Solutions for developing application information systems in the current Vietnamese banking system - 17


Appendix 10 Econometric Problems Proving the Benefits of TTTD


Using mathematical tools and econometric problems, scientists have proven the effects and benefits of TTTD as follows:

a) Problem model

We consider the analysis of Craig McIntosh, professor at the University of California at San Diego, and Bruce Wydick, University of San Francisco (September 2004), considering a loan pool characterized by a group of borrowers, indexed in order of uniformity of the initial endowments of borrowers ( k i Є K ). It is assumed that all lenders have access to the initial endowments of borrower i .

Borrowers can borrow money from both the informal sector or from

i

formal sector. Let the loan size be V i and the interest rate of the loan in the formal lending sector be r i , the loan will yield a profit of

low is â V i , with probability p i (k i, V i ) with < 1, and the high profit is

a ) V >

V i (1+r i ) with probability 1 - p i (k i, V i ). The probability of low returns, in which the borrower is forced to default on a 1- β loan, will decrease in k i (p k < 0) and increase in V i (p v > 0) with p kv < 0, p vv > 0 and p kk < 0 . In the event of default, formal sector borrowers will be able to seize the entire value of ΁For reference, we assume that the informal sector will earn zero profit from borrowers , which means that the interest rate from money lenders (or

The implicit interest rate of those who invest their own capital in business is equal to r- 1 .

The interest cost to the formal financial sector is c and there is a fixed administrative cost of F for each loan , which makes the lender's profit from any given borrower equal to:

i L = (1 - p i )(1+ r i )V i + p i β V i - (1+ c)V i - F (1)

The shape of the lender's iso-profit curve will be curved in the interval {V i ,r i }, we take the total differentiation of formula (1) with respect to V i and r i to obtain:

dV i dr i

v i (1 - p )

( p v V i p )(1 r i - ) - ( r - c )

(2)


In the formal lending sector, if a borrower's project fails to qualify for credit with a loan of size V i at a concessional interest rate r i < r , the borrower can accept a zero-interest project option by paying the lender both β V i and the future profits of the project.

In addition to being characterized by the level of productive assets, each borrower i is also characterized by an individual time preference factor p Є | p , p | over the loan period from which future profits are deducted. We assume that defaulters will not be able to borrow any more money in the future, and so the deductible profit for each borrower i is given by:

B 1 - p - 1 - r V

i


(3)

i ii

p i


By completely differentiating the profit function of borrower i with respect to V i and r i , we get the slope of the iso-profit curve of borrower i in the interval {V i , r i } :

dV i dr i

V i 1 - p

1 - p - p V - 1 r - p i

(4)

p

viii

i

Note that the slope of the lender's iso-profit curve is

inversely proportional to the value of V < (>)1

r i-c

-p .

i p 1 r -

v i


In contrast, the borrower's iso-yield curve is consensus.

with V i < (1-p)/p v when (1-pp v V i ) -1 r i p v

i , and vice versa, then it will be inversely

p

i

island. These relationships mean thatg value of V iat the point where the borrower's iso-profit curve curves backward is greater than the value of V iof the lender if 1+c> , or the borrower will lose money in the worst case. Suppose Bertrand competition exists among borrowers will decrease L0 at the debt equilibrium for borrower i. Equilibrium state

will occur at the point of tangency between the borrower's iso-profit curve and the

i

iso-lender's profit when L0 , depends on the preferred time factor

Borrower's treatment, see the following diagram:


B

i

P P

2 1

1

B

i

P

L 0

Diagram 01. Debt balance for borrowers


V i

V

* 2


V

* 1


r

r

r i

* *

1 2

The implementation of the TTTD system will bring about two positive and obvious effects that the thesis will analyze and describe in this section. To achieve that, we will consider

Borrower i has an initial useful asset k i (known to all potential lenders) but has p i p , p (which is unknown to any potential lender)

Since borrowers with smaller grace periods will place more weight on the favorable interest rate in their future credit evaluations, and since p v >0, patient borrowers will need a smaller loan to achieve debt equilibrium. Conversely, less patient borrowers with larger grace periods will demand larger loans. Lenders prefer to make these larger, riskier loans because they will charge a higher debt equilibrium rate, as shown in Figure 01 with borrowers represented by p 2 >p 1 . Thus, for a given subset of borrowers with tangible assets k i , a borrower's loan demand will, in effect, reflect his grace period.

We can examine impatient borrowers with “very high” time preference factors. Such borrowers are unlikely to place much weight on the risk associated with large loans relative to their assets when evaluating future credit. Specifically, consider a borrower whose initial asset is k i but whose P i is sufficiently high that the expected (net) return from the equilibrium contract for a single loan is less than or equal to the return he would earn from borrowing in a series of smaller contracts. This would occur if the interest rate on each small loan was lower than the interest rate on the single large loan.


To see this more clearly, consider the cooperation coefficient, which reflects the ability of a given lender to cooperate with another lender to determine the current outstanding balance of borrower i . Borrowers who are found to have taken out multiple loans are penalized by not being given credit at preferential interest rates. Since the preferential time coefficient

The incentive is implicit information from the lender, so a borrower will prefer to borrow two

a loan of size ~ is better than a loan of size V if:

V i

B 1 - p V ( - 1 - r (V (

i 1 - 1 -


~ - 1 -~


i

~ i



(5)

i i

ii p

p 2 V i

r i 2 V i

p i


i

The effects of TTTD can be analyzed into blocking effects and push effects, both of which lead to a reduction in the estimated default rate.

calculate. See() is the probability of borrowing multiple loans for borrower i , and the probability


estimated default of all borrowers (at a given level k i ) on a loan

Single loan and multiple loan respectively are

p ( i

( V i , k i ) and

~ p ~ , k

, then :

i V i i

p 1 - p i 1 - ~ p ii1 - 


(6)


See p*

( ) is the preferential time coefficient that will balance the function (5), α increases


will reduce the ability to borrow multiple loans, so,

dp * 0 and

d

0 .


b) Limiting credit risk through blocking effect

The blocking effect of TTTD is the direct change in lender profits that results from the ability to rely on the increased level of α to

prevent, eliminate borrowers with p p *, p (previously in debt) out

from the loan portfolio. The push effect can be seen clearly in the borrower switching condition in formula (5) where the number of impatient borrowers who dare to take on multiple loans will be less as the probability of them being detected increases. Different levels of α will change the attitude of borrowers in the neighborhood of p*, higher α will encourage borrowers to take on a single loan, while lower α will encourage borrowers to take on multiple loans.

As information is shared more widely among borrowers through a credit information agency, we can consider the blocking effect and the push effect as two clear and positive effects brought about by information sharing. We will get


The overall effect of default information by partial differentiation of the estimated default coefficient in (6) with respect to α, we get:

pp ˆ

1 - -

1 - p (-~ p

(7)

(1 - ) 2


Because reflects changes in borrowers' attitudes about the probability of detection, so we can isolate the blocking effect by letting =0 to

p 1 -  p (- ~ p

0

get:

i

0

ii

1 - 2

(8a)


From the total effect formula (7), we subtract the blocking effect in (8a), we will be able to isolate the repulsive effect in formula (8b) as follows:

p i

-

1 - p (i- ~ p i0

(8b)


1 - 2


Note in (8b) that when

(the borrower's sensitivity to

information sharing) increases, the default rate will decrease as the level of information sharing among lenders increases. In contrast, the blocking effect represents a direct effect of information sharing on the default rate; assuming that borrowers are unaware of α.

c) Improve credit quality through push effect

The push effect can be illustrated most clearly in the following way. First, we calculate the critical conversion value of p i *(α) to the borrower at a given tangible asset value k i from (5) to become:

a 1 - ~ -p V

p * a

p 2 V

~ ~

(

(9)

i

1 - 1 - p 2 V  - 1 - ~ r 2 V - - 1 - r (V

Note that in the case where the boundary is drawn at point _ =0, any borrower with p i less than p will borrow money from only one borrower.

Even if there is no TTTD sharing, there:

1 - p 2 V

)

p~ -p V


- 1 -ri V

i

p p * 0

~

2 V

- 1 - r 2 V

- 1 -p V i

~ ~

( 

( ( . at the same time also

It should be noted that when above the critical level , at point


1 - p V (  - 1 - r ( V (

i



= 1 -

i ii

p


then even poor borrowers

1 - p

~ - 1 - ~ r

~ i


2 V i

2 V i

p

Even the most patient would not dare to gamble with the system by borrowing multiple loans from multiple sources.



p

Diagram 02- Information sharing effect

i

Borrow many things

conversion line

p

Borrow a loan

=0

Share information

a

=0

Time coefficientpreferential time


i

Thus, for any level of information sharing < , then the level of information sharing

Information between credit institutions will determine whether the borrower group will take out multiple loans, as shown in diagram 02.

d) Bring economic benefits to borrowers

p )p p

As in formula (7), information sharing reduces the estimated default rate for every borrower with the initial asset coefficient k i . Then the profit equation for the lender in formula (1) can be used to obtain

Expression for the lender's estimated profit:

i i

i

L 1 - p r

-c V i

- pV 1 c - - F

(10)


When

p 1 - p (~ p . Consider the lender's profit and V iis constant,

We can completely differentiate (10) with respect to α and r i to get

dr i

d

p a 1 r i -

p

1 -


<0.


When , the increase in α from increased information sharing will translate into

shifts the lender's zero-profit iso-curve to the left, implying that the interest rate on loans of size V i decreases, resulting in a Bertrand equilibrium contract that will yield higher profits for all borrowers

formally i as we can see in diagram 03, when BV , rBV

, r :


i 2 2

i 1 i 1

Diagram 03 Sharing information brings profit to borrowers


ii'

B

i

V , r

V , r

B

i

ii

V i

L

i

0 '

L

i

0

V 2

V 1

r 2 r 1 r i

e) Restricting informal credit markets

Due to the fixed cost of lending, F , and the fact that borrowers can only borrow from the formal financial sector when the official interest rate is lower than r , there exists a group of borrowers whose initial tangible assets are low and who cannot easily profit from borrowing from formal borrowers. By setting (3) equal to (4) and completely differentiating, we immediately get

It is immediately seen that the profit-maximizing debt balance will increase k i , , or

dV *

i0 . Thus, initially richer borrowers will receive

dk i

larger loan. We define the smallest level of tangible assets

The first borrower's asset that satisfies the lender's feasibility conditions (at the level of information sharing α ) is the first asset of borrower i with k K.

Now suppose that by introducing a credit bureau, the level of information sharing α increases. The increased level of information sharing will allow the lender to acquire customers who are poorer borrowers at the marginal limit, whose initial wealth coefficient is lower than k . We can see this by substituting k into (10), and noting that since there is


fixed costs, the lender will earn zero profit when lending

the poorest borrowers in the loan portfolio. Take the full differential


part of (10) will give

dk ) p



, or as α increases, the marginal borrower becomes

0

d p k

As a result, increased information sharing leads to better credit ratings for poorer borrowers and a more efficient financial system through lower default rates. Lower default rates reduce the cost of lending, so it becomes more profitable for lenders to make small loans to borrowers with few assets.

This implies that the introduction of credit institutions is likely to provide greater flexibility to both the formal and informal financial systems in lending to marginal poor borrowers who have traditionally been denied credit by the formal financial sector. The effectiveness of credit institutions in reducing default rates and creating more opportunities for low-income borrowers has contributed to the development of credit activities.


Appendix 11 - Details of CIC's response to credit institutions in the first 6 months of 2006


STT


Name of the credit institution


First 6 months

2005

First 6 months of the year

2006

Increase/Decrease


SL


%

I

State Bank of Vietnam

867

313

-554

-63.90%

1

Vietnam Joint Stock Commercial Bank for Industry and Trade

2427

2174

-253

-10.42%

2

Bank for Agriculture and Rural Development

2592

2960

368

14.20%

3

Bank for Investment and Development of Vietnam

1329

1322

-7

-0.53%

4

Bank for Foreign Trade of Vietnam

2197

2455

258

11.74%

5

Mekong Delta Housing Bank

988

1418

430

43.52%

II

State Commercial Bank

9533

10329

796

8.35%

1

Maritime Commercial Joint Stock Bank

157

358

201

128.03%

2

Joint Stock Commercial Bank for Foreign Trade of Vietnam

755

1243

488

64.64%

3

Saigon Thuong Tin Commercial Joint Stock Bank

2467

4376

1909

77.38%

4

Southeast Asia Commercial Joint Stock Bank

294

307

13

4.42%

5

Saigon Commercial Joint Stock Bank

720

729

9

1.25%

6

Dong A Commercial Joint Stock Bank

408

420

12

2.94%

7

Ho Chi Minh City Housing Development Joint Stock Commercial Bank

944

704

-240

-25.42%

8

Hanoi Housing Commercial Joint Stock Bank

44

139

95

215.91%

9

International Commercial Joint Stock Bank

1482

1981

499

33.67%

10

Orient Commercial Joint Stock Bank

813

1338

525

64.58%

11

Gia Dinh Commercial Joint Stock Bank

282

541

259

91.84%

12

Nam A Commercial Joint Stock Bank

257

428

171

66.54%

13

Pacific Commercial Joint Stock Bank

554

241

-313

-56.50%

14

Saigon Joint Stock Commercial Bank for Industry and Trade

98

110

12

12.24%

15

First Commercial Joint Stock Bank

3

2

-1

-33.33%

16

Southern Commercial Joint Stock Bank

6064

4848

-1216

-20.05%

17

Vietnam Technological and Commercial Joint Stock Bank

1506

1496

-10

-0.66%

18

Asia Commercial Joint Stock Bank

3179

5512

2333

73.39%

19

Joint Stock Commercial Bank for Enterprises outside the country

3162

2826

-336

-10.63%

20

North Asia Commercial Joint Stock Bank

20

32

12

60.00%

21

Military Commercial Joint Stock Bank

839

961

122

14.54%

22

NT Rach Kien Commercial Joint Stock Bank

17

8

-9

-52.94%

23

Hai Hung Commercial Joint Stock Bank

22

1

-21

-95.45%

24

An Binh Commercial Joint Stock Bank

106

239

133

125.47%

25

Dai A Commercial Joint Stock Bank

112

261

149

133.04%

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Solutions for developing application information systems in the current Vietnamese banking system - 17



26

Vietnam Asia Commercial Joint Stock Bank

237

204

-33

-13.92%

27

KEXIM Financial Leasing Company

0

1

1


28

Dong Thap Muoi Commercial Joint Stock Bank

0

4

4


29

Nhon Ai Commercial Joint Stock Bank

7

17

10

142.86%

30

Nam Viet Commercial Joint Stock Bank

0

7

7


31

Kien Long Commercial Joint Stock Bank

0

3

3


III

Joint Stock Commercial Bank

24549

29337

4788

19.50%

1

Lao Viet Bank

46

93

47

102.17%

2

VID PUBLIC BANK

29

37

8

27.59%

3

VINASIAM JOINT STOCK COMPANY

24

16

-8

-33.33%

IV

NHLD

99

146

47

47.47%

1

INDOVINA BANK

53

74

21

39.62%

2

SHINHANVINA BANK

14

20

6

42.86%

3

Korea Exchange Bank

2

3

1

50.00%

4

ANZ BANK

19

7

-12

-63.16%

5

Standard Chartered Bank

0

2

2


6

CHIFON BANK

7

10

3

42.86%

7

BNP BANK

0

4

4


8

BANGKOK BANK

13

19

6

46.15%

9

CITI BANK

1

12

11

1100.00%

10

UNITED OVERSEAS BANK

3

135

132

4400.00%

11

HongKong and Shanghai Bank

19

104

85

447.37%

12

ICBC BANK

2

0

-2

-100.00%

13

WOORI BANK

2

1

-1

-50.00%

14

ChinaTrust Commercial Bank

18

14

-4

-22.22%

15

First Commercial Bank

45

70

25

55.56%

16

FAR EAST NATIONAL BANK

95

99

4

4.21%

V

Foreign Bank

293

574

281

95.90%

1

HANDICO Finance Company

0

22

22


2

VN International TC Leasing Company

14

4

-10

-71.43%

3

Petroleum Finance Company

306

354

48

15.69%

VI

Other credit institutions

320

380

60

18.75%

Total

35661

41079

5418

15.19%

Source CIC


Appendix 12

COMPARISON OF PUBLIC AND PRIVATE CREDIT AGENCIES


Public

- The number of members is regulated to ensure contribution.

- Quality is governed by the legal system.

- There is no other choice but to share information (except for special information)

- Add separate approach to third party information

a. Information


Private

- The number of members is unlimited.

- Quality is governed by the legal system.

- There is doubt in sharing information

- Pay attention to expanding third-party information sources to test and increase revenue.

Public

- External sources of information are used for short-term consulting. Management is based on existing internal sources of information.

b. Information sources


Private

- Have a centralized board that reviews shareholders, has approval for the use of external resources in management and consulting

- evaluate internal information sources to serve cultural issues

Public

- Focus directly on using the information

- Plus cost recovery.

c. Credit policies


Private

- Members are encouraged to implement credit control within existing policies.

- Focus on cost

- Historical approach to credit assessment

Public

- Operate according to existing regulations

- Can change regulations quickly to meet requirements.

- Cannot be considered a completely neutral organization.

d. Legal/Regulations


Private

- If there are no legal regulations, private TTTD companies will operate under their own regulations.

- If there are legal requirements, it may require extensive action to create an environment for sharing credit information, for example changing information from negative to positive.


Public

- Can quickly correct regulations if required

- The media is more cautious in transactions.

- Contrarian approach- Not dictated by customer groups but can be influenced by public perception

e. Customer information security

Private

- May be prohibited by law

- Every action is subject to scrutiny by the public and other mass media.

- The use of credit providers may be influenced by public perceptions in an effort to avoid government-related problems.

- Try to act as a trusted third party.


Private

- Will require comprehensive measures to protect against intrusions (both external/internal)

- Contact via B2B, Web or FTS

- Cost effective D/R solution

f. Safety

Public

- Will require comprehensive measures to ensure against intrusion (both external/internal)

- The credit agency will have to use the existing transaction network in addition to B2B, Web or FTS

- Work with existing D/R solutions



CREDIT BROADCAST BRANCH OF SINGAPORE (CBS)

- As a private company, collect information

consumer information and retention of positive information

CASE STUDY


CCRIS (OF MALAYSIA)

- Is a commercial, consumer and information storage company. This company is part of Bank Negara Malaysia (NBMA).


Singapore

- Credit Bureau of Singapore (CBS)

- Commercial activities

- 25% of shares are owned by the Association of Banks of Singapore (ABS)

- Monetary Authority Gazette (MAS) Request

OWN

Malaysia

- 100% owned and operated by Bank Negara Malaysia (BNM)

- Control all operating licenses for both domestic and foreign banks

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