Search

Dieses Buch gibt eine ausführliche und verständliche Einführung in die Technik der deutschen Lebensversicherung. Nach einer allgemeinen Einleitung werden die Rechnungsgrundlagen Zins, Biometrie und Kosten, die Berechnung von Prämien, Leistungen und Reserven sowie die Überschussbeteiligung erläutert. Über diese klassische Lebensversicherungsmathematik hinaus geht der Autor detailliert auf die Darstellung fondsgebundener Tarife ein und beschreibt auch das komplexe Teilgebiet der Berufsunfähigkeitsversicherung in aller Tiefe. Zudem werden Aspekte der Pflegeversicherung sowie Fragestellungen des Jahresabschlusses und der Bilanzierung behandelt. Zahlreiche Übungsaufgaben inklusive Lösungen unterstützen das Selbststudium und veranschaulichen die versicherungstechnischen Vorgehensweisen. Für die 2. Auflage wurde der Text aktualisiert und ergänzt. Ein umfassender Anhang mit biometrischen Rechnungsgrundlagen, mathematischen Grundformeln, Wörterbuch und Symbolverzeichnis rundet das Werk ab.

The book presents a collection of peer-reviewed short papers selected from those presented at the International Conference Mathematical and Statistical Methods for Actuarial Sciences and Finance – MAF2024. The year 2024 marks the twentieth anniversary of the first edition of this conference. The idea behind this book is that collaboration and cross-pollination between mathematicians and statisticians working in actuarial sciences and finance could enhance research in these fields. The effectiveness of this concept has been demonstrated by widespread participation across all editions, held at various locations including the University of Salerno, Italy (2004, 2006, 2010, 2014, and 2022); Ca'Foscari University of Venice, Italy (2008, 2012, and 2020); University Paris-Dauphine in Paris, France (2016); University Carlos III of Madrid, Madrid (2018); and University of Le Havre Normandie, Le Havre, France (2024). This effectiveness is also evident in the attention consistently shown by both the scientific community and professionals toward the volumes of peer-reviewed papers accompanying all past editions of MAF. The book is a valuable resource for academics, researchers, Ph.D. students, and professionals. Furthermore, it is also of interest to other readers with a quantitative background.

This textbook presents the fundamental economic dimensions of insurance companies and links them to managerial issues. Combining academic rigour and a strongly practice-oriented approach, it addresses both the competitive environment and the management of the insurance business. Further, it provides a general overview of insurance undertakings and technical topics are explained in depth. Filling an important gap in the market for textbooks on the insurance business, it is divided into four parts and 35 chapters. Part I (chapters 1 to 10) describes the fundamentals of the business, how the industry works, the Authorities and the regulations. It presents the insurance products (for life, non-life retail, and non-life commercial lines). Part II (chapters 11 to 17) explains the pricing and reserving for life and non-life insurance. Reinsurance business is also illustrated. Part III (chapters 18 to 25) describes business models in the industry and the organizational structures. The main processes of an insurance company (product development, underwriting, claims settlement, investments) are presented. Marketing and distribution are also described. Part IV (chapters 26 to 35) defines the financial statement and introduces IFRS principles. Solvency II calculation, ALM model, and Embedded Value are explained in detail. This part also describes management accounting, performance indicators, and the Business Plan in the insurance industry. The book offers a valuable resource for lower and upper undergraduate students, graduate students, professionals/practitioners working at insurance companies, insurance agents, brokers, bankers, and consultants.

This book offers an introduction to the technical foundations of discrimination and equity issues in insurance models, catering to undergraduates, postgraduates, and practitioners. It is a self-contained resource, accessible to those with a basic understanding of probability and statistics. Designed as both a reference guide and a means to develop fairer models, the book acknowledges the complexity and ambiguity surrounding the question of discrimination in insurance. In insurance, proposing differentiated premiums that accurately reflect policyholders'true risk—termed'actuarial fairness'or'legitimate discrimination'—is economically and ethically motivated. However, such segmentation can appear discriminatory from a legal perspective. By intertwining real-life examples with academic models, the book incorporates diverse perspectives from philosophy, social sciences, economics, mathematics, and computer science. Although discrimination has long been a subject of inquiry in economics and philosophy, it has gained renewed prominence in the context of'big data,'with an abundance of proxy variables capturing sensitive attributes, and'artificial intelligence'or specifically'machine learning'techniques, which often involve less interpretable black box algorithms.The book distinguishes between models and data to enhance our comprehension of why a model may appear unfair. It reminds us that while a model may not be inherently good or bad, it is never neutral and often represents a formalization of a world seen through potentially biased data. Furthermore, the book equips actuaries with technical tools to quantify and mitigate potential discrimination, featuring dedicated chapters that delve into these methods.

This book provides a compact and systematic overview of closure properties of heavy-tailed and related distributions, including closure under tail equivalence, convolution, finite mixing, maximum, minimum, convolution power and convolution roots, and product-convolution closure. It includes examples and counterexamples that give an insight into the theory and provides numerous references to technical details and proofs for a deeper study of the subject. The book will serve as a useful reference for graduate students, young researchers, and applied scientists.

This book offers a comprehensive examination of the Cramér–Lundberg model, which is the most extensively researched model in ruin theory. It covers the fundamental dynamics of an insurance company's surplus level in great detail, presenting a thorough analysis of the ruin probability and related measures for both the standard model and its variants.Providing a systematic and self-contained approach to evaluate the crucial quantities found in the Cramér–Lundberg model, the book makes use of connections with related queueing models when appropriate, and its emphasis on clean transform-based techniques sets it apart from other works. In addition to consolidating a wealth of existing results, the book also derives several new outcomes using the same methodology.This material is complemented by a thoughtfully chosen collection of exercises. The book's primary target audience is master's and starting PhD students in applied mathematics, operations research, and actuarial science, although it also serves as a useful methodological resource for more advanced researchers. The material is self-contained, requiring only a basic grounding in probability theory and some knowledge of transform techniques.

This proceedings volume features top contributions in modern statistical methods from Statistics 2021 Canada, the 6th Annual Canadian Conference in Applied Statistics, held virtually on July 15-18, 2021. Papers are contributed from established and emerging scholars, covering cutting-edge and contemporary innovative techniques in statistics and data science. Major areas of contribution include Bayesian statistics; computational statistics; data science; semi-parametric regression; and stochastic methods in biology, crop science, ecology and engineering. It will be a valuable edited collection for graduate students, researchers, and practitioners in a wide array of applied statistical and data science methods.

This open access book introduces the modern tontine and its applications in retirement and decumulation. Personal financial management in the later stages of life presents unique challenges, and renowned retirement planning expert Dr. Milevsky proposes the modern tontine as a solution. With the goal of guiding professionals and retirees in more efficient decumulation, the book demonstrates how to build a modern tontine. It is technically oriented, employing a cookbook format, featuring R code, and examining retirement planning through a statistical lens. This how-to guide, which is a sequel to his 2020 book “Retirement Income Recipes in R”, will be invaluable for retirement planning professionals and advisors, as well as for PhD scholars in retirement planning, quantitative finance, and related fields.This book is open access.

This volume presents techniques and theories drawn from mathematics, statistics, computer science, and information science to analyze problems in business, economics, finance, insurance, and related fields. The authors present proposals for solutions to common problems in related fields. To this end, they are showing the use of mathematical, statistical, and actuarial modeling, and concepts from data science to construct and apply appropriate models with real-life data, and employ the design and implementation of computer algorithms to evaluate decision-making processes. This book is unique as it associates data science - data-scientists coming from different backgrounds - with some basic and advanced concepts and tools used in econometrics, operational research, and actuarial sciences. It, therefore, is a must-read for scholars, students, and practitioners interested in a better understanding of the techniques and theories of these fields.

Intangible, invisible and worth trillions, risk is everywhere. Its quantification and management are key to the success and failure of individuals, businesses and governments. Whether you're an interested observer or pursuing a career in risk, this book delves into the complex and multi-faceted work that actuaries undertake to quantify, manage and commodify risk—supporting our society and servicing a range of multi-billion-dollar industries. Starting at the most basic level, this book introduces key concepts in actuarial science, insurance and pensions. Through case studies, explanations and mathematical examples, it fosters an understanding of current industry practice. This book celebrates the long history of actuarial science and poses the problems facing actuaries in the future, exploring complex global risks including climate change, aging populations, healthcare models and pandemic epidemiology from an actuarial perspective. It gives practical advicefor new and potential actuaries on how to identify an area of work to go into, how best to navigate (and pass!) actuarial exams and how to develop your skills post-qualification. A Risky Business illuminates how actuaries are central to society as we know it, revealing what they do and how they do it. It is the essential primer on actuarial science.

This book follows a conversational approach in five dozen stories that provide an insight into the colorful world of financial mathematics and financial markets in a relaxed, accessible and entertaining form. The authors present various topics such as returns, real interest rates, present values, arbitrage, replication, options, swaps, the Black-Scholes formula and many more. The readers will learn how to discover, analyze, and deal with the many financial mathematical decisions the daily routine constantly demands. The book covers a wide field in terms of scope and thematic diversity. Numerous stories are inspired by the fields of deterministic financial mathematics, option valuation, portfolio optimization and actuarial mathematics. The book also contains a collection of basic concepts and formulas of financial mathematics and of probability theory. Thus, also readers new to the subject will be provided with all the necessary information to verify the calculations.

R Programming for Actuarial Science Professional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples R Programming for Actuarial Science provides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work. In R Programming for Actuarial Science, readers will find: Basic theory for each chapter to complement other actuarial textbooks which provide foundational theory in depth. Topics covered include compound interest, statistical inference, asset-liability matching, time series, loss distributions, contingencies, mortality models, and option pricing plus many more typically covered in university courses. More than 400 coding examples and exercises, most with solutions, to enable students to gain a better understanding of underlying mathematical and statistical principles. An overall basic to intermediate level of coverage in respect of numerous actuarial applications, and real-life examples included with every topic. Providing a highly useful combination of practical discussion and basic theory, R Programming for Actuarial Science is an essential reference for BSc/MSc students in actuarial science, trainee actuaries studying privately, and qualified actuaries with little programming experience, along with undergraduate students studying finance, business, and economics.

Neben den klassischen Tätigkeitsfeldern der Versicherungsmathematik wie Produktentwicklung und Bilanzierung wird der praktisch tätige Aktuar zunehmend mit neuen Anforderungen aus IT-Automatisierung, Datenmanagement und weiteren spannenden Aufgaben aus den Bereichen Maschinelles Lernen/Künstliche Intelligenz betraut. Das vorliegende Buch bietet eine Einführung in Data-Science-Anwendungen in der Versicherungsbranche (= Actuarial Data Science). Es richtet sich an (werdende) Aktuare und allgemeiner an alle quantitativ im Finanz- und Versicherungsbereich Tätigen und Studenten, die sich einen Einblick in die eingesetzten Konzepte und Technologien verschaffen möchten. Neben den mathematisch-technischen Grundlagen werden auch mögliche Auswirkungen auf die Organisationsstruktur der Unternehmen sowie Fragen aus dem gesellschaftlichen Umfeld einschließlich Datenschutz ausführlich diskutiert. Aufgrund der Wichtigkeit dieser Themen hat die Deutsche Aktuarvereinigung e.V. (DAV) entschieden, sie in das Programm für Aus- und Weiterbildung der Aktuarinnen und Aktuare zu integrieren. Die sieben Autoren dieses Buches sind allesamt Dozenten in diversen Lehrveranstaltungen der Deutschen Aktuar Akademie (DAA) im Themenfeld Actuarial Data Science.

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

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

This book deals with Enterprise Risk Management (ERM) and, in particular, Quantitative Risk Management (QRM) in life insurance business. Constituting a “bridge” between traditional actuarial mathematics and insurance risk management processes, its purpose is to provide advanced undergraduate and graduate students in the Actuarial Sciences, Finance and Economics with the basics of ERM (in general) and QRM applied to life insurance business. The main topics dealt with are: general issues on ERM, risk management tools for life insurance and life annuities, deterministic and stochastic analysis of the behaviour of a portfolio fund, application of sensitivity testing to assess ranges of results of interest, stress testing to assess the impact of extreme scenarios, and the product development process for life annuity products.

A new textbook offering a comprehensive introduction to models and techniques for the emerging field of actuarial Finance Drs. Boudreault and Renaud answer the need for a clear, application-oriented guide to the growing field of actuarial finance with this volume, which focuses on the mathematical models and techniques used in actuarial finance for the pricing and hedging of actuarial liabilities exposed to financial markets and other contingencies. With roots in modern financial mathematics, actuarial finance presents unique challenges due to the long-term nature of insurance liabilities, the presence of mortality or other contingencies and the structure and regulations of the insurance and pension markets. Motivated, designed and written for and by actuaries, this book puts actuarial applications at the forefront in addition to balancing mathematics and finance at an adequate level to actuarial undergraduates. While the classical theory of financial mathematics is discussed, the authors provide a thorough grounding in such crucial topics as recognizing embedded options in actuarial liabilities, adequately quantifying and pricing liabilities, and using derivatives and other assets to manage actuarial and financial risks. Actuarial applications are emphasized and illustrated with about 300 examples and 200 exercises. The book also comprises end-of-chapter point-form summaries to help the reader review the most important concepts. Additional topics and features include: Compares pricing in insurance and financial markets Discusses event-triggered derivatives such as weather, catastrophe and longevity derivatives and how they can be used for risk management; Introduces equity-linked insurance and annuities (EIAs, VAs), relates them to common derivatives and how to manage mortality for these products Introduces pricing and replication in incomplete markets and analyze the impact of market incompleteness on insurance and risk management; Presents immunization techniques alongside Greeks-based hedging; Covers in detail how to delta-gamma/rho/vega hedge a liability and how to rebalance periodically a hedging portfolio. This text will prove itself a firm foundation for undergraduate courses in financial mathematics or economics, actuarial mathematics or derivative markets. It is also highly applicable to current and future actuaries preparing for the exams or actuary professionals looking for a valuable addition to their reference shelf. As of 2019, the book covers significant parts of the Society of Actuaries'Exams FM, IFM and QFI Core, and the Casualty Actuarial Society's Exams 2 and 3F. It is assumed the reader has basic skills in calculus (differentiation and integration of functions), probability (at the level of the Society of Actuaries'Exam P), interest theory (time value of money) and, ideally, a basic understanding of elementary stochastic processes such as random walks.

This book reviews some of the most recent developments in neural networks, with a focus on applications in actuarial sciences and finance. It simultaneously introduces the relevant tools for developing and analyzing neural networks, in a style that is mathematically rigorous yet accessible. Artificial intelligence and neural networks offer a powerful alternative to statistical methods for analyzing data. Various topics are covered from feed-forward networks to deep learning, such as Bayesian learning, boosting methods and Long Short Term Memory models. All methods are applied to claims, mortality or time-series forecasting. Requiring only a basic knowledge of statistics, this book is written for masters students in the actuarial sciences and for actuaries wishing to update their skills in machine learning. This is the third of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. Although closely related to the other two volumes, this volume can be read independently.

This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and case studies, providing numerical illustrations using the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. This is the first of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. Although closely related to the other two volumes, this volume can be read independently.

Dieses Buch gibt eine ausführliche und verständliche Einführung in die Technik der deutschen Lebensversicherung. Nach einer allgemeinen Einleitung werden die Rechnungsgrundlagen Zins, Biometrie und Kosten, die Berechnung von Prämien, Leistungen und Reserven sowie die Überschussbeteiligung erläutert. Über diese klassische Lebensversicherungsmathematik hinaus geht der Autor detailliert auf die Darstellung fondsgebundener Tarife ein und beschreibt auch das komplexe Teilgebiet der Berufsunfähigkeitsversicherung in aller Tiefe. Zudem werden Aspekte der Pflegeversicherung sowie Fragestellungen des Jahresabschlusses und der Bilanzierung behandelt. Zahlreiche Übungsaufgaben inklusive Lösungen unterstützen das Selbststudium und veranschaulichen die versicherungstechnischen Vorgehensweisen. Ein umfassender Anhang mit biometrischen Rechnungsgrundlagen, mathematischen Grundformeln, Wörterbuch und Symbolverzeichnis rundet das Werk ab.

Jan Natolski behandelt die Problematik der Quantifizierung des Risikokapitals aus einer theoretischen Perspektive, die in wertvolle Impulse für die praktische Handhabung mündet. Dies ist ein wichtiger Schritt, da Versicherungsunternehmen durch die Richtlinie Solvency II verpflichtet sind, genügend Risikokapital zu hinterlegen, um die Gefahr der Insolvenz möglichst gering zu halten. Als zentrales Resultat zeigt der Autor, dass die in der Praxis verwendete Methode der Replikation mathematisch fundiert ist. Dabei setzt er Methoden aus verschiedenen mathematischen Gebieten, so z.B. der Optimierung und der Stochastik, ein.

Reinsurance: Actuarial and Statistical Aspects provides a survey of both the academic literature in the field as well as challenges appearing in reinsurance practice and puts the two in perspective. The book is written for researchers with an interest in reinsurance problems, for graduate students with a basic knowledge of probability and statistics as well as for reinsurance practitioners. The focus of the book is on modelling together with the statistical challenges that go along with it. The discussed statistical approaches are illustrated alongside six case studies of insurance loss data sets, ranging from MTPL over fire to storm and flood loss data. Some of the presented material also contains new results that have not yet been published in the research literature. An extensive bibliography provides readers with links for further study.

Actuaries working in claims reserving are often faced, among others, with the following two tasks: the prediction of future outstanding loss liabilities, as well as the quantification of their risk. Within claims reserving there exist various methods in which vagueness and subjective judgement is often not considered. A formal approach is given e.g. by fuzzy set theory. Besides an overview of applications of fuzzy set theory in claims reserving the author presents three ways of how subjective assessment can be implemented in the chain-ladder as well as the Bornhuetter Ferguson method.

This handbook presents the basic aspects of actuarial loss reserving. Besides the traditional methods, it also includes a description of more recent ones and a discussion of certain problems occurring in actuarial practice, like inflation, scarce data, large claims, slow loss development, the use of market statistics, the need for simulation techniques and the task of calculating best estimates and ranges of future losses. In property and casualty insurance the provisions for payment obligations from losses that have occurred but have not yet been settled usually constitute the largest item on the liabilities side of an insurer's balance sheet. For this reason, the determination and evaluation of these loss reserves is of considerable economic importance for every property and casualty insurer. Actuarial students, academics as well as practicing actuaries will benefit from this overview of the most important actuarial methods of loss reserving by developing an understanding of the underlying stochastic models and how to practically solve some problems which may occur in actuarial practice.

This is the third edition of this well-received textbook, presenting powerful methods for measuring insurance liabilities and assets in a consistent way, with detailed mathematical frameworks that lead to market-consistent values for liabilities.Topics covered are stochastic discounting with deflators, valuation portfolio in life and non-life insurance, probability distortions, asset and liability management, financial risks, insurance technical risks, and solvency. Including updates on recent developments and regulatory changes under Solvency II, this new edition of Market-Consistent Actuarial Valuation also elaborates on different risk measures, providing a revised definition of solvency based on industry practice, and presents an adapted valuation framework which takes a dynamic view of non-life insurance reserving risk.

A Hands-On Approach to Understanding and Using Actuarial ModelsComputational Actuarial Science with R provides an introduction to the computational aspects of actuarial science. Using simple R code, the book helps you understand the algorithms involved in actuarial computations. It also covers more advanced topics, such as parallel computing and C/

This self-contained module for independent study covers the subjects most often needed by non-mathematics graduates, such as fundamental calculus, linear algebra, probability, and basic numerical methods. The easily-understandable text of Introduction to Actuarial and Mathematical Methods features examples, motivations, and lots of practice from a large number of end-of-chapter questions. For readers with diverse backgrounds entering programs of the Institute and Faculty of Actuaries, the Society of Actuaries, and the CFA Institute, Introduction to Actuarial and Mathematical Methods can provide a consistency of mathematical knowledge from the outset. - Presents a self-study mathematics refresher course for the first two years of an actuarial program - Features examples, motivations, and practice problems from a large number of end-of-chapter questions designed to promote independent thinking and the application of mathematical ideas - Practitioner friendly rather than academic - Ideal for self-study and as a reference source for readers with diverse backgrounds entering programs of the Institute and Faculty of Actuaries, the Society of Actuaries, and the CFA Institute

Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfängen des Verlags von 1842 erschienen sind. Der Verlag stellt mit diesem Archiv Quellen für die historische wie auch die disziplingeschichtliche Forschung zur Verfügung, die jeweils im historischen Kontext betrachtet werden müssen. Dieser Titel erschien in der Zeit vor 1945 und wird daher in seiner zeittypischen politisch-ideologischen Ausrichtung vom Verlag nicht beworben.

Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfängen des Verlags von 1842 erschienen sind. Der Verlag stellt mit diesem Archiv Quellen für die historische wie auch die disziplingeschichtliche Forschung zur Verfügung, die jeweils im historischen Kontext betrachtet werden müssen. Dieser Titel erschien in der Zeit vor 1945 und wird daher in seiner zeittypischen politisch-ideologischen Ausrichtung vom Verlag nicht beworben.

Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfängen des Verlags von 1842 erschienen sind. Der Verlag stellt mit diesem Archiv Quellen für die historische wie auch die disziplingeschichtliche Forschung zur Verfügung, die jeweils im historischen Kontext betrachtet werden müssen. Dieser Titel erschien in der Zeit vor 1945 und wird daher in seiner zeittypischen politisch-ideologischen Ausrichtung vom Verlag nicht beworben.

Motivated by the many and long-standing contributions of H. Gerber and E. Shiu, this book gives a modern perspective on the problem of ruin for the classical Cramér–Lundberg model and the surplus of an insurance company. The book studies martingales and path decompositions, which are the main tools used in analysing the distribution of the time of ruin, the wealth prior to ruin and the deficit at ruin. Recent developments in exotic ruin theory are also considered. In particular, by making dividend or tax payments out of the surplus process, the effect on ruin is explored.Gerber-Shiu Risk Theory can be used as lecture notes and is suitable for a graduate course. Each chapter corresponds to approximately two hours of lectures.

Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfängen des Verlags von 1842 erschienen sind. Der Verlag stellt mit diesem Archiv Quellen für die historische wie auch die disziplingeschichtliche Forschung zur Verfügung, die jeweils im historischen Kontext betrachtet werden müssen. Dieser Titel erschien in der Zeit vor 1945 und wird daher in seiner zeittypischen politisch-ideologischen Ausrichtung vom Verlag nicht beworben.

Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes, Statistical Methods with Applications to Demography and Life Insurance presents contemporary statistical techniques for analyzing life distributions and life insurance problems. It not only contains traditional material but also incorporates new problems and techniques not discussed in existing actuarial literature.The book mainly focuses on the analysis of an individual life and describes statistical methods based on empirical and related processes. Coverage ranges from analyzing the tails of distributions of lifetimes to modeling population dynamics with migrations. To help readers understand the technical points, the text covers topics such as the Stieltjes, Wiener, and Ito integrals. It also introduces other themes of interest in demography, including mixtures of distributions, analysis of longevity and extreme value theory, and the age structure of a population. In addition, the author discusses net premiums for various insurance policies.Mathematical statements are carefully and clearly formulated and proved while avoiding excessive technicalities as much as possible. The book illustrates how these statements help solve numerous statistical problems. It also includes more than 70 exercises.

Der gewählte Titel'Grundlagen der Lebensversicherungstechnik'soll deutlich machen, welche Ziele wir uns gesetzt haben: Lebensversicherung: Bewußt beschränken wir uns auf dieses Teilgebiet des Versiche­ rungswesens, weil die zugehörige Technik sehr weit ausgebaut ist. Selbstverständlich wollen wir hierdurch die Bedeutung anderer Zweige (wie der Krankenversicherung oder der Schadenversiche­ rung) nicht schmälern Technik: Wir wollen (vielleicht etwas überbetont) zwischen Versicherungs­ mathematik und Versicherungstechnik trennen - wie zwischen Theorie und Praxis. Da jede Praxis durch die Theorie begründet wird, sind gelegentliche Ausflüge in die Versicherungsmathematik nicht zu vermeiden. Grundlagen: Es liegt uns daran, erkennen zu lassen, welche Grundgedanken die gebräuchliche Lebensversicherungstechnik gestaltet haben. In gewisser Weise sollen die einzelnen Kapitel die in Jahrzehnten gewachsenen Er­ fahrungen aus Lehre und Praxis wiedergeben. Dabei sollen kritische Anmerkungen nicht zu kurz kommen - dankenswerter Weise äußert sie mitunter Peregrinus Stocha­ sius, den wir uns vielleicht als einen Kollegen, dem die beruflichen Sachzwänge ein we­ nig Weitblick ließen, vorstellen können. Wen wünscht sich der Autor als Leser? Wir denken besonders an Absolventen von Fachhochschulen und Hochschulen, die sich während ihres Studiums mit der Versicherungsmathematik befassen oder die nach einem Studium der Mathematik ihren beruflichen Weg im Versicherungswesen begin­ nen. Ihnen soll vor allem das erste, wie uns scheint, nicht übliche Kapitel Motivationen vermitteln und zum weiteren Lesen anregen.

Reformen im Bereich der Gesetzlichen Krankenversicherung (GKV) nehmen auf der politischen Agenda seit längerem einen oberen Platz ein. Eines der Hauptthemen ist die Stärkung der Eigenverantwortung von Versicherten und Leistungserbringern. Aus der Perspektive der Principal-Agent-Theorie analysiert Antje Musil, welche Instrumente geeignet sind, die Eigenverantwortung der Versicherten und der niedergelassenen Vertragsärzte zu stärken. Aufbauend auf einer Darstellung des GKV-Systems untersucht sie das Moral-Hazard-Verhalten der Versicherten, diskutiert monetäre Anreiz- und Sanktionsinstrumente, die eine Interessenangleichung zwischen Versicherten und Gesetzlicher Krankenkasse bewirken sollen, und verdeutlicht den engen Zusammenhang zwischen der Eigenverantwortung des Patienten und der Arzt-Patient-Beziehung. Die Autorin entwickelt ein Vergütungssystem, das die Entlohnung des Arztes stärker an das Leistungsergebnis knüpft und so für eine stärkere Patientenorientierung des Leistungserbringers sorgt.

Creating the Future with All Finance and Financial Conglomerates comprises an academic search for an understanding of all finance and financial conglomerates. It presents a strategic and economic analysis of diversification strategies and the growing interface between different types of financial firms. On the basis of a solid analysis of theoretical foundations and practical value, the book develops basic concepts of creating the future: especially solutions in managing risks and fresh ideas for the development of integrated financial services. The structure of the book is logical: starting on theoretical foundations (section 1, part A) and examining the economic value of All Finance and Financial Conglomerates (part B), leads to creating a concept for the future (part C). Case studies add additional practical value to this research. The review of the subject is completed by aspects of risk management in this sector and by political guidelines for the EU single market (section 2). The book builds further on Professor Van den Berghe's first publication, entitled Financial Conglomerates - New Rules for New Players (published by Kluwer Academic Publishers in October 1995) and broadens the scope in the direction of strategic and managerial aspects. The following five aspects underline the innovativeness of the material: The volume is not only focused on the diversification of banks via `bancassurance', but also analyses in depth the parallel developments in the insurance market, whereby insurers and insurance intermediaries launch themselves in the direction of `assurfinance'; The material analyses not only the cross-selling of each other's products and the blurring of the market boundaries, but also the diversification, collaboration, and integration on all other levels and functions; New conceptual tools (the financial conglomerates control board) are developed toprovide a more in-depth comparison of the many cases of this international trend; The book goes far beyond the categorisation of the mode of diversification, by looking at all managerial aspects of such a growth strategy; and The work looks at the economic and legal aspects involved as well as at the more strategic and managerial aspects. This research has been made possible thanks to the financial support of The LEVOB Foundation.

This book consists of a series of new, peer-reviewed papers in stochastic processes, analysis, filtering and control, with particular emphasis on mathematical finance, actuarial science and engineering. Paper contributors include colleagues, collaborators and former students of Robert Elliott, many of whom are world-leading experts and have made fundamental and significant contributions to these areas.This book provides new important insights and results by eminent researchers in the considered areas, which will be of interest to researchers and practitioners. The topics considered will be diverse in applications, and will provide contemporary approaches to the problems considered. The areas considered are rapidly evolving. This volume will contribute to their development, and present the current state-of-the-art stochastic processes, analysis, filtering and control.Contributing authors include: H Albrecher, T Bielecki, F Dufour, M Jeanblanc, I Karatzas, H-H Kuo, A Melnikov, E Platen, G Yin, Q Zhang, C Chiarella, W Fleming, D Madan, R Mamon, J Yan, V Krishnamurthy.

Financial Risk and Derivatives provides an excellent illustration of the links that have developed in recent years between the theory of finance on one hand and insurance economics and actuarial science on the other. Advances in contingent claims analysis and developments in the academic and practical literature dealing with the management of financial risks reflect the close relationships between insurance and innovations in finance. The book represents an overview of the present state of the art in theoretical research dealing with financial issues of significance for insurance science. It will hopefully provide an impetus to further developments in applied insurance research.

The interaction between mathematicians and statisticians reveals to be an effective approach for dealing with actuarial, insurance and financial problems, both in an academic and in an operative perspective. The international conference MAF 2008, held at the University Ca'Foscari of Venezia (Italy) in 2008, had precisely this purpose, and the collection here published gathers a selection of about the one hundred papers presented at the conference and successively referred and reviewed to this aim. They cover a wide variety of subjects in actuarial, insurance and financial fields, all treated in light of the successful cooperation between the two quantitative approaches.

'Dit is oratie 392, verschenen in de oratiereeks van de Universiteit van Amsterdam'--T.p. verso.

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

Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics. This second and much expanded edition emphasizes the implementation of these techniques through the use of R. This free but incredibly powerful software is rapidly developing into the de facto standard for statistical computation, not just in academic circles but also in practice. With R, one can do simulations, find maximum likelihood estimators, compute distributions by inverting transforms, and much more.

Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science, and finance. The book builds on students'existing knowledge of probability and statistics by establishing a solid and thorough understanding of

Disability insurance, long-term care insurance, and critical illness cover are becoming increasingly important in developed countries as the problems of demographic aging come to the fore. The private sector insurance industry is providing solutions to problems resulting from these pressures and other demands of better educated and more prosperous

Both in insurance and in finance applications, questions involving extremal events (such as large insurance claims, large fluctuations in financial data, stock market shocks, risk management,...) play an increasingly important role. This book sets out to bridge the gap between the existing theory and practical applications both from a probabilistic as well as from a statistical point of view. Whatever new theory is presented is always motivated by relevant real-life examples. The numerous illustrations and examples, and the extensive bibliography make this book an ideal reference text for students, teachers and users in the industry of extremal event methodology.

This book is different from all other books on Life Insurance by at least one of the following characteristics 1-4. 1. The treatment of life insurances at three different levels: time-capital, present value and price level. We call time-capital any distribution of a capital over time: (•) is the time-capital with amounts Cl, ~,..., C at moments Tl, T,..•, T resp. N 2 N For instance, let (x) be a life at instant 0 with future lifetime X. Then the whole oO oO life insurance A is the time-capital (I,X). The whole life annuity ä is the x x time-capital (1,0) + (1,1) + (1,2) +... + (I,'X), where'X is the integer part ofX. The present value at 0 of time-capital (•) is the random variable T1 T TN Cl V + ~ v, +... + CNV. (••) In particular, the present value ofA 00 and ä 00 is x x 0 0 2 A = ~ and ä = 1 + v + v +... + v'X resp. x x The price (or premium) of a time-capital is the expectation of its present value. In particular, the price ofA 00 and äx 00 is x 2 A = E(~) and ä = E(I + v + v +... + v'X) resp.