The ramifications of the financial crisis are well versed and nowhere is this more apparent than in the financial industry where an abundance of regulations have been driven through in line with the G20’s 92 point action plan. With the European Basel III and US Dodd-Frank directives evolving at an unprecedented rate, risk managers within investment banks have been thrust into the spotlight, charged with achieving an enterprise view of a bank’s risk exposure.
Prior to the collapse of Lehman’s, risk managers struggled to measure the multiple pillars of risk across their institutions and counterparty risk was no exception. While risk calculations at a desk level arguably achieved a reasonable view of risk exposure the complex nature of structured products coupled with the nuances between trading desks and inaccurate credit rating scoring meant that when the crisis struck risk assessments were far from accurate.
While hindsight is of course a wonderful thing, the failure of Lehman’s undisputedly highlighted the lack of an enterprise wide view of risk exposure, and in particular the complexity of mortgage-backed securities reiterated the intricacies of calculating counterparty risk.
Fundamental to the problems associated with calculating risk is data, and counterparty risk is no exception. Putting ratings aside, investment banks have not traditionally been identifying counterparties in the same way across trading desks, an issue which is further compounded when one considers the interrelationships between desks and the huge exposure to risk this approach has led too.
As such, regulators and industry associations are working hard to outline common identifiers to empower institutions to aggregate counterparty risk across books, desks and ultimately the company. This will not only help to achieve a view of systemic risk but also go some way to tying together netting agreements across books and desks, for example long versus short exposures.
A recent report on real-time risk, carried out by Lepus, and sponsored by SAS, reiterated this new found focus on counterparty risk from within investment banks, with one of the institutions surveyed indicating that not only are risk management departments taken more seriously and being treated more like business partners within firms, but there are a more balanced investments in other risk management tools such as issuer risk, stress testing and counterparty credit risk. Most importantly the report also pointed to the fact that the data quality underpinning risk calculations is being given more attention and scrutiny.
The motivations to accurately calculate counterparty risk do not stop with regulatory compliance; there is also a business advantage to be had by tieing counterparty risk metrics with credit value adjustment (CVA) calculations. With stringent capital adequacy requirements (CAR) limiting banks available capital, challenges are rife in regards to where to best allocate what capital is available. However, by working out the risk adjusted return on capital both traders and risk managers can make informed decisions based on pre-trade assessments.
In turn, with risk managers now firmly ensconced around the boardroom table, senior leadership can define their risk appetite and feed this down through the institution to the desk level – which to date has been hard to do. This not only increases control but also allows institutions to make returns from their capital allocation with ongoing risk adjustments being made and aggregated concentrations and exposures being highlighted.
It will come as no surprise that a transparent view of risk management, that offers a complete picture of all the different positions and trades at any given time, is needed. In order to ascertain an accurate view of their risk exposure investments banks will need to evolve the technology that underpins their risk management infrastructures. Where 10 to 15 years ago, real-time risk systems were described as ‘real-time enough’, in today’s market environment it is no longer sufficient to rely on periodical approximations.
Given the siloed nature of investment banks, coupled with the multitude of different systems which are running between lines of business and desks, the majority of risk managers within investment banks have quite a challenge ahead of them and will require the use of smarter and more agile technology. While this will mean substantial investments of both time and money, it will surely be a price worth paying if investment banks are to stay on top of both their counterparty risk exposure and capital allocation.
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