Building and Implementing Better Credit Risk Scorecards
De som köpt den här boken har ofta också köpt The 48 Laws of Power av Robert Greene (häftad).
Köp båda 2 för 731 krNAEEM SIDDIQI is the Director of Credit Scoring and Decisioning with SAS Institute. He has more than twenty years of experience in credit risk management, both as a consultant and as a user at financial institutions. He played a key role in developing SAS Credit Scoring and continues to provide worldwide support for the initiative.
Acknowledgments xiii Chapter 1 Introduction 1 Scorecards: General Overview 9 Notes 18 Chapter 2 Scorecard Development: The People and the Process 19 Scorecard Development Roles 21 Intelligent Scorecard Development 31 Scorecard Development and Implementation Process: Overview 31 Notes 34 Chapter 3 Designing the Infrastructure for Scorecard Development 35 Data Gathering and Organization 39 Creation of Modeling Data Sets 41 Data Mining/Scorecard Development 41 Validation/Backtesting 43 Model Implementation 43 Reporting and Analytics 44 Note 44 Chapter 4 Scorecard Development Process, Stage 1: Preliminaries and Planning 45 Create Business Plan 46 Create Project Plan 57 Why Scorecard Format? 60 Notes 61 Chapter 5 Managing the Risks of In-House Scorecard Development 63 Human Resource Risk 65 Technology and Knowledge Stagnation Risk 68 Chapter 6 Scorecard Development Process, Stage 2: Data Review and Project Parameters 73 Data Availability and Quality Review 74 Data Gathering for Definition of Project Parameters 77 Defi nition of Project Parameters 78 Segmentation 103 Methodology 116 Review of Implementation Plan 117 Notes 118 Chapter 7 Default Definition under Basel 119 Introduction 120 Default Event 121 Prediction Horizon and Default Rate 124 Validation of Default Rate and Recalibration 126 Application Scoring and Basel II 128 Summary 129 Notes 130 Chapter 8 Scorecard Development Process, Stage 3: Development Database Creation 131 Development Sample Specification 132 Sampling 140 Development Data Collection and Construction 142 Adjusting for Prior Probabilities 144 Notes 148 Chapter 9 Big Data: Emerging Technology for Todays Credit Analyst 149 The Four Vs of Big Data for Credit Scoring 150 Credit Scoring and the Data Collection Process 158 Credit Scoring in the Era of Big Data 159 Ethical Considerations of Credit Scoring in the Era of Big Data 164 Conclusion 170 Notes 171 Chapter 10 Scorecard Development Process, Stage 4: Scorecard Development 173 Explore Data 175 Missing Values and Outliers 175 Correlation 178 Initial Characteristic Analysis 179 Preliminary Scorecard 200 Reject Inference 215 Final Scorecard Production 236 Choosing a Scorecard 246 Validation 258 Notes 262 Chapter 11 Scorecard Development Process, Stage 5: Scorecard Management Reports 265 Gains Table 267 Characteristic Reports 273 Chapter 12 Scorecard Development Process, Stage 6: Scorecard Implementation 275 Pre-implementation Validation 276 Strategy Development 291 Notes 318 Chapter 13 Validating Generic Vendor Scorecards 319 Introduction 320 Vendor Management Considerations 323 Vendor Model Purpose 326 Model Estimation Methodology 331 Validation Assessment 337 Vendor Model Implementation and Deployment 340 Considerations for Ongoing Monitoring 341 Ongoing Quality Assurance of the Vendor 351 Get Involved 352 Appendix: Key Considerations for Vendor Scorecard Validations 353 Notes 355 Chapter 14 Scorecard Development Process, Stage 7: Post-implementation 359 Scorecard and Portfolio Monitoring Reports 360 Reacting to Changes 377 Review 399 Notes 401 Appendix A: Common Variables Used in Credit Scoring 403 Appendix B: End-to-End Example of Scorecard Creation 411 Bibliography 417 About the Author 425 About the Contributing Authors 427 Index 429