Credit Scoring For Risk Managers
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Credit Scoring For Risk Managers
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Author : Freda Elizabeth Mays
language : en
Publisher: South Western Educational Publishing
Release Date : 2004
Credit Scoring For Risk Managers written by Freda Elizabeth Mays and has been published by South Western Educational Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Credit ratings categories.
With the growing concern about personal bankruptcy and quality of consumer lending, an effective credit scoring system is crucial to efficient and profitable lending practices. Featuring essays from seven experts in the risk management and banking/financial institution lending environment, this unique book offers valuable insights and proven techniques for developing effective credit scoring systems. It provides in-depth coverage of the roles of credit scoring, generic vs. customized scoring models, credit bureau data, scorecard development, performance measures, neural networks, project management, scorecard monitoring reports, how to use a scorecard to a lender's best advantage and much more.
Credit Risk Scorecards
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Author : Naeem Siddiqi
language : en
Publisher: John Wiley & Sons
Release Date : 2012-06-29
Credit Risk Scorecards written by Naeem Siddiqi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-29 with Business & Economics categories.
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
Credit Risk Management
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Author : Jiří Witzany
language : en
Publisher: Springer
Release Date : 2017-02-24
Credit Risk Management written by Jiří Witzany and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-24 with Business & Economics categories.
This book introduces to basic and advanced methods for credit risk management. It covers classical debt instruments and modern financial markets products. The author describes not only standard rating and scoring methods like Classification Trees or Logistic Regression, but also less known models that are subject of ongoing research, like e.g. Support Vector Machines, Neural Networks, or Fuzzy Inference Systems. The book also illustrates financial and commodity markets and analyzes the principles of advanced credit risk modeling techniques and credit derivatives pricing methods. Particular attention is given to the challenges of counterparty risk management, Credit Valuation Adjustment (CVA) and the related regulatory Basel III requirements. As a conclusion, the book provides the reader with all the essential aspects of classical and modern credit risk management and modeling.
Handbook Of Credit Scoring
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Author : Elizabeth Mays
language : en
Publisher: Global Professional Publishi
Release Date : 1995-03
Handbook Of Credit Scoring written by Elizabeth Mays and has been published by Global Professional Publishi this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-03 with Business & Economics categories.
· 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
Credit Scoring And Its Applications
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Author : Lyn C. Thomas
language : en
Publisher: SIAM
Release Date : 2002-01-01
Credit Scoring And Its Applications written by Lyn C. Thomas and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-01-01 with Mathematics categories.
The only book that details the mathematical models that help creditors make intelligent credit risk decisions.
Credit Risk Management
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Author : Tony Van Gestel
language : en
Publisher: OUP Oxford
Release Date : 2008-10-23
Credit Risk Management written by Tony Van Gestel and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-23 with Mathematics categories.
Credit Risk Management: Basic Concepts is the first book of a series of three with the objective of providing an overview of all aspects, steps, and issues that should be considered when undertaking credit risk management, including the Basel II Capital Accord, which all major banks must comply with in 2008. The introduction of the recently suggested Basel II Capital Accord has raised many issues and concerns about how to appropriately manage credit risk. Managing credit risk is one of the next big challenges facing financial institutions. The importance and relevance of efficiently managing credit risk is evident from the huge investments that many financial institutions are making in this area, the booming credit industry in emerging economies (e.g. Brazil, China, India, ...), the many events (courses, seminars, workshops, ...) that are being organised on this topic, and the emergence of new academic journals and magazines in the field (e.g. Journal of Credit Risk, Journal of Risk Model Validation, Journal of Risk Management in Financial Institutions, ...). Basic Concepts provides the introduction to the concepts, techniques, and practical examples to guide both young and experienced practitioners and academics in the fascinating, but complex world of risk modelling. Financial risk management, an area of increasing importance with the recent Basel II developments, is discussed in terms of practical business impact and the increasing profitability competition, laying the foundation for books II and III.
Credit Risk Analytics
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Author : Bart Baesens
language : en
Publisher: John Wiley & Sons
Release Date : 2016-10-03
Credit Risk Analytics written by Bart Baesens and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-03 with Business & Economics categories.
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.
Consumer Credit Models
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Author : Lyn C. Thomas
language : en
Publisher: OUP Oxford
Release Date : 2009-01-29
Consumer Credit Models written by Lyn C. Thomas and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-29 with Business & Economics categories.
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.
Managing Portfolio Credit Risk In Banks An Indian Perspective
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Author : Arindam Bandyopadhyay
language : en
Publisher: Cambridge University Press
Release Date : 2016-05-09
Managing Portfolio Credit Risk In Banks An Indian Perspective written by Arindam Bandyopadhyay and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-09 with Business & Economics categories.
This book explains how a proper credit risk management framework enables banks to identify, assess and manage the risk proactively.
Interpretable Machine Learning
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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020
Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.