The banking industry needs a regulatory framework that is carefully designed to maximize economic outcomes, both in terms of stability and growth, rather than one dictated by past banking sector excesses.
Many people – with a great deal of justification – want a pound of flesh extracted from the banking industry. The notion that big banks enjoy the fruits of the upside, while socializing downside risk, is compelling and highly damaging to economic development.
The stress testing framework developed by the Federal Reserve (the Fed) since the Great Recession, known as the Comprehensive Capital Analysis and Review (CCAR), goes a long way toward addressing the incentives of the banking industry. The Fed will not be able to miss future lending bubbles given the data collected in CCAR, and banks should be well capitalized on the eve of the next financial crisis.
The recent round of CCAR highlighted the fact that the Fed is taking a very conservative approach to capital adequacy assessment. All banks were projected to have much higher losses than suggested by internal estimates under the rather severe economic scenarios used in CCAR. Many individual credit product loss forecasts were also high, implying that the Fed is trying to discourage banks from sectors. If a bank has to quarantine a lot of cash to cover, say, a new mortgage or small business loan, it increases the cost to the bank and thus allocating capital to those the interest rate at which the loan is offered.
In a normal economic environment, an overly tough stress test poses few problems for policymakers. If excessive bank reserve requirements were having an undue effect on economic growth, and if rates were clearly positive and stable, the Fed could respond by simply reducing the headline federal funds interest rate. Big banks would still be forced to meet strict capital requirements. Small lenders, those not deemed “too big to fail” and thus not subject to the increased scrutiny of stress testing, would see cost structures fall and profits and market share rise.
The current economic situation is rather different. The federal funds rate is effectively zero, inflation is tame and falling, and unemployment is unacceptably high. The Fed Chairman, Ben Bernanke, has been forced to massage inflationary expectations and use unconventional monetary policies like quantitative easing (QE) to keep the economy growing. In such circumstances, policy shifts cannot easily be used to counter the effect of economic shocks, one example being an overly strict stress test. Given that the purpose of QE is to reduce interest rates and encourage bank lending, having the stress testing arm of the Fed discourage lending is completely anathema. At the moment, the Fed is both for and against accelerated loan growth. Figure 1 outlines how stress testing addresses shocks and their impact on the bank.
In the short term, the Fed should tone down or even reverse the rank conservatism of the CCAR. This may be galling to taxpayers still angry about bailing out big banks during the financial crisis; it is, though, better to spare the nose even if it means the face goes spite free. When the economy is truly recovered – hopefully soon – the flesh can be extracted from the banks without worsening the plight of the unemployed and others desperate for normal economic service to resume.
In the long term, a discussion about society’s appetite for bank failure risk should take place. A world where bank failures are rendered impossible due to strict capital standards is not optimal, nor is a world where big banks line up for bailouts within months of posting record profits. The economy grows fastest and most assuredly when banks take sensible risks in extending credit to potentially profitable businesses and seemingly creditworthy individuals. In an ideal model, bank failures, even big ones, will still occasionally occur.
We need a regulatory framework that is carefully designed to maximize economic outcomes, both in terms of stability and growth. Such an outcome is impossible if we let our malice over past banking sector excesses dictate future policy development.
Explores how North American financial institutions can leverage stress testing regulations to add value to their business, for compliance and beyond.
We look at climate risk and consider how a heating planet might impact a bank's performance
Expanding Roles of Artificial Intelligence and Machine Learning in Lending and Credit Risk Management
With ever-expanding and improving AI and Machine Learning available, we explore how a lending officer can make good decisions faster and cheaper through AI. Will AI/ML refine existing processes? Or lead to completely new approaches? Or Both? What is the promise? And what is the risk?
When banks manage risk, conservatism is a virtue. We, as citizens, want banks to hold slightly more capital than strictly necessary and to make, at the margin, more provisions for potential loan losses. Moreover, we want them to be generally cautious in their underwriting. But what is the best way to arrive at these conservative calculations?
The traditional build-and-validate modeling approach is expensive and taxing. A more positive and productive validation experience entails competing models developed by independent teams.
The industry is currently a hive of CECL-related activity. Many banks are busily testing their systems or finalizing their preparations for the go-live date, which is either in January 2020 or somewhat later, depending on the organization. Some are still making plans for implementation, and the rest are worried that they should be.
The theory that banks are now safer because of CCAR, though, has not yet been tested.
Loan-loss provisioning models must take a variety of economic and client factors into account, but, with the right approach, banks can develop sensible loss forecasts that are more accurate and less susceptible to volatility.
As evidence of climate change builds and threats materialize,data will be invaluable in creating a framework for making future credit decisions.
In recent years, attention has increasingly turned to the promise of artificial intelligence (AI) to further increase credit availability and to improve the profitability of banks and other lenders. But what is AI?
Good-quality CECL projections can be developed using high-quality data that is available free of charge.