Analytical Techniques in the Assessment of Credit Risk: An Overview of Methodologies and Applications
by Michalis Doumpos (Author), Christos Lemonakis (Author), Dimitrios Niklis (Author), Constantin Zopounidis (Author)

About the Author
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.

About this book
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.

Table of contents
1 Introduction to Credit Risk Modeling and Assessment 1
    1. 1 Introduction 1
    1. 2 Credit Risk Management for Financial Institutions 4
    1. 3 Uncertainties and Risk Factors 5
    1. 4 Elements of Credit Risk Modeling 7
    1. 5 The Regulatory Framework for Financial Institutions 8
    1. 6 Types of Credit Risk Assessment Approaches 10
        1. 6. 1 Judgmental Approaches 10
        1. 6. 2 Data-Driven Empirical Models 12
        1. 6. 3 Financial Models 13
    1. 7 Measuring the Financial Performance of Loans 18
    1. 8 Notes and References 20
2 Credit Scoring and Rating 23
    2. 1 Introduction 23
    2. 2 The Contexts of Credit Scoring and Rating Systems 25
        2. 2. 1 Through the Cycle and Point in Time Assessments 25
        2. 2. 2 Issuer Ratings and Issue-Specific Ratings 25
        2. 2. 3 Behavioral and Profit Scoring 26
        2. 2. 4 Social Lending 27
    2. 3 Modeling Requirements 27
    2. 4 Development Process 28
        2. 4. 1 Data Collection and Pre-processing 29
        2. 4. 2 Model Fitting 33
        2. 4. 3 Model Validation 34
        2. 4. 4 Definition and Validation of Ratings 36
        2. 4. 5 Implementation 37
    2. 5 Credit Rating Agencies 37
    2. 6 Notes and References 40
3 Data Analytics for Developing and Validating Credit Models 43
    3. 1 Introduction 43
    3. 2 Modeling Approaches 46
        3. 2. 1 Statistical Models 46
        3. 2. 2 Machine Learning 53
        3. 2. 3 Optimization Approaches 58
        3. 2. 4 Multicriteria Decision Aiding 62
    3. 3 Performance Measures 68
        3. 3. 1 Misclassificatio n Costs 68
        3. 3. 2 Classification Accuracies 69
        3. 3. 3 Receiver Operating Characteristic Curve 71
        3. 3. 4 Kolmogorov-Smirnov Distance 73
    3. 4 Notes and References 74
4 Applications to Corporate Default Prediction and Consumer Credit 77
    4. 1 Introduction 77
    4. 2 Prediction of Corporate Defaults 77
        4. 2. 1 Data Description 78
        4. 2. 2 Selection of Variables 80
        4. 2. 3 Analytical Approaches for Predictive Modeling 84
        4. 2. 4 Results 84
    4. 3 Retail Banking 88
        4. 3. 1 Clustering Techniques 90
        4. 3. 2 Applying Cluster Analysis to Credit Risk Assessment 92
        4. 3. 3 Data and Variables 93
        4. 3. 4 Results 95
        4. 3. 5 Perspectives 97
    4. 4 Notes and References 98
5 Conclusions and Future Research 99
References 103
Index 109

Series: EURO Advanced Tutorials on Operational Research
Length: 111 pages
Publisher: Springer; 1st ed. 2019 edition (November 13, 2018)
Language: English
ISBN-10: 3319994107
ISBN-13: 978-3319994109

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