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Practical Credit Risk and Capital Modeling, and Validation - (Management for Professionals) by Colin Chen (Hardcover)
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Highlights
- This book provides professionals and practitioners with a comprehensive guide on credit risk modeling, capital modeling, and validation for Current Expected Credit Loss (CECL), International Financial Reporting Standard 9 (IFRS9), Basel Capital and Comprehensive Capital Analysis and Review (CCAR) procedures.
- About the Author: Colin Chen is the Founder and Director of Data Science and Analytics Consultants (Bayside, NY, USA), which focuses on data science projects from financial and media industries.
- 391 Pages
- Business + Money Management, Insurance
- Series Name: Management for Professionals
Description
Book Synopsis
This book provides professionals and practitioners with a comprehensive guide on credit risk modeling, capital modeling, and validation for Current Expected Credit Loss (CECL), International Financial Reporting Standard 9 (IFRS9), Basel Capital and Comprehensive Capital Analysis and Review (CCAR) procedures. It describes how credit risk modeling, capital modeling, and validation are done in big banks with code and examples. The book features innovative concepts such as Binary Logit Approximation (BLA) for Competing Risk Framework; Adaptive and Exhaustive Variable Selection (AEVS) for automatic modeling; Full Observation Stratified Sampling (FOSS) for unbiased sampling; and Prohibited Correlation Index (PCI) for Fair Lending Texts. It also features a chapter on credit underwriting and scoring, addressing the credit underwriting risk with some innovations. It is a valuable guide for professionals, practitioners and graduate students in risk management.
From the Back Cover
This book provides professionals and practitioners with a comprehensive guide on credit risk modeling, capital modeling, and validation for Current Expected Credit Loss (CECL), International Financial Reporting Standard 9 (IFRS9), Basel Capital and Comprehensive Capital Analysis and Review (CCAR) procedures. It describes how credit risk modeling, capital modeling, and validation are done in big banks with code and examples. The book features innovative concepts such as Binary Logit Approximation (BLA) for Competing Risk Framework; Adaptive and Exhaustive Variable Selection (AEVS) for automatic modeling; Full Observation Stratified Sampling (FOSS) for unbiased sampling; and Prohibited Correlation Index (PCI) for Fair Lending Texts. It also features a chapter on credit underwriting and scoring, addressing the credit underwriting risk with some innovations. It is a valuable guide for professionals, practitioners and graduate students in risk management.
About the Author
Colin Chen is the Founder and Director of Data Science and Analytics Consultants (Bayside, NY, USA), which focuses on data science projects from financial and media industries. He has over 15 years of experience in financial risk management having worked at JP Morgan Chase as an Executive Director of the Operational Risk Modeling Group and at Bank of America as a Director of Model Risk Management. He has also worked for Wells Fargo and Fannie Mae on credit and market risk models and for the SAS Institute as a Senior Software Developer.