2020 Universal registration document and annual financial report - BNP PARIBAS414

5 risks and CaPital adequaCy Pillar 3

5

Counterparty credit risk

5.6 Counterparty credit risk

Counterparty credit risk is the translation of the credit risk embedded in financial transactions, investments and/ or settlement transactions between counterparties. Those transactions include bilateral contracts such as over-the-counter (OTC) derivative contracts as well as contracts settled through clearing houses. The amount of this risk may vary over time in line with changing market parameters which then impacts the replacement value of the relevant transactions.

Counterparty risk lies in the event that a counterparty defaults on its obligations to pay the Bank the full present value of the flows relating to a transaction or a portfolio for which the Bank is a net receiver. Counterparty credit risk is also linked to the replacement cost of a derivative or portfolio in the event of counterparty default. Hence, it can be seen as a market risk in case of default or a contingent risk.

In respect of counterparty risk, the RISK Function is structured according to five main priorities:

■ measuring exposure to counterparty credit risk;

■ checking and analysing these exposures and the limits that apply to them;

■ implementing mechanisms to reduce risk;

■ calculating and managing credit valuation adjustments (CVA);

■ defining and implementing stress tests.

COUNTERPARTY CREDIT RISK VALUATION

COUNTERPARTY EXPOSURE CALCULATION Exposure to counterparty risk is measured using two approaches:

Modelled exposure Internal model method

With regard to modelling counterparty risk exposure, the exposure at default (EAD) for counterparty risk is calculated based on the Effective Expected Positive Exposure (EEPE) indicator multiplied by the alpha regulatory factor as defined in article 284-4 of Regulation (EU) No. 575/2013. The Effective Expected Positive Exposure (EEPE) is measured using an internal exposure valuation model to determine exposure profiles. The model was developed by the Group and approved by the supervisor.

The principle of the model is to simulate the main risk factors, such as commodity and equity prices, interest rates and foreign exchange rates, affecting the counterparty risk exposure, based on their initial respective values. The Bank uses Monte-Carlo simulations to generate thousands of time trajectories (corresponding to thousands of potential market scenarios) to define potential changes in risk factors. The diffusion processes used by the model are calibrated on the most recent historic data set over a four-year period.

Based on all the risk factor simulations, the model assesses the value of the positions from the simulation date to the transaction maturity date (from one day to more than thirty years for the longest-term transactions) to generate an initial set of exposure profiles.

Exposure may be reduced by a Master Agreement, and may also be covered by a Credit Support Annex (CSA). For each counterparty, the model aggregates the exposures taking into consideration any netting agreements and credit support annexes, as well as the potentially risky nature of the collateral exchanged.

Based on the breakdown of exposure to the counterparty, the model determines the following in particular:

■ the average risk profile, the Expected Positive Exposure (EPE), from which the EEPE (Effective Expected Positive Exposure) is calculated:

The Expected Positive Exposure (EPE) profile is calculated as the average of the breakdown of counterparty exposures at each point in the simulation, with the negative portions of the trajectories set to zero (the negative portions correspond to situations where BNP Paribas Group is a risk for the counterparty). The EEPE is calculated as the first-year average of the non-decreasing EPE profile: at each simulation date, the value taken is the maximum of the EPE value and the value on the previous simulation date;

■ the Potential Future Exposure (PFE) profile:

The Potential Future Exposure (PFE) profile is calculated as a 90% percentile of the breakdown of exposure to the counterparty at each point in the simulation. This percentile is raised to 99% for hedge fund counterparties. The highest Potential Future Exposure value (Max PFE) is used to monitor maximum limits.