By Charlie Browne, Head of Market Data and Risk Solutions at GoldenSource
Around this time 10 years ago, a certain investment bank’s stock plummeted amid concerns that its short-term liabilities were far greater than its liquid assets. The crucial issue Lehman Brothers failed to address, was how much capital it needed to hold. Yes, that all important difference between assets and liabilities.
Typically, banks need to review their capital for operational, credit and market risk. And a decade on from Lehman’s demise, it is assessing the latter which has triggered a set of rules forcing banks to calculate exactly how much capital is needed to protect themselves from sharp price falls. These prescriptive and global measures, more commonly known as the Fundamental Review of the Trading Book (FRTB). Despite the recent news that FRTB will be delayed beyond 2019, banks can ill afford to kick FRTB into the long grass. Due to the sheer scale and complexity the FRTB framework, firms need to start trying to work out exactly how much cash will be needed to underpin their market risk.
The difficulty, particularly for banks operating in traditionally less liquid and emerging markets, is assessing which of their diverse range of assets hold the most risk. A prime example is a bank based in APAC, where there is neither a single currency such as the euro, or a default reserve currency like the U.S. dollar for transactions. A common challenge a bank like this faces is trying to start with FRTB calculations, such as assessing the value of assets at risk (VAR), before shoe-horning in the vital information that determines the asset’s value. It is the equivalent of building a house on sand instead of bedrock. Or to put it another way, taking the Lehman Brothers approach to tackling FRTB.
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The point that so many firms are struggling to grasp is that doing the calculations, from expected shortfall to risk weighted sensitives, is not the main issue. The real challenge is assembling the right information to underpin the calculations. Call it taking the high-end builders approach to FRTB – laying the foundations. Easily said, but what does it look like and how can it be done?
Most of the FRTB calculations require the marriage of market and risk data, but historically, banks have struggled to achieve this without introducing errors. And with over 10 years’ worth of market data requiring assessment under FRTB, many now face an unprecedented challenge. Without collating this backlog of information, and without ingesting new data from the traditional markets data vendors, banks will not be able to identify and address any non-modelable risk factors (NMRFs). It is these NMFRs that have the biggest effect on whether trading can be done with a smaller pool of capital set aside based on the internal model approach. Or whether trading can be carried out under higher capital restraints which could lead to lower profitability.
Also, if a bank wants to ensure its calculations are fully auditable, it needs to be able to pull together and store market, position and risk data. This includes intel such as the contributor of the market data, its sensitivity, and exactly when it was distributed. A bank, as a case in point, may well have a portfolio of different interest rate positions. In this situation, a risk officer needs to fully understand the nature of each position. Whether measured in credit spreads or basis and volatility points, banks can only be confident in carrying out accurate FRTB calculations by understanding the market and risk data points that help quantify the difference between positions.
Even all these years on, many still struggle to fully comprehend the Lehman saga. It’s hard to imagine how, if FRTB was enforced way back in the late 2000s, simply ignoring key information underpinning calculations for mortgage backed securities would have made life easier for those taking the decisions that ultimately, changed the world. One thing’s for certain, any bank continuing to build their FRTB solutions on sand, as opposed to a bedrock of data, will soon find, as Lehman’s did, that its assets may not be enough to cover its liabilities.