Andrew Bailey (AMCT, MSTA), National Grid Money Markets Team:

There is no simple answer to this problem, but there are a range of measures that corporates can employ to monitor and mitigate their exposures. Counterparty risk management policies have traditionally been based on credit ratings, on the grounds that they provide simple and independent metrics of creditworthiness. However, throughout the financial crisis, market-based indicators have revealed deteriorating credit quality faster than ratings downgrades. Credit default swap (CDS) levels can be used as a leading indicator of distress, using changes in levels as much as the absolute values, although not all CDS prices will be liquid or efficient.

Treasurers should look outside of the individual entity to the wider group and the country of domicile, taking into account potential support from the parent or sovereign in the event of default. If practical, take the time to analyse capital adequacy measures such as tangible common equity (TCE) and Tier 1 capital ratios. However, with the best risk analysis in the world we will still not prevent events of default, so controls must be in place for when the inevitable happens.

Corporates should start with a diversified banking group, spread over geographies and specialisms, with alternative banks able to cover key trading or cash management functions. When investing cash within the group, companies have recently favoured short-dated, high quality investments at the expense of yield opportunities with lower liquidity or credit quality. Corporates can add a layer of security by investing on a secured basis via the repo market, which can also achieve a yield advantage versus unsecured deposits. Longer duration money market funds (MMFs) can exploit an upward-sloping yield curve, while maintaining diversification and liquidity to keep a low credit risk profile.

Within the derivative portfolio, offsets can be identified or created to minimise aggregate exposures. Where possible, trading should take place on a collateralised basis (using bilateral credit support annexes (CSAs) with minimal thresholds, or trading on a cleared basis), while managing potential liquidity risks that may arise from mark-to-market volatility and resultant collateral requirements. Break clauses can be inserted in longer-dated instruments. Companies should also be cognisant of secondary effects of counterparty risk, such as credit value adjustment (CVA) charges, which can in part be managed using credit auctions and options.

Treasurers should maintain vigilance when monitoring the financial health of their counterparties and employ a creative and multi-faceted approach to counterparty risk management.

Rohan Douglas, CEO, Quantifi Solutions:

Firms new to counterparty risk management can learn from early mistakes and benefit from the most recent modelling innovations that improve accuracy and simplify usage. The first step is accurately measuring counterparty exposure.

The most consistent and flexible approach is ‘American’ Monte Carlo that captures right and wrong-way risk, taking into account the impact of CSAs, collateral and existing positions. Right and wrong-way risks exist when the credit of the counterparty is related to the exposure of the trade with that counterparty.

The CSA terms, collateral posted and existing positions all need to be captured and their impacts measured when calculating counterparty exposure. New models accurately capture the expected future exposure profiles of each counterparty. A second step is pricing the costs associated with counterparty exposure. This includes the CVA and the funding cost adjustment (FVA). CVA measures the expected loss from counterparty default. CVA is needed to match bank counterparty methodologies and is also required by accounting standards. FVA measures the expected cost of funding a margined trade. It is important for evaluating alternate counterparties, CSAs and clearing options. Data and model calibration are often overlooked but play key roles in usability and effectiveness.

Counterparty risk measurement requires a large amount of data – including the terms of all trades with a counterparty, market data required to price these trades, terms of any CSA in place, details regarding collateral posted under the CSA, credit data about the counterparty, volatility information, and information about the relationships between market instruments. This data is both large and changing continually. Accumulation and management of this data is a key driver in the simplicity of implementation and operations of any counterparty risk tool.

Effective measurement and control of counterparty risk starts with accurate measurement, but even the most sophisticated models are not useful unless the right data management tools provide accurate data as input and a simple and transparent calibration process makes the models usable.

Dr. Tim Thompson, Senior Manager, Enterprise and Risk Services, Deloitte:

For a medium-sized to large corporate, the primary risk management goal with respect to counterparty credit risk (CCR) should be to prevent unwanted exposures from developing. That goal informs the measures to be gathered, risk limits, the controls and governance arrangements needed to keep risk within those agreed guidelines and the skill sets of the teams needed to manage the exposure.

The industry standard way to measure CCR is through expected exposure (EE), calculated for various points in time, and with a particular focus on the next 12 months. EE takes into account movements in the underlying risk factors as well as any netting and collateral agreements that the corporate has in place with its counterparties, who will nearly always be the banks that have facilitated particular trades. You need to have a clear view of each counterparties’ EE. Limits need to be set to guard against concentrations and, depending on the scale of operations, also at a sector or country level.

For more sophisticated corporates, EE can be modelled using a Monte Carlo or historic simulation approach, while for less sophisticated corporates it may be sufficient to take the mark-to-market value and apply an add-on (based on standard tables available in the Basel II banking regulations, or a one-off Monte Carlo calculation). The key skills sets required for these tasks are market risk and quantitative finance.

However, your team also needs credit risk skills, since you need to understand the probability of default (PD) of your counterparties. Multiplying the EE by the PD gives the expected loss (in the assumption of zero recovery). The more conservative approach will also factor in correlations between counterparties, since the kind of scenario that sees Bank A default will usually involve a deterioration in the credit quality of Bank B (especially if they are in the same country).

From an operational perspective, successful CCR management requires accurate – and as far as possible – automated capture of trade term sheet data into the front office systems and legal information on your netting agreements (ISDAs) or collateral agreements (CSAs) into a collateral system. This information is then combined into a risk system, which is where many firms can suffer from a weak control environment.

Finally, now that some corporates have better credit ratings than their banking counterparties, it is they who should be requiring collateral from the banks, not the other way round. For those firms, it can make business sense to hire resources that can calculate and manage counterparty risk and the associated collateral requirements independently.

Jonathan Chesebrough, Head of Risk Advisory, Royal Bank of Scotland (RBS):

In the past few years we have seen a lot of interest in this topic and are frequently engaging with our corporate clients as they reassess their bank CCR framework. We have heard of a number of corporates being ‘full’ on some of their counterparty banks, mainly if they evaluate counterparty credit risk by solely using credit rating and/or CDS level. An over reliance on these two measures of credit risk had to be questioned as CDS levels spiked in 2011 and the June 2012 Moody’s downgrade of 15 of the 17 major global banks left very few Aa (or AA) rated banks. For CDS, there has been a realisation that the lack of liquidity in the market limits their effectiveness as a gauge of credit risk. Indeed, studies have shown that even the most actively traded names may only have ten to 15 trades per day, indicating that single trades could overly impact CDS prices.

Instead it may be more appropriate to complement a counterparty credit assessment based solely on market indicators with a relatively easy to perform fundamental analysis, including both quantitative and qualitative considerations. Some quantitative measures include looking at: capital adequacy such as Tier 1 capital ratio; liquidity including dependence on wholesale funding, loan-to-deposit ratio, and size of liquidity buffer; core business profitability to ensure the counterparty is running a sustainable business; and asset quality such as Portugal, Ireland, Italy, Greece and Spain (PIIGS) exposure. All of these measures indicate the likely ability of a bank to honour their commitments.

Qualitative measures are harder to implement, but can still complement the quantitative ones. These include assessing: the home government’s support to the industry in cases of turmoil; the strength of local supervision and regulators; the home country’s bankruptcy and resolution process and rights; and the strength of the company’s management.