131-2009: cibc case study: risk management and sas® tools
TRANSCRIPT
©CIBC 2009 All R
ights Reserved
1SA
S Global Foru
m 2009
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atters.
Paper 1
31
-20
09 C
ase Study
Risk M
anagem
ent:
Risk M
anagem
ent:
Usin
g the SA
S Platform
at CIB
CU
sing th
e SAS P
latform at C
IBC
Rick M
illerR
ick Miller
Vice
Vice- -P
resident, C
redit Risk D
ata Solution
sP
resident, C
redit Risk D
ata Solution
sR
isk Man
agemen
t, CIB
CR
isk Man
agemen
t, CIB
C
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ights Reserved
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Disclaim
er
Any views, opinions, advice, statem
ents, or other information or
content
expressed or implied in the follow
ing presentation are solely those of the
presenter and do not necessarily state or reflect the views, positions, or
opinion of
Canadian Im
perial Bank of
Comm
erce (CIBC)
or any
of its
subsidiaries or affiliates.
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Today’s Discu
ssion
•A
Brief O
verview of th
e Basel II Fram
ework
•In
creased Spotlight on
Credit R
isk Data
•K
ey Data C
hallen
ges
•Th
e Journ
ey Ah
ead
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ights Reserved
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atters.
Abou
t CIB
C•
Can
adian Im
perial Ban
k of Com
merce (C
IBC
) is a leading
North
Am
erican Fin
ancial in
stitution
•w
e offer a full ran
ge of products an
d services to almost
11
million
individu
als and sm
all busin
esses, corporate and
institu
tional clien
ts
•A
t year-end (O
ctober 31
, 20
08
):•
Market capitalization
was $
20
.8 billion
•Tier 1
capital ratio was 1
0.5
%•
employed n
early 40
,00
0 em
ployees worldw
ide•
had 1
,05
0 bran
ches in
Can
ada and m
ore than
3,7
00
AB
Ms
•con
stituen
t of the D
ow Jon
es Sustain
ability Index (D
JSI)for seven
consecu
tive years (one of 2
5 ban
ks worldw
ide)
All am
oun
ts in C
$
Financial ServicesSAS Global Forum 2009
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ights Reserved
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atters.
The B
asel II Framew
ork Goals
Pillar I
Calcu
lation of
Min
imu
m
Capital
Requ
iremen
ts
Pillar IIS
elf-A
ssessmen
t an
dSu
pervisoryR
eview
Pillar III
Disclosu
rean
dM
arketD
iscipline
Credit R
iskO
perational R
iskM
arket Risk
•a global fram
ework issu
ed by Ban
k of Intern
ational
Settlemen
ts (BIS) an
d man
aged by nation
al supervisors
•developed over th
e period 19
99
–2
00
5 w
ith broad
consu
ltation globally alon
g with
quan
titative impact stu
dies
•Th
e Basel II C
omm
ittee Goals w
ere:•
to enh
ance risk sen
sitivity of capital requirem
ents
•greater em
phasis on
banks ow
n assessm
ent of risk
•im
prove transparen
cy for market disciplin
e
•B
asel II was im
plemen
ted Novem
ber 1, 2
00
7 by C
IBC
and
other m
ajor banks in
Can
ada
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The B
asel II Framew
ork
Pillar I
Calcu
lation of
Min
imu
m
Capital
Requ
iremen
ts
Pillar II
Self-
Assessm
ent
and
SupervisoryR
eview
Pillar III
Disclosu
rean
dM
arketD
iscipline
Credit R
iskO
perational R
iskM
arket Risk
Financial ServicesSAS Global Forum 2009
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Distribu
tion of C
redit Risk
Defau
lt Ratin
g
Exposure ($)
Bank A
Bank B
Best
Worst
Corporate
Loan P
ortfolio
•assu
me credit portfolio size is iden
tical for both ban
ksbu
t with
a different m
ix of credit risk
ILLUSTR
ATIV
E
Financial ServicesSAS Global Forum 2009
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ights Reserved
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S Global Foru
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atters.
Previou
s CA
R: N
o Differen
tiation
•U
nder previou
s Capital A
dequacy ru
les, both portfolios
wou
ld require th
e same am
oun
t of min
imu
m regu
latory capital
ILLUSTR
ATIV
E
TotalC
apital
ExposuresC
AR 1
($)
Bank ABank B
Corporate
Loan P
ortfolio
Financial ServicesSAS Global Forum 2009
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S Global Foru
m 2009
For what m
atters.
Basel II: R
isk Sensitive, M
ore Capital
•Th
e strategic implication
is that ban
ks with
riskier portfoliosw
ill have h
igher m
inim
um
regulatory capital requ
iremen
ts
ILLUSTR
ATIV
EA
IRB
Approach
TotalC
apitalC
apital
Exposures
CA
R 1
Basel II
($)
Bank A
Bank B
Corporate
Loan P
ortfolio
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atters.
Basel II G
lossary: Credit R
isk Capital
•Th
e Basel II Fram
ework allow
s the u
se of bank-specific
estimates of risk com
ponen
ts in determ
inin
g the capital
compon
ent for a given
exposure:
•P
robability of default (P
D)
•Exposu
re at default (EA
D)
•Loss given
default (LG
D)
•Effective m
aturity
•Firm
-size adjustm
ent for Sm
all Mediu
m En
terprises (SME)
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Basel II G
lossary: Credit R
isk Capital
•Expected Loss (EL) =
PD
* EA
D *
LGD
•U
nexpected Loss (U
L) calculated u
sing soph
isticated Basel II
formu
lae incorporatin
g PD
, EAD
, LGD
Loss
Probability of D
efault
Un
expectedloss
Expected loss
99
.9th
percentile
of loss
•m
inim
um
regulatory capital is a fu
nction
of the calcu
lationof u
nexpected loss (U
L) and expected loss (EL)
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atters.
Basel II: Th
ree Option
s for Credit R
isk
Standardized
Approach
More Strin
gent Q
ualifyin
g Criteria
More Sophistication and Risk Sensitivity
STAN
DA
RD
IZED A
PP
RO
AC
H
•sim
ilar to existing B
IS’88
•m
ore gradations of risk
•ban
ks can u
se external credit ratin
gs
•som
e capital relief for credit riskm
itigation (e.g., collateral)
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Basel II: Th
ree Option
s for Credit R
isk
Foun
dation
Intern
al Ratin
gs B
ased Approach
Standardized
Approach
FOU
ND
ATIO
N IN
TERN
AL R
ATIN
GS
BA
SED A
PP
RO
AC
H (FIR
B)
•based on
intern
al data and risk ratin
gs
•ban
ks use th
eir own
estimates of:
Probability of D
efault (P
D)
•su
pervisors provide estimates for:
Loss Given
Defau
lt (LGD
) and
Exposure A
t Defau
lt (EAD
)
•expected M
inim
um
requirem
ent for
intern
ationally active ban
ks
More Sophistication and Risk Sensitivity
More Strin
gent Q
ualifyin
g Criteria
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Basel II: Th
ree Option
s for Credit R
isk
Foun
dation
Intern
al Ratin
gs B
ased Approach
Standardized
Approach
AD
VA
NC
ED IN
TERN
AL R
ATIN
GS
BA
SED A
PP
RO
AC
H (A
IRB
)
•based on
intern
al data and risk ratin
gs
•ban
ks use th
eir own
estimates of:
Probability of D
efault (P
D)
Loss Given
Defau
lt (LGD
)Exposu
re at Defau
lt (EAD
)
•com
plex and in
ternation
ally activeban
ks encou
raged to move to th
isapproach
Advan
ced In
ternal R
atings
Based A
pproach
(AIR
B)
More Sophistication and Risk Sensitivity
More Strin
gent Q
ualifyin
g Criteria
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S Global Foru
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For what m
atters.
Basel II: Th
ree Option
s for Credit R
isk
Foun
dation
Intern
al Ratin
gs B
ased Approach
Standardised
Approach
•B
anks m
ust m
eet broadrisk-qu
antification
standards
for own
estimates of P
D,
LGD
, EAD
•B
anks m
ust h
ave a robust
system in
place to validate the
accuracy an
d consisten
cy of:-
rating system
s, -
processes, and
-estim
ation of all relevan
trisk com
ponen
ts
•Su
pervisor expects all major
Can
adian ban
ks to implem
ent
AIR
B
Advan
ced In
ternal R
atings
Based A
pproach
(AIR
B)
More Sophistication and Risk Sensitivity
More Strin
gent Q
ualifyin
g Criteria
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atters.
Basel II G
lossary: Exposure C
lasses•
un
der the IR
B approach
, banks m
ust categorize ban
king-book
exposures in
to broad classes of assets, specifically:
•C
OR
PO
RA
TE•
SOV
EREIG
N•
BA
NK
•R
ETAIL
•R
esidential Secu
red•
Qu
alifying R
evolving R
etail•
All O
ther R
etail•
EQU
ITIES (non
-traded)
•th
e work h
ere was focu
sed on en
surin
g that th
e identifiers to
classify exposures w
ere available, accurate, com
plete, and
persistent in
the sou
rce data
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Basel II G
lossary: Exposure Types
•addition
al granu
larity of reporting u
sing cou
nterparty type
Credit Exposu
resby type for the period ending...
(Canadian $ millions)
Draw
nU
ndrawn
Repo style
transaction
sO
TC
derivativesO
ther
TOTA
L
Residential secured
xxxxxx
xxxxxx
xxxxxx
Qualifying revolving retail
xxxxxx
xxxxxx
xxxxxx
Other R
etailxxx
xxxxxx
xxxxxx
xxx
Corporatexxx
xxxxxx
xxxxxx
xxx
Sovereignxxx
xxxxxx
xxxxxx
xxx
Bankxxx
xxxxxx
xxxxxx
xxx
Total Gross Credit R
isk Exposuresxxx
xxxxxx
xxxxxx
xxx
ILLUSTR
ATIV
E
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atters.
Data M
ainten
ance Focu
s by Regu
lators•
Implem
entation
Note by th
e Can
adian su
pervisor (OSFI),
“Data M
ainten
ance at IR
B In
stitution
s”•
provides general gu
idance on
data main
tenan
ce an
d principles to apply
•su
pervisor will m
onitor on
going data m
ainten
ance
complian
ce
•D
ata Main
tenan
ce Prin
ciples inclu
de guidan
ce on:
•Sen
ior Man
agemen
t Oversigh
t Accou
ntabilities
•D
ata Life-Cycle M
anagem
ent
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S Global Foru
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atters.
So, Wh
at Is the P
rize?
•regu
latory complian
ce is critical
•for C
IBC
’s mix of bu
siness, u
sing th
e Basel II A
IRB
approachresu
lts in a sm
alloverall reduction
of capital for credit risk
•for lin
e of busin
ess operations, ties th
e allocation an
d use
of regulatory capital to th
e risk profile of the bu
siness
•prom
otes an en
terprise-wide focu
s on th
e importan
ce ofaccu
rate and com
plete risk data
•in
troduces form
al requirem
ents for “back testin
g”an
d“stress testin
g”of ratin
g systems an
d parameter estim
atesto su
pplemen
t and en
han
ce existing practices
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atters.
CIB
C C
ase Study
•G
etting Started
•D
eveloping P
arameter Estim
ates
•C
alculatin
g Basel II R
egulatory C
apital
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S Global Foru
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atters.
CIB
C C
ase Study: W
here W
e Started
•developed a broad u
nderstan
ding of th
e Basel II Fram
ework
requirem
ents
•assessed w
hat already existed, in
terms of:
•P
eople•
Processes
•D
ata•
Systems / tools
•developed a “gap an
alysis”an
d secured sen
ior man
agemen
tsu
pport and fu
ndin
g for projects to close the gaps
•strategy w
as to leverage existing capability, w
herever possible
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atters.
•u
se the B
asel II Framew
ork docum
ent to u
nderstan
d and
then
define th
e “man
datory risk data”
•create a logical m
odel to consolidate an
d organise
the data
•determ
ine w
here th
e data exists and iden
tify any data gaps
•en
han
ce systems to collect an
d store the requ
ired data
•h
armon
isedifferen
t data definition
s throu
gh th
e application
of busin
ess logic
•im
plemen
t a data main
tenan
ce framew
ork to inclu
de:•
risk data stewardsh
ip roles & respon
sibilities•
data standards for accu
racy, completen
ess, timelin
ess•
data controls, m
easurem
ent, an
d mon
itoring
•data secu
rity and access
The D
ata Approach
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ights Reserved
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S Global Foru
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For what m
atters.
Differen
t Credit R
isk Data C
hallen
gesC
OR
PO
RA
TE, SOV
EREIG
N,
BA
NK
, EXP
OSU
RE C
LASSES
RETA
IL EXP
OSU
RE
CLA
SSES
VIEW
OF
CR
EDIT R
ISKB
orrower-cen
tric(across all org u
nits an
d all produ
cts)
Produ
ct-centric
(hom
ogeneou
s pools)
ASSIG
NM
ENT O
F R
ISK P
AR
AM
ETERS
Assign
ed to each borrow
erA
ssigned to each
pool
EXP
OSU
RE
DIM
ENSIO
NS
Large auth
orization /
outstan
ding balan
ces per borrow
er -m
ultiple facilities
Small au
thorization
/ ou
tstandin
g balances
BO
RR
OW
ER
VO
LUM
EH
un
dreds of thou
sands
Man
y million
s
RA
TING
SYSTEM
SR
equires soph
isticated “risk ratin
g”system
sR
equires less
complex “credit
scoring”
REC
ON
CILIA
TION
: EX
PO
SUR
ES TO G
/LC
hallen
ging across exposu
re classes an
d exposure types
More straigh
tforward
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atters.
Key C
hallen
ges: Credit R
isk Data
•sign
ificant am
oun
t of data is required
•requ
ire nu
merou
s feeds from differen
t kinds of sou
rce system
s
•state of cu
rrent credit risk data
•h
ow to recon
cile credit risk balances origin
ating in
these
disparate systems to th
e Gen
eral Ledger
•system
s constrain
ts / timin
g
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atters.
Wh
at Data D
o We N
eed?
Borrow
er / Gu
arantor
Identity
Risk R
ating /
Scoring M
odels
Basel II C
apitalC
alculation
s
Risk
Weigh
ted Assets
(RW
A)
Param
eterEstim
ates(P
D, LG
D, EA
D)
Econom
icLoss H
istoryExtern
alC
reditA
ssessmen
ts
Borrow
er / Gu
arantor
Ch
aracteristics
ExpectedLoss
Facility Info
Collateral
Ch
aracteristics
Basel II
Exposure
Classes
Borrow
erD
efault
Ratin
gs
EffectiveM
aturity
Credit R
iskM
itigationExposu
res
•decom
pose Basel II Fram
ework clau
ses into “m
andatory”
credit risk data for AIR
B com
pliance
ILLUSTR
ATIV
E
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ights Reserved
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For what m
atters.
Wh
ere To Look For The D
ata
Credit
Adju
dicationC
reditA
pplication
Fulfillm
ent
and
Operation
s
Mon
itoring
and
Reportin
g
ILLUSTR
ATIV
E
(1) in
itialdata captu
re,verification
,validation
(2) approve
terms an
dcon
ditions
(e.g., limits,
default ratin
gs)
(3) bookin
g,m
anagin
g exposu
res, an
d collateralvalu
e
An
alyze the
Credit R
isk Data Lifecycle
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ights Reserved
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atters.
How
Do W
e Organ
ize The D
ata?
Risk
Calcu
lations
(PD
, LGD
, EAD
)
Risk
Weigh
ted Assets
(RW
A)
Basel II
Regu
latoryC
apital
“Man
datory”C
redit Risk D
ata
ILLUSTR
ATIV
E
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ights Reserved
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S Global Foru
m 2009
For what m
atters.
How
Do W
e Organ
ize The D
ata?
Risk R
ating /
Scoring M
odels
Risk
Calcu
lations
(PD
, LGD
, EAD
)
Risk
Weigh
ted Assets
(RW
A)
Param
eterEstim
ates
Basel II
Regu
latoryC
apital
“Man
datory”C
redit Risk D
ata
ILLUSTR
ATIV
E
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ights Reserved
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S Global Foru
m 2009
For what m
atters.
How
Do W
e Organ
ize The D
ata?B
orrower /
Gu
arantor
Identity
Risk R
ating /
Scoring M
odels
Risk
Calcu
lations
(PD
, LGD
, EAD
)
Risk
Weigh
ted Assets
(RW
A)
Param
eterEstim
ates
Econom
icLoss H
istory
External
Credit
Assessm
ents
Borrow
er /G
uaran
torC
haracteristics
Basel II
Regu
latoryC
apital
FacilityD
etails
Credit R
iskM
itigation
“Man
datory”C
redit Risk D
ata
Instru
men
tB
alances
ILLUSTR
ATIV
E
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For what m
atters.
Wh
at We Learn
ed Abou
t Ou
r Data
•th
e most ch
allengin
g task was m
apping data
•th
ere was n
o comm
on data m
odel
•th
ere were som
e “data breaks”
•w
e didn’t h
ave granu
lar enou
gh h
istorical data
•data defin
itions w
ere incon
sistent
•as th
e parallel year progressed, we m
easured su
ccess by the
reduction
in th
e use of “defau
lts”for R
WA
calculation
s
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For what m
atters.
Case Stu
dy #1
: Param
eter Estimation
Borrow
er /G
uaran
torIden
tity
Risk R
ating /
Scoring M
odels
Risk
Calcu
lations
(PD
, LGD
, EAD
)
Risk
Weigh
ted Assets
(RW
A)
Param
eterEstim
ates
Econom
icLoss H
istory
External
Credit
Assessm
ents
Borrow
er /G
uaran
torC
haracteristics
Basel II
Regu
latoryC
apital
FacilityD
etails
Credit R
iskM
itigation
Instru
men
tB
alances
usin
g Residen
tial Mortgages
as an exam
ple
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For what m
atters.
Overview
: Param
eter Estimation
•risk ratin
g systems ran
k order the qu
ality of individu
al creditrisk exposu
res and grou
pings of exposu
res
•th
ere are three im
portant dim
ension
s:•
the risk of th
e borrower defau
lting (P
D)
•factors specific to in
dividual tran
sactions to estim
ateth
e econom
ic loss, given defau
lt (LGD
)•
the calcu
lation of exposu
re amou
nt at defau
lt (EAD
)
•th
e estimates for P
Ds
need to be lon
g-run
averages of the
actual on
e-year default rates
•LG
Ds
mu
st be developed from h
istorical losses and recoveries
•th
ese parameters m
ust be good predictors of fu
ture loss even
ts
•ban
ks are expected to reflect conservative estim
ates
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
33SA
S Global Foru
m 2009
For what m
atters.
Key C
hallen
ges: Param
eter Estimation
•requ
ired history (at least on
e full econ
omic cycle) n
ot readilyavailable for som
e required attribu
tes
•scarcity of C
IBC
-specific default data (e.g., Sovereign
s, Ban
ks)
•gran
ularity of data n
ot always available
•persisten
ce of key data over time du
e to systems ch
anges
•requ
ires un
ique an
alytical skill sets to build param
eterestim
ation m
odels
•param
eter estimation
models m
ust be in
dependen
tly validated
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
34SA
S Global Foru
m 2009
For what m
atters.
Developin
g Retail P
D Estim
ates•
Basel II requ
ires banks to pool retail exposu
res with
similar risk
characteristics an
d estimate th
e Probability of D
efault (P
D)
•each
individu
al exposure w
ithin
the pool th
en acqu
ires the
parameters of th
e pool to wh
ich it belon
gs
Pool1
Pool2
Pool3
Pool4
Pool5
Pooln
Borrower Metrics
Transaction Metrics
Historic P
ortfolio P
erforman
ce Data
Historic Econ
omic D
ata
Pool1
Pool2
Pool3
Pool4
Pool5
Pooln
Borrower Metrics
Transaction Metrics
PD
An
alytic Engin
e:•
determin
es pools•
forecasts PD
for each pool
•revises pools to en
sure
appropriate Capital
•stress testin
g
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
35SA
S Global Foru
m 2009
For what m
atters.
Basel II D
efinition
s: Probability of D
efault (P
D)
•P
robability of Defau
lt (PD
) is a measu
re of the likelih
ood of anu
ncertain
futu
re event.
•th
e Basel II R
esidential M
ortgages Exposure C
lass inclu
desm
ortgages for:•
single-fam
ily hom
es, wh
ether th
ey are own
er-occupied or n
ot•
mu
lti-family bu
ildings w
ith m
aximu
m of 4
un
its
•B
asel II definition
of default (clau
ses 45
2-4
53
), either or both
of:•
obligor is past due 9
0 days on
credit obligation to th
e bank
•th
e bank con
siders the obligor u
nlikely to pay credit
obligations in
full
•B
asel II time h
orizon (clau
se 46
6) specifies h
istorical observations
of at least five years
•B
asel II data sources (clau
se 46
4) specifies “ban
ks mu
st regardin
ternal data as th
e primary sou
rce of inform
ation for estim
ating
loss characteristics”
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
36SA
S Global Foru
m 2009
For what m
atters.
Creatin
g Pools for R
esidential M
ortgages•
throu
gh an
alysis, we derived the key available risk factors
•w
e pooled mortgage loan
s on th
e followin
g criteria:•
arrears status in
bands, e.g., curren
t, 1-2
9 days delin
quen
t, etc.•
Loan-To-V
alue (LTV
) ratio•
Occu
pancy Statu
s, e.g., rental, ow
ner-occu
pied, etc.
ILLUSTR
ATIV
EIn
ternal
source data
60-89 days delinquent
Current30-59 days delinquent
1-29 days delinquent
LTV <=
0.x
Ow
ner-occupied / m
ixedRental property
LTV > 0.x
Pool APool F
Pool EPool C
Pool DPool B
Poolin
g for Residen
tial Mortgages
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
37SA
S Global Foru
m 2009
For what m
atters.
Meetin
g the B
asel II Requ
iremen
ts
To conform
to the B
asel II requirem
ents, w
e ensu
re that:
1.
The pools clearly differen
tiate the P
Ds
(clause 4
01
)•
PD
in on
e pool shou
ld not sign
ificantly in
tersect with
others
2.
Each pool con
tains en
ough
borrowers an
d defaulted borrow
ersto allow
for mean
ingfu
l quan
tification an
d validation of loss
characteristics at th
e pool level (clause 4
09
)
3.
PD
pools display sufficien
tly hom
ogenou
s behaviou
rover tim
e•
subject to policy ch
anges, etc.
4.
If any pool w
ould h
ave a PD
less than
3 basis poin
ts, we assign
the B
asel II floor of 3 basis poin
ts (clause 3
31
)
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
38SA
S Global Foru
m 2009
For what m
atters.
Review
ing th
e Historical P
erforman
ce Data
ILLUSTR
ATIV
E
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
39SA
S Global Foru
m 2009
For what m
atters.
Next Steps –
Derivin
g the P
Ds
•for each
Residen
tial Mortgages pool, data w
as analyzed to produ
celow
er quartile, median
, and u
pper quartile valu
es
PD(bps)
Pool IDM
ean PDStd
Min
Max
Adjusted PD
PD
Estimate
Average Balance
A0000.00
0000.000000.00
0000.000000.00
0000.0000.0
B0000.00
0000.000000.00
0000.000000.00
0000.0000.0
C0000.00
0000.000000.00
0000.000000.00
0000.0000.0
D0000.00
0000.000000.00
0000.000000.00
0000.0000.0
E0000.00
0000.000000.00
0000.000000.00
0000.0000.0
F0000.00
0000.000000.00
0000.000000.00
0000.0000.0
ILLUSTR
ATIV
E
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
40SA
S Global Foru
m 2009
For what m
atters.
Next Steps –
Implem
entin
g & M
onitorin
g•
statistical analysis w
as performed to test for:
•m
eanin
gful distribu
tion of borrow
ers across pools•
hom
ogenou
s behaviou
rw
ithin
pools•
trendin
g•
adjustm
ent n
eeded for samplin
g error(s)
•w
e derived our estim
ate of long-ru
n average P
D for each
pool
•w
e tested the accu
racy of our prediction
s
•w
e implem
ented th
e PD
model in
to production
for calculation
of Risk W
eighted A
ssets (RW
A’s) for R
esidential M
ortgages
•w
e mon
itor and an
alyze the observed defau
lt rate over time
against th
e estimate
•reports to sen
ior man
agemen
t high
light perform
ance over tim
e
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
41SA
S Global Foru
m 2009
For what m
atters.
Case Stu
dy #2
: Calcu
lating R
isk Weigh
ted Assets
Borrow
er /G
uaran
torIden
tity
Risk R
ating /
Scoring M
odels
Risk
Calcu
lations
(PD
, LGD
, EAD
)
Risk
Weigh
ted Assets
(RW
A)
Param
eterEstim
ates
Econom
icLoss H
istory
External
Credit
Assessm
ents
Borrow
er /G
uaran
torC
haracteristics
Basel II
Regu
latoryC
apital
FacilityD
etails
Credit R
iskM
itigation
Instru
men
tB
alances
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
42SA
S Global Foru
m 2009
For what m
atters.
The R
oad to Basel II R
isk Weigh
ted Assets
•m
inim
um
regulatory capital u
nder B
asel II is based on th
ecalcu
lation of R
isk Weigh
ted Assets (R
WA
s)
•R
WA
sare calcu
lated according to establish
ed math
ematical
formu
lae utilizin
g PD
s, LGD
s, EAD
s, and in
some cases,
matu
rity adjustm
ents
•Sou
rcing, processin
g, and recon
ciling data in
order to calculate,
store, and report on
RW
As
for the calcu
lation of m
inim
um
regulatory capital is th
e core of the B
asel II data challen
ge
•Th
e Basel II C
apital Adequ
acy Requ
iremen
ts (BC
AR
) Retu
rnprovides C
anadian
regulators w
ith qu
arterly status on
the
Ban
k’s capitalization in
relation to th
e risks it has assu
med
•In
Can
ada, the m
inim
um
ratio for Total Capital to R
isk Assets
and Total A
ssets is 8%
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
43SA
S Global Foru
m 2009
For what m
atters.
Credit R
isk Data A
rchitectu
re Overview
RETA
IL &
WH
OLESA
LEC
RED
ITR
ISK D
ATA
WA
REH
OU
SES
Bu
siness
Ru
les
RW
Acalcu
lationen
gines
Risk
An
alyticsM
odels
Party
Referen
ceD
ata
Credit
Application &
Adju
dication
Accou
nt
Man
agemen
t&
Mon
itoring
Transaction
Systems
External
Ratin
gs
Data Integration Layer (various ETL tools – push/pull)
Business Intelligence Layer
Reports
View
s
Direct
Feed toR
egulators
G/L
Balances &
Hierarch
ies
Economic
Capital
calculation
engin
es
Oth
erA
pplications&
Models
staging areas
ILLUSTR
ATIV
E
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
44SA
S Global Foru
m 2009
For what m
atters.
The P
rocess for RW
As
–R
etail Credit R
isk
extract monthly source
data for all retail assetsas at m
onth-end
staging areadata validation
assign retail assets to Basel II Exposure Class
reconcile balances of retail assets to G
eneral Ledger
ILLUSTR
ATIV
E
General Ledger
analytic engine to assignretail assets into pools
reference data
Parameter tables
(PD, LG
D, EAD
)
RW
A calculator enginefor all retail assets andpool sum
maries
creation of BCAR andother regulatory reports
final reconciliation ofall risk assets
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
45SA
S Global Foru
m 2009
For what m
atters.
Recon
ciliation To Th
e Gen
eral Ledger
AccountingCode block
Credit R
isk data wareh
ouses
BalanceO
ther Risk D
ata Attributes
Product
Org
BOA
Account
CustGrp
SubAcct
Finan
ce systems
BalanceO
ther Financial Attributes
Product
Org
BOA
Account
CustGrp
SubAcct
•recon
ciliation is requ
ired for all Basel II Exposu
re Classes an
dExposu
re Types (drawn
, un
drawn
, other off-balan
ce sheet)
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
46SA
S Global Foru
m 2009
For what m
atters.
Recon
ciliation To Th
e Gen
eral Ledger
AccountingCode block
Credit R
isk data wareh
ouses
BalanceO
ther Risk D
ata Attributes
Product
Org
BOA
Account
CustGrp
SubAcct
Finan
ce systems
BalanceO
ther Financial Attributes
Product
Org
BOA
Account
CustGrp
SubAcct
•recon
ciliation is requ
ired for all Basel II Exposu
re Classes an
dExposu
re Types (drawn
, un
drawn
, other off-balan
ce sheet)
Ch
allenges:
•sou
rce systems are n
ot un
ique by B
asel II Exposure C
lass•
ensu
ring accu
rate booking of tran
sactions across m
ultiple source
systems
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
47SA
S Global Foru
m 2009
For what m
atters.
An
alysis and R
eporting
•m
ultiple bu
siness stakeh
olders have regu
latory and
man
agemen
t reporting n
eeds for credit risk data
•R
egulators requ
ire specific credit risk reports quarterly,
due 3
0 days after fiscal qu
arter-end:
•B
CA
R (B
asel II regulatory capital)
•N
CR
(new
credit risks)
•B
oard of Directors an
d senior m
anagem
ent oversigh
t
•Lin
e of Bu
siness A
nalysis of:
•exposu
res, risk calculation
s (e.g., EAD
, EL, RW
A, etc.)
•risk profiles -
OD
R/LG
D distribu
tions, etc.
•portfolio m
etrics –geograph
ic, indu
stry, etc.
•P
erforman
ce measu
remen
t of risk analytics m
odels forcon
tinu
ous im
provemen
t
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
48SA
S Global Foru
m 2009
For what m
atters.
SAS P
latform for R
etail Credit R
isk
staging areasB
usin
ess R
ules
Risk
An
alyticsM
odels
Party
Referen
ceD
ata
Credit
Application &
Adju
dication
Accou
nt
Man
agemen
t&
Mon
itoring
Transaction
Systems
External
Ratin
gs
Data Integration Layer (various ETL tools – push/pull)
Business Intelligence Layer
Reports
An
alytic Cu
bes / Marts
Direct
Feed toR
egulators
G/L
Balances &
Hierarch
ies
Oth
erA
pplications&
Models
RW
Acalcu
lationen
gines
SAS
DI S
tudio
SAS
Enterprise G
uide
SAS
Enterprise M
iner
SAS
Risk D
imen
sions
ILLUSTR
ATIV
E
Economic
Capital
calculation
engin
es
RETA
ILC
RED
ITR
ISK D
ATA
WA
REH
OU
SE
SAS
OLA
P
Studio
SAS
Enterprise G
uide
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
49SA
S Global Foru
m 2009
For what m
atters.
Sum
mary
•u
nder B
asel II AIR
B, a ban
k will be able to self-assess an
d report m
inim
um
regulatory capital for credit risk
•approval an
d ongoin
g complian
ce is dependen
t upon
banks
demon
strating th
e integrity of th
eir risk rating m
ethodologies
and data u
sed to calculate regu
latory capital
•sen
ior man
agemen
t has accou
ntability for establish
ing an
dm
onitorin
g the en
terprise-wide observan
ce of the risk data
man
agemen
t framew
ork
•th
e “payback on th
e Basel II in
vestmen
t”com
es from th
e u
se of the n
ew regu
latory capital inform
ation for bu
sinesses
to more effectively m
anage risk
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
50SA
S Global Foru
m 2009
For what m
atters. Wh
ile we are w
ell on ou
r way
at CIB
C, th
e journ
ey contin
ues…
Financial ServicesSAS Global Forum 2009
©CIBC 2009 All R
ights Reserved
51SA
S Global Foru
m 2009
For what m
atters. Than
k You
Than
k You
contact:
contact: rick.m
rick.miller@
cibc.ca
Financial ServicesSAS Global Forum 2009