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Economic capital (EC) is the amount of risk capital that a bank estimates in
order to remain solvent at a given confidence level and time horizon.
Regulatory capital (RC), on the other hand, reflects the amount of capital that
a bank needs, given regulatory guidance and rules. This article will highlight
how EC is measured, examine its relevance for banks and compare economic and
regulatory capital.
See: How Protests Could Change Banking
Risk Management
Banks and financial institutions are faced with long-term future uncertainties
that they intend to account for. It is in this context that the Basel Accords
were created, aiming to enhance the risk management functions of banks and
financial institutions. Basel II provides international directives on the
regulatory minimum amount of capital that banks should hold against their
risks, such as credit risk, market risk, operational risk, counterparty risk,
pension risk and others. Basel II also sets out regulatory guidance and rules
for modeling regulatory capital and encourages firms to use EC models. EC as a
concept and a risk measure is not a recent phenomenon, but has rapidly become
an important measure among banks and financial institutions. (For background
reading, see Basel II Accord To Guard Against Financial Shocks and How Basel I
Affected Banks)
Regulatory Capital
When banks calculate their RC requirement and eligible capital, they have to
consider regulatory definitions, rules and guidance. From a regulatory
perspective, the minimum amount of capital is a part of a bank's eligible
capital. Total eligible capital according to regulatory guidance under Basel II
is provided by the following three tiers of capital:
Tier 1 (core) capital: broadly includes elements such as common stock,
qualifying preferred stock, and surplus and retained earnings.
Tier 2 (supplementary) capital: includes elements such as general loan loss
reserves, certain forms of preferred stock, term subordinated debt, perpetual
debt, and other hybrid debt and equity instruments.
Tier 3 capital: includes short-term subordinated debt and net trading book
profits that have not been externally verified.
Note that these tiers may be constituted in various ways according to legal and
accounting regimes in Bank for International Settlement (BIS) member countries.
Additionally, the capital tiers differ in their ability to absorb losses; Tier
1 capital has the best abilities to absorb losses. It is necessary for a bank
to calculate the bank's minimum capital requirement for credit, operational,
market risk and other risks, to establish how much Tier 1, Tier 2 and Tier 3
capital is available to support all risks.
Economic Capital
EC is a measure of risk expressed in terms of capital. A bank may, for
instance, wonder what level of capital is needed in order to remain solvent at
a certain level of confidence and time horizon. In other words, EC may be
considered as the amount of risk capital from the banks' perspective;
therefore, it differs from RC requirement measures. Economic capital primarily
aims to support business decisions, while RC aims to set minimum capital
requirements against all risks in a bank under a range of regulatory rules and
guidance.
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So far, since economic capital is rather a bank-specific or internal measure of
available capital, there is no common domestic or global definition of EC.
Moreover, there are some elements that many banks have in common when defining
EC. EC estimates can be covered by elements of Tier 1, Tier 2, Tier 3 or
definitions used by rating agencies and/or other types of capital, such as
planned earning, unrealized profit or implicit government guarantee.
Relevance of Economic Capital
EC is highly relevant because it can provide key answers to specific business
decisions or for evaluating the different business units of a bank. It also
provides an instrument for comparing RC.
Performance Measure
A bank's management can use EC estimates to allocate capital across business
streams, promoting those units that provide desirable profit per unit of risk.
An example of performance measure that involves EC is return on risk adjusted
capital (RORAC), risk adjusted return on capital (RAROC) and economic value
added (EVA). Figure 1 shows an example of an RORAC calculation and how it can
be compared between the business units of a bank or financial institution.
Business Return and/or Profit EC Estimates RORAC
Unit 1 $50 millions $100 millions 50% ($50/$100)
Unit 2 $30 millions $120 millions 25% ($30/$120)
Figure 1: RORAC of two business units during one year.
Figure 1 shows that business unit 1 generates higher return in EC terms (i.e.
RORAC) compared to business Unit 2. Management would favor business Unit 1,
which consumes less EC, but at the same time generates higher return. This kind
of assessment is more practical in a bottom-up approach. The bottom-up approach
implies that the EC assessments are made for each business unit and then
aggregated to an overall EC figure. By contrast, the top-down approach is more
arbitrary, because EC is calibrated at a group level and then delivered to each
business stream, where criteria for capital allocation can be vague.
Comparing to RC
Another use of EC is to compare it with RC requirement. Figure 1 provides an
example of some risks that can be assessed by an EC framework and how it could
be compared to RC requirement.
Figure 2: RC requirement and EC estimate
Measuring EC
While a bank's EC figure is partly driven by its risk appetite (the desire for
risk), RC requirement is driven by supervisory metrics set out in the
regulatory guidance and rule books. Moreover, by contrast with regulatory
capital models under Basel II, such as the advanced internal rating based
(AIRB) model for credit risk, banks can make their own choices on how to model
EC. For example, banks can choose the functional form and the parameter
settings of their model. Therefore, EC modeling may adjust or ignore
assumptions of AIRB for credit risk. AIRB assumes that a loan portfolio is
large and homogeneous, that longer term assets are more risky, as reflected in
the so-called maturity adjustment capped at five years, and that higher quality
ratings have higher correlation to reflect systemic risk. It also evaluates
risk by rating classes and assumes perfect correlation between rating classes
and diversification within a rating class. (For more, see Measuring And
Managing Investment Risk.)
Value-at-risk (VaR) models are typical EC frameworks for market, credit risk
and other risks. However, for credit risk it is usually referred to as credit
value-at-risk (CVaR). Figure 3 provides an example of loss distribution of a
loan portfolio for relatively secure loans. Figure 3 shows the expected losses
and the unexpected losses. The expected loss represents a loss that arises from
the daily business, while the unexpected loss is the number of standard
deviations away from the expected loss (the tail of the distribution). In the
current example, the unexpected loss is calibrated at the 99.95% confidence
level, which corresponds to an 'AA' rating. Therefore, banks may calibrate
their economic capital models according to the managements risk appetite, which
is usually in line with the bank's target rating. (For more, see An
Introduction to Value at Risk.)
Figure 3: Economic capital for the credit risk
Some banks may use internally developed models to calculate their ECs. However,
banks may also use commercial software to assist them in their EC calculations.
A typical example of such software for credit risk is the Portfolio Manager by
Moody's KMV, Strategic Analytics, Credit risk+ by Credit Suisse and
CreditMetrics by JP Morgan.
The Bottom Line
EC is a measure of a bank's risk capital. It is not a recent concept, but it
has rapidly become an important measure among banks and financial institutions.
EC provides a useful supplementary instrument to RC for business based
decisions. Banks are increasingly using EC frameworks and it will most likely
continue to grow in the future. The relevant question might be whether EC could
one day supersede RC requirements.
by Fadi Zaher
Fadi Zaher completed his Ph.D. in financial economics at Lund University in
Sweden in 2006. He also holds master's degrees in economics and econometrics.
He has worked as a lecturer at the University of Skovde in Sweden, the European
Central Bank in Germany and the Financial Services Authority in the UK. He is
currently an analyst at Rabobank in the U.K.