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Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications

Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications
  

Combine complex concepts facing the financial sector with the software toolsets available to analysts. The credit decisions you make are dependent on the data, models, and tools that you use to determine them. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT:... read full description below.

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ISBN 9781642953152
Barcode 9781642953152
Published 3 July 2019 by SAS Institute
Format Hardback
Alternate Format(s) View All (1 other possible title(s) available)
Author(s) By Brown, Iain
Availability Internationally sourced; ships 6-12 working days

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Full details for this title

ISBN-13 9781642953152
ISBN-10 1642953156
Stock Available
Status Internationally sourced; ships 6-12 working days
Publisher SAS Institute
Imprint SAS Institute
Publication Date 3 July 2019
Publication Country
Format Hardback
Author(s) By Brown, Iain
Category Probability & Statistics
Number of Pages 174
Dimensions Width: 216mm
Height: 280mm
Spine: 11mm
Weight 694g
Interest Age General Audience
Reading Age General Audience
Library of Congress Financial risk management
NBS Text Science & Mathematics: Textbooks & Study Guides
ONIX Text General/trade
Dewey Code 519.5
Catalogue Code Not specified

Description of this Book

Combine complex concepts facing the financial sector with the software toolsets available to analysts. The credit decisions you make are dependent on the data, models, and tools that you use to determine them. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications combines both theoretical explanation and practical applications to define as well as demonstrate how you can build credit risk models using SAS Enterprise Miner and SAS/STAT and apply them into practice. The ultimate goal of credit risk is to reduce losses through better and more reliable credit decisions that can be developed and deployed quickly. In this example-driven book, Dr. Brown breaks down the required modeling steps and details how this would be achieved through the implementation of SAS Enterprise Miner and SAS/STAT. Users will solve real-world risk problems as well as comprehensively walk through model development while addressing key concepts in credit risk modeling. The book is aimed at credit risk analysts in retail banking, but its applications apply to risk modeling outside of the retail banking sphere. Those who would benefit from this book include credit risk analysts and managers alike, as well as analysts working in fraud, Basel compliancy, and marketing analytics. It is targeted for intermediate users with a specific business focus and some programming background is required. Efficient and effective management of the entire credit risk model lifecycle process enables you to make better credit decisions. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications demonstrates how practitioners can more accurately develop credit risk models as well as implement them in a timely fashion.

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Author's Bio

Dr. Iain Brown is an Analytics Specialist Consultant at SAS, specializing in Credit Risk. Prior to joining SAS in 2011, he worked as a Credit Risk Analyst at a major UK retail bank where he built and validated PD, LGD, and EAD models using SAS software. He has spoken at a number of internationally renowned conferences and conventions and has published papers on the topic of credit risk modeling in the International Journal of Forecasting and the Journal of Expert Systems with Applications. In 2011, he won the SAS Student Ambassador award for his doctoral research, which recognizes and supports students who use SAS technologies in innovative ways to benefit their respective industries and fields of study. Iain has a BBA in Business from the University of Kent, an MSc in Operational Research from the London School of Economics and Political Science (LSE), and a PhD in Credit Risk from the University of Southampton. Iain is also an active member of the Operational Research (OR) Society; in July 2014, he was awarded the title of Associate Fellow of the OR Society (AFORS) for his contribution to the field of OR. His research interests include data mining, credit scoring, credit risk modeling, and Basel compliancy.

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