Since the start of the financial crisis, extreme market turbulence and increased regulatory scrutiny have brought counter-party credit risk management to the top of the banking agenda. The collapse of Lehman Brothers has led to a deterioration in confidence that financial institutions are capable of fulfilling their obligations to their counter-parties. The continuing troubles in the Eurozone, combined with the widespread downgrading of sovereign debt, have resulted in a loss of faith in the ability of nation states to fulfill their obligations.
Banks subsequently have been developing sophisticated methodologies to cope with the increase in counter-party risk. The credit valuation adjustment (CVA) is a calculation central to good counter-party credit risk management. CVA represents the price assigned to trades to take into account the possibility of a counter-party defaulting/migrating.
The Bank of International Settlements estimated that nearly two thirds of the losses from the financial crisis of 2008 were in fact the result of CVA volatility as opposed to actual defaults, which highlights the importance of CVA to the integrity of the banking system and capturing migrations rather than simply focusing on defaults
The specialised CVA trader has risen to prominence in recent years and many banks now have their own CVA desks. However, IT infrastructure limitations and a vast array of complex modelling techniques means that CVA is an area with which many banks still struggle. And with Basel III set to require banks to hold capital against CVA volatility, these fiendishly difficult calculations will become even more important to financial institutions.
In a recent survey of 39 global financial institutions conducted by the Lepus Institute and sponsored by SAS, 92 per cent of banks said that they were not fully capable of effective CVA calculations. This figure is worrying and highlights the investment required by the vast majority of banks to ensure that they are adequately protected by future market shocks.
Critical to effective CVA management is a bank’s ability to perform computations in near real-time, so that the bank has up-to-date information on exposures to counter-parties when making a trade and managing positions. The massive growth in the derivatives space means that banks can no longer get away with risk calculations processed at the end of day or even at the end of week.
In the survey, only five per cent of respondents said they were capable of calculating CVA in near real-time while only 24 per cent do it on an intra-day basis. If banks operate with out-of-date risk information, they are trading with a blind spot; a failing which could wound them.
Most current enterprise risk systems in place at banks are neither powerful nor agile enough to cope with calculating CVA in near-real time. Another impediment to effective CVA is that many banks still operate in siloes; for such banks, aggregating data to calculate risk exposures across the business in near real-time is a big headache.
For the majority of banks, upgrading to an infrastructure capable of calculating CVA in near-real time across asset classes will be a challenge due to the huge volume and variety of big data that they must analyse, but those that do will quickly reap the benefits.