Optimal Control of Credit Risk presents an alternative methodology to deal with a financial problem that has not been well analyzed yet: the control of credit risk. Credit risk has become recently the center of interest of the financial community, with new instruments (such as Credit Risk Derivatives) and new methodologies (such as Credit Metrics) being developed. The recent literature has focused on the pricing of credit risk. On the other hand, practitioners tend to eliminate credit risk rather than price it. They do so via collateralization. The authors propose here a methodological basis for an optimal collateralization. The monograph is organized as follows: Chapter 1 reviews the main avenues of literature related to our problem; Chapter 2 provides a brief overview of the main optimal control principles; and Chapter 3 presents the models and their setting. In the remaining chapters, the authors propose two sets of programs. One set of programs will apply in cases where the information on the assets=value is readily available (full observation case), while the other applies when costly audits are needed in order to assess this value (partial observation case). In either case, the modeling stage leads to a set of quasi-variational inequalities which the authors attempt to solve numerically in the simpler case of full observations. This is done in Chapter 6. Finally a simulation analysis is carried out in Chapter 7, in which the authors study the influence on the control process of changes in the different model parameters. This precedes a discussion on possible extensions in Chapter 8 and some concluding remarks in Section 9.

This book provides a unique, focused introduction to the analytical skills, methods and techniques in the assessment of credit risk that are necessary to tackle and analyze complex credit problems. It employs models and techniques from operations research and management science to investigate more closely risk models for applications within the banking industry and in financial markets. Furthermore, the book presents the advances and trends in model development and validation for credit scoring/rating, the recent regulatory requirements and the current best practices. Using examples and fully worked case applications, the book is a valuable resource for advanced courses in financial risk management, but also helpful to researchers and professionals working in financial and business analytics, financial modeling, credit risk analysis, and decision science.

In recent years public attention has focused on an array of low-probability/high-consequence (LC/HC) events that pose a signif­ icant threat to human health, safety, and the environment. At the same time, public and private sector responsibilities for the assessment and management of such events have grown because of a perceived need to anticipate, prevent, or reduce the risks. In attempting to meet these responsibilities, legislative, judicial, regulatory, and private sector institutions have had to deal with the extraordinarily complex problem of assessing and balancing LP/ HC risks against the costs and ben if its of risk reduction. The need to help society cope with LP/HC events such as nuclear power plant accidents, toxic spills, chemical plant explosions, and transportation accidents has given rise to the development of a new intellectual endeavor: LP/HC risk analysis. The scope and complexity of these analyses require a high degree of cooperative effort on the part of specialists from many f~elds. Analyzing technical, social, and value issues requires the efforts of physicists, biologists, geneticists, statisticians, chemists, engineers, political scientists, sociologists, decision analysts, management scientists, economists, psychologists, ethicists, lawyers, and policy analysts. Included in this volume are papers by authors in each of these disciplines. The papers share in common a focus on one or more of the following questions that are generic to the analysis of LP/HC risks.

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