Risk management for financial institutions is one of the key topics the financial industry has to deal with. The present volume is a mathematically rigorous text on solvency modeling. Currently, there are many new developments in this area in the financial and insurance industry (Basel III and Solvency II), but none of these developments provides a fully consistent and comprehensive framework for the analysis of solvency questions. Merz and Wuthrich combine ideas from financial mathematics (no-arbitrage theory, equivalent martingale measure), actuarial sciences (insurance claims modeling, cash flow valuation) and economic theory (risk aversion, probability distortion) to provide a fully consistent framework. Within this framework they then study solvency questions in incomplete markets, analyze hedging risks, and study asset-and-liability management questions, as well as issues like the limited liability options, dividend to shareholder questions, the role of re-insurance, etc. This work embeds the solvency discussion (and long-term liabilities) into a scientific framework and is intended for researchers as well as practitioners in the financial and actuarial industry, especially those in charge of internal risk management systems. Readers should have a good background in probability theory and statistics, and should be familiar with popular distributions, stochastic processes, martingales, etc.

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

Risk management for financial institutions is one of the key topics the financial industry has to deal with. The present volume is a mathematically rigorous text on solvency modeling. Currently, there are many new developments in this area in the financial and insurance industry (Basel III and Solvency II), but none of these developments provides a fully consistent and comprehensive framework for the analysis of solvency questions. Merz and Wuthrich combine ideas from financial mathematics (no-arbitrage theory, equivalent martingale measure), actuarial sciences (insurance claims modeling, cash flow valuation) and economic theory (risk aversion, probability distortion) to provide a fully consistent framework. Within this framework they then study solvency questions in incomplete markets, analyze hedging risks, and study asset-and-liability management questions, as well as issues like the limited liability options, dividend to shareholder questions, the role of re-insurance, etc. This work embeds the solvency discussion (and long-term liabilities) into a scientific framework and is intended for researchers as well as practitioners in the financial and actuarial industry, especially those in charge of internal risk management systems. Readers should have a good background in probability theory and statistics, and should be familiar with popular distributions, stochastic processes, martingales, etc.

This book constitutes the refereed proceedings of the International Conference on Trends in Electronic Commerce, TREC'98, held in Hamburg, Germany, in June 1998.
The book presents 19 revised full papers selected from a total of 75 submissions. While focussing mainly on technological issues, the book also takes into account important social, administrative, regulatory, and legal aspects. The papers are organized in sections on business over the Internet, security and payment, middleware and brokerage, interorganisational workflow management, and agent technology.

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

Das Internet stellt zunehmend auch ein Medium zur Abwicklung von Geschaftsprozessen dar. Die Unterstutzung solcher Handelstransaktionen wird unter dem Begriff "Electronic Commerce" zusammengefasst. Dieses Buch zeigt, wie eine Softwareplattform gestaltet sein sollte, die Anforderungen von Nachfragern und Anbietern kommerzieller Softwarekomponenten effizient unterstutzt. Hierbei leitet sich der Softwareentwurf unmittelbar aus der mikrookonomischen Marktdefinition ab. Insbesondere Fragen der Transaktionskostenreduktion und der Innovationsfahigkeit der Marktsoftware fuhren zum Modell eines Elektronischen Dienstemarktes. Bestehende Realisierungsverfahren zur Kooperation in verteilten Systemen werden hinsichtlich ihrer Vereinbarkeit mit diesem Dienstemarkt evaluiert, und es werden neue Verfahren und ihre Integration vorgestellt.

Die vorliegende Arbeit widmet sich dem Projekt Business Combinations" des IASB. Gegenstand dieses Projektes ist die Neufassung der Vorschriften zur Allokation des Unternehmenskaufpreises nach IFRS. Dazu veroffentlichte das IASB im Marz 2004 einen vorlaufigen neuen Standard (IFRS 3). Voraussichtlich im dritten Quartal 2007 wird dessen Neufassung ED-IFRS 3 verabschiedet. Gegenuber dem bisher gultigen Standard wurden dabei eine Vielzahl von Regelungen grundlegend neu gestaltet, um eine noch realistischere Ermittlung des Fair Value eines erworbenen Unternehmens zu gewahrleisten. Ziel der Arbeit ist die kritische Untersuchung dieses Zieles der wahrheitsgemassen Darstellung des Fair Value. Die Arbeit gliedert sich dazu in zwei Teile. Zunachst wird der gegenwartig gultige Standard IFRS 3 eingehend dargestellt und analysiert. Dabei wird insbesondere auf Probleme eingegangen, die sich nach Ansicht des Autors aus den Vorschriften im Hinblick auf deren Anwendung in der Praxis ergeben. Daruber hinaus werden auch Losungsvorschlage vorgestellt, mit deren Hilfe diesen Problemen entgegengewirkt werden kann. Dabei wird stets der Blickwinkel der Unternehmenspraxis eingenommen. Der zweite Teil der Arbeit unterzieht die Neufassung ED-IFRS 3 einer eingehenden Betrachtung. Dabei werden die neuen Vorschriften auf Ihre Praxistauglichkeit hin gepruft und gleichzeitig den Untersuchungsergebnissen der Analyse des IFRS 3 gegenubergestellt. Dadurch wird deutlich, inwieweit durch die Neufassung der Regelungen eine Verbesserung bzw. Verschlechterung gegenuber dem derzeit noch gultigen Standard erreicht wird. Das Fazit der Arbeit: Die derzeit gultigen Regelungen sind als unbefriedigend zu erachten. Die Neufassung ED-IFRS 3 tragt hierzu noch bei, da sich die Ermittlung des Fair Value noch starker auf das Ideal des vollkommenen Marktes stutzt. Der Autor deckt jedoch nicht nur entsprechende Schwachstellen der jeweiligen Regelwerke auf. Es werden auch Vorschlage erarbeitet, die vor allem aus dem