SME Funding (eBook)

Gianluca Oricchio has held senior capital and risk management positions at several global financial institutions for over 20 years. He has previously served as Head of Credit Treasury at Unicredit Group, Italy, and as Head of ACPM at Capitalia Banking Group, Italy. He has written several books on financial markets, corporate finance and risk management.Andrea Crovetto is co-founder and CEO of EPIC, a web-based securities trading platform focused on European SMEs. Over the past 20 years Andrea has held senior management positions at several major banks and has launched many innovative initiatives such as TLX, MAC/AIM and Kilovar. Sergio Lugaresi is currently Project Manager at the Italian Banking Association and interim Head of the Office of the World Bank in Rome, Italy. He is a member of the Panel of Experts at the International Monetary Fund (IMF). He has published several articles on banking, economics, monetary and fiscal policy. < Stefano Fontana is Assistant Professor in accounting and corporate management at La Sapienza State University in Rome, Italy. He is the author of many publications on corporate finance, business valuation, accounting.

Dedication 5
Foreword 6
Contents 9
List of Figures 11
List of Tables 15
1: Banking Crisis and SME Credit Risk Assessment 18
1.1 Introduction 18
1.2 The structure of the book 22
2: SMEs in Europe: An Overview 24
2.1 Introduction 24
2.2 European Commission Definition of SMEs 26
2.3 US Small Business Administration Definition of SMEs 29
2.4 Other Definitions of SMEs 29
2.5 The OECD Study 30
2.6 The SMEs Business Environment in Europe 30
2.7 A Comparison between the EU-28, Japan and the USA 33
2.8 A Brief Analysis of Sector Trends in the Period 2008–2013 36
2.9 The Major Problems Confronting European SMEs 37
2.10 SMEs in EU: A Comparison Analysis of France, Germany, Italy, the Netherlands, Spain, Sweden and the United Kingdom 45
3: European Funding of SMEs through Securitization: An Introduction 59
3.1 Securitization Models: A Brief Overview 61
3.2 Securitization in Europe and the USA: A Comparison 64
3.3 Securitization in Europe according to Country and Typology 64
3.4 Securitization in Europe for SMEs 66
3.5 European Union Reform of Stock Markets 70
4: Corporate and SME Credit Rating Models 74
4.1 PD Corporate SME Model Development 74
4.1.1 Step 1: Perimeter of Applicability and Definitions 74
4.1.2 Step 2a: Data Collection and Sampling 77
4.1.3 Step 2b: Model Structure 82
4.1.4 Step 2c: Methodological Approach 83
4.1.5 Statistical Methodology 85
4.1.5.1 Expert-based Methodology 86
4.1.6 Step 3: Univariate Analysis 89
4.1.7 Step 4: Multivariate Analysis 95
4.1.8 Step 5: Calibration, Integration and Mapping to the Master Scale 102
4.1.9 Step 6: Embedding the Model in the Banking Processes 105
4.2 PD Corporate SME Sub-segment Models 106
4.2.1 Statistical Expert-based Models 108
4.2.1.1 Qualitative Modules 108
4.2.1.2 Integration of the Statistical and Expert-based Components 109
4.2.2 Pure Expert-based Models 112
4.2.2.1 Financial Modules 114
4.2.2.2 Qualitative/Behavioral Modules 114
4.2.2.3 Integration of Pure Expert-based Modules 114
4.3 Term Structure of Probability of Default 120
4.3.1 Observed Term Structures 120
4.3.2 Marginal, Forward, and Cumulative Probability of Default 121
4.3.3 Mapping PD Ratings to Observed Term Structures 122
4.4 Transition Matrix State – Dependent 122
4.5 Validation of Internal Credit Rating Models 123
4.6 Validation of the PD Model 135
4.6.1 PD Model Design Validation 137
4.6.2 PD Estimation Process Validation 137
4.7 PD Performance Assessment and Backtesting 140
4.7.1 Process Impact on the PD Model’s Performance 140
4.7.2 PD Discriminatory Power Tests 143
4.7.3 PD Calibration Tests 147
4.7.3.1 PD Stability Tests 151
5: SME Credit Rating Models: A New Approach 154
5.1 Definition of Default 154
5.2 Data Description 157
5.2.1 Data Exclusions 157
5.2.2 Descriptive Statics of the Data 158
5.2.2.1 Overview of the Data 158
5.2.2.2 Robustness of the Data 159
5.2.3 Cleaning the Data 159
5.3 Model Architecture 161
5.3.1 Model Development 162
5.3.2 Development Samples 164
5.3.3 Univariate Analysis, Multivariate Analysis and Model Weights 171
5.3.4 Central Tendency 176
5.4 Validation of the Model 176
5.5 Leveraging Behavioral Data and Enhancing Model Accuracy 178
5.6 Two SME Credit Risk Assessment Cases 180
5.6.1 Company A 180
5.6.2 Company B 181
5.7 SME Credit Risk: An Empirical Analysis 182
6: Restarting the Credit Engine in Europe 187
6.1 Introduction 187
6.2 The Actors 189
6.2.1 Promotional Institutions 189
6.2.2 Central Banks 190
6.2.3 European Institutions 191
6.2.4 Public-Private Partnership 192
6.2.5 Initiatives by Aim 193
6.2.6 Reducing the Cost of Bank Funding 194
6.2.6.1 National Initiatives 194
6.2.6.2 Europe-Wide Initiatives 195
The European Central Bank 195
Prime Collateralized Securities (PCS) 196
6.2.7 Sharing Risk and Lowering Interest Rates 200
6.2.7.1 Direct Lending 200
6.2.7.2 Guarantee Schemes 201
6.2.7.3 Public Guarantee Schemes 202
6.2.7.4 Mixed Schemes 204
6.2.7.5 Europe-Wide Initiatives 206
6.2.7.6 Credit Insurance 206
6.2.7.7 Favouring Non-bank Financing 206
6.2.7.8 Equity Finance 208
6.2.7.9 Capital Markets 209
6.2.7.10 Funding Escalator 210
6.3 Non-bank Financing: Credit Funds, Peer-­to-­Peer Lending and Crowd Funding 211
6.3.1 Shadow Banking Definition 211
6.3.2 Shadow Banking and the Crisis 214
6.3.3 Regulation of the Shadow Banking System 217
6.3.3.1 Direct Lending 220
6.3.3.2 Crowdfunding 221
6.3.3.3 Peer-to-Peer Lending 222
6.3.4 Summary 223
7: Alternative Funding Options: E-platforms 224
7.1 Why E-platforms? 224
7.2 Upstream (of Capital)-Side Driven Opportunities 226
7.3 Downstream Opportunities 226
7.4 The Need for Liquidity 227
7.5 From One-to-One Lending to Aggregators 229
7.6 From Aggregators to E-platforms 230
7.7 A Brief Thought on Responsible Borrowing (and Lending) 233
7.8 Lending-based and Investment-based E-platforms 234
7.8.1 A Special Focus on Investment-based E-platforms and Their Future in the European Union 239
7.9 The UK’s Focus on FinTech 241
7.10 Investors 243
7.10.1 Fundraisers 247
7.10.2 Financial Instruments 248
7.11 Why E-Platforms? 248
8: The Epic Case Study 249
References 259
References on CCRs 264
Index 269