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1、Modeling Credit Risk in Asian Context: The Building Block Approach May 2002,Introduction to Credit Risk Modeling,Introduction: Recent Developments in Credit Risk Modeling,Regulatory New Basel Accord sets regulatory acceptance of internal-rating based models (foundation and advanced approach),Competi
2、tion Asian crisis revealed vulnerability of concentration loans (large loans) to default, inadequate margin to cover credit risk General move to lending to consumers and SMEs, higher volume business, need to balance risk management and credit processing cycle time,Technology More robust credit risk
3、modeling technology Integration of data management, statistical analysis and decision support technology,注意,Data issue Historical portfolio information often not available Applicability of external data is (highly) questionable Quality of data is highly questionable,Introduction: Challenges in Imple
4、menting Credit Risk Models in Asia,Comparability of Financial Statements Lack of transparency No publicly traded debt Disparity in accounting standards,Unpredictable recovery rates Tax and regulatory rules Bankruptcy laws underdeveloped and incomparable,注意,Credit Risk Modeling: Conceptual Framework
5、and Building Block Approach,Credit Risk Modeling: Conceptual Framework,Credit risk modeling has to be enabled by effective credit risk infrastructure where critical historical risk factors for modeling can be stored. To effectively transform credit risk management of a bank, it is important to integ
6、rate credit risk models and infrastructure into a transformed credit risk process.,注意,Modeling Credit Risk: The Building Block Approach,Phase 1 Component,External Component,Phase 2 Component,Phase 3 Component,方法,Phase 1: Designing and Implementing an Effective Credit Risk Infrastructure,Objectives R
7、isk-adjusted pricing Portfolio risk diversification Risk capital planning BIS 2 compliance (global best practice) Cross-country analysis,Block 1& 2: Determine Credit Risk Modeling Scope,Exclusions Employees Deceased Specific industry,Modeling Credit Risk: Phase 1 - Credit Risk Infrastructure,Realist
8、ic implementation plan, typically not more than 10 credit risk models for first attempt.,Modeling Credit Risk: Phase 1 - Credit Risk Infrastructure,Block 3: Business Environment Study,Credit Risk Infrastructure Design,Credit Risk Management Tools Design,Credit Risk Process Integration Design,Evaluat
9、e Existing Credit Management Systems and IT strategy Develop IT blue-print for Credit Risk Solution Architecture,Evaluate Existing Credit Risk Models Develop Definition for Exposure, Exposure Aggregation (Related-Party), and Customer, Industry and Product Segmentation Feasibility Study of Empirical
10、Scorecard vs. Subjective Judgmental Rating-Based Approach,Map Existing Credit Risk Management Processes Identify Key Credit Controls,No. Past Due 90d,% 90d PD within Industry,No. of Past Due 90d,% of 90d PD within Industry,Distribution of No. of Corporate Client within 90d Past Due by Industry:,Mode
11、ling Credit Risk: Phase 1 - Credit Risk Infrastructure,Block 3: Business Environment Study (I),Wholesale & Retail,Manufacturing,Real Estate,Financial Services,Construction,Professional Services,Social Services,Telecommunication & IT,Utilities,Fishery & Farming,Feasibility Cut-off,注意,Determination of
12、 Credit Risk Modeling Approach based on Business Composition Study for CorporateLoan Portfolio:,Modeling Credit Risk: Phase 1 - Credit Risk Infrastructure,Block 3: Business Environment Study (I),Modeling Credit Risk: Phase 1 - Credit Risk Infrastructure,Block 3: Business Environment Study (II),18.9%
13、approved loan were below cut-off,Example of Evaluation of an Internal Subjective Scorecard Model of an Asian Bank Developed for Unsecured Consumer Loan: Excessive subjective intervention to the use of scorecard were found,17.5%above cut-off score were rejected,Subjective Cut-off,注意,Modeling Credit R
14、isk: Phase 1 - Credit Risk Infrastructure,Block 3: Business Environment Study (II),Score distribution revealed that model was not able to discriminate between good and bad accounts,Subjective Cut-off,注意,Modeling Credit Risk: Phase 1 - Credit Risk Infrastructure,Block 3: Business Environment Study (I
15、II),Example of Definition of Small and Medium Sized Enterprises (SMEs) where banks internal client information is not available:,Underlying assumption: SMEs are non-listed and non-issuer of public debt Segmentation approach: Model listed companies on the stock exchange, determine 5% tail of smallest
16、 listed companies as cut-off criteria and model non-listed companies, determine 25% tail of large non-listed companies. Take lowest cut-off of the 2 cumulative distribution Segmentation criteria: Gross revenue, total asset and total capital,Gross Revenue cut-off at HK$10 million,Gross Revenue cut-off at HK$20 million,注意,Modeling Credit Risk: Phase 1 - Credit Risk Infrastructure,Block 3: Business Environment Study (III),Total asset cut-off at HK$50 mil
