Risk-adjusted return on capital measures are enjoying extensive and justly deserved popularity in asset-liability management.

Banks increasingly use risk-adjusted return on capital to shape and guide their most fundamental business decisions.

Such analysis may determine such critical issues as pricing products and relationships, entering or exiting major business lines, shrinking or expanding retail branch networks, and approving or rejecting proposed capital investments.

In view of the uses to which these measures are put, it is vital that banking executives and analysts understand that the numbers can be very misleading if not properly developed.

As every analyst of asset-liability management knows, measures of risk- adjusted return on capital (RAROC) are ratios developed from two independent factors: after-tax profit (the numerator) and capital (the denominator).

These ratios can be extremely sensitive to subtle changes in the profit or capital totals used to derive them. Such sensitivity can have major implications for the decisions to which a ratio is being applied.

Banks and banking consultants spend a great deal of time and money estimating the proper capital figures to use in developing their RAROC ratios, and it is important that they do. But they need to dedicate at least as much time and care on the methods they use to compute the seemingly straightforward profit term.

That's a serious challenge, because in actual banking practice RAROC ratios are far more sensitive to the profit term than to the capital term.

Computing the profit term is a fundamentally more complex task. Profit totals are generally the product of many incremental decisions about cost and revenue allocations, and they require the netting of many large numbers. Slight differences in allocating large components, along with minor variations in allocation methods, may produce very significant changes in the final risk-adjusted return on capital.

In some industries, variations in the numerator might not prove so important. There are, however, at least three distinct characteristics of the banking industry that can magnify the effect of the numerator in these ratios.

The lower the required capital, the greater the weight of the profit term.

In comparison with many other types of businesses, banks are highly leveraged institutions. The capital required to support a business line in banking is usually 10% or less. Deposit-taking may require as little as 1.5%.

The capital term in a risk-adjusted-return ratio is therefore quite small in relation to the revenues and costs used to compute profit. In mathematical terms, a ratio with a small denominator will be more sensitive to changes in the numerator.

The smaller the denominator (capital), the larger the impact of any change in value of the numerator (the estimated profit).

The more specific and targeted the decisions being addressed, the greater the weight of the profit term.

When bankers attempt to apply risk-adjusted-return ratios to specific operating decisions, such as closing branches or evaluating specific products, they must often deal with highly aggregated data.

As we have said, computing profit generally requires the application of various allocations and assumptions. The lower down in the data hierarchy we move, the more assumptions and allocations we must apply to break down the highly aggregated data.

Small inaccuracies and minor variations in the assumptions and allocations applied to the large components of the profit calculation (revenues and costs) will produce large swings in the profit totals computed, and these swings will distort subsequent risk-adjusted-return measures.

The thinner the profit margin, the greater the weight of the profit term.

Bank balance sheets and transaction volumes are very large, but profit margins are razor thin. As competition intensifies, margins are likely to grow even thinner.

Bankers often make critical business decisions on the basis of a few hundredths of a percentage point.

As noted above, very small inaccuracies in the calculation of profit can easily produce major swings in the profit total. Even slight variations in the way two analysts apply the same allocation methods and assumptions may skew the perceived profitability of a product or distribution channel.

A modestly profitable operation may even appear to be losing money. The exquisite sensitivity of a thin profit margin will necessarily be reflected in risk-adjusted-return measures.

These considerations are far from academic.

Current asset-liability management practices offer us numerous examples of the uncertainties inherent in our current methods for calculating profits.

Discussions at a recent BAI conference, for example, focused on inaccuracies in the ways banks assess the interest rate risk embedded in nonmaturity accounts, along with the corresponding transfer rates and transfer charges.

Bankers have been transfer pricing nonmaturity deposits incorrectly because traditional methods have overlooked the effect of rate changes on changes in balances. Both volumes and balances for nonmaturity accounts are more sensitive to rate shifts than the banking industry had previously supposed.

Work by scholars like Donald van Deventer and Robert Jarrow has demonstrated that the estimated changes in value on these accounts can easily double once the changes in balances are accounted for.

This issue is a critical one for bankers, since nonmaturity accounts such as credit card and demand deposit account balances constitute an increasing component of business at most retail banks. The effect of the underassessment will be reduced as asset-liability management analysts implement new option-based capital markets approaches.

Banks also need to institute a new approach in regard to equity transfer pricing practices. Current transfer pricing methods often assume that a given asset or liability is 100% debt-funded.

In practice, equity is required to support debt-funding. Current practice attempts to account for the required equity component using the debt rate corresponding to a targeted duration for equity, rather than by applying the weighted average transfer rates associated with the entity in question, such as the product or business unit.

The reasons that the second alternative is preferable are technical in nature and beyond the scope of this article. The essential point is that the current practice of using a debt rate corresponding to a target duration of equity distorts the computed profit before capital charges.

These distortions depend on a number of factors, including the term structure of interest rates, the leverage ratio, and the difference between the assumed duration of equity and the duration of the funding mix.

Such distortions will increase in direct proportion to the steepness of the yield curve, the difference in the durations of equity and funding mix, and the percentage of equity required to support a business.

Another example of current practices that will distort risk-adjusted- return ratios is the use of historical costs in allocating occupancy expenses, a practice commonly observed in branch profitability analysis. The problem with this practice is that historical costs will vary widely between leased and owned properties, and between branches leased or purchased at different times.

This wide divergence in cost may say a great deal about the efficiency of the bank's real estate function, but it says very little about the current business economics of the branch.

If the bank is trying to decide which branches it should continue to operate, it should assign occupancy costs on the basis of current market rates rather than allocate historical costs. The use of historical costs can distort risk-adjusted-return ratios among individual branches by a factor of two in either direction, doubling or halving a measure that could determine operating decisions.

As the examples above illustrate, banks must do a better job of developing profitability numbers - the numerators in the RAROC equation - if they are to continue using such analysis as a guide to critical decisions.

They must understand the limitations and sensitivities of the methodologies they employ. And they must insure that their information technology systems are powerful enough to implement the most sophisticated methodologies, and flexible enough to change as those methodologies inevitably evolve or are replaced by even more powerful ones.

In a bank of any size, profitability analysis is a team effort. It consists of a long chain of discrete building blocks or processes, and each process may be performed by different individuals in different units.

Each process requires its own set of methodologies, and the uses of each methodology will in turn have a significant impact on every other methodology and on the final profit figure.

In this regard, banking executives and financial analysts are in the same positions as sprinters running the anchor legs in Olympic relays. Their own abilities may be extraordinary, but their ultimate success is dependent on the performance of the teammates who run before them. And their RAROC estimates can be only as good as the profitability analysis that informs them.

Mr. Reich is vice president and general manager and Mr. Shih is a director at Treasury Services Corp., Santa Monica, Calif.

Subscribe Now

Access to authoritative analysis and perspective and our data-driven report series.

14-Day Free Trial

No credit card required. Complete access to articles, breaking news and industry data.