professional examinations.

Claims Reserving in General Insurance
  • David Hindley
  • Published online:
    27 October 2017
    Print publication:
    26 October 2017
  • This is a comprehensive and accessible reference source that documents the theoretical and practical aspects of all the key deterministic and stochastic reserving methods that have been developed for use in general insurance. Worked examples and mathematical details are included, along with many of the broader topics associated with reserving in practice. The key features of reserving in a range of different contexts in the UK and elsewhere are also covered. The book contains material that will appeal to anyone with an interest in claims reserving. It can be used as a learning resource for actuarial students who are studying the relevant parts of their professional bodies' examinations, as well as by others who are new to the subject. More experienced insurance and other professionals can use the book to refresh or expand their knowledge in any of the wide range of reserving topics covered in the book.

Financial Enterprise Risk Management
  • 2nd edition
  • Paul Sweeting
  • Published online:
    12 August 2017
    Print publication:
    07 August 2017
  • This comprehensive, yet accessible, guide to enterprise risk management for financial institutions contains all the tools needed to build and maintain an ERM framework. It discusses the internal and external contexts with which risk management must be carried out, and it covers a range of qualitative and quantitative techniques that can be used to identify, model and measure risks. This new edition has been thoroughly updated to reflect new legislation and the creation of the Financial Conduct Authority and the Prudential Regulation Authority. It includes new content on Bayesian networks, expanded coverage of Basel III, a revised treatment of operational risk and a fully revised index. Over 100 diagrams are used to illustrate the range of approaches available, and risk management issues are highlighted with numerous case studies. This book also forms part of the core reading for the UK actuarial profession's specialist technical examination in enterprise risk management, ST9.

Insurance Risk and Ruin
  • 2nd edition
  • David C. M. Dickson
  • Published online:
    17 November 2016
    Print publication:
    27 October 2016
  • The focus of this book is on the two major areas of risk theory: aggregate claims distributions and ruin theory. For aggregate claims distributions, detailed descriptions are given of recursive techniques that can be used in the individual and collective risk models. For the collective model, the book discusses different classes of counting distribution, and presents recursion schemes for probability functions and moments. For the individual model, the book illustrates the three most commonly applied techniques. Beyond the classical topics in ruin theory, this new edition features an expanded section covering time of ruin problems, Gerber–Shiu functions, and the application of De Vylder approximations. Suitable for a first course in insurance risk theory and extensively classroom tested, the book is accessible to readers with a solid understanding of basic probability. Numerous worked examples are included and each chapter concludes with exercises for which complete solutions are provided.

Predictive Modeling Applications in Actuarial Science
  • Volume 2, Case Studies in Insurance
  • Edited by Edward W. Frees, Glenn Meyers, Richard A. Derrig
  • Published online:
    05 August 2016
    Print publication:
    27 July 2016
  • Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries routinely apply in insurance and other risk-management applications. 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 to gain a competitive advantage in situations with complex data. Volume 2 examines applications of predictive modeling. Where Volume 1 developed the foundations of predictive modeling, Volume 2 explores practical uses for techniques, focusing on property and casualty insurance. Readers are exposed to a variety of techniques in concrete, real-life contexts that demonstrate their value and the overall value of predictive modeling, for seasoned practicing analysts as well as those just starting out.

Predictive Modeling Applications in Actuarial Science
  • Volume 1, Predictive Modeling Techniques
  • Edited by Edward W. Frees, Richard A. Derrig, Glenn Meyers
  • Published online:
    05 August 2014
    Print publication:
    28 July 2014
  • 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 practising analysts who would like an overview of advanced statistical topics that are particularly relevant in actuarial practice. Predictive Modeling Applications in Actuarial Science emphasizes lifelong 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.

Computation and Modelling in Insurance and Finance
  • Erik Bølviken
  • Published online:
    05 May 2014
    Print publication:
    10 April 2014
  • Focusing on what actuaries need in practice, this introductory account provides readers with essential tools for handling complex problems and explains how simulation models can be created, used and re-used (with modifications) in related situations. The book begins by outlining the basic tools of modelling and simulation, including a discussion of the Monte Carlo method and its use. Part II deals with general insurance and Part III with life insurance and financial risk. Algorithms that can be implemented on any programming platform are spread throughout and a program library written in R is included. Numerous figures and experiments with R-code illustrate the text. The author's non-technical approach is ideal for graduate students, the only prerequisites being introductory courses in calculus and linear algebra, probability and statistics. The book will also be of value to actuaries and other analysts in the industry looking to update their skills.

Risk Modelling in General Insurance
  • From Principles to Practice
  • Roger J. Gray, Susan M. Pitts
  • Published online:
    05 August 2012
    Print publication:
    28 June 2012
  • Knowledge of risk models and the assessment of risk is a fundamental part of the training of actuaries and all who are involved in financial, pensions and insurance mathematics. This book provides students and others with a firm foundation in a wide range of statistical and probabilistic methods for the modelling of risk, including short-term risk modelling, model-based pricing, risk-sharing, ruin theory and credibility. It covers much of the international syllabuses for professional actuarial examinations in risk models, but goes into further depth, with worked examples, exercises and detailed case studies. The authors also use the statistical package R to demonstrate how simple code and functions can be used profitably in an actuarial context. The authors' engaging and pragmatic approach, balancing rigour and intuition and developed over many years of teaching the subject, makes this book ideal for self-study or for students taking courses in risk modelling.

Solutions Manual for Actuarial Mathematics for Life Contingent Risks
  • David C. M. Dickson, Mary R. Hardy, Howard R. Waters
  • Published online:
    05 June 2012
    Print publication:
    26 March 2012
  • This must-have manual provides solutions to all exercises in Dickson, Hardy and Waters' Actuarial Mathematics for Life Contingent Risks, the groundbreaking text on the modern mathematics of life insurance that is the required reading for the SOA Exam MLC and also covers more or less the whole syllabus for the UK Subject CT5 exam. The more than 150 exercises are designed to teach skills in simulation and projection through computational practice, and the solutions are written to give insight as well as exam preparation. Companion spreadsheets are available for free download to show implementation of computational methods.

Financial Enterprise Risk Management
  • Paul Sweeting
  • Published online:
    07 October 2011
    Print publication:
    01 September 2011
  • Financial Enterprise Risk Management provides all the tools needed to build and maintain a comprehensive ERM framework. As well as outlining the construction of such frameworks, it discusses the internal and external contexts within which risk management must be carried out. It also covers a range of qualitative and quantitative techniques that can be used to identify, model and measure risks, and describes a range of risk mitigation strategies. Over 100 diagrams are used to help describe the range of approaches available, and risk management issues are further highlighted by various case studies. A number of proprietary, advisory and mandatory risk management frameworks are also discussed, including Solvency II, Basel III and ISO 31000:2009. This book is an excellent resource for actuarial students studying for examinations, for risk management practitioners and for any academic looking for an up-to-date reference to current techniques.

Regression Modeling with Actuarial and Financial Applications
  • Edward W. Frees
  • Published online:
    05 June 2012
    Print publication:
    30 November 2009
  • This text gives budding actuaries and financial analysts a foundation in multiple regression and time series. They will learn about these statistical techniques using data on the demand for insurance, lottery sales, foreign exchange rates, and other applications. Although no specific knowledge of risk management or finance is presumed, the approach introduces applications in which statistical techniques can be used to analyze real data of interest. In addition to the fundamentals, this book describes several advanced statistical topics that are particularly relevant to actuarial and financial practice, including the analysis of longitudinal, two-part (frequency/severity), and fat-tailed data. Datasets with detailed descriptions, sample statistical software scripts in 'R' and 'SAS', and tips on writing a statistical report, including sample projects, can be found on the book's Web site: http://research.bus.wisc.edu/RegActuaries.

Actuarial Mathematics for Life Contingent Risks
  • David C. M. Dickson, Mary R. Hardy, Howard R. Waters
  • Published online:
    05 June 2012
    Print publication:
    24 September 2009
  • How can actuaries best equip themselves for the products and risk structures of the future? Using the powerful framework of multiple state models, three leaders in actuarial science give a modern perspective on life contingencies, and develop and demonstrate a theory that can be adapted to changing products and technologies. The book begins traditionally, covering actuarial models and theory, and emphasizing practical applications using computational techniques. The authors then develop a more contemporary outlook, introducing multiple state models, emerging cash flows and embedded options. Using spreadsheet-style software, the book presents large-scale, realistic examples. Over 150 exercises and solutions teach skills in simulation and projection through computational practice. Balancing rigour with intuition, and emphasising applications, this text is ideal for university courses, but also for individuals preparing for professional actuarial exams and qualified actuaries wishing to freshen up their skills.

Nonlife Actuarial Models
  • Theory, Methods and Evaluation
  • Yiu-Kuen Tse
  • Published online:
    05 June 2012
    Print publication:
    17 September 2009
  • Actuaries must pass exams, but more than that: they must put knowledge into practice. This coherent book gives complete syllabus coverage for Exam C of the Society of Actuaries (SOA) while emphasizing the concepts and practical application of nonlife actuarial models. Ideal for those approaching their professional exams, it is also a class-tested textbook for undergraduate university courses in actuarial science. All the topics that students need to prepare for Exam C are here, including modeling of losses, risk and ruin theory, credibility theory and applications, and empirical implementation of loss models. The book also covers more recent topics, such as risk measures and bootstrapping. Readers are assumed to have studied statistical inference and probability at the introductory undergraduate level. Numerous examples and exercises are provided, with many exercises adapted from past Exam C questions. Computational notes on the use of Excel are included. Teaching slides are available for download.

Generalized Linear Models for Insurance Data
  • Piet de Jong, Gillian Z. Heller
  • Published online:
    04 June 2010
    Print publication:
    28 February 2008
  • This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are provided on the website.

Market-Valuation Methods in Life and Pension Insurance
  • Thomas Møller, Mogens Steffensen
  • Published online:
    13 August 2009
    Print publication:
    18 January 2007
  • In classical life insurance mathematics the obligations of the insurance company towards the policy holders were calculated on artificial conservative assumptions on mortality and interest rates. However, this approach is being superseded by developments in international accounting and solvency standards coupled with other advances enabling a market-based valuation of risk, i.e., its price if traded in a free market. The book describes these approaches, and is the first to explain them in conjunction with more traditional methods. The various chapters address specific aspects of market-based valuation. The exposition integrates methods and results from financial and insurance mathematics, and is based on the entries in a life insurance company's market accounting scheme. The book will be of great interest and use to students and practitioners who need an introduction to this area, and who seek a practical yet sound guide to life insurance accounting and product development.

Insurance Risk and Ruin
  • David C. M. Dickson
  • Published online:
    19 January 2010
    Print publication:
    10 January 2005
  • Based on the author's experience of teaching final-year actuarial students in Britain and Australia, and suitable for a first course in insurance risk theory, this book focuses on the two major areas of risk theory - aggregate claims distributions and ruin theory. For aggregate claims distributions, detailed descriptions are given of recursive techniques that can be used in the individual and collective risk models. For the collective model, different classes of counting distribution are discussed, and recursion schemes for probability functions and moments presented. For the individual model, the three most commonly applied techniques are discussed and illustrated. Care has been taken to make the book accessible to readers who have a solid understanding of the basic tools of probability theory. Numerous worked examples are included in the text and each chapter concludes with exercises, which have answers in the book and full solutions available for instructors from www.cambridge.org/9780521846400.