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Managing portfolio credit risk in banks /

This book explains how a proper credit risk management framework enables banks to identify, assess and manage the risk proactively.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Bandyopadhyay, Arindam (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York : Cambridge University Press, 2016.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Bandyopadhyay, Arindam,  |e author. 
245 1 0 |a Managing portfolio credit risk in banks /  |c Arindam Bandyopadhyay. 
264 1 |a New York :  |b Cambridge University Press,  |c 2016. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
520 |a This book explains how a proper credit risk management framework enables banks to identify, assess and manage the risk proactively. 
505 0 |a Cover; Title; Copyright; Dedication; Contents; Tables, Figures, Charts; Preface; Acknowledgements; Abbreviations; Chapter 1: Introduction to Credit Risk; Major Drivers of Credit Risk; Borrower Level Risk vs. Portfolio Risk; Importance of Management of Credit Risk in Banks; A. Market realities; B. Changing regulatory environment; C. Institution's risk vision; Role of Capital in Banks: The Difference between Regulatory Capital and Economic Capital; Credit Risk Management Framework; Credit Risk Management: Emerging Challenges for the Banking Sector in India; Summary; Key learning outcomes. 
505 8 |a Review questionsReferences; Chapter 2: Credit Rating Models; Types of Scoring Models; Different Rating Approaches; Expert Rating Systems; Internal Credit Rating System; One Tier vs. Two-tier Rating System; Rating Model for Project Finance (PF); Rating Model for SMEs; Risk Rating for Microfinance Institutions (MFIs); Country Risk Rating Model; External Credit Rating Systems; Brief History about Rating Agencies in India; Issue Rating vs. Issuer Rating; Risk Differentiation; Statistical Credit Scoring Models; Limitations of the Z-score Model; Default Prediction Model for Indian Corporates. 
505 8 |a Ratios usedLogit PD Prediction Model; Most Powerful Drivers of Default Risk in Corporate and SME loans; Statistical Scoring Model for SMEs; Credit Scoring Models for Retail Portfolio; How a Customized Retail Credit Scoring Model can be developed by Banks; Phase I; Phase II; Risk Parameters; Estimation Method; Key Decision Points Pertaining to Statistical Scoring Models; Examples of Retail Scoring Models; Agriculture Rating Model to Evaluate Risk in Farm Loans; Modern Methods; Market-based Corporate Default Risk Model; MKMV equations: Loans as options; Payoff for the Borrower and the Creditor. 
505 8 |a Market-based Measure to Assess the Banks' Risks: Distance to InsolvencyAdvantages of Market-based Model; Limitations of Structural Model; Reduced Form or Intensity-based Credit Scoring Models; Hybrid Credit Scoring Models; Summary; Key learning outcomes; Review questions; References; Chapter 3: Approaches for Measuring Probability of Default (PD); Methods for Estimating PD; Transition Matrix; Tasks for computing PDs; Method for estimation of PD through transition matrix; PD Estimation for a Low Default Portfolio (LDP); Cumulative Probability of Default (CPD). 
505 8 |a Pooled PD for Homogenous Buckets of Retail Exposures (Tracking the Numbers)Retail Pooled PD Approach; Frequency-based Measure; Exposure-based Rupee (or) weighted pooled PD; Summary; Key learning outcomes; Review questions; References; Chapter 4: Exposure at Default (EAD) and Loss Given Default (LGD); What is Exposure at Default (EAD)?; Critical components of exposure at default (EAD); Different approaches for estimating exposure at default (EAD); Description about Loan Facilities of Banks in India; Fund-based facilities; Non-fund-based facilities. 
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650 6 |a Gestion du risque. 
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650 7 |a Credit  |x Management.  |2 fast  |0 (OCoLC)fst00882536 
650 7 |a Risk management.  |2 fast  |0 (OCoLC)fst01098164 
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