Quantitative risk management deals with modeling and calculations used for predicting frequencies and impacts of adversary events. McNeil et al. focus on financial risks, that is, events associated with bond prices, derivatives, economic losses, and so on. The work helps in understanding various aspects of such risks and teaches how to quantify them with advanced mathematical methods. Although the presentation is clear and elegant, to understand the contents the reader must know the mathematical tools being used.

In Part 1, after stressing the importance of the topics and their practical significance in the banking and insurance sector, the authors use clear examples to introduce the very heart of the problems (such as basic financial risk measures).

Part 2 elaborates on various methods (time series analysis, extreme value theory, multivariate models, modeling with copulas, and methods to aggregate risks), while Part 3 focuses on practical applications (quantification of market and credit risk, portfolio credit risk management, portfolio credit derivatives, modeling of operational risk, and elements of insurance analytics).

Some of the more advanced theoretical aspects of topics introduced in Part 2 are elaborated in Part 4, including multivariate time series, multivariate modeling, and more complex issues related to extreme value theory.

The appendices provide a sketch of the fundamentals (such as properties of various probability distributions). The book ends with a competent and up-to-date review of literature related to the covered topics.

A specialist in financial modeling will compare this work to other fundamental books like Alexander’s [1]. Alexander’s work is approximately two-and-a-half times longer (there are four volumes, while Quantitative risk management contains less than 700 pages in one volume) and elaborates more thoroughly the mathematical foundations. Therefore, it may be better for student teaching. On the other hand, McNeil et al.’s book is focused on practical applications, making it a more attractive textbook for practitioners.

Now, why might a computer or information technology (IT) specialist be interested in this book? Well, I can say why it is inspiring for me. First, this work increases my awareness of various types of threats--useful knowledge for a specialist in system management and planning. Additionally, the risk assessment elaborated in the financial field provides generally interesting results. Behind some of them, there is theoretical background material encountered in the computing and IT fields (time series or principal component analysis, for instance). A new, nontechnical perspective of its application is refreshing to me and potentially provides new insights. Moreover, getting acquainted with the presented material helped me to realize that as an engineer I need to give attention to the role of business management, since technical staff has to cooperate with business entities, especially in security or reliability. And last but not least, the book elaborates on interesting real examples related to well-known IT enterprises. This provides a taste of how well-known technological leaders deal with financial aspects in their companies.

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