Author: Naeem Siddiqi
Publisher: John Wiley & Sons
ISBN: 1118429168
Category : Business & Economics
Languages : en
Pages : 124
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Book Description
Praise for Credit Risk Scorecards "Scorecard development is important to retail financial services in terms of credit risk management, Basel II compliance, and marketing of credit products. Credit Risk Scorecards provides insight into professional practices in different stages of credit scorecard development, such as model building, validation, and implementation. The book should be compulsory reading for modern credit risk managers." —Michael C. S. Wong Associate Professor of Finance, City University of Hong Kong Hong Kong Regional Director, Global Association of Risk Professionals "Siddiqi offers a practical, step-by-step guide for developing and implementing successful credit scorecards. He relays the key steps in an ordered and simple-to-follow fashion. A 'must read' for anyone managing the development of a scorecard." —Jonathan G. Baum Chief Risk Officer, GE Consumer Finance, Europe "A comprehensive guide, not only for scorecard specialists but for all consumer credit professionals. The book provides the A-to-Z of scorecard development, implementation, and monitoring processes. This is an important read for all consumer-lending practitioners." —Satinder Ahluwalia Vice President and Head-Retail Credit, Mashreqbank, UAE "This practical text provides a strong foundation in the technical issues involved in building credit scoring models. This book will become required reading for all those working in this area." —J. Michael Hardin, PhD Professor of StatisticsDepartment of Information Systems, Statistics, and Management ScienceDirector, Institute of Business Intelligence "Mr. Siddiqi has captured the true essence of the credit risk practitioner's primary tool, the predictive scorecard. He has combined both art and science in demonstrating the critical advantages that scorecards achieve when employed in marketing, acquisition, account management, and recoveries. This text should be part of every risk manager's library." —Stephen D. Morris Director, Credit Risk, ING Bank of Canada
Author: Naeem Siddiqi
Publisher: John Wiley & Sons
ISBN: 1119279151
Category : Business & Economics
Languages : en
Pages : 469
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Book Description
A better development and implementation framework for credit risk scorecards Intelligent Credit Scoring presents a business-oriented process for the development and implementation of risk prediction scorecards. The credit scorecard is a powerful tool for measuring the risk of individual borrowers, gauging overall risk exposure and developing analytically driven, risk-adjusted strategies for existing customers. In the past 10 years, hundreds of banks worldwide have brought the process of developing credit scoring models in-house, while ‘credit scores' have become a frequent topic of conversation in many countries where bureau scores are used broadly. In the United States, the ‘FICO' and ‘Vantage' scores continue to be discussed by borrowers hoping to get a better deal from the banks. While knowledge of the statistical processes around building credit scorecards is common, the business context and intelligence that allows you to build better, more robust, and ultimately more intelligent, scorecards is not. As the follow-up to Credit Risk Scorecards, this updated second edition includes new detailed examples, new real-world stories, new diagrams, deeper discussion on topics including WOE curves, the latest trends that expand scorecard functionality and new in-depth analyses in every chapter. Expanded coverage includes new chapters on defining infrastructure for in-house credit scoring, validation, governance, and Big Data. Black box scorecard development by isolated teams has resulted in statistically valid, but operationally unacceptable models at times. This book shows you how various personas in a financial institution can work together to create more intelligent scorecards, to avoid disasters, and facilitate better decision making. Key items discussed include: Following a clear step by step framework for development, implementation, and beyond Lots of real life tips and hints on how to detect and fix data issues How to realise bigger ROI from credit scoring using internal resources Explore new trends and advances to get more out of the scorecard Credit scoring is now a very common tool used by banks, Telcos, and others around the world for loan origination, decisioning, credit limit management, collections management, cross selling, and many other decisions. Intelligent Credit Scoring helps you organise resources, streamline processes, and build more intelligent scorecards that will help achieve better results.
Author: Mamdouh Refaat
Publisher:
ISBN: 9781447511199
Category : Business & Economics
Languages : en
Pages : 428
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Book Description
This book provides a systematic presentation of credit risk scorecard development and implementation. The text covers the theoretical foundations, the practical implementation and programming using SAS. The book topics include: - Data acquisition - data preparation - EDA, predictive measures and variable selection - Optimal segmentation and binning - Coarse classing and WOE transformations - Development of logistic regression models - Methods of model assessment and evaluation - Scorecard creation and scaling - Automatic generation of scoring code (SAS, SQL, C) - Scorecard monitoring and reporting - Reject inference The SAS implementation contains over 50 ready-to-use SAS macros that can be implemented in the automation of the scorecard creation process.
Author: Lyn Thomas
Publisher: SIAM
ISBN: 1611974569
Category : Business & Economics
Languages : en
Pages : 380
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Book Description
Credit Scoring and Its Applications is recognized as the bible of credit scoring. It contains a comprehensive review of the objectives, methods, and practical implementation of credit and behavioral scoring. The authors review principles of the statistical and operations research methods used in building scorecards, as well as the advantages and disadvantages of each approach. The book contains a description of practical problems encountered in building, using, and monitoring scorecards and examines some of the country-specific issues in bankruptcy, equal opportunities, and privacy legislation. It contains a discussion of economic theories of consumers' use of credit, and readers will gain an understanding of what lending institutions seek to achieve by using credit scoring and the changes in their objectives. New to the second edition are lessons that can be learned for operations research model building from the global financial crisis, current applications of scoring, discussions on the Basel Accords and their requirements for scoring, new methods for scorecard building and new expanded sections on ways of measuring scorecard performance. And survival analysis for credit scoring. Other unique features include methods of monitoring scorecards and deciding when to update them, as well as different applications of scoring, including direct marketing, profit scoring, tax inspection, prisoner release, and payment of fines.
Author: Raymond Anderson
Publisher: Oxford University Press
ISBN: 9780199226405
Category : Business & Economics
Languages : en
Pages : 791
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Book Description
The Credit Scoring Toolkit provides an all-encompassing view of the use of statistical models to assess retail credit risk and provide automated decisions.In eight modules, the book provides frameworks for both theory and practice. It first explores the economic justification and history of Credit Scoring, risk linkages and decision science, statistical and mathematical tools, the assessment of business enterprises, and regulatory issues ranging from data privacy to Basel II. It then provides a practical how-to-guide for scorecard development, including data collection, scorecard implementation, and use within the credit risk management cycle.Including numerous real-life examples and an extensive glossary and bibliography, the text assumes little prior knowledge making it an indispensable desktop reference for graduate students in statistics, business, economics and finance, MBA students, credit risk and financial practitioners.
Author: Elizabeth Mays
Publisher: Global Professional Publishi
ISBN: 9781888988017
Category : Business & Economics
Languages : en
Pages : 392
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Book Description
· Credit scoring is a vital and sometimes misunderstood tool in financial services · Evaluates the different systems available Bankers and lenders depend on credit scoring to determine the best credit risks--and ensure maximum profit and security from their loan portfolios. Handbook of Credit Scoring offers the insights of a select group of experts on credit scoring systems. Topics include: Scoring Applications, Generic and Customized Scoring Models, Using consumer credit information, Scorecard modelling with continuous vs. Classed variables, Basic scorecard Development and Validation, Going beyond Credit Score, Data mining, Scorecard collection strategies, project management for Credit Scoring
Author: Lyn C. Thomas
Publisher: OUP Oxford
ISBN: 0191552496
Category : Business & Economics
Languages : en
Pages : 400
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Book Description
The use of credit scoring - the quantitative and statistical techniques to assess the credit risks involved in lending to consumers - has been one of the most successful if unsung applications of mathematics in business for the last fifty years. Now with lenders changing their objectives from minimising defaults to maximising profits, the saturation of the consumer credit market allowing borrowers to be more discriminating in their choice of which loans, mortgages and credit cards to use, and the Basel Accord banking regulations raising the profile of credit scoring within banks there are a number of challenges that require new models that use credit scores as inputs and extensions of the ideas in credit scoring. This book reviews the current methodology and measures used in credit scoring and then looks at the models that can be used to address these new challenges. The first chapter describes what a credit score is and how a scorecard is built which gives credit scores and models how the score is used in the lending decision. The second chapter describes the different ways the quality of a scorecard can be measured and points out how some of these measure the discrimination of the score, some the probability prediction of the score, and some the categorical predictions that are made using the score. The remaining three chapters address how to use risk and response scoring to model the new problems in consumer lending. Chapter three looks at models that assist in deciding how to vary the loan terms made to different potential borrowers depending on their individual characteristics. Risk based pricing is the most common approach being introduced. Chapter four describes how one can use Markov chains and survival analysis to model the dynamics of a borrower's repayment and ordering behaviour . These models allow one to make decisions that maximise the profitability of the borrower to the lender and can be considered as part of a customer relationship management strategy. The last chapter looks at how the new banking regulations in the Basel Accord apply to consumer lending. It develops models that show how they will change the operating decisions used in consumer lending and how their need for stress testing requires the development of new models to assess the credit risk of portfolios of consumer loans rather than a models of the credit risks of individual loans.
Author: Bart Baesens
Publisher: John Wiley & Sons
ISBN: 1119143985
Category : Business & Economics
Languages : en
Pages : 517
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Book Description
The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.
Author: David Jamieson Bolder
Publisher: Springer
ISBN: 3319946889
Category : Business & Economics
Languages : en
Pages : 704
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Book Description
The risk of counterparty default in banking, insurance, institutional, and pension-fund portfolios is an area of ongoing and increasing importance for finance practitioners. It is, unfortunately, a topic with a high degree of technical complexity. Addressing this challenge, this book provides a comprehensive and attainable mathematical and statistical discussion of a broad range of existing default-risk models. Model description and derivation, however, is only part of the story. Through use of exhaustive practical examples and extensive code illustrations in the Python programming language, this work also explicitly shows the reader how these models are implemented. Bringing these complex approaches to life by combining the technical details with actual real-life Python code reduces the burden of model complexity and enhances accessibility to this decidedly specialized field of study. The entire work is also liberally supplemented with model-diagnostic, calibration, and parameter-estimation techniques to assist the quantitative analyst in day-to-day implementation as well as in mitigating model risk. Written by an active and experienced practitioner, it is an invaluable learning resource and reference text for financial-risk practitioners and an excellent source for advanced undergraduate and graduate students seeking to acquire knowledge of the key elements of this discipline.
Author: L. C. Thomas
Publisher:
ISBN: 9780198527978
Category : Business & Economics
Languages : en
Pages : 352
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Book Description
Credit scoring is one of the most successful applications of statistical and management science techniques in finance in the last forty years. This unique collection of recent papers, with comments by experts in the field, provides excellent coverage of recent developments, advances and sims in credit scoring. Aimed at statisticians, economists, operational researchers and mathematicians working in both industry and academia, and to all working on credit scoring and data mining, it is an invaluable source of reference.
