Dynamic financial analysis (DFA) has become an important tool in analyzing the financial situation of insurance companies. Constant development and documentation of DFA tools has occurred during the last years. However, several questions concerning the implementation of DFA systems have not been answered in the DFA literature to date. One such important issue is the consideration of management strategies in the DFA context. The aim of this paper is to study the effects of different management strategies on a non-life insurer's risk and return profile. Therefore, we develop several management strategies and test them numerially within a DFA simulation study.

Major challenges for life insurance companies have been posed by an unprecedented wave of mergers and acquisitions in the insurance industry and the emergence of non-traditional competitors such as banks, mutual fund companies and investment advisory firms. This is the first book to analyze the determinants of firm performance in the life insurance industry by identifying the `best practices' employed by leading insurers to succeed in this dynamic business environment. The book draws upon data from insurer financial statements as well as upon an extensive survey of life insurer management practices and strategic choices in distribution systems, information technology, mergers and acquisitions, human resources and financial strategies. Generic strategies such as cost leadership, customer focus, and product differentiation are analyzed as well as strategic practices specific to the insurance industry. Best practices are identified by measuring the economic efficiency of insurers and by comparing firms across the industry. Both cost and revenue efficiency are measured relative to best practice efficient frontiers consisting of the industry's dominant life insurance firms. Economies of scale and the effects of mergers and acquisitions on efficiency are also analyzed. Financial strategies are examined with specific reference to pricing policy, valuation of assets and liabilities, and the current state of firm-level risk management systems. The benchmarks established are the result of extensive fieldwork that identifies key financial risks and methodologies to both measure and manage them at the firm level. The results discussed in the book indicate that firm performance is significantly correlated with management practices and strategic choices. Thus, life insurers can improve profitability by adopting optimal combinations of strategies. The book contains important new material on the effects of strategic choices in product distribution systems, information technology, mergers and acquisitions, human resources, and financial risk management policies. In the area of efficiency, the methodology provides a new approach for identifying peer groups of insurers and measuring the performance of individual insurers relative to their peer group. On the topics of risk and pricing, new insights are offered relative to current methodologies and in regard to areas where improvement is clearly warranted. The book concludes with an analysis of the future opportunities and challenges in the life insurance industry facing managers, and the strategic options available to them to cope with these changes.

The recent crises facing thrifts, banks, and other financial service institutions have caused insurance regulators, executives, and investors to become increasingly concerned about the insurance industry's vulnerability. This thoughtful reference explores the financial dynamics of the insurance industry, explaining the past and offering guidance for the future.

This paper explores insurance as a source of financial system vulnerability. It provides a brief overview of the insurance industry and reviews the risks it faces, as well as several recent failures of insurance companies that had systemic implications. Assimilation of banking-type activities by life insurers appears to be the key systemic vulnerability. Building on this experience and the experience gained under the FSAP, the paper proposes key indicators that should be compiled and used for surveillance of financial soundness of insurance companies and the insurance sector as a whole.

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 Wüthrich 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.

Historically, financial and insurance risks were separate subjects most often analyzed using qualitative methods. The development of quantitative methods based on stochastic analysis is an important achievement of modern financial mathematics, one that can naturally be extended and applied in actuarial mathematics. Risk Analysis in Finance and Insurance offers the first comprehensive and accessible introduction to the ideas, methods, and probabilistic models that have transformed risk management into a quantitative science and led to unified methods for analyzing insurance and finance risks. The author's approach is based on a methodology for estimating the present value of future payments given current financial, insurance, and other information, which leads to proper, practical definitions of the price of a financial contract, the premium for an insurance policy, and the reserve of an insurance company. Self-contained and full of exercises and worked examples, Risk Analysis in Finance and Insurance serves equally well as a text for courses in financial and actuarial mathematics and as a valuable reference for financial analysts and actuaries. Ancillary electronic materials will be available for download from the publisher's Web site.

Developing a Questionnaire: 2nd Edition is a comprehensive guide to the successful design and implementation of questionnaires as a research method. It covers: how, why and when to use questionnaires how to analyse data how to present results how to relate questionnaires to other forms of research. This second edition contains new chapters on the use of questionnaires in surveys, face-to-face questionnaires and telephone interviews.