Intelligent Credit Scoring. Siddiqi Naeem
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Library of Congress Cataloging-in-Publication Data :
ISBN 9781119279150 (Hardcover)
ISBN 9781119282334 (ePub)
ISBN 9781119282297 (ePDF)
Acknowledgments
As with the first edition, I am indebted to many people who have provided ideas, advice, and inspiration for the content of this book.
● I would like to thank Dr. Billie Anderson, Dr. Hendrik Wagner, Clark Abrahams, Bradley Bender, and Charles Maner for graciously agreeing to contribute very informative guest chapters to this book.
● The Roman poet Ovid once said, “A horse never runs so fast as when he has other horses to catch up and outpace.” I am grateful to the incredibly talented group of people I work with at SAS who continue to enhance my knowledge of risk management and analytics.
● I want to thank Nikolay Filipenkov and Clark Abrahams for reviewing this book and providing excellent ideas for improvements.
● I continue to learn about the contemporary issues in the industry, the challenges, and innovative ways to deal with them from my customers and colleagues in the credit scoring business. What we know today is due in large part to the generous sharing of knowledge and research work done by credit scoring practitioners. We are indebted to them.
My family – Saleha, Zainab, and Noor – who have been incredibly supportive and tolerant of my frequent work-related absences from home, and have done much of the heavy lifting at home during those times (especially during snowstorms in Markham while I am at warmer locales).
Finally, as always, I want to acknowledge my parents for encouraging me to continuously seek knowledge, and for their constant prayers and blessings, without which there would be no success.
Chapter 1
Introduction
“The only virtue of being an aging risk manager is that you have a large collection of your own mistakes that you know not to repeat.”
Much has changed since the publication of the first edition of this book in 2006. The use of credit scoring has become truly international, with thousands of lenders now developing their own scorecards in-house. As a benchmark, The SAS Credit Scoring1 solution, which started out around that time, now has hundreds of customers – but more importantly, they are spread out across 60-plus countries. Many more banks, of course, use products from other vendors to build and use credit risk scorecards in-house, but in general, the trend has moved away from outsourcing the development of scorecards to internal builds. The following factors, listed in the order discussed, have led to more widespread usage of scorecards and the decision by banks to build them in-house.
Factors driving the increased use of scorecards include:
● Increased regulation.
● Ease of access to sizable and reliable data.
● Better software for building scorecards.
● Availability of greater educational material and training for would-be developers.
● Corporate knowledge management fostering retention and sharing of subject-matter expertise.
● Signaling capabilities to external and internal stakeholders.
● Efficiency and process improvement.
● Creating value and boosting profitability.
● Improved customer experience.
In the past decade, the single biggest factor driving banks to bring credit scorecard development in-house has been the Basel II Accord.2 Specifically, banks that have opted to (or were told to) comply with the Foundation or Advanced Internal Ratings Based approaches of Basel II were required to internally generate Probability of Default (PD) estimates (as well as estimates for Loss Given Default [LGD] and Exposure at Default [EAD]). Larger banks expanded their production and usage of credit scoring, and were compelled to demonstrate their competence in credit scoring. In many countries, particularly in Europe, even small banks decided to go for these approaches, and thus had to start building models for the first time. This led to some challenges – when you have never built scorecards in-house (and in some cases, not really used them either), where do you start? Many institutions went through significant changes to their data warehousing/management, organizational structure, technology infrastructure, and decision making as well as risk management cultures. The lessons from some of these exercises will be shared in chapters on creating infrastructures for credit scoring, as well as the people who should be involved in a project.
While there is a lot of variance in the way Basel II has been implemented in Europe, it is largely a finished process there.3 Some of the lessons, from Basel II, specifically on how the default definition should be composed will be detailed in a guest chapter written by Dr. Hendrik Wagner. The implementation of Basel II is still ongoing in many countries, where the same exercise is being repeated many times (and in most cases, the same questions are being asked as were 10 years ago in Europe). Many institutions, such as retail credit card and automotive loan companies, that were not required to comply with Basel II, voluntarily opted to comply anyway. Some saw this as a way to prove their capabilities and sophistication to the market, and as a seal of approval on the robustness of their internal processes. But the ones who gained most were those who saw Basel II compliance not just as a mandatory regulatory exercise, but rather as a set of best practices leading to an opportunity to make their internal processes better. This theme of continuous improvement will be addressed in various parts of the book, and guidance given on best practices for the scorecard development implementation process.
In some countries where Basel II was not a factor, local banks decided to take on analytics to improve and be more competitive. In many developing countries, the banking industry became deregulated or more open, which allowed international banks to start operating there. Such banks generally tended to have a long history of using advanced analytics and credit scoring. This put competitive pressures on some of the local banks, which in many cases were operating using manual and judgmental methods. The local banks thus started investing in initiatives such as data warehousing, analytics, and in-house credit scoring in order to bring costs down, reduce losses, and create efficiencies. Another factor that points to a wider acceptance of credit scoring is the tight market for scorecard developers globally. In almost all the countries,
Basel Committee for Banking Supervision, Basel II: International Convergence of Capital Measurement and Capital Standards: A Revised Framework, Bank for International Settlements, November 2005.
European Banking Federation, Study on Internal Rating Based (IRB) models in Europe, 2014.