NATIXIS -2020 Universal Registration Document

RISK FACTORS, RISK MANAGEMENT AND PILLAR III Risk management

model performance indicators: the model’s performance is V measured to validate the segmentation and also to quantify, overall, the differences between the forecast and actual figures. This is achieved by using statistical indicators, which are compared against those calculated during modeling. Loss given default models (internal LGD) are calculated: based on internal and external histories and an external V benchmark for banks and sovereigns; on a statistical basis for the corporate asset class; V using stochastic models if there is a claim against a financial V asset.

The results of the backtesting may require recalibrating the risk input, where appropriate. Once complete, a backtesting report is produced to represent: all the results of the backtesting indicators used; V any additional analyses; V an overall opinion of the results in accordance with the Group’s V standards. The report is then submitted to the internal validation teams (Model Risk Management)for their input, and subsequentlypresented to the various Committees to inform the bank’s management.

Backtesting of LGDs and PDs by exposure class

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2020 backtesting figures

Observed LGDs

Model LGDs

Observed default rate

Estimated PD

Sovereigns

40.20% 29.33% 29.64%

65.20% 58.37% 32.77%

0.37% 0.18% 0.55%

2.23% 0.49% 0.66%

Banks

Corporate

In respect of the market risk factor, backtesting uses historical trends to test risk factor predictions based on the stochastic processes. Backtesting can be performed ex-post by taking the aggregate historical market data for the selected backtestingperiod, or, to expand the results over wider time horizons and/or cover a broader range of market conditions. It may also be performed retroactively: this specific approach is called retro-backtesting.Here, the aim is to demonstrate that the models would have worked correctly had they been implemented in earlier periods and are thus suitable for future use. In terms of exposure, the backtest applies historical Mark-to-Market (MtM) values of static backtesting portfolios to test the predicted futureMtM values. In terms of risk factors, exposuresare backtested ex-post by gathering the historical prices achieved, even though retro-backtestingcapacities have been introduced for a sub-groupof products. The ex-post approach involves duplicatingthe transactions in the dedicated backtesting portfolios directly in the front-office systems. The ageing process is thus similar to that of real portfolios. Retro-backtestinguses a specific tool to retro-backtest MtM on the main product categories. The results are factored in at transaction level for historical and retroactive approaches and at several aggregated levels, including the product type and the counterparty for the historical approach only. The transactionsconsideredfor static backtestingduplicated in the front-office portfolios were chosen in such a way as to ensure the representativenessof portfoliosand are discountedon an annual basis. Present and future prices are taken from the CCR (Counterparty Credit Risk) model engine, current prices being reconciled every quarter with those of the front-office systems, acting as reference.

This table provides a general summary of the system’s performance but differs from the annual backtests carried out within the Group, which are conducted on a model-by-model basis and not overall by portfolio. However, this table allows a comparison of estimates and actual results for each internal input over an extended period and for a significant, representative percentage of each exposure class. The results come from data warehouses used for modeling. This is based on all performing customers for default rates and PD, and on all customers in default for LGD. These results also take into account the latest regulatory changes (guidanceon probabilityof default (PD) estimates and loss given default estimates (LGD) estimates). Backtesting and validation are key items of governance in the Internal Model Method approach. In accordance with general regulatory requirements, the reliability of internal models must be monitored regularly using a comprehensive backtesting program. This process is essential for ensuring the quality and relevanceof the results obtained from the models that have been developed and used for both internal risk management, and to meet regulatory obligations. The counterparty risk backtesting program is designed to validate the key assumptions on which the exposure model is built – stochasticprocesses for market risk factors, correlationsand pricing models – and to identify notable discrepancies in specific model elements. The developed framework is based on the following twobacktests: market risk factor backtesting, i.e. to assess the predictivecapacity V of the stochastic processes used to describe the dynamics of unique risk factors; portfolio backtesting: i.e. to assess the full exposure model V (stochastic process, correlations and pricing) for portfolios representing Natixis’ exposures. Monitoring and backtesting of counterparty risk model

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NATIXIS UNIVERSAL REGISTRATION DOCUMENT 2020