Groupthink Is Defeating the Purpose of Stress Tests

Recent discussion has focused on whether the Federal Reserve's stress testing regime could add risk to the financial system. Some have argued market participants are working to reverse-engineer the Fed's loss estimate models across a narrow range of potential future economic conditions, thereby introducing additional risk.

The concern, simply put, is that banks will practice the risk-management equivalent of "teaching to the test" by trying to second-guess the Fed rather than make fundamental improvements to their risk and finance infrastructure and cash-flow analytics. Such changes are now required if a firm is to convert the stress test from a chore, and a compliance nightmare, into a real opportunity for enriching the firm's planning and balance sheet risk analytics.

However, it is important to look at the history of stress tests, their promised utility, and recommend a solution to the groupthink. Simply identifying the known industry problem is not enough.

Stress testing is nothing new. While the current framework adopted by the Fed­—the Dodd-Frank Act Stress Test and the Comprehensive Capital Analysis and Review —is an innovation over historical supervisory risk analysis requirements, banks have been conducting stress tests for decades, some more proactively and more effectively than others.

Historically, stress tests were conducted by risk type rather than in a unified fashion across categories of risk. For instance, credit default and loss emergence modeling was performed independently of accrual book interest rate risk, trading risk, operational risk, capital risk and liquidity risk. If there is one lesson learned from the financial crisis, it is that these risks are correlated, and looking at exposures in isolation tends to understate potential spillover effects across risk types, at the firm and the system level.

The unique feature of the stress testing framework mandated by the Dodd-Frank Act is that it requires banks to model, in a forward-looking fashion, the entire firm's balance sheet and income statement across multiple risk types. This is done to assess capital adequacy under plausible but severe economic downturn conditions. While only a reduced set of scenarios are currently required, with sound design, numerous scenarios can be – and in time should be – performed, particularly more tailored, idiosyncratic scenarios.

In order to conduct an enterprise-wide stress test, a bank must possess or develop strong internal risk management processes. The bank must be able to integrate a complex pro-forma risk simulation across credit, interest rate, operational, capital (economic and regulatory) and – if designed properly – liquidity risk (although the Dodd-Frank tests and CCAR, oddly, explicitly ignore liquidity risk), and ensure that inputs and assumptions are consistent with planning and risk systems.

Performing this task is no easy chore and requires an unprecedented level of coordination, data, econometric and statistical models, and cross-functional integration of business processes. Very few banks would opine – nor is it likely that their stakeholders, creditors and supervisors would believe – that having better infrastructure to support cross-risk transparency and analytical capability is a socially or financially bad outcome. In fact, the rigorous data requirements mandated by the Fed may be one of the more important outcomes of the stress testing exercise, and not just for purposes of the stress test.

It would be a shame if the granular data required by the Fed isn't leveraged by the regulators (mostly the FDIC)  for recovery and resolution planning; by the Office of Financial Research for its annual report to Congress; by the FDIC to refine pricing of FDIC deposit insurance and – in time perhaps – by the Fed itself to provide needed collateral transparency for discount window crisis lending programs and to support, rather than detract, from the upcoming Comprehensive Liquidity Assessment and Review, among other things.