assessing financial stability conceptual and organisational challenges istanbul, 18 may 2005
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Assessing Financial Stability Conceptual and organisational challenges Istanbul, 18 May 2005. Peter PRAET Executive Director, National Bank of Belgium Member of the Board, Banking, Finance and Insurance Commission. I. The building blocks. Prevention design of rules, regulation, standards... - PowerPoint PPT PresentationTRANSCRIPT
Assessing Financial StabilityConceptual and organisational challengesIstanbul, 18 May 2005
Peter PRAET
Executive Director, National Bank of Belgium
Member of the Board, Banking, Finance and Insurance Commission
© National Bank of Belgium
I. The building blocks
Prevention
design of rules, regulation, standards...
Surveillance
micro / macro
Crisis management
"orderly exit"
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II. Challenges (1/2)
Traditional bank
illiquid assets, originated & held to maturity
liquid liabilities
uninformed depositors
Highly powered incentive structure
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Changing borders of banks risk profile can change rapidly / more dynamic
balance sheet
cross-sector: from narrow banks to financial conglomerates
size: firms as market infrastructures
cross-border
perimeter of control / outsourcing issues
fiduciary role?
II. Challenges (2/2)
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III. Three horizontal questions
What is risk? "Just a probabilistic concept"?
What financial structure carries the risks?
Understanding leverage
What governance setting takes and
manages the risks?
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IV. Illustration: credit risk
Major changes over the past 10/15 years
in the management of credit risk and in
the nature of market participants
Regulation tries to be as close as possible
to "Market best practices"
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Value-at-risk (VaR) approach
Amount capital >= VaR
VaR measures the maximum loss in value that can occur at a given
confidence level and in a specified time period
Example: if confidence interval = 99.9% and time period = 1 year, then
there is 1 chance in a 1000 that the loss in 1 year is greater than the VaR.
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VaR approach
Realised losses over time gives loss frequency distribution
Unexpected losses
Expected losses
Time
Los
ses
Frequency losses
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Credit VaR
Example of losses distribution: the EL and UL parts
0
0,05
0,1
0,15
0,2
0,25
0,3
Expected losses Unexpected losses
Losses
Average
Loss frequency distribution
Credit Value-at-Risk
A
0.07%
AA
0.03%
AAA
0.01%
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Credit VaR: risk parameters
Risk parameters loss distribution
PD (probability of default)
LGD (loss given default)
EAD (exposure at default)
Maturity
Correlation
Additional parameter Credit -VaR: confidence interval
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Credit VaR: risk parameters Illustration maturity
(in %) AAA A BBB BB
PD 1 year 0.02 0.14 0.75 2
PD 3 year 0.03 0.24 0.99 6.14
PD 5 year 0.1 0.57 2.16 10.59
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Credit - VaR: risk parameters Illustration: Impact correlation on loss distribution
Correlation = 0 % Correlation = 50 % Correlation = 100 %
Loss LossLoss
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VaR in credit institutions: economic capital / rating agencies' capital / supervisory capital
Convergence? "Same business same rules?"
Credit - VaR parameters: market participants and supervisors
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Outlook: banks / non-banksE
quit
yJu
nior
Mez
zani
ne
Sen
ior
Sup
er
seni
or
Losses
Los
s pr
obab
ilit
y
Illustration: CDO tranching loss distributionVolume
Equity 2%
Junior 1%
Mezz. 4%
Senior 8%
Super senior
85%
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Main issues
The increasing difficulty to track the circulation
of credit risk (for authorities and markets)
Possible excessive reliance on the output of
models that have not been tested sufficiently
Lack of risk management tools that consider the
interlinkages between market risk, credit risk,
operational risk ("silo" approach to risk)
How to deal with "tail risks"?