Credit Intelligence Modelling

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Credit Intelligence and Modelling

Author : Raymond A. Anderson
Publisher : Oxford University Press
ISBN 13 : 0192658158
Total Pages : 608 pages
Book Rating : 4.1/5 (926 download)

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Book Synopsis Credit Intelligence and Modelling by : Raymond A. Anderson

Download or read book Credit Intelligence and Modelling written by Raymond A. Anderson and published by Oxford University Press. This book was released on 2021-11-26 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credit Intelligence and Modelling provides an indispensable explanation of the statistical models and methods used when assessing credit risk and automating decisions. Over eight modules, the book covers consumer and business lending in both the developed and developing worlds, providing the frameworks for both theory and practice. It first explores an introduction to credit risk assessment and predictive modelling, micro-histories of credit and credit scoring, as well as the processes used throughout the credit risk management cycle. Mathematical and statistical tools used to develop and assess predictive models are then considered, in addition to project management and data assembly, data preparation from sampling to reject inference, and finally model training through to implementation. Although the focus is credit risk, especially in the retail consumer and small-business segments, many concepts are common across disciplines, whether for academic research or practical use. The book assumes little prior knowledge, thus making it an indispensable desktop reference for students and practitioners alike. Credit Intelligence and Modelling expands on the success of The Credit Scoring Toolkit to cover credit rating and intelligence agencies, and the data and tools used as part of the process.

Credit Intelligence & Modelling

Author : Raymond A. Anderson
Publisher : Oxford University Press
ISBN 13 : 0192844199
Total Pages : 934 pages
Book Rating : 4.1/5 (928 download)

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Book Synopsis Credit Intelligence & Modelling by : Raymond A. Anderson

Download or read book Credit Intelligence & Modelling written by Raymond A. Anderson and published by Oxford University Press. This book was released on 2022 with total page 934 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credit Intelligence and Modelling provides an indispensable explanation of the statistical models and methods used when assessing credit risk and automating decisions. Over eight modules, the book covers consumer and business lending in both the developed and developing worlds, providing the frameworks for both theory and practice. It first explores an introduction to credit risk assessment and predictive modelling, micro-histories of credit and credit scoring, as well as the processes used throughout the credit risk management cycle. Mathematical and statistical tools used to develop and assess predictive models are then considered, in addition to project management and data assembly, data preparation from sampling to reject inference, and finally model training through to implementation. Although the focus is credit risk, especially in the retail consumer and small-business segments, many concepts are common across disciplines, whether for academic research or practical use. The book assumes little prior knowledge, thus making it an indispensable desktop reference for students and practitioners alike. Credit Intelligence and Modelling expands on the success of The Credit Scoring Toolkit to cover credit rating and intelligence agencies, and the data and tools used as part of the process.

Credit Intelligence and Modelling

Author : Raymond Anderson
Publisher :
ISBN 13 : 9781082136085
Total Pages : 418 pages
Book Rating : 4.1/5 (36 download)

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Book Synopsis Credit Intelligence and Modelling by : Raymond Anderson

Download or read book Credit Intelligence and Modelling written by Raymond Anderson and published by . This book was released on 2019-08 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forest Paths is a follow-up to Anderson's The Credit Scoring Toolkit, published by Oxford University Press in 2007, which was considered the bible of the industry. Where the Toolkit was broad-brush, this book focuses on the model-development process, but not without providing significant context. It assumes little prior knowledge and is appropriate for both university students and practitioners. It is the first real textbook on the topic, including chapters'-end questions. There are six modules: 1) an introduction to credit and predictive modelling; 2) micro-histories of credit, credit intelligence, and risk modelling; 3) statistical and predictive modelling theory; 4) project management and data assembly; 5) data preparation from sampling to reject inference; and 6) model training through to implementation. Appendices include an extensive glossary, bibliography, and index. The book is comprehensive, with much applicable to other domains, and includes many historical and contemporary anecdotes as well as numerous examples and illustrations. Although the focus is credit risk, especially in the retail consumer and small-business segments, many concepts are common across disciplines as diverse as psychology, biology, engineering, and computer science, whether academic research or practical use. It also covers issues relating to the use of machine learning for credit-risk assessment.#creditintelligence #creditrisk #creditscoring #creditscore #creditscores #creditbureau #credithistory #predictivemodeling #predictiveanalytics

Credit Intelligence and Modelling

Author : Raymond Anderson
Publisher :
ISBN 13 : 9780191926976
Total Pages : pages
Book Rating : 4.9/5 (269 download)

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Book Synopsis Credit Intelligence and Modelling by : Raymond Anderson

Download or read book Credit Intelligence and Modelling written by Raymond Anderson and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bio-Inspired Credit Risk Analysis

Author : Lean Yu
Publisher : Springer Science & Business Media
ISBN 13 : 3540778039
Total Pages : 248 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Bio-Inspired Credit Risk Analysis by : Lean Yu

Download or read book Bio-Inspired Credit Risk Analysis written by Lean Yu and published by Springer Science & Business Media. This book was released on 2008-04-24 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.

Intelligent Credit Scoring

Author : Naeem Siddiqi
Publisher : John Wiley & Sons
ISBN 13 : 1119279151
Total Pages : 469 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Intelligent Credit Scoring by : Naeem Siddiqi

Download or read book Intelligent Credit Scoring written by Naeem Siddiqi and published by John Wiley & Sons. This book was released on 2017-01-10 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Credit Risk Scorecards

Author : Naeem Siddiqi
Publisher : John Wiley & Sons
ISBN 13 : 1118429168
Total Pages : 124 pages
Book Rating : 4.1/5 (184 download)

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Book Synopsis Credit Risk Scorecards by : Naeem Siddiqi

Download or read book Credit Risk Scorecards written by Naeem Siddiqi and published by John Wiley & Sons. This book was released on 2012-06-29 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Fair Lending Compliance

Author : Clark R. Abrahams
Publisher : John Wiley & Sons
ISBN 13 : 9780470241899
Total Pages : 356 pages
Book Rating : 4.2/5 (418 download)

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Book Synopsis Fair Lending Compliance by : Clark R. Abrahams

Download or read book Fair Lending Compliance written by Clark R. Abrahams and published by John Wiley & Sons. This book was released on 2008-03-14 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Fair Lending ComplianceIntelligence and Implications for Credit Risk Management "Brilliant and informative. An in-depth look at innovative approaches to credit risk management written by industry practitioners. This publication will serve as an essential reference text for those who wish to make credit accessible to underserved consumers. It is comprehensive and clearly written." --The Honorable Rodney E. Hood "Abrahams and Zhang's timely treatise is a must-read for all those interested in the critical role of credit in the economy. They ably explore the intersection of credit access and credit risk, suggesting a hybrid approach of human judgment and computer models as the necessary path to balanced and fair lending. In an environment of rapidly changing consumer demographics, as well as regulatory reform initiatives, this book suggests new analytical models by which to provide credit to ensure compliance and to manage enterprise risk." --Frank A. Hirsch Jr., Nelson Mullins Riley & Scarborough LLP Financial Services Attorney and former general counsel for Centura Banks, Inc. "This book tackles head on the market failures that our current risk management systems need to address. Not only do Abrahams and Zhang adeptly articulate why we can and should improve our systems, they provide the analytic evidence, and the steps toward implementations. Fair Lending Compliance fills a much-needed gap in the field. If implemented systematically, this thought leadership will lead to improvements in fair lending practices for all Americans." --Alyssa Stewart Lee, Deputy Director, Urban Markets Initiative The Brookings Institution "[Fair Lending Compliance]...provides a unique blend of qualitative and quantitative guidance to two kinds of financial institutions: those that just need a little help in staying on the right side of complex fair housing regulations; and those that aspire to industry leadership in profitably and responsibly serving the unmet credit needs of diverse businesses and consumers in America's emerging domestic markets." --Michael A. Stegman, PhD, The John D. and Catherine T. MacArthur Foundation, Duncan MacRae '09 and Rebecca Kyle MacRae Professor of Public Policy Emeritus, University of North Carolina at Chapel Hill

Credit Scoring and Its Applications, Second Edition

Author : Lyn Thomas
Publisher : SIAM
ISBN 13 : 1611974569
Total Pages : 380 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Credit Scoring and Its Applications, Second Edition by : Lyn Thomas

Download or read book Credit Scoring and Its Applications, Second Edition written by Lyn Thomas and published by SIAM. This book was released on 2017-08-16 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Credit Risk Modeling

Author : Elizabeth Mays
Publisher : Global Professional Publishi
ISBN 13 : 9781888998382
Total Pages : 280 pages
Book Rating : 4.9/5 (983 download)

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Book Synopsis Credit Risk Modeling by : Elizabeth Mays

Download or read book Credit Risk Modeling written by Elizabeth Mays and published by Global Professional Publishi. This book was released on 1998-12-10 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers: � Implementing an application scoring system � Behavior modeling to manage your portfolio � Incorporating economic factors � Statistical techniques for choosing the optimal credit risk model � How to set cutoffs and override rules � Modeling for the sub-prime market � How to evaluate and monitor credit risk models This is an indispensable guide for credit professionals and risk managers who want to understand and implement modeling techniques for increased profitability. In this one-of-a-kind text, experts in credit risk provide a step-by-step guide to building and implementing models both for evaluating applications and managing existing portfolios.

Credit Risk Analytics

Author : Bart Baesens
Publisher : John Wiley & Sons
ISBN 13 : 1119143985
Total Pages : 517 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Credit Risk Analytics by : Bart Baesens

Download or read book Credit Risk Analytics written by Bart Baesens and published by John Wiley & Sons. This book was released on 2016-10-03 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

The Credit Scoring Toolkit

Author : Raymond Anderson
Publisher : Oxford University Press
ISBN 13 : 9780199226405
Total Pages : 791 pages
Book Rating : 4.2/5 (264 download)

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Book Synopsis The Credit Scoring Toolkit by : Raymond Anderson

Download or read book The Credit Scoring Toolkit written by Raymond Anderson and published by Oxford University Press. This book was released on 2007-08-30 with total page 791 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Intelligence and Credit Risk

Author : Rossella Locatelli
Publisher : Springer Nature
ISBN 13 : 3031102363
Total Pages : 115 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Artificial Intelligence and Credit Risk by : Rossella Locatelli

Download or read book Artificial Intelligence and Credit Risk written by Rossella Locatelli and published by Springer Nature. This book was released on 2022-09-13 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the alternative techniques and data leveraged for credit risk, describing and analysing the array of methodological approaches for the usage of techniques and/or alternative data for regulatory and managerial rating models. During the last decade the increase in computational capacity, the consolidation of new methodologies to elaborate data and the availability of new information related to individuals and organizations, aided by the widespread usage of internet, set the stage for the development and application of artificial intelligence techniques in enterprises in general and financial institutions in particular. In the banking world, its application is even more relevant, thanks to the use of larger and larger data sets for credit risk modelling. The evaluation of credit risk has largely been based on client data modelling; such techniques (linear regression, logistic regression, decision trees, etc.) and data sets (financial, behavioural, sociologic, geographic, sectoral, etc.) are referred to as “traditional” and have been the de facto standards in the banking industry. The incoming challenge for credit risk managers is now to find ways to leverage the new AI toolbox on new (unconventional) data to enhance the models’ predictive power, without neglecting problems due to results’ interpretability while recognizing ethical dilemmas. Contributors are university researchers, risk managers operating in banks and other financial intermediaries and consultants. The topic is a major one for the financial industry, and this is one of the first works offering relevant case studies alongside practical problems and solutions.

Artificial Intelligence in Financial Markets

Author : Christian L. Dunis
Publisher : Springer
ISBN 13 : 1137488808
Total Pages : 349 pages
Book Rating : 4.1/5 (374 download)

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Book Synopsis Artificial Intelligence in Financial Markets by : Christian L. Dunis

Download or read book Artificial Intelligence in Financial Markets written by Christian L. Dunis and published by Springer. This book was released on 2016-11-21 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.

Advanced Credit Risk Analysis and Management

Author : Ciby Joseph
Publisher : John Wiley & Sons
ISBN 13 : 111860489X
Total Pages : 454 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Advanced Credit Risk Analysis and Management by : Ciby Joseph

Download or read book Advanced Credit Risk Analysis and Management written by Ciby Joseph and published by John Wiley & Sons. This book was released on 2013-04-22 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credit is essential in the modern world and creates wealth, provided it is used wisely. The Global Credit Crisis during 2008/2009 has shown that sound understanding of underlying credit risk is crucial. If credit freezes, almost every activity in the economy is affected. The best way to utilize credit and get results is to understand credit risk. Advanced Credit Risk Analysis and Management helps the reader to understand the various nuances of credit risk. It discusses various techniques to measure, analyze and manage credit risk for both lenders and borrowers. The book begins by defining what credit is and its advantages and disadvantages, the causes of credit risk, a brief historical overview of credit risk analysis and the strategic importance of credit risk in institutions that rely on claims or debtors. The book then details various techniques to study the entity level credit risks, including portfolio level credit risks. Authored by a credit expert with two decades of experience in corporate finance and corporate credit risk, the book discusses the macroeconomic, industry and financial analysis for the study of credit risk. It covers credit risk grading and explains concepts including PD, EAD and LGD. It also highlights the distinction with equity risks and touches on credit risk pricing and the importance of credit risk in Basel Accords I, II and III. The two most common credit risks, project finance credit risk and working capital credit risk, are covered in detail with illustrations. The role of diversification and credit derivatives in credit portfolio management is considered. It also reflects on how the credit crisis develops in an economy by referring to the bubble formation. The book links with the 2008/2009 credit crisis and carries out an interesting discussion on how the credit crisis may have been avoided by following the fundamentals or principles of credit risk analysis and management. The book is essential for both lenders and borrowers. Containing case studies adapted from real life examples and exercises, this important text is practical, topical and challenging. It is useful for a wide spectrum of academics and practitioners in credit risk and anyone interested in commercial and corporate credit and related products.

Credit-Risk Modelling

Author : David Jamieson Bolder
Publisher : Springer
ISBN 13 : 3319946889
Total Pages : 704 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Credit-Risk Modelling by : David Jamieson Bolder

Download or read book Credit-Risk Modelling written by David Jamieson Bolder and published by Springer. This book was released on 2018-10-31 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning and Artificial Intelligence for Credit Risk Analytics

Author : Tiziano Bellini
Publisher : Wiley
ISBN 13 : 9781119781059
Total Pages : 304 pages
Book Rating : 4.7/5 (81 download)

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Book Synopsis Machine Learning and Artificial Intelligence for Credit Risk Analytics by : Tiziano Bellini

Download or read book Machine Learning and Artificial Intelligence for Credit Risk Analytics written by Tiziano Bellini and published by Wiley. This book was released on 2023-06-26 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Artificial Intelligence for Credit Risk Analytics provides a comprehensive, practical toolkit for applying ML and AI to day-to-day credit risk management challenges. Beginning with coverage of data management in banking, the book goes on to discuss individual and multiple classifier approaches, reinforcement learning and AI in credit portfolio modelling, lifetime PD modelling, LGD modelling and EAD modelling. Fully worked examples in Python and R appear throughout the book, with source code provided on the companion website. Machine Learning and Artificial Intelligence for Credit Risk Analytics fully covers the key concepts required to understand, challenge and validate credit risk models, whilst also looking to the future development of AI applications in credit risk management, demonstrating the need to embed economics and statistics to inform short, medium and long-term decision-making.