Judgment versus Risk Management Science: Are We Getting the Balance Right?
Samuels, David, The RMA Journal
This article argues that the drive toward objectivity on risk and capital is a good thing, so long as the industry accepts that the role of the new risk numbers is to support and enhance management judgment. But if either regulators or banks are tempted to think that the new risk numbers will lead to automatic answers, they will make mistakes in their risk-based decisions.
Recent banking regulations and the search for competitive advantage are encouraging institutions to base their decisions on a new generation of risk and capital metrics. This has given rise to worry in some quarters that "objective" risk information might begin to circumscribe, or even supplant, the traditional role of management judgment across a range of important bank activities (Table 1).
The challenge for top executives is to foster a culture in the bank (policies, attitude toward risk quantification, systems) that builds the right balance between judgment and objective numbers across a diverse range of decision making. It's a balance that often changes as businesses mature and evolve and as more risk information becomes available. Let's explore how to get the balance right in four critical areas: loss reserving, risk-based pricing, capital adequacy, and start-up businesses.
In the ongoing debate among securities regulators, banking regulators, and the accounting profession over how banks should calculate their allowance for loan and lease losses (ALLL), all parties agree on one thing: Banks must start to calculate reserves in a more systematic, rigorous, and objective manner that reduces the role of subjective management judgment.
Part of the momentum for this comes from the suspicion that banks use provisioning to flatten out volatile earnings over time. For external observers, the benefit of objective risk measurement is that it should lead banks to provision more as their objective expectations about credit losses increase (or less as they decrease), better representing the economics of the business at any one time.
One way to make ALLL more accurate and objective is to base it on the loss distributions created by the bank's credit portfolio model. An additional approach is to apply loss migration analytics to determine the hold-to-maturity losses inherent in a portfolio. (1)
A big advantage of this kind of analysis is that forecasts of expected loss can be tightly integrated with risk-based capital analysis to provide executives with the most comprehensive picture possible of the condition of their bank. In this sense, objective risk calculations can be seen as a platform for making sure that a wide range of different kinds of management judgments are consistent with one another.
But it would be wrong to suppose that an objective statistical analysis of expected loss in the bank's credit portfolio leads directly to the bank's ALLL. Many other factors have to be taken into account, such as management's judgment concerning the effect of the credit cycle over time on portfolio loss expectations and an appropriately conservative view of the robustness of the analysis. Even the most carefully implemented credit portfolio model simply offers an analytical platform for the eventual management judgment on ALLL.
The "bad" news, therefore, is that management will need to continue devoting time to making clearly defined judgments that transform objective credit portfolio expected loss numbers into a final ALLL number. The "good" news is that, far from becoming slaves to the new numbers, best-practice management teams will use this analytical platform to probe into why the numbers look like they do, and to examine and communicate more clearly any trends in loss expectations. Time once spent number crunching can now be used in a more productive way. In this sense, objective risk metrics help to leverage, rather than curtail, the role of bank executives' judgment. …