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Library of Congress Cataloging-in-Publication Data:
Names: Baesens, Bart, author. | Rösch, Daniel, 1968– author. | Scheule, Harald, author.
Title: Credit risk analytics : measurement techniques, applications, and examples in SAS / Bart Baesens, Daniel Rösch, Harald Scheule.
Description: Hoboken, New Jersey : John Wiley & Sons, Inc., 2016 | Series: Wiley & SAS business series | Includes index.
Identifiers: LCCN 2016024803 (print) | LCCN 2016035372 (ebook) | ISBN 9781119143987 (cloth) | ISBN 9781119278344 (pdf) | ISBN 9781119278283 (epub)
Subjects: LCSH: Credit—Management—Data processing. | Risk management—Data processing. | Bank loans—Data processing. | SAS (Computer file)
Classification: LCC HG3751 .B34 2016 (print) | LCC HG3751 (ebook) | DDC 332.10285/555–ldc23
LC record available at https://lccn.loc.gov/2016024803
Cover image: Wiley
Cover design: © styleTTT/iStockphoto
To my wonderful wife, Katrien, and kids Ann-Sophie, Victor, and Hannelore.
To my parents and parents-in-law. Bart Baesens
To Claudi and Timo Elijah. Daniel Rösch
To Cindy, Leo, and Lina: a book about goodies and baddies. Harald Scheule
It is a great pleasure to acknowledge the contributions and assistance of various colleagues, friends, and fellow credit risk analytics lovers to the writing of this book. This text is the result of many years of research and teaching in credit risk modeling and analytics. We first would like to thank our publisher, John Wiley & Sons, for accepting our book proposal less than one year ago, and Rebecca Croser for providing amazing editing work for our chapters.
We are grateful to the active and lively scientific and industry communities for providing various publications, user forums, blogs, online lectures, and tutorials, which have proven to be very helpful.
We would also like to acknowledge the direct and indirect contributions of the many colleagues, fellow professors, students, researchers, and friends with whom we have collaborated over the years.
Last but not least, we are grateful to our partners, kids, parents, and families for their love, support, and encouragement.
We have tried to make this book as complete, accurate, and enjoyable as possible. Of course, what really matters is what you, the reader, think of it. The authors welcome all feedback and comments, so please feel free to let us know your thoughts!
Bart Baesens
Daniel Rösch
Harald Scheule
September 2016
Bart Baesens is a professor at KU Leuven (Belgium) and a lecturer at the University of Southampton (United Kingdom). He has done extensive research on big data and analytics, credit risk modeling, customer relationship management, and fraud detection. His findings have been published in well-known international journals and presented at top-level international conferences. He is the author of various books, including Analytics in a Big Data World (see http://goo.gl/kggtJp) and Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques (see http://goo.gl/P1cYqe). He also offers e-learning courses on credit risk modeling (see http://goo.gl/cmC2So) and advanced analytics in a big data world (see https://goo.gl/2xA19U). His research is summarized at www.dataminingapps.com. He regularly tutors, advises, and provides consulting support to international firms with respect to their big data, analytics, and credit risk management strategy.
Daniel Rösch is a Professor of Business and Management and holds the chair in Statistics and Risk Management at the University of Regensburg (Germany). Prior to joining the University of Regensburg in 2013, he was Professor of Finance and Director of the Institute of Banking and Finance at Leibniz University of Hannover from 2007 to 2013. He earned a PhD (Dr. rer. pol.) in 1998 for work on empirical asset pricing. From 2006 to 2011 he was visiting researcher at the University of Melbourne. Since 2011 he has been visiting professor at the University of Technology in Sydney. His research interests cover banking, quantitative financial risk management, credit risk, asset pricing, and empirical statistical and econometric methods and models. He has published numerous papers in leading international journals, earned several awards and honors, and regularly presents at major international conferences.
Rösch's service in the profession has included his roles as president of the German Finance Association, co-founder and member of the board of directors of the Hannover Center of Finance, and deputy managing director of the work group Finance and Financial Institutions of the Operations Research Society. He currently serves on the editorial board of the Journal of Risk Model Validation. Professor Rösch has worked with financial institutions and supervisory bodies such as Deutsche Bundesbank in joint research projects. Among others, his work has been funded by Deutsche Forschungsgemeinschaft, the Thyssen Krupp Foundation, the Frankfurt Institute for Finance and Regulation, the Melbourne Centre for Financial Studies, and the Australian Centre for International Finance and Regulation. In 2014 the German Handelsblatt ranked him among the top 10 percent of German-speaking researchers in business and management.
Harald “Harry” Scheule is Associate Professor of Finance at the University of Technology, Sydney, and a regional director of the Global Association of Risk Professionals. His expertise is in the areas of asset pricing, banking, credit and liquidity risk, home equity release, house prices in distress, insurance, mortgages, prudential regulation, securities evaluation, and structured finance
Scheule's award-winning research has been widely cited and published in leading journals. He currently serves on the editorial board of the Journal of Risk Model Validation. He is author or editor of various books.
Harry has worked with prudential regulators of financial institutions and undertaken consulting work for a wide range of financial institutions and service providers in Asia, Australia, Europe, and North America. These institutions have applied his work to improve their risk management practices, comply with regulations, and transfer financial risks.