Post on 03-Apr-2018
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Systemic estimation of PD, LGDand EAD for credit card as a
reserve requirement andvalidation method.
Mexican Experience
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Mexican Banking SystemThe Mexican banking system is concentrated in 7 banks that accumulate 87% of
the total loan portfolio and are mainly foreign owned (US, Spain, UK, Canada).
Jul-11 Aug-11 Jul-11 Aug-11 Jul-11 Aug-11 Jul-11 Aug-11
Banking System 2,271 2,298 2,510 2,542 12.53 12.32 16.39 16.21
BBVA Bancomer 581 588 620 634 20.65 19.95 15.58 15.51
Banamex 359 359 447 446 8.97 8.53 17.04 16.90
Banorte 271 275 288 282 14.59 14.23 15.94 15.67
Santander 297 301 316 338 15.77 15.61 14.81 14.24
Inbursa 153 155 123 120 8.48 8.21 24.82 23.21
HSBC 182 184 279 281 1.41 1.64 14.27 14.78
Scotiabank 114 115 121 121 10.20 10.04 16.60 16.43
Loan Portfolio Deposits
Balance sheet (Billions MXN)ROE (12m) (%) Capital Ratio (%)
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Mexican Banking SystemHowever the rate of deterioration of the credit card portfolio showed a
significant increase in 2009.
DelinquencyIndex (Past DueLoans / TotalBalance) of
consumer loansportfolio
Credit Cards
3.2%
9.8%
4.5%
2.7%
6.6%
1.4%0%1%2%3%4%5%
6%
7%8%9%
10%
Jan-05 Jan-06 Jan-07 Jan-08 Jan-09
ConsumerCredit
Other**
11%
Mortgage ConsumerCredit
CorporateCredit
Loan loss provisionAnnual Cash Flow
0
25,000
50,000
75,000
100,000
125,000
mar-06 sep-06 mar-07 sep-07 mar-08 sep-08 mar-090.0
1.0
2.0
3.0
4.0
5.0
** Includes Personal credit, leases, and other consumer credits
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Mexican Banking SystemThis deterioration was mostly explained by a systemic increase in household
indebtedness
Monthly Average Debt-Capacity per Debtor(Sample)
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
800,000
900,000
1 2 3 4 5 6 7 8
Number of Credit Cards
Available CreditLimit (left axis)
Dec. 2005 Nov 2007
MXN pesos
Number of debtors(right axis)
Credits per Person by Credit Type
3
3.2
3.4
3.6
3.8
4
4.2
4.4
D J F M A M J J A S O N D J F M A M J J A S O N
2005 2006 2007
1.00
1.05
1.10
1.15
1.20
1.25
1.30
1.35
1.40
Bank credit cards (left axis) Mortgage (right axis) Car (right axis)
Source: Credit bureau
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G20 and Basel recommendations on
loan loss provisionsIn April 2009 the G20 issued recommendations on financial supervision and regulation that led
the Basel committee to propose the following recommendations related to loan loss
provisions:
1. Loan loss provisioning should be robust and based on sound methodologies that
reflect expected credit losses in the banks existing loan portfolio over the life of
the portfolio.
2. The accounting model for provisioning should allow early identification andrecognition of losses by incorporating a broader range of available credit
information than presently included in the incurred loss model.
3. The new standard should utilize approaches that draw from relevant
information in banks internal risk management and capital adequacy systems
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IASB and Basel recommendations on
loan loss provisionsRecommendations were sent to IASB in order to promote the necessary coordination between
standard setters, supervisors and regulators on their respective efforts to implement the G20
recommendations.
Consequently IASB issued in November 2009 a proposal to modify loan loss provisionsaccounting.
Incurred loss model (current IASB standard)
Assumes that loans will be paid until evidence on the contrary is identified (loss event).
The financial crisis has evidenced that these models are characterized by evaluating
optimistically the loan portfolio and are suddenly followed by large credit losses.
Expected loss models (proposal adopted by Basel and IASB)
Losses are estimated on a forward looking basis according to the quality of theportfolios. It implies an approximation of the PD, LGD and EAD.
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Content
1. Introduction
2. Systemic estimation of PD, LGD and EAD
3. Risk Analysis of the Credit Card Loans Portfolio
4. Conclusions
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Incurred LossesUntil August 2009, Mexico had an incurred loss type regulatory provisioning
model. Provisions were created by applying fixed percentages to loans in
different levels of delinquency.
Number of delinquent
periods
% of Provisions
0 2.5%
1 19%
2 48%
3 58%
4 62%
5 85%
6 95%
7 100%
8 100%
9 or more 100%
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Incurred Losses12 month write offs were significantly higher than the balance of loan loss
provisions revealed on banks balance sheets.
Q y C / C V
1 2 M E S E S
0 %
2 0 0 %
4 0 0 %
6 0 0 %
8 0 0 %
E ne -0 6 A g o -0 6 A b r-0 7 D ic -0 7 A g o -0 8
Write offs (next 12 months) / loan loss provision balance
Jan-06
Credit card overall portfolio
1 Write Offs in the following 12 months,.
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Incurred LossesSome disadvantages of the Incurred Loss Model are:
Loans are provisioned when factual evidence is available that
a loan or portfolio of loans will not be repaid in full. (Laterecognition of losses)
Generate provisions for no concrete time horizon.
Show pro-cyclicality since they generate largest amount ofprovisions when there is evidence that loans will not be
repaid.
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Incurred LossesSome disadvantages of the Incurred Loss Model are (continued):
Do not generate provisions for loans with no delinquency
even though these loans have a positive expected loss.
They do not consider the potential growth of the exposure atthe time of default (relevant feature in revolving credit).
Similar financial assets in different entities may generate losscoverage for different periods of time.
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Expected LossesInternal Models are characterized for estimating the components of the
expected loss.
Expected losses standardize the time horizon and the default definition
for all institutions.
Expected Loss = PD * LGD * EAD
Where:PD = Probability of default
LGD= Loss given default
EAD = Exposure at default
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PD estimationA window of 25 months was established to carry out the analysis of the
behavior "profile" of each credit card.
Historical Period (T-12, T0).
Performance Period (T0, T12)
Reference Point = T0
t= -12 t= 0 t= +12
Historical Period Performance
Period
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PD estimation
Default is declared when a borrower attains a past due status on his
payment obligations of 90 days.
t= -12 t= 0 t= +12
Performance Period
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Sample for analysisA sample of loan-level data representing 97.3% of total credit card loans in thesystem was extracted from banks.
# Contratos % SistemaInformacin
Recabada
% Informacin
Recabada
% Sistema
Ajustado
Inbursa 712,034 2.03% 712,034 2.03% 2.09%
AMEX 1,025,869 2.93% 1,025,869 2.93% 3.01%Banorte 1,256,316 3.59% 1,256,316 3.59% 3.69%
Santander 3,448,425 9.85% 3,448,425 9.85% 10.13%
Banamex 8,971,960 25.63% 8,971,960 25.63% 26.34%
BBVA Bancomer\Finanzia 13,999,809 40.00% 13,999,809 40.00% 41.11%
GE Money 796,019 2.27% 796,019 2.27% 2.34%
Invex 853,343 2.44% 853,343 2.44% 2.51%
Scotiabank 790,995 2.26% 790,995 2.26% 2.32%
HSBC 2,201,229 6.29% 2,201,229 6.29% 6.46%
Otros 946,902 2.71% - - -
TOTAL 35,002,901 100.00% 34,055,999 97.29% 100.00%
The sample allowed a maximum error of 40 basis points on a PD estimation with (1- ) =
99% confidence.
( ) > 1 dppP
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DatabaseData were organized in 12 windows of information spanning 25 months ofpayment history.
WINDOW FROM TO
Apr05
May05
Jun05
Jul05
Aug05
Sep05
Oct05
Nov05
Dec05
Jan05
Feb06
Mar06
Apr06
May06
Jun06
Jul06
Aug06
Sep06
Oct06
Nov06
Dec06
Jan07
Feb07
Mar07
Apr07
May07
Jun07
Jul07
Aug07
Sep07
Oct07
Nov07
Dec07
Jan08
Feb08
Mar08
1 Apr 05 Apr 07 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
2 May 05 May 07 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
3 Jun 05 Jun 07 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
4 Jul 05 Jul 07 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
5 Aug 05 Aug 07 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
6 Sep 05 Sep 07 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
7 Oct 05 Oct 07 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
8 Nov 05 Nov 07 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
9 Dec 05 Dec 07 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
10 Jan 06 Jan 08 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 1211 Feb 06 Feb 08 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
12 Mar 06 Mar 08 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12
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DatabaseThree sources of information were used for the analysis.
DATABASE 2Credit BureauInformation
DATABASE 1Bank Information
DATABASE 3Social securityInformation
t= -12 t= 0 t= +12
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PD
BorrowerBehavior
Product Policy CreditBureau
t= -12 t= 0 t= +12
Social securityinformation
10 Variables 46 Variables 9 Variables 10 Variables
Examples:
- Minimum payment amount of
the last 12 months.
-Maximum credit limit in the last
12 months.
-Theoretical time that will take
to repay the balance according
to the minimum payment and
the interest rate of the product.
Examles:
- Average use of the credit limit in
the last 12 months.
-Percentage of payment over the
balance.
- Number of times that the
borrower paid the total balance.
- Number of non-payments in the
credit card.
Examples:
- Number of credit cards
opened in the period.- Record of payment in other
open accounts
- Number of credits that the
borrower has at the reference
point.
Examples:
-The borrower has formal or
informal employment
- The borrower has a mortgage
with the Social Housing
institute (INFONAVIT)
- Borrowers Income at the
reference point (measured in
minimum wage).
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PDFor the estimation of the systemic PD standard logistic regression was used tocorrelate the historical period constructed variables with the observation
period binary event of default.
)...(1 1101
1),...,(
nnxxn exx
++++
=
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Percentage of paymentAmount of payment made by the cardholder as a proportion of the outstandingbalance at the reference point.
Credit Card Portfolio
Interval PD
0% 26.00%
10% 20.94%
20% 16.65%
30% 13.10%
40% 10.21%
50% 7.90%
60% 6.07%
70% 4.65%
80% 3.55%
90% 2.70%
100% 2.05%
110% 1.55%
% PMT (T0)
% default
Ave 0.3695
Std Dev 0.4051
Max 1.1000Q75 0.7109
Median 0.1464Q25 0.0557
Min 0.0000
Frecuency %
Default
%PMT (T0)
0%
20%
40%
60%
80%
100%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
110%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
Pmt = Payment
Bal = Balance
0
0)(%0
T
T
Bal
PmtTPMT =
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Credit Limit ConsumptionOutstanding balance of the credit card as a percentage of the credit limitoffered by the bank to the client.
Sistema
Interval PD
0% 5.67%
10% 6.75%20% 8.02%
30% 9.51%
40% 11.24%
50% 13.24%
60% 15.53%
70% 18.13%
80% 21.06%
90% 24.33%
100% 27.92%
250% 86.38%
% USE (T0)
% default
Ave 0.4851
Std Dev 0.3976
Max 2.5000
Q75 0.8657Median 0.4124
Q25 0.0984
Min 0.0000
Frecuency %
Default
% USE (T0)
0%
20%
40%
60%
80%
100%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
250%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%35.0%
40.0%
45.0%
Credit Card Portfolio
Bal = Balance
0
0)0(%T
T
LimitCredit
BalTUSE =
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Current Non-Payment (ACT)Consecutive periods, in which the cardholder has not covered the paymentobligation.
Sistema
Interval PD
0 9.24%
1 30.49%
2 65.39%
3 89.06%
ACT% Default
Ave 0.2386Std Dev 0.6219
Max 3.0000Q75 0.0000
Median 0.0000Q25 0.0000
Min 0.0000
Frecuency %
Default
ACT
0%
20%
40%
60%
80%
100%
0 1 2 30.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
Credit Card Portfolio
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Historical Non-Payment (HIS)Number of periods in which the cardholder has not covered the minimumpayment in the last 6 months.
Sistema
Interval PD
0 6.60%1 14.31%
2 28.30%
3 48.26%
4 68.79%
5 83.89%
6 92.49%
HIS
% Default
Ave 0.7226Std Dev 1.1467
Max 6.0000Q75 1.0000
Median 0.0000Q25 0.0000Min 0.0000
Frecuency %
Default
HIS
0%
20%
40%
60%
80%
100%
0 1 2 3 4 5 6 0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
Credit Card Portfolio
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Type of EmploymentNon formal employment = 0
Formal employment (social security) = 1
Sistema
Interval PD
0 24.26%
1 10.77%
T_Employ
% Default
Ave 0.6227Std Dev 0.4847
Max 1.0000Q75 1.0000
Median 1.0000Q25 0.0000Min 0.0000
Frecuency %
Default
T_Employ
0%
20%
40%
60%
80%
100%
0 10.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
20.0%
Credit Card Portfolio
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Income LevelNumber of times the minimum wage
Sistema
Interval PD
0 40.03%
1 33.08%
2 26.79%3 21.32%
4 16.71%
5 12.93%
10 3.20%
15 0.73%
20 0.16%
25 0.04%
30 0.01%
35 0.00%
Income
% default
5.4320
7.3905
116.91007.7700
2.6100
0.0000
AveStd Dev
Max
Q75Median
Q25
Min 0.0000
Frecuenc
y %Default
Income
0%
20%
40%
60%
80%
100%
[0,5
)
[5,1
0]
>10 0.0%
2.0%
4.0%
6.0%
8.0%
10.0%12.0%
14.0%
16.0%
18.0%
20.0%
Credit Card Portfolio
0
0)(_ 0T
T
wageMinimum
IncomeTMWINCOME =
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Social Housing Institute BehaviorThe cardholder has (or does not have = 0) a Social Housing Institute mortgage.
Sistema
Interval PD
0 14.81%
1 17.25%
CREDIT (T0)
% Default
0.1510
0.3581
1.0000
0.0000
0.0000
0.0000
0.0000
Frecuency %
Default
CREDIT (T0)
0%
20%
40%
60%
80%
100%
0 10.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
Credit Card Portfolio
AveStd Dev
Max
Q75Median
Q25
Min
INFONAVIT is the Mexican Social Housing Institute (National Workers Housing Fund
Institute) that gives mortgage credits and deducts the monthly payment from the worker
salary.
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Maturity of the Credit Card in the Bank
Age of the credit card measured in months
Sistema
Interval PD
12 19.11%
24 16.87%
36 14.85%
48 13.03%
60 11.40%
72 9.95%
84 8.67%
96 7.54%
108 6.55%
120 5.68%
MAT (T0)
% Default
46.8745
64.1524
455.5333
48.7000
22.0000
10.80000.2667
Frecuency %
Default
MAT
0%
20%
40%
60%
80%
100%
12
24
36
48
60
72
84
96
108
120
>120 0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
Meses
Credit Card Portfolio
AveStd Dev
Max
Q75Median
Q25
Min
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Maturity in the Credit BureauAge on the credit bureau
Sistema
Interval PD
12 24.91%
24 22.96%
36 21.11%
48 19.38%
60 17.75%
72 16.24%
84 14.83%
96 13.52%
108 12.31%
120 11.20%
MAT_CB (T0)
% Default
91.2057
60.4804
455.5333
129.7333
81.8000
44.4000
0.9000
Frecuency %
Default
MAT_CB (T0)
0%
20%
40%
60%
80%
100%
12
24
36
48
60
72
84
96
1
08
1
20
>1
20
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
Meses
Credit Card Portfolio
Ave
Std DevMax
Q75
Median
Q25
Min
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Open AccountsNumber of existing credit cards at the reference point (Open credit cards, notclosed before the reference point).
Sistema
Interval PD0 13.61%
1 13.82%
2 14.03%
3 14.24%
4 14.46%
5 14.68%
6 14.91%
7 15.13%
8 15.36%
9 15.59%10 15.83%
ACCOUNTS TOT% Default
6.9802
5.057584.0000
9.00006.0000
3.0000
0.0000
Frecuency %
Default
ACCOUNTS_TOT
0%
20%
40%
60%
80%
100%
0 1 2 3 4
5ym
s 0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%45.0%
Credit Card Portfolio
AveStd Dev
Max
Q75Median
Q25
Min
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Delinquency in the Credit BureauIndicates if the cardholder presented in the previous 12 months delinquency onany other debt obligation different than the credit card.
Sistema
Interval PD
0 6.59%
1 24.89%
DELINQ_CB_HIST
% Default
0.4754
0.4994
1.0000
1.0000
0.00000.0000
0.0000
Frecuency %
Default
DELINQ_CB_HIST
0%
20%
40%
60%
80%
100%
0 1 0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
Credit Card Portfolio
AveStd Dev
Max
Q75Median
Q25
Min
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PDSelected Variables
The selected variables in the model are:
Current Non-Payment (ACT): Number of consecutive periods, up to the reference
point, in which the cardholder has not covered the minimum payment.
Historical Non-Payment (HIS): Number of periods in which the cardholder has not
covered the minimum payment in the last 6 months.
Percentage of payment (% PAY): Amount of payments made by the cardholder
over the total balance at the reference point.
Credit Limit Use (% USE): Percentage that represents the total balance from the
credit limit at the reference point.
Maturity (MAT): Number of months elapsed since the opening of the credit card
to the reference point.
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Average Cardholder
The average cardholder of the Credit Card Loans Portfolio has the followingvalue for each selected variable in the model.
Credit CardPortfolio
Actual Non-Payment (ACT) 0.24
Historical Non-Payment (HIS) 0.72
Maturity (MAT) 46.87
Percentage of payment (%PAY) 36.95%
Credit Limit Use (%USE) 48.51%
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PD
Final Estimation of PD
Receiver operating characteristic ROC = 86%
Estimator Description Value
Constant -2.9704
C1 ACT +0.6730
C2 HIS +0.4696
C3 MAT -0.0075
C4 % PAY -1.0217
C5 % USE +1.1513
INCUMP_90D_4 / Coeficientes estandarizados(Int. de conf. 95%)
MORAMIN_SA
MORAMIN_HIS
ANTIG_T0 PJE_PAGO_T0
PUSO_LINEA_T0
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
Variable
Coeficientes
estandarizados
)*1513.1*0217.1*0075.0*4696.0*6730.09704.2( 54321
1
1CCCCC
e
++++
=)
Standardized Coefficients
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Parameters Estimation
Loss GivenDefault
(LGD)
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LGD
3 months
Frequency of Classes
The Loss Given Default was established at 81%.
% Payment % ClassAverage
Payment% Recovery
3 months
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Estimation of Parameters
Exposure atDefault
(EAD)
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EAD
Credit limit use at the time of analysis (horizontal axis) and the final exposure atthe time of default (vertical axis)
0%
500%
1000%
1500%
2000%
2500%
3000%
0% 50% 100% 150% 200% 250% 300%
PUSO_LINEA_T0
F
actor=EAD/Saldo_
T0
Exposureatdefault/
balancetoday
%USE: Percentage that represents
the balance at the reference point
from the credit limit.
Factor: Exposure at the date of
default over the balance at the
reference point.
Balance_T0: Balance at the point of
analysis (date of reference).
%USE = Balance today / Credit Limit
%USE is the same variable used to estimate PD
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EAD
An EAD adjustment factor is deducted from data.
Factor
0% 5% 845%
5% 10% 447%
10% 15% 333%
15% 20% 274%
20% 25% 237%
25% 30% 211%
30% 35% 192%
35% 40% 176%
40% 45% 164%
45% 50% 154%
50% 55% 145%
55% 60% 138%
60% 65% 131%
65% 70% 126%
70% 75% 120%75% 80% 116%
80% 85% 112%
85% 90% 108%
90% 95% 105%
95% 100% 101%
100% 105% 100%
105% 110% 100%
110% 115% 100%
115% 120% 100%
%USE
EAD = Balance_T0* Factor
0%
100%
200%
300%
400%500%
600%
700%
800%
900%
1000%
0% 20% 40% 60% 80% 100% 120% 140%
% USE
Fac
tor
{ }%100,*0_ 5784.05CMaxTBalance
C5 = Credit Limit Use (Balance_T0 / Credit Limit) at the reference point.
%USE is the same variable used to estimate PD
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Final Proposal
Current regulation for credit card reserve. Entered into effect september 2009
Credit Card Provisionsi = PDi * LGD * EADi
Where:
=
+< +++
%1004
1
14
1
)5*1513.14*0217.13*0075.02*4696.01*6730.09704.2(1
CSi
eCSi CCCCC
PD
C1 = Number of consecutive periods in which the cardholder didnt cover the minimum payment at the reference point
C2 = Number of periods in which the cardholder did not cover the minimum payment in the last 6 months
C3 = Maturity of the credit card in the Institution at the reference point (months)
C4 = Amount of payment made by the cardholder over the outstanding balance at the reference point
C5 = Percentage of the outstanding balance at the reference point over the credit limit.
%75=LGD
{ }%100,*0_ 5784.05 CMaxTBalanceEAD =
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Content
1. Introduction
2. Provisions Based on Expected Loss for a Revolving Credit Portfolio
3. Risk Analysis of the Credit Card Loans Portfolio
4. Conclusions
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Credit Card Loans Portfolio
Interest SpreadThe formula allowed for loan level expected loss estimation. Expected loss iscompared to interest rate.
5%
10%
15%
20%
25%
30%
35%
40%
Sep-05 Dec-05 Mar-06 Jun-06 Sep-06 Dec-06 Mar-07 Jun-07 Sep-07 De-07 Mar-08
Expected Losses Spread
Expected Losses were estimated for the Mexican credit card loans portfolio using the presented model for provisions.
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Spreads vs Expected LossesBased on the risk-return relationship found for each bank, 4 types of
institutions were identified.
0%
10%
20%
30%
40%
50%
60%
0% 10% 20% 30% 40% 50% 60%
Spread
WELL
ESTABLISHED
MULTISEGMENT(low & high
incokme)
COMPETE IN NEW SECTOR
PRICECOMPETITION
InsufficientPrice
Over-Priced
Expected Losses
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Maturity and Expected LossesMore recent clients to the financial sector are riskier.
The size of thecircle indicates theexpected loss
EL %
0
20
40
60
80
100
120
0 20 40 60 80 100 120Maturity in the Financial System (Credit Bureau first record) (months)
Average
MaturityintheBank
(months)
LOYAL CREDITCARDHOLDERS
HIGHCOMPETITION
PRICECOMPETITIONOLD USERS
CLIENTS THAT HAVENEVER HAD ACREDIT CARDBEFORE
1/ Expected Loss is the average of the expected losses for the period between April 2006 and March 2007
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IRB model validation
PD CNBV vs PD Bank X
Modelo PD CNBV
IRB
PD CNBV vs PD BankY
PD Model IRB
PD CNBV
Observed default rate
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Interest rate differentation according to riskcharacteristics of clients
*/ Ex-post (in the next 12 months after the horizontal axis computation)
Outstanding balance / Credit limit
Payment / outstanding balance
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PD Through the Cycle vs PD Point in Time
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Content
1. Introduction
2. Provisions Based on Expected Loss for a Revolving Credit Portfolio
3. Risk Analysis of the Credit Card Loans Portfolio
4. Conclusions
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Credit Card Loans PortfolioThe impact in the system was significant (average 2.14 times the previous
requirement).
0%
10%
20%
30%
40%
50%
60%
70%
BANK 1 BANK 2 BANK 3 BANK 4 BANK 5 BANK 6 BANK 7 BAN K 8 BANK 9 BANK 10 SISTEMA
Incurred Loss Expected Loss
Institution
Expected Loss
vs Incurred
Loss
BANK 1 2.13x
BANK 2 1.8x
BANK 3 1.75x
BANK 4 2.14x
BANK 5 2.61x
BANK 6 2.53x
BANK 7 2.26x
BANK 8 3.25x
BANK 9 1.56x
BANK 10 2.02x
PORTFOLIO 2.14x
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Capital Requirement and ProvisionsCredit Card Portfolio
Basel I & incurred lossprotection
Expected Loss
18.4%
BIS II (1-k=0.001)36.5%
Provisions (Incurred Loss)9.3%
BIS I (1-k=0.6487)17.3%
9.3%
18.12 %
% portfolio
FREC
UENCY
18.4%
36.5%
17.3%
8.%
Basel II & expectedloss protection
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Individual bank estimation
Best bank
Expected loss13.70%
BIS II (1-k=0.001)27.49 %
Reserves8.10%
BIS I (1-k=0.6689)16.10%
8% cartera
13.79% cartera
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Individual bank estimation
Worst bank
Expected loss30.21%
BIS II (1-k=0.001)54.11%
Reserves15.84%
BIS I (1-k=0.6689)23.84%
8% cartera
23.90% cartera
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Systemic PD, EAD, LGD as validationmethod
In Mexico no bank had an internal model before the introduction of this rule
because the incentive of capital reduction was the opposite.
This method does not intend to substitute internal models. On the contrary it seeks
to incentivize its use and development by setting a comparable standard as the
standard method of reserves.
One bank has certified its internal model in parallel with the introduction of this
rule. Loan level comparisons were done and general parameters compared for
sample portfolio. Differences in parameters were modest and subject to
explanation.
This approach allows a rich validation process as specific differences on PD
estimation can be explained by bank specific policies which are made evident by
comparing parameter estimates.
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Conclusions
The National Banking and Securities Commission (CNBV) is gradually changing theregulation from an incurred loss to an expected loss provisioning scheme
The first portfolio that changed was the revolving consumer loans (credit cards)
which is now being provisioned with the presented expected loss model. In March
2011 mortgage and personal loans were introduced. September 2011 saw the stateand municipalities reserve rule change and december 2011 is the objective date for
corporate and SMEs loans (D&B score).
The objectives of these reforms are to recognize losses in a timely manner, to
assure that provisions cover losses for a 12 month horizon, to apply international
standards and encourage banks to use more information in the process.
This type of models also represent an incentive for the banks to develop their
internal rating models for provisioning and capital assessment.
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Systemic estimation of PD, LGD
and EAD for credit card as areserve requirement and
validation method.
Mexican Experience