24 the use_of_economic_capital

McKinsey Working Papers on Risk, Number 24
January 2011
© Copyright 2011 McKinsey & Company
Tobias Baer
Amit Mehta
Hamid Samandari
The use of economic
capital in performance
management for banks:
A perspective

This report is solely for the use of client personnel. No part of it may be circulated, quoted, or
reproduced for distribution outside the client organization without prior written approval from
McKinsey & Company, Inc.

Contents
Introduction 1
Why is economic capital important? 2
Granularity of economic-capital allocation 4
Linking economic capital to performance management 6
Setting RAROC targets and hurdle rates 9
Looking to the future 13
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(rob_mcnish@mckinsey.com)

1
Theuseofeconomiccapitalin
performancemanagementforbanks:
Aperspective
EXECUTIVE SUMMARY
Amid heightened concern about the future of regulatory-capital requirements, economic-capital modeling and
its application are enjoying a renaissance in the post-crisis banking world. This trend is driven by three factors:
(i) The crisis has fostered a renewed appreciation by both banks and regulators of the need for standard
economic-risk measures informed by internal data
(ii) Institutions perceive a heightened need for performance-tracking and pricing tools that incorporate an
economic cost of risk.
(iii) Changes in the culture of financial institutions, as well as new developments in data architecture and
modeling, are removing practical obstacles that hindered earlier efforts.
Our discussions with 11 banks around the world provide ample evidence of this resurgence. These discussions
also revealed that the typical bank uses risk-adjusted return on capital (RAROC) in a backward-looking manner
and at the aggregate, not the transaction, level. This suggests that the adoption of return hurdles that capture
the contribution of each business to the cost of capital, as well as the capital requirement, of an institution would
constitute a major improvement in capital allocation, business-performance tracking, and risk management.
I. INTRODUCTION
In the wake of the global credit crisis, capital has become a scarce resource. Still reeling from the effect of
important and unanticipated losses, a large number of banks are now struggling to conserve and manage
capital. The impact on the banking system has been significant and immediate: many institutions have had no
other choice but to reallocate or even reduce their portfolios.
Capital management is first and foremost driven by risk. Indeed, because risk can trigger losses that deplete
their capital, banks must carefully consider the potential unexpected losses that are associated with each
individual activity. Value maximization requires financing only businesses that are sufficiently profitable after their
capital consumption is taken into account. It is therefore crucial that performance measurement adequately
reflects this consumption.
In order to understand the current state of practice in the evaluation of risk-adjusted performance in the banking
system, we recently surveyed a diverse group of 11 leading banks in North America, Europe, and the Asia-
Pacific region. The purpose of this paper is to present the survey’s results.
These results show growing interest in risk-capital models. However, these models are at present mostly
restricted to the evaluation of business units and other top-management decisions; they are not used to drive
day-to-day business decisions. In particular, they are rarely explicitly used in the pricing or approval of individual
transactions. Financial institutions have not yet fully taken advantage of the benefits of these techniques, and
there is substantial room for improvement in the optimal allocation of constrained capital resources.

2
The paper proceeds as follows. The next section presents the motivations behind risk-capital modeling and
explains its scope. Section III examines the granularity of capital allocation. Section IV discusses applications to
transaction evaluation, pricing, and approval decisions. Section V considers the hurdle rates used in evaluating
returns, and Section VI presents our conclusions.
II. WHY IS ECONOMIC CAPITAL IMPORTANT?
Two important metrics constitute the foundation of risk-capital models: RAROC and economic value added
(EVA). RAROC expresses expected profit as a percentage of economic capital. The formulation of these two
input variables is quite specific. The first variable, expected profit, takes expected loss into account. The second
variable, economic capital, reflects the risk appetite of the institution or, in other words, the probability of failure
that it is willing to accept. More specifically, economic capital is the bank’s best estimate of the capital required to
absorb losses up to a chosen probability of failure.1
The mathematical expression for RAROC can be written as
follows:
RAROC =
EVA is a related concept. The difference between the two metrics is that RAROC, like any return, is a relative
measure of the profitability of capital and is particularly useful to compare alternative investments or to determine
whether a target rate has been met. EVA, on the other hand, is an absolute measure that provides the actual
amount of profit an institution earns beyond the cost of its equity. Indeed, the “excess return” measured by
RAROC above the cost of capital is EVA. Of the two metrics, RAROC appears to be the most widely used by
survey respondents; however, EVA is a necessary complement or alternative to RAROC.
RAROC and EVA are not new. As early as the 1970s, pioneers such as Bankers Trust were using RAROC. By the
1990s, a fair number of banks were pursuing internal risk-capital models; however, most of these efforts were
unsuccessful because companies lacked data, made use of an imperfect methodology, or faced other business
pressures.
Although the challenges of implementation should clearly not be underestimated, when properly set up,
these tools empower management to maximize the bank’s return on capital (subject to business and other
constraints). Indeed, recent experience, for instance, in the area of mortgage loan pricing, suggests that
some RAROC models may have been prematurely abandoned or their results ignored. An incomplete and
rudimentary implementation is often the underlying cause of these issues.
The survey reveals that the vast majority of respondents use economic-capital models. However, they use them
to varying degrees, as illustrated in Exhibit 1, with approximately half the respondents having an economic-
capital model for the full bank.2
This indicates that the notion of economic capital is gaining acceptance in the
banking industry. This is a significant development because, after an initial wave of implementation in the 1990s,
economic capital fell out of favor. In addition to the requirements imposed by the Basel II framework (the Internal
Capital Adequacy Assessment Process of Pillar II), this resurgence is due to recent successes in addressing
several issues that thwarted earlier efforts. In particular, four main problems needed to be solved.
1 Readers interested in the details of calculating economic capital may refer to McKinsey’s Working Paper on Risk
No. 11, “Best practices for estimating economic capital,” available at http://www.mckinsey.com/clientservice/risk/
risk_working_papers.asp
2 Quantitative results from a survey of 11 respondents are not statistically representative, and as such, the detailed
numbers are not shown. However, the height of the bars indicates the relative strength of each practice as uncove-
red by our discussions.
Expected profit
Economic capital
Return – expected loss – expenses
Economic capital
≥ Cost of capital
Economic capital
≥ Marginal cost of capital
Marginal economic capital
=

3The use of economic capital in performance management for banks: A perspective
First, the cultural gap between the “quants” who promote risk models and the skeptical business managers
who use these models had to be bridged. Successful implementation requires that all levels of the organization
support and accept these methods as an essential part of the bank’s modus operandi.
Second, the different data architectures for risk and return had to be reconciled. The resulting improvements in
data consistency have allowed the development of more accurate, reliable, and informative models.
Third, sufficient data on the “tails” of loss distributions needed to be collected. Such data are generated by rare
“stress” events and have now become much more available thanks to the recent crisis. In particular, these data
provide better estimates of correlations between losses across different risk categories. This enables models to
better predict how, for example, market-risk losses could coincide with credit- or operational-risk events.
Fourth, misleading shortcuts, such as the use of regulatory-capital requirements instead of a much more risk-
sensitive variable, had to be rejected. It is also worth noting that banks now recognize the need for discipline in
assigning capital charges during expansions as well as contractions of the credit cycle.
RAROC’s power comes from a few key characteristics. Banks can use RAROC to identify deals that may appear
to generate great profit but have more than a commensurate capital requirement. This feature is crucial not only
because it exposes seemingly profitable but excessively risky businesses, but also because it draws attention to
businesses that offer high risk-adjusted returns despite perhaps deceptively low gross returns.
Another useful quality of RAROC is that it is forward-looking. This discourages short-term optimization of
sales volume at the expense of large losses in the future. Finally, RAROC is exhaustive and flexible: all financial
variables, such as revenue, cost, and capital, are taken into account and can be aggregated up to the business-
unit or company level or refined to the level of individual branches, customers, or deals. This flexibility is only
limited by the availability of data.
Banks use models of economic capital to varying degrees.
Responses from survey respondents
Exhibit 1
Bank-wide
economic-
capital model
No economic-
capital model
Partial bank
coverage
“We do not yet have an
economic-capital model, but
some proponents are pushing it”
“‘Common sense’ controls are in
place; our skill is in ensuring that
quantitative methods pass a
business ‘sniff test’”
Consensus of sample supports
the use of economic-capital
modeling, although the breadth of
coverage varies
“We have a global economic-
capital framework that influences
capital allocated to business
units”
“Economic capital is limited for
our new acquisitions because of
data-compatibility problems”
“An economic-capital model is
used for products where
regulatory capital is inadequate
(such as structured products)”

4
As mentioned above, about half of the respondents have implemented a bank-wide economic-capital model. Of
the remaining banks, some face technical constraints to roll out economic capital into all their divisions; others
calculate economic capital explicitly only for the most critical cases. For instance, in corporate lending, it is
necessary to carefully evaluate each transaction because of the thin margins.
Therefore, our observations suggest that the current state of practice is widespread but rather incomplete use
of economic capital in bank decision making. The primary role of economic capital is to track business-unit
performance and ensure safety for bondholders. This approach reduces economic capital to its canonical
function: providing a cushion to absorb losses. Within this context, a few sampled banks emphasize the use of
economic capital as a better risk metric than regulatory-capital requirements.
However, more sophisticated applications, such as pricing commercial transactions, using risk-based strategic
decision making, and conducting risk-based allocation of regulatory capital, as well as determining the optimal
size of subportfolios, appear less prevalent in our sample. Exhibit 2 gives an overview of survey responses.
III. GRANULARITY OF ECONOMIC-CAPITAL ALLOCATION
In principle, a financial institution could allocate economic capital to every transaction; however, in practice,
the granularity of allocation is limited by the precision of risk measurement. The quantification of risk must be
consistent across the institution, its technical infrastructure, and its operational constraints. For instance, it may
not be practical for the front line to communicate credit-card pricing on a case-by-case basis.
Our observations suggest that economic capital is often allocated at the business-unit level; more detailed
applications are made selectively. For example, economic capital is allocated by desk in capital markets and
Institutions have incorporated economic capital in decision making.
Responses from survey respondents who hold economic capital, multiple answers per respondent
Exhibit 2
Pricing commercial transactions
Setting risk-sensitive limits to
the size of individual portfolios
by means of allocated capital
Informing strategic/
business decisions
Using as weight to break
down/allocate regulatory capital
for business units (technical
matter)
Tracking performance of
individual business units or
portfolios via return on
economic capital
Achieving safety for
bondholders/bank as a whole
Uses of economic capital vary
within the sample:
▪ Frequently used to track
business-unit performance and
for safety
▪ Occasionally used to price
commercial deals, inform
strategy, and allocate regulatory
capital
“Economic capital is computed ex
post and used for portfolio review
but not for decision making”
“Economic capital is important
because regulatory capital
underestimates many of our risks”
“Economic capital is used for
products where regulatory capital
is deficient (for example, for
structured products)”
“We hold regulatory capital, but we
use a stochastic economic-capital
model to allocate it”
“An important function of economic
capital is to limit the size of
portfolios that exceed an
economic-capital leverage limit”

by business in private banking. A minority of institutions allocate capital by individual transaction for particular
transaction types, especially large commercial loans. When evaluating client relationships, a number of
institutions allocate economic capital by counterparty, and only a few players aggregate these results to the
country level. Exhibit 3 summarizes these findings.
In our view, the best practice is to allocate economic capital at the margin to distinct contributors of risk (such
as product line or client relationship) and at a level of detail that is consistent with the precision of the measure.
This allows the best possible pricing of risk and minimizes internal arbitrage opportunities that arise when riskier
transactions are underpriced because they are bundled with safer ones.
In order to achieve this level of detail, the best models compute economic capital from the bottom up,
incorporate every significant transaction, and explicitly allocate diversification benefits. Although measurement
noise may be high for individual transactions, it should average out when aggregated to a business unit or a
client segment.
However, when economic capital is allocated from the top down, the bank may experience a vicious circle in
which the portfolio grows more and more in the very areas where risk is underestimated. This could leave the
institution critically exposed to a particular risk scenario. Only a rigorous stress test would be able to detect such
a scenario and trigger corrective actions through other levers such as portfolio limits.
At the product level, the industry will benefit from wider adoption of the practice of allocating economic capital to
all desks and businesses but only to selected transactions, especially the larger ones in commercial lending and
capital markets. Although it is difficult to price transactions correctly without such a detailed analysis of capital
costs, only a minority of our survey respondents currently go this deep.
Economic capital can be allocated at a number of levels.
Responses from survey respondents who hold economic capital, multiple answers per respondent
Exhibit 3
By business unit or
subportfolio
By desk or business
By product
By transaction, for
selected transactions
By counterparty
By geography/
country
Consensus view of
sampled banks
supports business-
unit or subportfolio
allocation; a few
allocate by
geography,
counterparty, product,
or transaction
Business unit is the
most common product
dimension …
… but some institutions
allocate at a more
granular level
Counterparty is the
most common client
dimension …
… and some
institutions aggregate
to geographies

6
Banks will also find it useful to sort and track capital consumption by specific embedded market risks, such as
the sensitivity to oil price or to exchange rates for the US dollar and Japanese yen. When borrowers are sensitive
to market risks, it is increasingly important for institutions to integrate these risks with similar ones elsewhere in
the organization (for instance, in flow trading). Exhibit 4 presents the different levels of granularity.
Additional insights can be gained by aggregating and identifying some risk concentrations: first, by sector (for
example, automobiles, shoes, or commercial-real-estate developers) or client segment (for instance, subprime
customers), and second, by region, especially for countries with unique regulatory environments (such as China,
India, and Argentina).
As noted earlier, the possibility of developing correlation matrices across asset classes is a powerful feature of
the economic-capital framework. These matrices allow companies to better estimate the marginal contribution
of each type of risk to the overall risk profile. While this was not a core survey issue, a few institutions noted that
the lack of a robust correlation matrix prevented bank-wide aggregation of the economic-capital model.
IV. LINKING ECONOMIC CAPITAL TO PERFORMANCE MANAGEMENT
RAROC reflects the economic view of the marginal risks.3
It can be used ex post, to measure the risk-adjusted
profitability of a business unit or segment. It can also be used ex ante, to set prices or make significant
transaction decisions based on a minimum acceptable RAROC.
The discussion has thus far focused on the challenges in estimating and allocating economic capital, the
denominator in RAROC’s formula; proper application of RAROC also requires care in estimating the numerator,
3 In the literature, semantic variants on RAROC have included RORAC (return on risk-adjusted capital) and RARORAC
(risk-adjusted return on risk-adjusted capital); these are more or less equivalent.
Banks can also allocate economic capital based on
embedded market risk.
Most common
Minority
Not observed
Subportfolio
Geography
Segment
Obligor
Bank
Product cut
Client-segment cut
Embedded
market risk
(foreign
exchange,
commodity
price)
Business unit
Transaction
(at least
selectively)
Exhibit 4

expected profit. For instance, during the credit bubble, returns were overestimated because current average
losses were used in place of lifetime expected losses when computing expected profit. Average losses are
usually low during periods of high growth in origination because new loans do not generate much loss. This
experience illustrates how important it is to calibrate risk models that are based on expected loss in a forward-
looking manner.
A specific and often underappreciated implication of this postulation is that calculation of RAROC will require
to different calibrations of a bank’s risk models (especially for the probability of default, or PD): while the
capital model—in line with the requirements of Basel II/III and the objective of stable, not procyclical, capital
requirements over time—should use PD estimates calculated “through the cycle,” expected-loss estimates used
for the forward-looking estimation of return should ideally be based on forward-looking point-in-time estimates
of PD. This philosophy is in contrast with today’s practice; many banks currently use just one type of calibration
for all purposes.
Using RAROC as a key performance indicator
Executive compensation is a thorny issue because it is important for banks to reward performance and give
employees the right incentives. Traditional metrics such as P&L performance or return on assets create perverse
incentives to increase risk exposures, especially when the reward for good performance exceeds the penalty for
bad.
RAROC normalizes financial performance by the amount of risk undertaken. Because of this, the best practice
uses RAROC to evaluate performance at the same level of granularity with which economic capital can reliably
be estimated. This system rewards decisions that generate the highest return over time. However, there are three
important caveats.
First, given the above-mentioned limitations of economic-capital models, RAROC should not be used alone but
as one important quantitative variable among more traditional ones. Decision-making processes that are based
on multiple models tend to be more robust because noise is filtered out when information from different variables
is pooled.
Second, the model should be accurate enough to avoid unfairly penalizing some businesses. Within the
institution, managers must perceive the model as fair and credible. This requirement has strong implications
both for the selected approach and the development process.
Third, risk managers must be vigilant and look carefully for hidden risk. For instance, they must ensure that
volatility assumptions are always updated; they must be cautious when validating trading-asset marks via bids
from institutions that have an incentive to keep these marks high; they must be wary of bets on basis risks that are
not explicitly captured by the model.
In the subset of banks that use economic-capital models, the state of practice can be summarized as follows.
A few do not use RAROC for performance evaluation at all; about half of the remaining banks only evaluate
performance at the business-unit level, leaving more in-depth evaluations to business-unit leadership, while the
rest have implemented a detailed model. In the latter group, some banks use RAROC to evaluate divisions within
capital markets but not commercial or retail lending, while others use RAROC and other metrics to evaluate
portfolios, subportfolios, and geographic risk. Exhibit 5 presents an overview of survey results.
The challenges of using RAROC for performance management follow a clear pattern: at more detailed levels of
performance, methodological imperfections tend to become more pronounced, and the divergence between
economic- and regulatory-capital requirements becomes more difficult to manage.

Using RAROC in pricing and transaction decisions
To the extent that economic capital can reliably be allocated to individual transactions, it should also be used
to set minimum acceptable returns. This is usually the case for larger transactions. The best practice ensures
that pricing reflects economic risk and transactions are rejected if the price does not meet a target RAROC.
Exceptions should only be made for transactions that complement other, more profitable ones, or when properly
identified model limitations cause results to be noisy or biased.
Complementarities are often claimed to justify pricing concessions, for instance, when fee business is bundled
with considerable financing. Exceptions should be granted only if the bank can track and enforce these
complementarities. In all other cases, the rule should be applied with the same discipline throughout the credit
cycle. Indeed, banks must avoid the danger of countercyclical enforcement, when economic capital is used to
price loans during credit contractions but ignored during expansions.
If RAROC is not implemented at least at the level of the business unit, it is possible that many transactions will
destroy economic value. Exhibit 6 shows an example of a bank that deployed approximately 75 percent of its
economic capital in business units earning less than the cost of capital.
Of the nine banks that use economic capital, five did not use RAROC at all when evaluating transactions; one
used it only for pricing decisions, one for transaction decisions other than pricing, and two for all transaction-
related decisions. This is illustrated in Exhibit 7. Generalizing from our sample, relatively few banks seem to have
adopted the best practice in transaction evaluation. A lack of consensus on the value of the risk model’s output is
often cited as the reason for this situation.
8
RAROC can be used in KPIs.
Responses from survey respondents, excluding some not using economic capital and some not answering
Exhibit 5
Comprehensive
evaluation of
(all) business units
Selective evaluation of
(some) business units
More granular
evaluations (of
subportfolios, significant
new investments, and
clients)
“‘Economic capital is just
another data point for use in
business decisions; it is not
used for performance
evaluations”
“RAROC1
is used as a KPI2
in
our business units alongside
revenue and cost”
“RAROC is used for perform-
ance evaluation at the LOB3
level; sub-LOB evaluations are
done by business units”
“RAROC is used to evaluate by
sector and unit in our capital-
market division, but not in
commercial and retail lending”
Not used in evaluations
Of sampled institutions,
most used RAROC in
business-performance
evaluations
at the business-unit level
or below
1 Risk-adjusted return on capital.
2 Key performance indicators.
3 Line of business.

One bank’s example illustrates how business units
can destroy economic value.
Segment-level RAROC1
%
Cost of
capital
Economic capital
% of total
Business units
~25% of economic capital was
deployed at RAROC of 1.9 times cost
of capital on average
~75% of economic capital was
deployed at only 0.44 times cost of
capital on average
Exhibit 6
Some institutions use RAROC for transaction approval and pricing.
Responses from survey respondents, excluding those not using economic capital
Exhibit 7
Use selectively
in approval
and pricing
Use selectively
in approval but
not pricing
Use selectively
in pricing but
not approval
Do not use in
either pricing or
approval
Views diverge on the
use of RAROC for
pricing and approval:
▪ Consensus tends
toward not using
RAROC for
transaction
approval or pricing
▪ Various approaches
have been taken
by the minority that
uses RAROC for
such purposes
“‘RAROC is used for commercial loan
pricing, but go/no-go decisions are based
solely on a credit view”
“RAROC1
is part of pricing models;
business units can, however, execute at
lower prices as informed by business
judgment”
“Approval decisions are based on several
criteria, including ROE,2
RAROC, and
impact on RWA3
—these criteria differ by
investment type”
“‘RAROC informs go/no-go decisions in
new businesses, but not by transaction”
“‘RAROC influences only capital-allocation
decisions”
“RAROC is used for pricing large loans
and derivatives”
2 Return on equity.
3 Risk-weighted assets.

V. SETTING RAROC TARGETS AND HURDLE RATES
The previous section discussed the use of RAROC targets in benchmarking business-unit performance and
evaluating transactions. This section discusses how banks should determine these targets.
Comparing RAROC targets and RAROC hurdles
In the context of RAROC, hurdles are sometimes confused with targets. Targets represent the average
aspiration for a business unit or activity and may be derived from capital-market expectations. Hurdles are the
minimum required to generate economic value. The distinction is illustrated in Exhibit 8.
The absolute nature of a RAROC hurdle can be best understood by way of analogy. Retailers long ago
recognized that to stay competitive, they need to charge as low a price as possible for some products—even
when these sales do not contribute to fixed cost—while for other products, they can charge healthy margins that
allow them to reach overall profit targets. However, for each product, the wholesale purchase price defines an
absolute minimum below which the retailer loses money. For example, there is no point in buying watermelons on
the wholesale market for $2 and selling them at $1—the supermarket would be better off not selling watermelons
at all. The wholesale purchase price therefore defines a hurdle for introducing a product. The RAROC hurdle is
similar for banks: below that level, a bank would be better off not doing the deal at all.
Given the complexity of risk modeling and pricing, these fundamental concepts are not easily applied in banking.
For instance, among the nine banks in the survey that compute economic capital, only five apply a RAROC
hurdle rate. In our view, the best practice is to incorporate the “cost” of risk—as reflected by the cost of holding
economic capital against the risk—in a minimum product price. This ensures that over time, revenue not only
Hurdle rates represent the minimum RAROC that should be achieved
by business unit or transaction in order to create economic value.
▪ Hurdle should be met by every
transaction (or at least every business unit
overall and every significant transaction
type)
▪ Hurdle shifts only if:
– Future systematic risk is expected to
decrease
– Future RAROC will increase (eg, fixed-
cost dilution from volume growth or
proprietary knowledge development)
– Externalities/bank-wide benefits not
captured in RAROC (eg, cross-selling)
Transaction below hurdle destroys
economic value
▪ Target needs to be met only in average
▪ RAROC target shifts in response to growth
target (eg, one can create an “isoquant” of
constant value, relating ROE2 to growth)
RAROC1
Target
Hurdle
0
Transaction
RAROC
Economic
value
Exhibit 8
0
2 Return on equity.
10

covers expected losses but also earns a sufficient return for shareholders. Failure to take this cost into account
destroys shareholder value and will eventually cause the share price to fall.
The hurdle rate is generally not affected by growth. This is true because growth does not inherently create value.
Indeed, a company that earns less than its cost of capital merely destroys value as fast as it grows. However,
transactions that are priced below the hurdle rate can be approved as exceptions when they enable gains
elsewhere.
This may be the case when an activity contributes to proprietary knowledge development (for example, if the
bank accumulates experience in a new segment through a pilot program) or when losses on a product are more
than offset by gains on a complement as discussed in the previous section (for instance, when the overdraft line
is the “entry ticket” for highly profitable fee businesses such as international payments). Guidelines should be set
and enforced to ensure that complementarities are indeed real and necessary. In any case, the target return on
capital for any institution should always exceed the cost of capital.
Granularity of RAROC hurdles
The common approach in setting RAROC hurdles requires that the return on economic capital exceed the cost
of capital for the institution. There is a mathematical expression for this rule:
The right side of the inequality, the cost of capital, is usually determined according to the capital asset pricing
model (CAPM). This paradigm sorts risks into two broad categories: those that can be diversified away and those
that the marginal equity holder is unable to diversify away. The latter category is usually called systematic risk,
and the parameter that quantifies it is represented by the Greek letter beta (ß). Systematic risk drives the price
at which the institution can obtain capital from the equity market. This is represented in the well-known CAPM
formula:
Cost of capital = risk-free rate + ß × market-risk premium
It is well understood that financial risk and its associated losses are transaction-specific and that, as a result,
each transaction makes its own contribution to institutional economic capital. However, it is often overlooked
that transactions also contribute differently to institutional cost of equity capital, at the margin. After all, an
institution’s beta is nothing more than a weighted sum of its divisions’ betas. Hence, in principle, RAROC hurdles
can be set according to the following formula:
All the variables in this expression are specific to the transaction. While allocation of capital at the level of
transactions is thus far unrealistic, it is possible to estimate the cost of capital for each business unit.
For instance, an institution that allocates capital equally between its commercial and investment-banking
divisions faces a higher beta than the commercial segment would alone, because the investment bank adds
significant systematic risk at the margin. If the institution uses a single hurdle rate that is based on its total
systematic risk, the commercial bank may be denied value-creating transactions, and the investment bank may
be allowed value-destroying deals.
Expected profit
Economic capital
Economic capital
≥ Cost of capital
Economic capital
=
Expected profit
Economic capital
Economic capital
≥ Cost of capital
Economic capital
=

Survey results suggest that this may be a common issue. Four of the five institutions that impose RAROC hurdles
use a single hurdle for all business units, usually the cost of capital of the whole institution. Only one institution
imposes different hurdle rates for different businesses; however, these rates are determined informally and not
through systematic analysis. One respondent had attempted to use multiple hurdle rates, but could not get
business units to agree on appropriate differentials.
The use of multiple hurdles is sometimes complicated by technical issues in the determination of the cost of
equity for lines of business. The traditional method of estimating these betas relies on the existence of “pure
play” comparables. When such comparables are not readily available, it is necessary to rely on a number of
econometric and other techniques. Moreover, companies must undertake careful analysis and use judgment to
identify nonsensical estimates that could lead to potentially damaging decisions.
Even when pure-play comparables exist, some discernment is required. For example, in a recent sample of
asset-management pure plays, the median beta was around 1.1, while a similar retail-banking sample had a
higher median, 1.3; however, about 30 percent of the pure-play asset-management companies had a beta
above 1.3.
Furthermore, betas can vary significantly from one line of business to the next within the same institution.
In extreme cases, the betas of riskier business units can be twice as high as the betas of safer ones. Exhibit
9 presents an example of the differences that can arise when the cost of equity is derived from a number of
methods for various lines of business. For a universal bank with a wide range of businesses, the difference
between the lowest and highest cost of capital can easily be 4 to 5 percentage points, large enough to affect
strategic decisions to grow, shrink, or divest a business.
Granular hurdle rates and economic-capital requirements are not double counted
When an institution applies specific hurdles, some business units are inevitably charged an above-average cost
of equity. An argument that is often proffered in opposition to this practice is that this higher hurdle constitutes a
“double penalty” because economic capital already penalizes a business for higher risk. This is not the case; the
two metrics measure fundamentally different things, economic risk and systematic risk, and they do not have to
be correlated.
Economic risk refers to the probability of default from extreme (“tail”) losses. Creditors and depositors require
a certain level of capital to absorb losses and thus reduce the risk of default. Equity holders, in contrast, are
Typical cost of equity of various banking activities
(based on equity beta/CAPM).
Exhibit 9
Less systematic risk More systematic risk
Retail lending
Mortgages
Advisory/finance
for mergers and
acquisitions
Proprietary
trading
Private banking
Asset
management
Corporate lending
Credit cards

concerned with overall earnings volatility and require a return that compensates them for systematic risk or the
correlation with the overall equity markets. Exhibit 10 schematizes these two concepts of risk.
Therefore, economic capital and betas measure different types of uncertainty and are not necessarily correlated.
For instance, assets with both high beta and high economic capital might include leveraged portfolios of US
stocks, while activities that are low in both would include holding (increasingly elusive) AAA-rated government
debt. However, assets with high economic capital but low beta would include portfolios of catastrophe bonds
providing hurricane insurance, while assets with low economic capital but high beta would include trade-finance
operations with hedged credit exposure (as they generate highly volatile profits but pose only limited loss risks).
VI. LOOKING TO THE FUTURE
Economic capital–based decision making is currently experiencing a revival in banking. A large number of
institutions are either developing new frameworks or improving the sophistication of existing ones. Although
most of these models are used to allocate capital, some banks also use RAROC as a performance indicator for
their business units. And a few institutions use RAROC for the pricing and evaluation of some transactions.
However, as banks overcome technical limitations and face the persistent reality of scarce and expensive capital,
RAROC is bound to play an even more central role in decision making. A small but growing number of banks
already rely on economic capital for detailed performance and transaction evaluations. This trend will accelerate
as institutional consensus builds around the need to hold capital against economic risks while at the same time
earning returns commensurate with these risks.
There are differences between economic capital and beta as
two measures of risk.
Exhibit 10
0
Expected earnings
Creditors care about tail events (ie,
default risk); this aspect of risk is
measured by value at risk and
economic capital
Equity holders care about the correlation between volatility and market
across the whole distribution; this aspect of risk is measured by beta
Portfolio-loss probability distribution
Portfolio return

14
Financial institutions now have the impetus to develop a refined set of RAROC hurdles that reflects the
contribution of each activity to overall risk more specifically and precisely. This development process involves
considerable learning, requires several iterations, and combines hard analytics with “softer” and more informal
business knowledge and experience. However, it ultimately delivers a reliable compass that points away from
the dangerous currents that have cost some dearly in the recent crisis. The renaissance of risk-capital models is,
therefore, both timely and warranted.
Tobias Baer is a senior expert in the Taipei office. Amit Mehta is a consultant in the New York office,
where Hamid Samandari is a director.

McKinseyWorkingPapersonRisk
The Risk Revolution1.
Kevin Buehler, Andrew Freeman, and Ron Hulme
Making Risk Management a Value-Added Function in the Boardroom2.
Gunnar Pritsch and André Brodeur
Incorporating Risk and Flexibility in Manufacturing Footprint Decisions3.
Martin Pergler, Eric Lamarre, and Gregory Vainberg
Liquidity: Managing an Undervalued Resource in Banking after the4.
Crisis of 2007-08
Alberto Alvarez, Claudio Fabiani, Andrew Freeman, Matthias Hauser, Thomas
Poppensieker, and Anthony Santomero
Turning Risk Management into a True Competitive Advantage: Lessons5.
from the Recent Crisis
Gunnar Pritsch, Andrew Freeman, and Uwe Stegemann
Probabilistic Modeling as an Exploratory Decision-Making Tool6.
Martin Pergler and Andrew Freeman
Option Games: Filling the Hole in the Valuation Toolkit for7.
Strategic Investment
Nelson Ferreira, Jayanti Kar, and Lenos Trigeorgis
Shaping Strategy in a Highly Uncertain Macro-Economic Environment8.
Natalie Davis, Stephan Görner, and Ezra Greenberg
Upgrading Your Risk Assessment for Uncertain Times9.
Martin Pergler and Eric Lamarre
Responding to the Variable Annuity Crisis10.
Dinesh Chopra, Onur Erzan, Guillaume de Gantes, Leo Grepin,
and Chad Slawner
Best Practices for Estimating Credit Economic Capital11.
Tobias Baer, Venkata Krishna Kishore, and Akbar N. Sheriff
Bad Banks: Finding the Right Exit from the Financial Crisis12.
Luca Martini, Uwe Stegemann, Eckart Windhagen, Matthias Heuser,
Sebastian Schneider, Thomas Poppensieker, Martin Fest, and
Gabriel Brennan
Developing a Post-Crisis Funding Strategy for Banks13.
Arno Gerken, Matthias Heuser, and Thomas Kuhnt
The National Credit Bureau: A Key Enabler of Financial Infrastructure14.
and Lending in Developing Economies
Tobias Baer, Massimo Carassinu, Andrea Del Miglio, Claudio Fabiani, and
Edoardo Ginevra
Capital Ratios and Financial Distress: Lessons from the Crisis15.
Kevin Buehler, Christopher Mazingo, and Hamid Samandari
Taking Control of Organizational Risk Culture16.
Eric Lamarre, Cindy Levy, and James Twining
After Black Swans and Red Ink: How Institutional Investors Can Rethink17.
Risk Management
Leo Grepin, Jonathan Tétrault, and Greg Vainberg
A Board Perspective on Enterprise Risk Management18.
André Brodeur, Kevin Buehler, Michael Patsalos-Fox, and Martin Pergler
Variable Annuities in Europe after the Crisis: Blockbuster or Niche19.
Product?
Lukas Junker and Sirus Ramezani
Getting to Grips With Counterparty Risk20.
Nils Beier, Holger Harreis, Thomas Poppensieker, Dirk Sojka, and Mario
Thaten
Credit Underwriting After the Crisis21.
Daniel Becker, Holger Harreis, Stefano E. Manzonetto, Marco Piccitto,
and Michal Skalsky
Top-down ERM: A Pragmatic Approach to Manage Risk from the C-Suite22.
André Brodeur and Martin Pergler
23. Getting risk ownership right
Arno Gerken, Nils Hoffmann, Andreas Kremer, Uwe Stegemann, and
Gabriele Vigo
24. The use of economic capital in performance management for banks:
A perspective
Tobias Baer, Amit Mehta, and Hamid Samandari
EDITORIAL BOARD
Rob McNish
Managing Editor
Director
McKinsey & Company
Washington, D.C.
Rob_McNish@mckinsey.com
Martin Pergler
Senior Expert
McKinsey & Company
Montréal
Martin_Pergler@mckinsey.com
Sebastian Schneider
Partner
McKinsey & Company
Munich
Sebastian_Schneider@mckinsey.com
Andrew Sellgren
Partner
McKinsey & Company
Washington, D.C.
Andrew_Sellgren@mckinsey.com
Mark Staples
Senior Editor
McKinsey & Company
New York
Mark_Staples@mckinsey.com
Dennis Swinford
Senior Editor
McKinsey & Company
Seattle
Dennis_Swinford@mckinsey.com

McKinsey Working Papers on Risk
January 2011
Designed by North American Design Center
Copyright © McKinsey & Company
www.mckinsey.com

24 the use_of_economic_capital

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