Don’t let a good crisis go to waste
In the aftermath of the financial crisis, regulators scratching their heads on how to prevent a repeat were in the early days of beefing up what would become a tough battery of annual stress-testing programmes – and a row broke out between one central bank and its prudential supervisory arm.
There was broad agreement that stress scenarios made sense as a means of getting banks to think about what would happen if an unlikely confluence of events led to another far-reaching, long-lasting crisis. The problem came when the question of how severe to make these scenarios arose, recalls one seasoned former regulator at the prudential watchdog – still the subject of endless rows between banks and regulators, and policy-makers themselves.
The central bank’s economists were pushing the regulator to make its stress scenarios countercyclical, recalls the veteran supervisor; the country was already mired in its deepest post-war recession, they argued, and surely things couldn’t get any worse – so why make the stress tests any more punitive for the country’s ailing banks than they needed to be?
Reluctant to call the bottom of the cycle, the regulator dug its heels in: “Sure enough, when we first came out with a really severe scenario, their economists were sceptical about how severe it was,” the supervisor – an economist by training – recalls. “The economic reality afterwards turned out to be even more severe.”
The episode cuts to the heart of a problem that has dogged administrators of stress tests – now established as the post-crisis barometer of the health of a nation’s banks – throughout the last decade: what does ‘severe but plausible’ look like?
Regulators’ worst-case scenarios, gradually watered down by intense lobbying from lenders and politicians, have not found their consensus on that point tested by real events – until now.
The economic devastation wrought by Covid-19 is already significant: the hits to employment, gross domestic product and other key macro factors regulators ask banks to test to has already surpassed supervisors’ severely adverse scenarios, and shows every sign of getting considerably worse before it gets better.
While the US is pressing ahead with its annual testing cycle, European regulators have already abandoned this year’s round altogether. The decision has raised eyebrows – not least since real-world loan-loss provisioning has already outstripped the Federal Reserve’s previous worst case. But, in fact, it’s more in tune with the shop-floor reality that banks are already pursuing in the wake of the crisis, where a clear trend is emerging. In the absence of credible inputs for standard models, banks are appraising the potential of methods borrowed from stress-testing to support everything from credit loss provisioning to real-time market risk management.
Conversations with scenario analysis experts at banks, buy-side firms and stress-testing vendors, as well as several former regulators, suggest a shift is under way: decades of established price theory underpinning stochastic modelling methods are being cast aside in terms of more fundamentally driven approaches: shocking loan books with prebuilt scenarios from vendors, running simulations using data from past crises and actively reappraising exposure to major creditors using expert judgement.
Once markets normalise, it seems unlikely firms will simply re-base their assumptions on the pandemic being the worst case for probability-of-default models, for instance, or gauges of interest rate volatility, and continue to model markets the way they always have. Even if models aren’t supplanted, they will rightly be subjected to challenge more routinely via alternative approaches.
A willingness by banks to cast aside the old and revisit the notion that the future can be predicted by selectively replaying the past should be embraced: it could unleash a period of immense creativity in risk management. As former Chicago mayor and investment banker Rahm Emanuel once observed, it’s a hell of shame to let a good crisis go to waste.
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