This book provides a unique, focused introduction to the analytical skills, methods and techniques in the assessment of credit risk that are necessary to tackle and analyze complex credit problems. It employs models and techniques from operations research and management science to investigate more closely risk models for applications within the banking industry and in financial markets. Furthermore, the book presents the advances and trends in model development and validation for credit scoring/rating, the recent regulatory requirements and the current best practices. Using examples and fully worked case applications, the book is a valuable resource for advanced courses in financial risk management, but also helpful to researchers and professionals working in financial and business analytics, financial modeling, credit risk analysis, and decision science.
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Using examples and fully worked case applications, the book is a valuable resource for advanced courses in financial risk management, but also helpful to researchers and professionals working in financial and business analytics, financial modeling, credit risk analysis, and decision science.
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Introduction to Credit Risk Modeling and Assessment.- Credit Scoring and Rating.-  Data Analytics for Developing and Validating Credit Models.- Applications to Corporate Default Prediction and Consumer Credit.- Conclusions and Future Research. 
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This book provides a unique, focused introduction to the analytical skills, methods and techniques in the assessment of credit risk that are necessary to tackle and analyze complex credit problems. It employs models and techniques from operations research and management science to investigate more closely risk models for applications within the banking industry and in financial markets. Furthermore, the book presents the advances and trends in model development and validation for credit scoring/rating, the recent regulatory requirements and the current best practices. Using examples and fully worked case applications, the book is a valuable resource for advanced courses in financial risk management, but also helpful to researchers and professionals working in financial and business analytics, financial modeling, credit risk analysis, and decision science.
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Introduces latest analytical models and techniques for credit risk analysis Demonstrates the main steps in building and testing credit risk models Includes illustrative examples and fully worked application studies
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Produktdetaljer

ISBN
9783030075996
Publisert
2018-12-14
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Graduate, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet

Om bidragsyterne

Michalis Doumpos is Professor of Operations Research at the School of Production Engineering and Management of the Technical University of Crete (Greece). His research interests include multiple criteria decision making, decision support systems, business analytics, financial risk management, and energy economics. He has published over 80 research articles in premier international journals. He has also co-authored several books, edited volumes, book chapters, conference papers, and edited special issues. He has extensive consulting experience with the financial industry on projects related to credit scoring systems, banking risk management, and real estate appraisal.

Christos Lemonakis is Assistant Professor at the Technological Educational Institute of Crete, Greece, Department of Business Administration (Agios Nikolaos Branch). He has auditing experience in banking for more than 15 years. His research interests are SMEs Entrepreneurship, Risk Management, Auditing and Management Accounting. He is a Fellow Certified Public Accountant (FCPA) and a Certified Management Accountant (CMA) from the Association of Certified Public Accountants Int'l (CPA-London). He is a co-author of two books on banking risks and has contributed with several chapters in others. He has also published research papers in international journals and presented research work in many international conferences around the world.

Dimitrios Niklis is Adjunct Assistant Professor at the department of Accounting and Finance, Western Macedonia, University of Applied Sciences and Adjunct Academic Staff at the Postgraduate Course of Banking at Hellenic Open University. He holds a PhD in Financial Decision Making, an MSc in Business Economics & Management and a bachelor degree in Economics. His research interests include accounting, corporate finance, financial risk management, financial markets, economics, decision analysis, and management science. He has participated in various national,EU and international research projects and has published in international journals, edited volumes, and conference proceedings. 

Constantin Zopounidis is Professor of Financial Engineering and Operations Research, at Technical University of Crete (Greece), Distinguished Research Professor in Audencia Nantes, School of Management (France), and Senior Academician of the Royal Academy of Economics and Financial Sciences of Spain. His research interests include financial engineering, financial risk management, and multiple criteria decision making. He has published over 300 papers in premier international journals, edited volumes, and conference proceedings. He has also published several books and edited volumes on multicriteria decision making, financial engineering, and operations research. Prof. Zopounidis is Editor-in-Chief and member of the editorial board of several international journals. For his research work, Prof. Zopounidis has received awards and honorary distinctions from international research organizations, including among others the ΜΟISIL International Foundation, the Decision Sciences Institute, the European Association of Management and Business Economics, the Royal Academy of Doctors of Spain, the Hellenic Operational Research Society, and the International Association for Fuzzy Set Management and Economy. In 2013 he was the recipient of the MCDM Edgeworth-Pareto Award of the International MCDM Society.