Modelling Operational Risk Using Bayesian Inference
The management of operational risk in the banking industry has undergone explosive changes over the last decade due to substantial changes in the operational environment. Globalization, deregulation, the use of complex financial products, and changes in i
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Pavel V. Shevchenko
Modelling Operational Risk Using Bayesian Inference
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Dr. Pavel V. Shevchenko CSIRO Mathematics, Informatics and Statistics Locked Bag 17, North Ryde NSW, 1670 Australia [email protected]
ISBN 978-3-642-15922-0 e-ISBN 978-3-642-15923-7 DOI 10.1007/978-3-642-15923-7 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2010938383 c Springer-Verlag Berlin Heidelberg 2011 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: WMXDesign GmbH, Heidelberg Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Dedicated to my wife, daughter and parents
Preface
You don’t write because you want to say something, you write because you have something to say. F. Scott Fitzgerald
The management of operational risk in the banking industry has undergone significant changes over the last decade due to substantial changes in the operational environment. Globalization, deregulation, the use of complex financial products and changes in information technology have resulted in exposure to new risks very different from market and credit risks. In response, the Basel Committee on Banking Supervision (BCBS) has developed a new regulatory framework for capital measurement and standards for the banking sector, referred to as Basel II, aimed at sound risk sensitive capital requirements. Basel II formally defined operational risk and introduced corresponding capital requirements. BCBS began discussions on operational risk management in 1998, leading to the inclusion of operational risk capital requirements into the latest Basel II developed during 2001–2006. Currently, major banks are undertaking quantitative modelling of operational risk to satisfy these requirements under the so-called Basel II Advanced Measurement Approaches (AMA). A popular method under the AMA is the Loss Distribution Approach (LDA) based on statistical quantification of the frequency and severity distributions for operational risk losses. The LDA is the main focus of this book. Over the last 3 years, major banks in most parts of the world have received accreditation under the Basel II AMA by adopting the LDA, despite there being a number of unresolved methodolog
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