
FRTB: a Sisyphean labour
Since the framework was finalised, banks have used up roughly half the time available to them for implementation before the rules are phased in from 2019

Greek mythology tells the unhappy tale of Sisyphus, doomed for all eternity to push a boulder up a hill – only to watch it roll back down and flatten him each time he completes the task. It’s a feeling banks in the throes of implementing the Basel Committee on Banking Supervision’s new market risk rules – the Fundamental review of the trading book (FRTB) – will be able to relate to.
The clock is ticking: almost 18 months since the framework was finalised, banks have used up roughly half the time available to them for implementation before the rules are phased in from 2019.
However, several major challenges must be brooked before banks can declare themselves ready. Many of them relate to banks’ freedom to continue calculating market risk capital requirements for a given desk or product by using their own models. Failure to win supervisory approval for this approach will force a desk to shift to the regulator-set standardised approach, which will carry a capital hit of anywhere between double and six times the numbers achieved using an internal model, according to one study.
Top of the list of concerns over achieving own-model approval is the profit-and-loss (P&L) attribution test, which compares the hypothetical P&L generated by a bank’s front-office pricing model for a desk with its risk-theoretical P&L. Both approaches are designed to reflect the P&L generated by revaluing yesterday’s portfolio using today’s end-of-day prices. To pass the test, there can only be a small variance between the two measures.
Basel’s final FRTB framework sets out two apparently conflicting ways of generating a desk’s risk-theoretical P&L, however – and one version is significantly more difficult than the other. Astonishingly, more than a year after the issue first came to light, banks are still unsure which version of the test they will be required to use.
Basel’s long-awaited FAQ document conspicuously failed to acknowledge the issue when it finally materialised in January – forcing banks to assume the worst and prepare to apply the more complex version of the test.
As a number of the contributors to our special report outline, banks are already allocating tens of millions of dollars in tech spending to the tasks that will enable them to gain own-models approval, such as sourcing the data required to generate the requisite sensitivities to model a particular product – a costly undertaking for exotic products, or those with non-linear payoffs.
For regional lenders, the hurdles to implementation look higher still: many complain local market liquidity – even for benchmark products such as longer-dated government bonds – is too patchy, with trading heavy around key events and then non-existent on all but the most liquid tenors for weeks on end.
This is a facet many have learned to live with when pricing trades using their own trusted models – but under Basel’s non-modellable risk factor framework, which penalises illiquid risk factors, it is a sure-fire route to a hefty capital add-on when modelling a product with highly variable liquidity.
Many will be hoping other supervisors take a leaf out of the European Commission’s approach in calling for a further three-year phase-in for the rules to take effect. But the risk of global regulators’ approaches diverging is already growing: with the mood music from Washington pointing to obstruction from US lawmakers, fears are being raised that the US may deliberately dally while other jurisdictions roll ahead with implementation.
With US banks dominating trading in many key global markets, a fragmented roll-out would render other houses at a crippling disadvantage. Already, say market watchers, many banks have begun to focus their implementation efforts on those portions of the rules that have the highest value-add for their business lines, in a bid to ensure that something positive comes from the Sisyphean task of implementing FRTB.
Read more articles from the FRTB special report
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