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The positioning of this text in the literature should help readers to identify how it complements the multitude of texts and articles that relate to risk and to risk management.

The "Model Divide"

Current risks are tomorrow's potential losses. Unfortunately, they are not as tangible as revenues and costs, thereby making risk modeling a conceptual and a practical challenge. Risk models and techniques have continuously expanded in recent years, enhancing the ability to monitor and control risk and to develop business activities without a myopic view on profitability. This is the "bright side" of risk models. The "dark side" is that, perhaps, the usage of risk models remained in the hands of a small group of "quants", who used them without caring too much about explaining model risk to non-specialists. This is not a good enough reason to throw everything to the trash can. The modeling effort was productive and a necessary step in the development of better risk practices.

The gap between the technicality of the literature and the capability of risk professionals, who are not model experts, to integrate the complexity of models in their own practices is damaging. Presumably, such a gap exists, and grew through time as the 2008 crisis seems to suggest.

It is noticeable that, instead of a dissemination of model expertise across the entire industry, modeling techniques tended to concentrate in a smaller core of experts. Such a concentration might explain the persisting and growing gaps between "model experts" and practitioners. Experts are "embedded" in banks, but being "embedded" does not imply that expertise is shared.

The book does not take harsh positions against models, even though it is relatively easy to pinpoint some model glitches1 that were the sources of the financial crisis. Instead, it capitalizes on progress achieved that should allow banks to implement truly efficient risk management. It addresses risk processes and risk models, hoping to narrow the gap between specialists of quantitative finance and risk managers. It builds on a long experience in the risk department of banks and on academic knowledge.

Modelers will find here some reminders on classical finance models, which are pre-requisites to risk models, because there is no need for expanding such finance models beyond the essentials required for understanding risk models. However, risk models are expanded, explaining the rationale of models and illustrating them with examples. The text should help increasing transparency across the technicalities of risk management. It is balanced rather than technical, with a minimal background on risk modeling and an emphasis on how to assemble risk models in a consistent way, and on techniques and processes for making bank-wide risk management achievable.

As a consequence, an important goal of this book, as in previous editions, remains to address the "model divide" between model designers and risk professionals. Experts will find that some of the introductory essentials on modeling are fairly basic in this text. On the other hand, the larger mass of practitioners and students of risk management should find the text helpful because it is largely self-contained and integrated.

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