Risk Management and Value Creation in ... - Arabictrader.com

182 RISK MANAGEMENT AND VALUE CREATION IN FINANCIAL INSTITUTIONS
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Equation (5.19) is a practicable way to calculate ULC. However, it
basically ignores the fact that loans are of different sizes and show
different correlations (e.g., by industry, geography, etc.). Therefore,
using Equation (5.19) does not reveal potential concentrations in
the credit portfolio. But banks try to avoid exactly these concentrations.
It is easy to show 216 that Equation (5.19) can be decomposed
for various segments of the portfolio so that, for example, default
correlations between various industries or even of a single credit can
be included. Using this approach (instead of the impractical “fullblown”
approach, as indicated by Equation (5.8), allows banks to
quantify exactly what they have done by intuition, prudent lending
policies, and guidelines for a very long time. 217
Default correlations are small, but positive. Therefore, and as indicated
previously, there are considerable benefits to diversification in
credit portfolios.
Overall, the analytical approach is very cumbersome and prone to
estimation errors and problems. To avoid these difficulties, banks
now use numerical procedures 218 to derive more exact and reliable
results.
Viewing the UL of a single credit in the context of a credit portfolio 219
reduces the standalone risk considerably in terms of its risk contribution
(ULC). 220
Economic Capital for Credit Risk As defined previously, the amount of economic
capital needed is the distance between the expected outcome and the unexpected
(negative) outcome at a certain confidence level. As we saw in the last
section, the unexpected outcomes at the portfolio level are driven by UL P
,
the estimated volatility around the expected loss. Knowing the shape of the
loss distribution, EL P
, and UL P
, one can estimate the distance between the
expected outcome and the chosen confidence level as a multiple (often labeled
as capital multiplier, or CM 221 ) of UL P
, as shown in Figure 5.7.
216 See Ong (1999), pp. 133–134.
217 These guidelines often state that a bank should not lend too much money to a
single counterparty (i.e., the size effect ignored in Equation [5.19]), the same industry
or geography (i.e., the correlation effect ignored in Equation [5.19]).
218 Such as Monte Carlo simulations; see, for example, Wilson (1997a) and (1997b).
219 An alternative for determining this marginal risk contribution would be to calculate
the UL of the portfolio once without and once with the transaction and to build
the difference between the two results.
220 The same approach is applicable to country risk. However, instead of borrower
default correlations, country default correlations are applied.
221 See Ong (1999), p. 163.