Société Générale / Risk Report - Pillar III

6 CREDIT AND COUNTERPARTY CREDIT RISK RISK MEASUREMENT AND INTERNAL RATINGS

TABLE 24: WHOLESALE CLIENTS - MAIN CHARACTERISTICS OF MODELS ANDMETHODS USED

Parameter modelled

Portfolio/Category of Basel assets

Number of methods, models

Methodology Number of years default/loss

WHOLESALE CLIENTS

Sovereigns

1 method.

Econometric method, low default portfolio.

Statistical (regression)/expert methods for the rating process, based on the combination of financial ratios and a qualitative questionnaire. Low default portfolio.

Public sector entities 4 models according to geographic region.

11 models according to type of counterparty: banks, insurance, funds, financial intermediaries, funds of funds.

Expert models based on a qualitative questionnaire. Low default portfolio.

Financial institutions

3 models according to type of transaction.

Expert models based on a qualitative questionnaire. Low default portfolio.

Specialised financing

Probability of Default (PD)

9 models according to geographic region.

Mainly statistical models (regression) for the rating process, based on the combination of financial ratios and a qualitative questionnaire. Defaults observed over a period of 8 to 10 years. Mainly statistical models (regression) for the rating process, based on the combination of financial ratios and a qualitative questionnaire, behavioural score. Defaults observed over a period of 8 to 10 years. Calibration based on historical data and expert judgements. Losses observed over a period of more than 10 years. Calibration based on historical data adjusted by expert judgements. Losses observed over a period of more than 10 years. Statistical calibration based on historical market data adjusted by expert judgements. Losses observed over a period of more than 10 years. Statistical calibration based on historical data adjusted by expert judgements. Losses observed over a period of more than 10 years. Statistical calibration based on historical data adjusted by expert judgements. Losses observed over a period of more than 10 years. Statistical calibration based on historical data adjusted by expert judgements. Losses observed over a period of more than 10 years. Statistical calibration based on historical data adjusted by expert judgements. Losses observed over a period of more than 10 years.

Large corporates

Small- and medium-sized companies

18 models according to the size of the Company and the geographic region.

6 models according to type of counterparty.

Public sector entities – Sovereigns

>20 models Flat-rate approach according to type of collateral. 16 models Discount approach according to type of recoverable collateral. 15 models Flat-rate approach according to type of collateral or unsecured. 8 models Flat-rate approach according to project type. 5 models Flat-rate approach according to type of counterparty: banks, insurance, funds, etc. and the nature of the collateral. 6 models: factoring, leasing with option to purchase and other specific cases. 5 models: term loans with drawing period, revolving credits, Czech Corporates.

Large corporates – Flat-rate Approach

Large corporates – Discount Approach

Small- and medium-sized companies

Loss Given Default (LGD)

Project financing

Financial institutions

Other specific portfolios

Credit Conversion Factor (CCF)

Models calibrated by segment. Defaults observed over a period of more than 10 years.

Large corporates

Real estate transactions

Statistical model based on expert judgements and a qualitative questionnaire. Low default portfolio.

Expected Loss (EL)

2 models by slotting.

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