Eric on chinese banks value creation analysis

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Chinese Banking Industry
Value Creation Study Who create shareholder
value ? Who destroy?

Eric Kuo

Shanghai, Oct 2013

1

This study selects 18 representable Chinese banks, leveraging
their year 2012 annual reports, conducting value creation analysis
to understand whether if banks' lending portfolio create value to
shareholders and concluded the following :
• The credit portfolio of 18 representable Chinese banks has an average 18.43% of RAROC that is higher
than 15% of market hurdle rate, therefore generated economic profit to shareholders.
• The first observation: larger loan size doesn't necessary generate more Economic Profit. One mega
bank one, national joint stock banks and two regional banks in this survey do not generate value to their
shareholders.
• Second observation: larger bank capital doesn’t necessary generate higher return (RAROC). Analysis
shows that higher bank capital usually has lower return
• The third observation: the source of value creation comes form proper pricing. Several banks are able to
charge higher rate therefore create more economic profit than his peers .

1

Value based
analysis

2

Portfolio
• Further, this study dig into banks' portfolio by industry and product and found that most industries /
analysis &
products do generate EP to banks, except eight industries/ products are not profitable. Especially,
Optimization
manufacturing and wholesaling industry are two main value destroyers.
• Most of non-profitable industries were miss priced, this suggests Chinese banks needs to enhance their
pricing mechanism.

3

Stress testing
/
Concentration
analysis

• This study performed stress testing in an event of banking portfolio default risk increased by 20% and
concluded that
− The average banking CAR ratio will be reduced 6-7%
− ROE will decreased by 6-8%
− Generally speaking only national wide joint stock banks will remain profitable
• In an extreme scenario, the current bank accumulated loan loss provision can stand up to 1 in 50 event .
• Taking the banks' 2012 net profit into account, Chinese banks can sustain in a 1 in 300 event
• This study found that most of Chinese banks encounter industry concentration risk, especially mega
banks.
• Wholesaling and manufacturing industries are two major sources of concentration risk for Chinese
banks, these two industries accounted for significant size of bank loan portfolio. Moreover, both
industries have higher default risk than others and banks were not making profit from it.
Eric on Chinese Banks Value Creation Analysis-en.pptx

2

Eric Kuo

Education

Professional experience

Past Presentation

Structured Finance Program
Certification, University of
California Irvine

Since Nov
2013

- Director

• Credit
portfolio
management
customer segmentation;

2003-2004

MBA , University of Southern
California

2012-Oct
2013

Roland Berger Strategy
Consultants
- Sr. Project Manager

• Value creation through risk management
and how bank prepare for the interest
rate liberalization;

1994-1996

MS in Finance, National
Central University; TW

2010-2011

• Experience sharing on bank process
reengineering; ZheJiang CBRC

1989-1994

BA in Japanese Study,
Chinese Culture University;
TW

2009

Asia-Pacific risk strategy,
HSBC, Hong Kong
- Senior Manager
Deloitte Consulting, Beijing
- Project Manager

2006

1999-2008

Chinatrust Commercial Bank,
Taiwan
- Credit Portfolio Manager
- Strategic Planning Manager

1998-1999

CosmosCommercial Bank,
Taiwan
- Product Manager

1996-1998

Military Service, Taiwan
- Army Deputy Commander

and

• Enterprise risk management
• Concentration risk management; Taiwan
FSA and Banking CEOs meeting
• Economic capital applications and
challenges; ABA /APEC/ABAC – Public
and private dialogue
• Practitioners panel for CPM experience
sharing; IACPM seminar
• Sound
practice
of
credit
risk
management; Vietnamese regulator and
financial institution visit


3

Agenda

1
Portfolio analysis & optimization under limited capital
2
Stress testing
3
Who create Value?

Appendix

A Why Risk Adjusted Performance
B Why IRB approach

4

1

Who create Value?


5

1

Who create Value?

This study selects 18 Chinese banks, based on their 2012 annual
reports, trying to understand if Chinese banks' lending portfolio
generate Risk Adjusted Value to shareholders

5

Mega Banks

7

National-wide
Joint-stock Banks

6

Regional
Joint-stock Banks

Who creates shareholder value? Who destroys shareholder values?


6

1

Who create Value?

The lending portfolio of these Chinese banks amounted for 42
trillion RMB and the lending portfolio has generated an estimated
18.43% of RAROC, contributing 144 billion of Economic Profit1)

Basic Information [100 Mn RMB]

Market Value2)

NPL

1,440

57,890

Loan portfolio

Net Fee Income
Associated with Loan

[100 Mn RMB]

20.91

ROE3)

51,991

Equity

Value created by lending portfolio
[%]

62,651

Net Capital

Net Interest Income

Avg. ROE,CAR, NPL[%]

427,152

13.21

CAR

18.43

14,512
4,851

NPL

0.95

RAROC4)

4,044

Economic
Profit
(Value
Creation) 5)

1) Economic Profit also known as Economic Value Added
2) Data source Wind database st the end of 2012
3) ROE (Net Profit Excl. Extraordinary) (Average Weighted)
4) The RAROC estimation Included fee that related loan
5) EP is estimated by subtracting the expected loss, capital cost and operating cost related to lending from total lending net revenue

7

1

Support

This study utilizes two measures to estimate value creation :
RAROC and EP
Value Based Measures
RAROC[Risk Adjusted Return on Capital]
Loan Interest Income

EP [Economic Profit]

100

FTP

50

Fee Income associated with
Loan

35

Operating cost1)

20

Expected Loss2)

20

Risk Adjusted Profit

45

Loan Interest Income

Credit Capital

300

RAROC [%]

This
study
estimat
ed
FIRB
credit
capital

Credit
Capital=
Credit
RWA *
target CAR
Ratio

100

FTP
Fee Income associated with
Loan

20

Expected Loss

20

Risk Adjusted Profit

15%

35

Operating cost

Using 15%
as Hurdle
rate

50

45

Credit Capital

Hurdle Rate

45

[$]

0

RAROC >=Hurdle Ratest EP >= 0
1) Operating cost only counts the cost related to leading
2) This study is using non performing loan as substitute of expected loss due to data limitation

8

Support

1

The hurdle rate is estimating based on CAPM theory and it is
around 15% for Chinese banking industry
Hurdle Rate Estimation

Relationship between SH Index & FS index
160

R2 91%
y = 1.29x + 0.0357

High

140

Cost of
equity = Risk free rate +

*

Market
excess premium

20
FS
Index
return

=

=

0

-20
(YoY,%
)
-40
-60

Low

1 Year
deposit
rate
3.5%
15%

+

*

(

Avg Stock Return

-

1Year Deposit

)

+ 1.29 * (13%-3.5%)
Hurdle
rate

-80
-80

Low

-60 -40

-20

0

80

100 120 140

SH Stock IndexReturn(YoY, %)

• This study select indices since year 2001 for
estimating hurdle rate of China financial service
industry. and the first step is to calculate the beta
based on CAPM theory
• The result shows strong relationship between SH
index and FS index (R square is above 91%)

High

• The long term hurdle rate for China financial service
industry is around 15% and this study uses it as
benchmarking as minimum return on capital and for the
economic profit estimation.
• In CAPM theory, the WACC ( can be used as minimum
return on capital) requires to gauge the cost of debt, we
have to skip this process due to lack of information.

9

Who create Value?

1

The first observation: larger loan size doesn't necessary generate
more Economic Profit. One mega bank, one national banks and
two regional banks do not generate EP to their shareholders
Bank lending size v.s Economic
Profit Margin per dollar of lending
High

3.5

Bank
Economic
Profit
margin comparison [%]

Mega
Bank

Value
1.5
creation
/

1.0
Avg EP
margin
Nation
=0.34%

Economic
0.5
Profit
Margin
0.0
Per
2)
lending
-0.5
[%]

alwide

-1.0

Low

Regio
nal

Value
destroyer

-1.5
0

Low

10,000 20,000 30,000 70,000 80,000 90,000
Lending Size1)[100Mn RMB]

• This analysis uses EP margin to
gauge the value creation
• As shown in the left had side
-0.94 0.9
graph we can observe that most
0.23
of the banks do create
economic profit to their
shareholders except for four
banks (1 mega bank, 1 national-1.03 1.79
wide and 2 regional joint stock
0.74
banks)destroy shareholder
value.
• In addition, some of joint stock
banks have higher EP margin
3.1 than mega banks, and this
-0.88
stands for that the larger size of
0.17
bank's lending portfolio doesn’t
necessary generate more value
to shareholders.
• Further, in the right hand side
0.34
chart depict that average
speaking that natoinal-wide joint
Regional
stock banks have highest EP
Joint-stock Banks
margin.

Min

Value
creator

High

Comments

Max

Mega bank
National-wide Joint Stock Bank( Large Joint Stock Bank)
1) Bank lending size includes corporate & retail lending
2) Economic Profit margin or EP margin: represents how much value, EP can be generated per dollar of lending.
The profit side also take into account of cross selling stem from lending activity;
The capital is using FIRB approach that calculated by this study based on assumptions.

10

Who create Value?

1

Positive correlation between net revenue and bank loan size, but
low relationship between loan size and economic profit
Mega bank

National-wide JS bank

Regional JS bank

Bank Economic Profit v.s Bank loan size

Bank revenue v.s Bank loan size

500

High 4,200

High
250

Net

2,800

150

NII +
Fee
[100Mn
RMB]

Value
These two mega
banks demonstrate creator
that higher EP
contribution relative
low loan size
Negative
EP, large
loan size

Economic 100
Profit (EP)
50
[100Mn
RMB]
0

800
600
400

Most of nationalwide JS banks
have similar loan
size but EP varies

-50
200

Low

0
0

Low

10,000 20,000 30,000 70,000 80,000 90,000
LoanSize1)[100Mn RMB]
High

• Although linier relationship between bank net
revenue and loan size can be found …

Low

-650
0

Low

Value
destroyer

20,000 40,000 60,000 80,000 100,000
Loan Size1)[100Mn RMB]
High

• ..however, this linier correlation rule doesn’t
apply to EP and loan size


11

Who create Value?

1

Second observation: higher bank capital doesn’t necessary
generate higher return (RAROC), study shows that higher bank
capital usually has lower return
Mega

50

High 50

High Return
on Capital

30
Avg.RA
ROC=

RAROC20

18.4%

15

5

RAROC20
[%]
15

0

Low

1,000

2,000

7,000

8,000

FIRB Credit Capital[100Mn RMB]

Hurdle
rate=

10

15%

5

Low Return
on Capital

0

•

25

Hurdle
rate3)=
15%

10

Low

High return
low capital
usage

Avg. Capital ratio=9.8%
High return
high capital
usage

30

25

[%]

Regional JS bank

RAROC & Credit Capital usage per
dollar of loan

RAROC & Credit Capital usage
High

National JS bank

Low

9,000

Low
•
•

1) Hiher risk requires more capital under Basel 3 IRB approach, therefore this study
uses FIRB to gauge capital

0

8.0

High

Mega banks generally have higher bank capital, but it doesn’t
necessary generate higher return on capital compare to his peer
joint stock banks

Low return high
capital usage

8.5
9.0
9.5
10.0
10.5
Credit capital per dolar of loan[%]

11.0

High

Furthermore, we found that mega banks have higher credit capital
requirements per dollar of lending and it means that lending
business in mega banks have higher risk
For the value destroyers that have negative EP, their loan portfolio
not only attract more capital but also not compensate by return (Low
return high capital usage quadrant)

12

1

Who create Value?

The third observation: the source of value creation comes form
proper pricing. Several banks are able to charge higher rate
therefore create more economic profit than his peers .
Economic Profit margin analysis[%]
One of the Mega banks

One of national Join stock banks

High value creator

Higher loan pricing
created value

3.84

Value created by
fee income

4.10

1.36

2.03
0.92 1.56

0.84 0.90

0.76

1.50 0.06
NII

Op
Cost

EL Profit Cap Loan Fee Total
EP
Cost EP

One of the Mega banks

-0.08
NII

Op
Cost

No value creator

Under priced

2.06
1.33

1.48
-0.45 1.64

-0.50 1.48

-0.94
-2.10 1.16

Op
Cost

Cost EP
EP

3.05

2.26

NII

1.39

One of national Join stock banks

Under priced

3.14

1.87 1.79

1.31

Cost EP
EP

-1.03
-1.98 0.95

NII

Op
Cost

1) Due to lack of expected loss (EL) information, this study uses NPL as a proxy and EL
should be reflected on customer pricing.

Cost EP
EP

Comments
• Value creation in
banking comes
from either net
interest income or
fee income, banks
should either
charge higher loan
pricing to
compensate the
risk taking or
compensate the
risk at a
comprehensive
manner.
• The value
destroyers simply
under priced the
risk they were
taking.


13

1

Who create Value?

Overall speaking, different types of Chinese banks have their own
advantages and also face different challenges
Economic Profit margin analysis[%]
Mega Banks

1.01

EL

Fee
Total EP

1.20

1.44
-0.35

0.97
0.23

1.09

1.33
-0.25

-0.97

0.76

1.08

1.52

Cap Cost

1.74

0.75

0.55

Profit

3.59

1.71

1.79

Op Cost

Regional Joint
Stock Bnaks
3.53

3.34

NII

Loan EP

National Joint
Stock Banks

0.52
0.71

0.17

Leading practice
Lag practice
Comments
• Mega banks, in general, have
put significant efforts on the fee
income products to compensate
their lending business and this
is the source of value being
created from. More value can be
added if mega banks can further
control their credit related
operational cost and asset
quality.
• National joint stock banks play a
role model in cost control and
asset quality selection,
combining with their fee income
business that contributed to
highest EP among three types
of Chinese banks
• Regional joint stock banks have
a outstanding loan pricing that
reveal their local bank's
advantage, on the other hand,
regional banks require to invest
more in their product innovation
and services to attract fee
income.

1) This study uses margin to eliminate the bank loan size effect and for compraison. All figures above are divided by corresponding loan size.
2) Capital cost stands for credit risk capital requirement multiple by hurdle rate

14

1

Support

Value based metric provides banker a breakeven price to create
shareholder value
Value Based Pricing1)
Breakeven Pricing

Explanation

Operational cost

0.1%

2

Expect loss

0.5%

• Several ways to estimate the cost:
1. Leverage ABC Active based costing
2. Previous average cost of particular customer
3. Benchmarking by use average cost

2

• Basel II PD*LGD
• Average loss rate by collateral
• Average loss rate in a particular rating grade
• Cost of capital=capital usage* hurdle rate
• Capital can be economic capital or based on Basel
requirement
• For banks not yet implement Basel, can leverage their
exist rating system and apply a PD and then estimate the
capital based on Basel's capital formula

4

• FTP= internal fund transfer pricing

0.4%

Cost before Capital
cost

1

3

1

3

Capital cost
Required breakeven
margin for lending

4

FTP
Required lending
interest rate

1%
1.5%
5%
6.5%

1) Value based pricing also can be considered as risk based pricing

15

1

Support

The term "pricing" in this study represents the margin or spread
above FTP
Pricing calculation process
Value (risk)based pricing1)

Actual (comprehensive ) pricing 2)
FTP

FTP + 2.6%

FTP + 2.2%
FTP + 0.8%
FTP + 0.1%
FTP + 0.2%

0.8%
1.2%

FTP + 1.2%
Margin

0.7%

FTP
Risk cost Operating
cost

Capital
cost

FTP

Value
Lending Guarantee
Fee
Deposit
Actual
based
Pricing
pricing
• Value/ risk based pricing takes into risk cost, operational cost and capital cost consideration, that is useful for bankers
to understand the breakeven before adding FTP and therefore bankers can price to customer in accordance with
Explanation
client relationship
• Comprehensive pricing is the spread/ margin after FTP, that banks can compare with risk based pricing to see if
relationship manager follow the pricing mechanism
1) The spread in this study is backward estimation by dividing loan size.
e.g. Fee spread =net fee income/ lending size


16

1

Who create Value?

Most of mega banks generate economic value to shareholders
except for one bank
Leading practice

Pricing analysis[%]
Margin

Negative
EP margin
(Value
destroy)

6%

5%

4%

3%

Breakeven pricing

1

2

0.56%

4.81%

0.31%

4.32%

0.54%

1.33% 2.27% 1.64% 5.24% 4.31%

-0.94%

4.07%

1.48%

2.05% 1.46% 4.50%
0.99%

Contribution of
fee income

Capital
cost

Op
Cost

1%

3

EL

2

3

4

5

1.52% 3.78%
0.95% 1.31%

4
5

1

4.62%

1.74%
0.85%

2%

0%

Total net EP
margin1) margin

Breakeven pricing

Total margin
Positive (Loan +Fee)
EP
margin
(Value
creation)

Loan actual
margin

Lag practice

1.51% 3.78%

4.68%

0.9%

0.92% 1.35%
Expected loss

Op Cost

Cap Cost

• Value/ risk based pricing takes into risk cost, operational cost and capital cost consideration, that is useful for bankers
to understand the breakeven before adding FTP and therefore bankers can price to customer in accordance with
Explanation
client relationship
• Comprehensive pricing is the spread/ margin after FTP, that banks can compare with risk based pricing to see if
relationship manager follow the pricing mechanism
1) Total net margin=lending margin + Fee margin

17

1

Who create Value?

Some national joint stock banks are focusing more on the fee
based products / services and has higher EP margin than his peers
Leading practice
Pricing analysis[%]

Breakeven pricing

Total net EP
margin
margin

Negative

Margin

Breakeven EP margin
(Value
pricing

6%

5%

Lag practice

1

destroy)
Total margin
(Loan +Fee)

Highest fee
income
contribution

4%

0.92%

4.07%

0.31%

3.93%

0.97%

5.98%

1.79%

4.27%

0.9%

4.24%

0.07%

4.0%

-1.03%

0.61%

2
Capital
cost

4.9%

2.14% 1.23% 3.98%
1.32
3.76%
1.32%

1.69%
0.74%

3

1.24% 2.96%
0.58% 1.14%

Loan margin

4

Generate positive
loan EP margin

3%

Op
Cost

2.03% 1.39% 4.18%
0.76%
1.36% 3.37%

5

2%

0.74% 1.27%

6

0.95%

1%
EL

0%

1
Explanation

2

3

4

5

6

7

7

4.17%

1.67%
1.55%

1.48% 2.06% 1.48% 5.03%
Expected loss

Op Cost

Cap Cost

• Different banks have their own strategy, some banks focus on operating cost control, some are focusing on charging
the right lending price and some choose on fee income generation


18

1

Who create Value?

Regional banks rely on higher loan margin as source of value
creation. Fee based income is still tiny
Leading practice
Pricing analysis[%]

Breakeven pricing

Lag practice
Total net EP
margin
margin

Margin
1

8%

6%

2

Negative
EP margin
(Value
destroy)

Generate
positive loan
EP margin

5%

3.54%

0.16%

6.1%

1.31%

7.63%

3.1%

3.94%

-0.58%

3.66%

-0.88%

4.1%

0.84%

0.59% 1.34%

thin fee income
contribution

7%

3.37%

1.44%

Breakeven
pricing

Total margin

3

2.30% 1.43% 4.53%
0.80%

4

4% (Loan +Fee)

0.90% 2.30% 1.59% 4.79%

1.88% 1.63% 4.52%
1.01%

3%

Capital
cost

2%
1%
0%
Explanation

5

Op
Cost

Loan margin

6

EL

1

2

3

4

5

6

2.17% 1.53% 4.54%
0.83%

1.49%

3.27%

0.58% 1.21%
Expected loss

Op Cost

Cap Cost

• Half of regional banks were able to charge their loan price above the breakeven pricing that demonstrates these
banks have more bargaining power while faced the competition of mega banks and national banks.


19

1

Who create Value?

In sum, the source of value creation are pricing and cost control.
Value creators have higher pricing, better internal operational cost
control and asset quality.
2012 Chinese Banking Economic Profit Tree[%]

3.45%

3.15%

3.40%

1.14%

1.11%

1.14%

2.23%

1.77%

NII
(Lending margin)
Risk adjusted profit margin
2.05%

1.81%

Fee

0.70%
Value
creation
(Positive
EP)

EP margin

0.61%

Value
Banking
destor
average
(Negative
EP)

1.68%

Operating cost

0.87%

0.34%

Capital cost rate
Value
destor
(Negative
EP)

0.95%

Expected loss
91.65%

-0.93%
Value
creation
(Positive
EP)

1.32%

Banking
average

1.44%

Value
creation
(Positive
EP)

1.63%

1.48%

Value
Banking
destor
average
(Negative
EP)

Credit risk

103.38%

93.72%

Value
creation
(Positive
EP)

Value
destor
(Negative
EP)

Banking
average

weigh)

10.5% of CAR
15% of hurdle rate

•The core to value generation is the pricing, this includes net interest income and fee based product. Bankers can yield
Explanation lending and gain from fee based products, as long as bankers stick to value/risk based pricing
•On the cost side, we found value creation group has better operating cost control and better asset quality that differentiate
themselves than the value destroy group

20

2

Portfolio analysis & optimization under limited
capital


21

Portfolio analysis

2

We dig into banks' portfolio and found that most industries /
products do generate EP to banks, except eight industries/
products cannot generate economic profit
RAROC analysis by industry[%]
Avg.
RAROC=18.4%

200%
152%

RAROC lower than

119%
15% of hurdle rate
53% 48% 42%
33%
26%
24%
40% 34%
17%
32% 26%
13%
25% 24%
23%
17% 14%
12% 10% 7% 6%
3% 1%

Economic profit analysis by industry / products[100Mn RMB]
487
305

295
54

58 40

3

Negative EP

589
297

187
7

389
134

23 100

184
3

25
-8

-7 -47

0 -10

-4

-595
-1,069

Comments

Tourism

Wholesaling

Manufacturing

Computer

Post & Telecom

Others

Credit card

Off shore

Trading

Accommodation

Electronics

Constructure

Education

Transportation

Leasing

Real estate

Mortgage

Personal lending

Mining

Engery

Service

Public infrastructure

Environmental

Agriculture

Financial Service

Guarantee

• Most banks provide portfolio
breakdown and this study
further diagnose portfolio
performance and concludes:
1. Most industries / products
do generate EP
2. Among products,
Guarantee has highest
RAROC
3. Mortgage, personal
lending product
contributed highest EP to
the banks, benefiting to
low capital requirement1)
and low historic loss
4. Manufacturing &
wholesaling industry were
two value destructors,
both of them destroy
shareholder value by
166.4 Bn RMB
5. This study didn’t find
credit card create value

1) Retail products general has lower capital requirement under Basel Accord and even PD, LGD, EAD are all identical,
corporate lending attracts higher capital
;

22

Portfolio analysis

2

The reason of not be able to contribute EP is "miss-priced".
The revenue (or price) generated from these industries lower than
their required breakeven price…
Pricing analysis [%]

Actual pricing

Value/ risk based pricing (Breakeven price)

6.32
5.93
5.18

5.30

5.06
4.71 4.61 4.64

4.53 4.57

3.67
4.55

4.05

2.91
2.54 2.58
1.92 2.06

3.33

3.18

4.31

4.53 4.55

3.62

4.36 4.47

4.69

4.98 4.80
4.68

4.23

4.65
4.30

5.81
5.22

4.50 4.38

3.75

3.53 3.71

3.54 3.34 3.59

3.54

4.46

5.40

3.15

3.23

3.26

3.26

2.32

1.73

Tourism

Wholesaling

Manufacturing

Computer

Post & Telecom

Others

Credit card

Off shore

Trading

Accommodation

Electronics

Constructure

Education

Transportation

Leasing

Real estate

Mortgage

Personal lending

Mining

Engery

Service


Environmental

Agriculture

Financial Service

Guarantee

Comments

• The white bar stands for the net revenue generated from industry and the light blue bar represents the breakeven price.
• The unprofitable industries/ products were under priced and not meeting breakeven price requirement therefore, destroy
shareholder value.
• For example, manufacturing industry has an average price of 4.5% per dollar of loan, however, to generate EP in this industry
banks need to charge above 5.81%

Note : The actual price listed above includes NII and Fee income and divided by its corresponding loan
amount,in order to gauge the revenue generation per dollar of lending.


23

2

Portfolio analysis

…and these industries have higher NPL that requires more capital
and therefore need higher price to compensate the risk
NPL

FIRB Risk Weight

NPL(%)

Credit Risk Weight (%)

2.5

160
140

2.0

120

RW=94%

100

1.5

80

1.0

60
40

0.5

20

0.0

0

Tourism

Wholesaling

Manufacturing

Computer

Post & Telecom

Others

Credit card

Off shore

Trading

Accommodation

Electronics

Constructure

Education

Transportation

Leasing

Real estate

Mortgage

Personal lending

Mining

Engery

Service


Environmental

Agriculture

Financial Service

Guarantee

Comments

• In our estimation, the average FIRB based risk wegiht is around 94%, that means that 100 dollars of lending equals to
94 dollars of risk weighted asset. Generally speaking, higher NPL requires more Risk weight as shown in the graph.
• For those industries/products who have lower than 15% of RAROC reveal higher NPL and thus higher risk weight than
average.
• Therefore, the core reason of why these industries do not profitable is still pricing, banks in this study, in general, do not
price at risk or price at value

24

2

Portfolio analysis

We found some banks created EP in these non-profitable
industries through price differentiation.
Loan margin

Economic profit margin benchmarking by non profitable industry
Total net margin ( %)

EP Margin ( %)
Non-profitable industry
average EP margin
Off shore
Credit card

Highest EP mergin
among banks

-0.08
-0.12

1.13

-0.50

Post & Telecom

2.53
-0.50
2.69

-1.31

Wholesaling

-1.94

Tourism

-1.96

0.93
-0.56

-1.96

3.3

1.0 3.2
1.4 4.7
0.9 4.2

3.3

3.0 0.3 3.3

-1.11

Computer

Non-profitable industry
average pricing

2.2

2.08

-0.41

Others

Manufacturing

Fee margin

1.0 4.3

3.3
3.4

Highest pricing
among banks

0.9 4.4

3.3

3.0
0.3

1.6 7.2

5.5

0.6 4.2

3.6

0.3 3.3

3.0
3.7

1.1 4.5

3.5

0.7 3.9

3.2

2.3 6.0
0.3 7.1

6.9
3.6

0.6 4.2

3.0 3.3
0.3

• Some banks in this survey still can generate EP in these non-profitable industries through price differentiation.
Comments • For example, the average EP margin of manufacturing industry in the market is -1.31, however, one bank can
generate 0.93 % of EP margin through higher loan pricing than market average (6.9% v.s 3.4% of loan
margin)
• This example proves that bank definitely need to enhance their pricing approach and stick to the value / risk
based price in order to add value to shareholders

25

Portfolio analysis

2

We found most of pricings do not make much sense: some high
risk industries charged lower margin than lower risk industries'.
Pricing comparison by industry
Value/ Risk based breakeven
pricing by industry

NPL & Total net margin by industry
High risk low
margin

risk

Wholesaling
Manufacturing
Computer

High risk high
margin

[%]

1.0

Others

Low risk low
0.8 margin

Constructure
0.4

Leasing
Off shore

0.2
Engery

0.0

0.0

Low risk

Accommodation

Electronics Real estate

Post & Telecom Transportation

0.6

Low
risk

Credit card

Avergae
NPL=

Credit card

1.2

Mining

Computer
Manufacturing

1.4

Tourism

1.4

Wholesaling

1.6

Trading

1.6

NPL

High
risk 2.4

Avg. total margin4.53%

High 2.4

Low risk high
margin

0.95%

Accommodation

[%] 1.0

0.95%

0.4
0.2

Guarantee

6.0

High risk

• Low correlation between total margin and NPL can be found
in the above graph.
• Take manufacturing industry as an example that average
NPL is 2.33%, much higher than survey banks' NPL average,
but the average margin received is lower than banking
industry average

Avergae
NPL=

Education
Electronics
Personal lending
Transportation
Real estate
Post & Telecom
Constructure
Off shore
Mortgage
Service
Leasing
Environmental
Mining
Agriculture
Engery
Financial Service
Guarantee

0.6

Mortgage
Financial Service

3.5
4.0
4.5
5.0
5.5
Total margin (NII+Fee) [%]

Others

0.8

Personal lending
Education

Service
Environmental
Agriculture

NPL 1.2

Tourism
Trading

Low
0.0
risk

0.0

Low risk

2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5
High risk
Breakeven [%]

• The proper pricing for manufacturing industry is at least
6.32% based on risk based pricing mechanism.
• If bank can charge higher margin than breakeven, it will
contributes more value to shareholders and enhance
bank's ROE

26

Portfolio analysis

2

Chinese banks need to start to proactive manage their portfolio by
allocating capital to 'low capital usage high return' industries and
enhancing their pricing mechanism
Industry average default
probability & loan size

S& P Rating
5.5

High
risk
B+

Relative high
risk

Manufacturing

Agriculture
Environmental

2.0
Tourism
Credit card

3.0

Probability
of default
2.5
BB- 2.12
[%]
BB 1.21
1.0
BB+ 0.71
0.5
Low

Trading

Others
Accommodation
Education

Avg
PD=
Electronics
Personal lending

Post & Telecom

2.1%

EP
1.0
margin
0.5
[%]

0.0

0

10,000 20,000
Loan size [100 Mn RMB]

Transportation
Education
Constructure

Leasing

Real estate
Personal lending Electronics
Accommodation

0.0

Off shore
Credit card
Post & Telecom

Relative low
risk

-1.5

• This study further estimate the average probability
of default by each industry and found that
Wholesaling and Manufacturing industry have
higher default risk in our survey and surveyed
banks were concentrated in these two industries.

Value destroy
Low capital usage

Trading

Value destroy high
Others capital usage
Computer
Manufacturing
Wholesaling
Tourism

Low -2.0

90,000

High

Value creation
high capital
usage

Service

Mining
Engery
Mortgage

Constructure
Real estate
Leasing

Off shore
Mortgage
Service
Transportation
Mining
Environmental
Engery
Financial Service Agriculture Guarantee

Low

Value creation
Guarantee Low capital
usage
Financial Service

Wholesaling

3.5

risk

Average capital usage=9.8%

High 4.5

Computer

3.76

Industry average EP margin &
Capital usage

2

Low

3

4 5 6 8 9 10 11 12 13 14 15 16
Capital usage per unit of loan[%]
High

• Higher concentration risk weren't compensated by return
generated by these two industries.
• We suggest banks should start to manage their portfolio
by reallocating more resources to high return low capital
usage industry and in the meantime enhancing pricing for
value destroy industries

27

Optimization example

2

This study took one bank's portfolio and perform optimization and
found that bank can enhance their EP, ROE through this capital
allocation process
Performance comparison – Pre & Post Optimization
Optimization

FIRB Capital Usage
(100 Mn RMB)

Loan Size
(100 Mn RMB)

EP (100 Mn RMB)

Capital Adequacy
Ratio

+7.0%
0.0%
29,473
2,953

+8.8%

31,523

+1.0%
+15.0%

2,953

14.07%
413

• One
important
•
restriction is we try to
enhance EP by not
increasing
current
credit capital usage

Through optimization,
the
portfolio
is
adjusted
the
proportion of lending
based on risk and
return.
• In this example the
lending
business
grows

ROE 1)

18.4%

20.1%

14.21%

475

• Economic profit
improved by 15%

is

• Improved EP further
strengthen
bank's
CAR

• Also enhanced ROE

1)Optimized ROE= Profit+increatmental EP / equity

28

Optimization example

5

Bank portfolio optimization example
Portfolio comparison – Pre & Post Optimization
Comments

Economic Profit
115
110

Transportation

Pre-Optimization

• A meaningful optimization requires

Post Optimization

105
100

reasonable restrictions to prevent
Transportation
Personal lending

75
70

from allocating all bank's capital to

the highest sector.

65
60
55

Real estate

Personal lending

Service

• Most banks have their own practices

Real estate

50
45
40

in the setting of restrictions,

Service

Energy

Environmental
Environmental

35
30

generally speaking bank needs to

Energy

consider market size of industry,

Financial service
25 Guarantee
Construction
Guarantee
Construction
20
Mining
Mining
15
Education
Education

10
5

Financial service

Others
Telecom
Telecom
0Accommodation
Accommodation

50

100 150

reducing exposure in low return

Manufacturing

Manufacturing

Others

Wholesale & retailing

-5

0

GDP growth rate, possibility of

300

500 550

industries, forward looking expected
Wholesale & retailing

600

650

700

750 800

Capital
850

return ..and so forth

900


29

3

Stress testing


30

3

Stress Testing

This study performed stress testing in an event of default risk
increased by 20% and concluded: the average banking coverage
ratio reduced by 17% and CAR ratio decreased by 6-7%
Current

Impact to banking under stressed scenario
Portfolio Probability
of default (%)

1.69%

NPL Ratio(%)

0.76%

Stressed scenario

Coverage Ratio
(%)

Portfolio average
Credit RW

344%

92%
-17%

Regional Joint stock bank

0.91%

286%

97%

2.23%

1.01%

283%

96%
-17%

2.68%

1.68%

1.21%

0.76%

235%

0.91%

237%

15%
+7%

-7%

14%

85%
-17%

2.02%

-6%

17%

103%

284%

National Joint stock bank

Comments

18%
+6%

2.03%

Mega bank

CAR(%)

17%
+7%

90%

-6%

16%

• This study estimates impacts of stressed scenario when banks' average PD increased by 20%.
• Banking industry in China will remain solvent but CAR will be tightened

31

3

Stress Testing

The impacts to banks' profitability is more significant. ROE recued
by 6-8%. Mega and Regional banks will no longer generate positive
EP.
Current

Impact to banking under stressed scenario
Portfolio Probability
of default (%)

1.69%

Stressed scenario

EP margin per
dollar of loan1)

RAROC

16.76%

Regional Joint stock bank

2.23%

14.29%

-143%

18.43%

0.23%
-17%

2.68%

1.68%

14.32%

20.91%
-132%

19.28%

21.15%

0.74%
-13%

2.02%

-8%

-0.07%

23.37%

National Joint stock bank

-6%

-0.07%

17.31%

Mega bank

19.59%

0.17%
-15%

2.03%

ROE

20.33%

-32%

0.50%

-6%

19.81%

• While banks will still be sustained in this stressed scenario, the profitability of banks face significant challenge.

Comments • RAROC reduced by 13% -15% and only national joint stock banks will maintain above 15% of hurdle rate.
• Loan portfolio will no longer contribute EP for mega and regional banks.
• Overall impact to bank ROE is expected a 6-8% of reduction


32

3

Stress Testing

Bank's asset quality is a key factor and closely linked to the
stressed scenario performance. Low NPL banks perform better
than high NPL banks
RAROC analysis under stress testing

20.33%

Size = NPL in 2012

14.29%

Regional

High

Hurdle rate=15%

14.32%

Mega

Comments

National

45
40

• Average speaking, National joint
stock banks have better
performance:
1.

One mega bank, two
national banks and three
regional banks will not be
able to perform a return
above hurdle rate

2.

Lower NPL
Better Return

Overall speaking, these
banks suffer higher NPL
and we can conclude that
if banks have a better
asset quality under normal
economic situation, they
will have more chances to
survive and out perform
their peers.

35
30
RAROC 25
[%]

20
15
10
5

Low

0

Higher NPL
Worse Return


33

3

Stress Testing

In terms of industry, credit RW exceeds 100% per dollar of lending
for Electronics, Trading, Manufacturing and Wholesaling industry
in the stressed scenario
Stress testing RAROC & RW analysis
High 55

Normal

Environmental

50

Comments

Environmental

Mortgage

Mining
Personal loan

25

Real estate

Leasing

[%]
15

risk

Construction
Real estate

Transportation

20

Credit card

weight

Transportation
Electronics Electronics
Construction
Trading

Off shore

10

1.

Low

2.

Manufacturing

below

Manufacturing
Wholesaling
Wholesaling

Hurdle rate

-5
0

Low

50

60

70

RAROC decreased below
hurdle rate in credit card,
off shore business, trading,
manufacturing and
wholesaling

Trading

Credit card

0

Four industries will have an
average RW exceeds
100%, they are electronics,
trading, manufacturing and
wholesaling

Off shore

Return

5

• In an economic downturn,
both of the NPL and the RWA
will be increased and results
in lower return on capital, the
study shows:

Higher

Mining

Others
Personal loan
Others
Mortgage
Leasing

30

RAROC

Stressed

80

90

100 130

Risk Weight [%]

140

150

160

High

34

3

Stress Testing

Mortgage shows the most impact on the risk weight increasing,
although RAROC is still high
Stress testing RAROC & RW analysis
High 55

Normal

Environmental

Comments

Stressed

50

30

Mining
Personal loan
Mortgage
Others
Real estate Leasing

25
RAROC

Transportation
Construction
Electronics

20

[%]

Mining
Personal loan
Others
Real estate
Transportation
Construction

Leasing

Mortgage

1.

Among the portfolio, Mortgage
has a significant impact and
increased by 11% of risk weight

3.

Environmental industry is next
to mortgage and increased by
9%

4.

Electronics

Risk weight in general, will be
increased by at least 6%

2.

High
return

The significant RW increased is
due to both of mortgage and
environmental have a relative
low PD (NPL).When PD
increased in the stress testing,
RW boost outpace others

Trading

15

Off shore
Trading

Credit card

10

Off shore
Credit card

Lower
Return

Manufacturing

5

Wholesaling

0

Low

• The graph on the left hand side
shows the risk weight change
before and after stress testing and
found that :

Environmental

Manufacturing
Wholesaling

-5
0

100 101 102 103 104 105 106 107 108 109 110 111 112
Risk weight impact under stress testing [%]


35

Stress Testing

3

We further estimate economic capital and simulate banking loan
loss distribution in order to analyze if banks can survive in an
extreme economic turn
Loss distribution for 18 surveyed banks
Probability

Loss Probability(%)

Comments
•

9

This study simulate 18 banks'
portfolio and draw loss
distribution, trying to diagnose if
the accumulated loan loss
provision is enough for banks to
sustain in extreme stressed
scenario

1.

It shows that the current
accumulated 1,149 Bn RMB
provision is able to cover 63%
of stress scenarios. There is a
2% of chance (1 in 50 year) that
the banking industry will face a
stress loss that will wipe out all
provision.

2.

28

Only 0.3% of probability that
banks will suffer even extreme
loss at 2,249 Bn RMB that will
erode both of provision and
profit. Under this scenario bank
still remain capitalized

63% of occurrences

8

1

3

1 in 50 year

2%

2

1

1 in 300 year

0.3%

0.001%

Loss (Bn RMB)

0

0

1,149
18 banks' total
Loan
provision=1,149
Bn RMB

18 banks' Net
profit = 1,087 Bn
RMB

42,715

8,5016

2,249
Capital =6,265 Bn
RMB

Tail risk

Loan size of 18 surveyed banks= 42,715 Bn RMB


36

Stress Testing

3

To understand concentration risk, we leverage EC and generate
concentration ratio
Example

Capital concept
2,953

Book capital

85

• Accounting concept

What bank
has on the
book

306
2,647

Regulatory capital

EC

75

60

• Regulatory requirement
• Under Basel, Credit Capital
estimated based on
– PD
– LGD
– EAD

• A customized method and
depends on bank's credit
portfolio mix and considering the
correlation of portfolio

Minimum
requirement
to compliant
RC (FIRB
Divrsification
Credit Capital) Effect

The risk
capital bank
should hold
for the risk
taking
activity

Concentrat
ion ratio
EC over RC

=

EC

89%

• If EC less than regulatory capital (RC), it is
considered there is a diversification effect, or
concentration risk on the other hand.
• The example above demonstrates EC is
89% of RC. 11% lower than regulatory
requirement due to bank's portfolio is relative
diversified

37

3

Stress Testing

Compare to multinational banks, Banks in China has plenty of
room in improving their credit concentration risk
Unit[USD Billion]

Concentration risk Benchmarking
Deutsche
Bank

ING

One National One Mega
Bank
Bank

NedBank

One Regional
Bank

118.0
113.5
30.3

23.0

22.6

16.9
13.0
9.7
2.8

AIRB
Credit
Capital

EC over
RC Ratio3)

EC

43%

AIRB
Credit
Capital
43%

EC

2.2

2.0

AIRB
Credit
Capital
71%

EC

FIRB
Credit
Capital
73%

EC

FIRB
Credit
Capital

EC

103%

2.1

FIRB
Credit
Capital

EC

89%

1) DB, ING and Ned Bank capital information is at year2010 DB & ING are multinational banks while as Nedbank is relative
localized and concentrated in South Africa 2) exchaneg rate at 1USD =RMB 6.1
3) EC over RC is used in this study as concentration risk measure, it is considered that of this ration exceeds 100% then there is
concentration risk concern

38

3

Stress Testing

We found three mega banks, three national banks have credit risk
concentration
Mega

National

Regional

Concentration risk analysis
EC= RC

4.0

Mega
Bank

Comments

EC>RC

EC< RC

• This study utilize the EC model
to analyze banks portfolio
diversification / concentration
effect, and found that :

3.5
3.0

1.

Three mega banks and three
national banks have
concerns of concentration
risk that their EC are 4% to
15% higher than regulatory
capital requirement. This
results reflect that most of
mega banks were
concentrated in certain
industries as a means to
support government policy

2.

Regional banks in our survey
were more diversified ,
further analysis needs to be
done to explore the reason

2.5

National
Bank

2.0
1.5
1.0

Regional
Bank

0.5
0.0
-20

-15

-10

-5

Diversification

0

5

10

15

Concentration

20


39

3

Stress Testing

Manufacturing and Wholesaling industry are the main source of
industry concentration risk, resulting from their significant size of
lending.
Top 6 industry concentration risk analysis

Mega
Bank

Concentration ratio1) [%]
200
Wholesaling
150
Real estate
100
Electronics
50

Avg.
Concentration
Ratio

Manufacturing
Transportion

Mortgage

100.6

0
3

4

5

6 7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22

200

Natio
nal
Bank

Regio
nal
Bank

150

Transportation
Wholesaling
100 Construction
Manufacturing
Mortgage
50
Real estate
0
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
200

150

Wholesaling

100
50

Trading

0
3

Low

4

5

6 7

Manufacturing

Real estate
Leasing

95.1

Comments
• We found that mega bank
group has a concentration
ratio almost equal to 100%,
that means that the FIRB
credit capital almost
represent their economic
capital.
• Second, national bank group
and regional bank group has
5% of diversification effects
• All Chinese banks have
industry concentration risk
concern in Manufacturing
and Wholesaling industry

93.9

• It seems that Real estate
industry and mortgage are
not a concern of
concentration at year 2012.

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
High
As % of total loan portfolio

1) EC over RC
2) Part of regional banks classified mortgage into personal lending, therefore this study is not be
able to estimate average mortgage concentration measure for mortgage


40

3

Stress Testing

Moreover, these two industries have higher default risk that also
contributed to concentration risk.

Comments

Industry Concentration Analysis
High

Size of bubble = average industry PD
170
160
150

5.18%

Wholesaling

140
Manufacturing

130
Concen- 120
tration 110
ratio
100
[%]
90
80
70

Trading

Others

Concentration

60

• We found three industries
have concentration risk
concerns, and suggest
Chinese banks to adjust
their current portfolio

0.85%
Mortgage

Real estate
Transportation

Off shore Electronics

50
40 MiningLeasing
Environmental
0

Low

2

3

Low

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20

% of total loan portfolio

• Higher default risk
represents larger
uncertainty and it will
attract more unexpected
loss in the economic capital
simulation and resulted in
more capital requirement.
Hence, higher concentration

• Mortgage product is more
diversified due to lower
default risk and large
amount of individual
customers

High

41

3

Stress Testing

We found that mega bank has higher concentration risk and higher
default risk in manufacturing and wholesaling compare to others

Mega
Bank

=Average PD

Concentration ratio [%]
200
5.97% Wholesaling
150

100

4.77%

Real estate

50

Transportion

Electronics

Manufacturing
Mortgage

Average
portfolio
PD
2.23%

0.91%

0
3

4 5

6

7 8

9 10 11 12 13 14 15 16 17 18 19 20 21 22

200

Natio
nal
Bank

Regio
nal
Bank

Wholesaling

150

3.09%

Transportation
3.81%
100 Construction
Manufacturing
Mortgage 0.45%
50
Real estate
0
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
200

150

4%

3.04%
Wholesaling

100
50

Trading

0
3

Low

4 5

6

1.68%

Manufacturing

Real estate
Leasing

1.69%

Comments
• Further breakdown the
analysis by mega bank,
national and regional
banks and found that
the default risk in
manufacturing and
wholesaling industries
are higher
• In terms of mortgage,
mega bank has an
average 0.91% of low
default that mitigate
the concentration risk ,
even though the
mortgage accounted
for 19% of loan
portfolio.

7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
High


42

3

Stress Testing

The bigger issue for Chinese banks is that banking were not
making profit from these two concentrated industries.
High concentration risk

EP margin[%]
4

Mega
Bank

2

Low concentration risk

Value creation

Real estate

0
-2

Transportion

Electronics
Wholesaling

4 5

4

Natio
nal
Bank

6

7

Value creation
Mortgage

0 Construction
-2

0.74%

Real estate
Wholesaling

3

4

5 6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22

4

Value creation

2

Trading

0

Leasing

0.17%

Real estate
Wholesaling

-2

Manufacturing

Value destroy

-4
3

Low

Manufacturing

Value destroy

-4

Regio
nal
Bank

0.23%

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Transportation

2

Mortgage

Value destroy Manufacturing

-4
3

EP
margin
(%)

4

5 6

7

Comments
• It is unlikely banks can
prevent from industry
concentration risk due
to that if national GDP
is already concentrated
in certain industries
• Therefore the issue to
be discussed is how
we can create value
out of it.
• The analysis found that
Chinese banks were
incapable of making
profit in Manufacturing
and Wholesaling
industry. This brings
more concerns on their
internal management

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
High


43

Recommendation

To strengthen risk management, enhance value to shareholder,
suggest Chinese banks to manage their lending business in a
more proactive ways by implementing the following

Key actions

Explanation

Value based
management

• Implementing value based performance metrics into customer/
product level.
• Performing regular analysis and identify key value customer group
and as a foundation of credit portfolio management

Credit portfolio
management

• Managing portfolio at forward looking basis and embedding portfolio
relocation into the annual budgeting process, the results become
bank's KPI
• Open discussion on the risk appetite to clarify where to grow , where
to stop

3

1)

1

2

Reco
mmen
dation

Repositioning and
customer
segmentation

• Repositioning market and target customers ban has advantage.
• Segmented customer by industry and size of customer and fully
understanding customer needs to deepen relationship with clients and
therefore become customer's core bank

: Economic Profit

:Risk Adjusted Return on Capital

44

A

Appendix
Why Risk Adjusted Performance


45

A


A strong relationship between Chinese bank's market value and
Economic Profit based on our empirical test
Chinese banks market value v.s Economic profit
15,000

Comments
R2

=77%
High 14,000 y = 19.623x + 246844

Mega
National
Regional

13,000
12,000
11,000
Market
value1) 10,000
[100 Mn
RMB]

• EP takes into account of
shareholder reward, and
therefore it is considered as
better measure to gauge value
creation
• We regressed Chinese banks
market value and estimated EP
and found strong correlation
that implies that higher EP will
has higher market value

9,000

3,000
2,000
1,000

Low
0
-100 -50

Lower

0

50 100 150 200 250 300 350 400 650
Economic Profit2)
[100 Mn RMB]

High

1) Data source Wind database, end of 2012
2) Source 2012 bank annual report, EP =Net profit – bank capital * 15% of hurdle rate

46


A

RAROC is a better performance measure that link to bank's asset
quality
ROE v.s NPL ratio
R2 =5%
y = -2.5921x + 0.2273

25
24

[%]

R2 =33%
y = -25.049x + 0.4256

Mega
National
Regional

30

23
ROE

RAROC v.s NPL ratio

High 50

High 26

25

22

RAROC20

21

[%]

20

15

19

10

18
5
17

Low

Low 0

1
0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.5

Low

NPL [%]

High

• Regression result doesn’t support
relationship between ROE and Chinese
banks' NPL

0.0

Low

0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5
NPL [%]

High

• On the other hand, higher correlation (or R
square) can be found between RAROC
and NPL


47


A

Higher correlation can be found between EP margin and asset
quality and can concluded that EP is a good indicator of value
creation
Industry-wide EP margin v,s NPL ratio

High4.5
4.0
3.5

Guarantee
FS

3.0
2.5
EP
margin

R2 =69%
y = -2.0132x + 0.0202

Portfolio breakdown of one public listed
bank- EP margin v.s NPL
High 3.5
Agriculture
R2 =91%
Mining 2
y = -2.2976x + 0.0235
Guarantee
3.0
2.5

Agriculture
Service

2.0
1.5

EP

Environmental
Public Mining
Construction Personal Loan
Mortgage
Real estate
Education
Leasing
Electronics
Transportation
Trading
Off shore
Engery
Credit card
Accommodation
Others
Postal & telcom
Computer
Manufacturing

1.0
[%]
0.5
0.0
-0.5
-1.0
-1.5

Tourism

Low-2.0

NPL [%]

Energy

Real estate

Public service
Scientific
Construction

Margin) 1.5

Mining
Personal lending

[%]

Mortgage
Education

0.0

Manufacturing

Small lending

-0.5

Wholesaling

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4

Low

2.0

Health care
Transportation
Other

High

• This study aggregated 18 banks' portfolio and
analyze the relationship between EP margin
and NPL
• Result shows that there is a strong correlation
and EP is linked to bank's asset quality and is
good indicator of value creatoin

Wholesaling
Credit card

Low -1.5
0.0

Low

0.1

0.2

0.3 0.7
NPL [%]

1.5

1.6

High

• An even higher R square can be found for
single bank analysis


48

B

Appendix
Why IRB approach


49

B

Why IRB approach

Current approach of credit RW doesn’t link to bank's asset quality.
No linkage between both
Current approach Credit RW &
NPL
High 1.50

1.45
R2 =0%
1.40
1.35

Mega

Current approach Credit RW &
average Chinese portfolio PD

S & P Rating
3.8
High B+ 3.6

National

R2 =0%

3.4

Regional

3.2

1.00
0.95
NPL
0.90
[%] 0.85

3.0
PD
[%]

0.80
0.75
0.70
Low 0.65
0.60

2.2
2.0
BB- 1.8
1.6
1.4

Low

1.2
BB 1.0

0.00
100

Low

RW[%]

100

High

Low

RW[%]


High

50

B

Why IRB approach

Advance approach under Basel connects asset quality with risk
weight
FIRB approach Credit RW &
NPL
1.5

High

Mega

1.4

R2 =54%
y = 0.0212x - 0.0106

1.3

National

FIRB approach Credit RW &
average Chinese portfolio PD

S & P Rating
3.8
High B+ 3.6

R2 =54%
3.4
y = 0.0474x - 0.0239

Regional

3.2

1.2

3.0
1.1
NPL
[%]

2.2

PD

1.0

[%]

0.9

2.0
BB- 1.8

0.8

1.6

0.7

1.4

Low

Low

BB

0.0

75

Low

1.2

80

85

90
RW[%]

95

100

105

High

1.0

75

Low

80

85

90

95

100

RW[%]


105

High

51

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