Credit Risk In A Model World Bob Scanlon

Credit Risk In A Model World Backtesting Volatility of capital Database Rating requirements Consistency of rating Parameters for portfolio risk

Impact of Loan Portfolio MTM Introduction: The movement towards marking to market loan portfolios will have a significant impact on P&L volatility. The principle drivers will be; volatility in credit spreads. the nature of the portfolio, in terms of credit rating and the tenor of the loans.

Impact of Loan Portfolio MTM A hypothetical 5 year $25bn loan portfolio has been modelled to show the impact of changes in credit spreads;

Use in Credit Assessment RATING MODELS HAVE NOW BEEN DEVELOPED SUFFICIENTLY TO BE USED FOR STAND-ALONE RATINGS Benefits of using robust, well-validated rating models Consistent: All factors inherent in ratings are imputed into final ratings via universally-accepted benchmarks Unbiased: Subjective judgement can be consistently applied within the rating process. Transparent: Models provide a complete description of methodology employed Coverage: Ability to assess corporates and banks beyond coverage of the major rating agencies. Efficiency: Ratings can be quickly generated using extensive on-line databases.

Implementation CRS EMPLOYS ON-LINE FINANCIAL DATA TO GENERATE RATINGS BASED ON A PROVEN RATING METHODOLOGY CRS is an integrated system

Sample Output

Process of Development DEVELOPMENT OF CRS IS AN EVOLUTIONARY PROCESS, AND NOT PURELY QUANTITATIVE Development involves significant analytical evaluation and feedback Ratings Agencies: Have developed quantitative models for several years employing all means of modelling from expert systems to neural networks. Now increasingly see their franchise as providing a rating methodology, rather than rating names (so have all begun to market quantitative models on this basis.). We are in discussion with Moody’s to benchmark our model to their unpublished neural network model. Third Party: Mostly publicly led by KMV. But also includes Alcar and Zeta Models (which are based off multi discriminant analysis). Moody’s also operate as a third-party supplier, but the methodology employed is very different. Chase/Chemical: Have publicised their methodology, which is now inherent in methodologies used at CIB. All factors are weighted. based on expert based logic to introduce consistency into the internal rating allocation. Others?: Have publicised their methodology, which is now inherent in methodologies used at We really beleive the agencies and KMV represent our peer group in respect to the quantification of our credit risk at a counterparty level. But KMV is not yet a sufficiently accepted benchmark - which the proposals has done little to reinforce. An example of how they might impact our methodology is their approach to industry definitions. In terms of the agencies, we are most active in dialogue with them to understand how and where they are moving. A good recent example is the definition of ratings

Methodology CHOICE OF APPROACH IS BASED ON SEVERAL CRITERIA, BUT MUST BE SIMPLE !! Quantitative models must be supportive to the analysis of credit risk Cannot be a ‘black box’ – needs to be sufficiently transparent to allow interpretation of output Need for compatibility with benchmarks used within internal rating process

Approaches Used CRS IS A HYBRID APPROACH WITH MODELS DEFINED BY SECTOR AND JURISDICTION Input to the models

Fundamental Data HIGH CORRELATIONS BETWEEN VARIABLES ALLOW DEVELOPMENT OF SIMPLE, BUT EFFECTIVE MODELS Example - US food retailing

Fundamental Data NON-LINEAR METHODS ARE NECESSARY FOR OPTIMAL MODEL PERFORMANCE Example - Profits and Financial Strength Rating for European Banks

Model Validation CRS HAS BEEN VALIDATED USING SEVERAL APPROACHES, RATHER THAN A SIMPLE “ONE ANSWER” APPROACH Comprehensive validation should employ a multi-faceted approach We start with and then dig down into the definition of credit ratings. This step is impt as we require a more precise definition to evaluate our success within both models we will talk about and

Default Prediction CRS DEFAULT EXPERIENCE Analysis of rated defaults shows similar ratings at ‘near default’ Correspondence between CRS and public ratings by looking at ratings for a portfolio of names one year prior to default. Source: Moody’s Default Risk Service

Impact of Size STABILITY OF KEY DRIVERS, SUCH AS SIZE, IS CRITICAL TO USE ON DISPARATE PORTFOLIOS Example – Impact of asset size on model performance for chemicals

Credit Risk In A Model World Once adopted how do you integrate model use for Credit decisions Exposure methodology Profit / risk maximisation minimisation or risk/reward Control or business function

Credit Risk In A Model World Limit homogenisation Weighted approach Benchmarks New deals into portfolio Immunisation Credit derivatives ? Next generation

Credit Risk In A Model World Out-performance through monitoring Parameter adjustment Staffing levels Information inputs Fall back process Prayers