Korea Fixed Income Research Institute Chung Ang University Risk Management and Sharing Case of South Korea Gyutaeg, Oh AFDC Workshop on Developing Asian

Korea Fixed Income Research Institute

Chung Ang University

Risk Management and SharingRisk Management and Sharing Case of South Korea Case of South Korea

Gyutaeg, OhGyutaeg, OhGyutaeg, OhGyutaeg, Oh

AFDC Workshop on Developing Asian Bond Markets:AFDC Workshop on Developing Asian Bond Markets:Facilitating the pricing mechanism for Asian bondsFacilitating the pricing mechanism for Asian bondsMay 29- June2, ShanghaiMay 29- June2, Shanghai

ContentsContents

IV

I

II

III

V

Risk Management: Early Warning System in Bond MarketsRisk Management: Early Warning System in Bond Markets Risk Management: Early Warning System in Bond MarketsRisk Management: Early Warning System in Bond Markets

Risk Management : Early Warning Systems for Individual Credit RisksRisk Management : Early Warning Systems for Individual Credit Risks Risk Management : Early Warning Systems for Individual Credit RisksRisk Management : Early Warning Systems for Individual Credit Risks

Risk Management : SME Credit RisksRisk Management : SME Credit RisksRisk Management : SME Credit RisksRisk Management : SME Credit Risks

Risk Sharing: SME SecuritizationRisk Sharing: SME Securitization

Implications to Asian Bond Market Initiative (ABMI)Implications to Asian Bond Market Initiative (ABMI)

Risk Management: The Cases of KoreaRisk Management: The Cases of KoreaI

: : Early Warning Systems in Bond MarketsEarly Warning Systems in Bond Markets: : Early Warning Systems in Bond MarketsEarly Warning Systems in Bond Markets

Development of Corporate Bond Market

Currency Crisis (1997.11)

Daewoo Crisis (1999.8)

SKG & Credit Card Crisis

(2003.3)

Credit shock

Market Impact

Massive corp.Bond Issuance to refinance bank debts (from banks to ITCs)

ABS (Asset backed securities) development to handle NPLs

Market Impact

MTM accounting

for ITCs

Establish bond pricing agency

Improve post-

trade transparency

Market Impact

Credit card Debt roll-

over problems

Realizing the need for

systemic risk

monitoring system

Realizing the

importance of credit

Bureau

Plunge of ABS markets

Credit shock Credit shock

Market Impact

Issuance of P-CBOs to

refinance corp. bond

debt

Rapid pick-up of ABS

markets

Credit shock

Maturity Concentration Crisis

(2000)

Necessities of Early Warning Systems in Bond Markets

I. Concentration Index

Creating various “bond market indices” and reporting them periodically will enable market participants to systematically expect the directions, credit risks, and concentration risks of the bond market.

Creating various “bond market indices” and reporting them periodically will enable market participants to systematically expect the directions, credit risks, and concentration risks of the bond market.

II. Credit Spread Index

III. Market Sentiment Index

Problems both inside and outside bond markets prevented the proper function of price discovery and pricing, finally leading up to the financial crisis.

Problems both inside and outside bond markets prevented the proper function of price discovery and pricing, finally leading up to the financial crisis.

Information on interest rates, issuing or trade volume is not enough to warn the potential risks of bond markets.

Information on interest rates, issuing or trade volume is not enough to warn the potential risks of bond markets.

-

500

1,000

1,500

2,000

2,500

01- 01 01- 07 02- 01 02- 07 03- 01 03- 07 04- 01 04- 07 05- 01 05- 07

Outstanding Issue by bond types (including the entire bonds)

Outstanding Issue and trade volume by industries (confined to credit-risky bond)

Prevention of risks caused by excessive concentration in specific sectors or industries

I. Concentration Index of Bond MarketsI. Concentration Index of Bond Markets

Concentration IndexConcentration Index (Herfindahl-Hirschman index )

Market Concentration on Bonds

GB LB SB MSB FB CB

Concentration in overall marketsdecreases a little, but differently

-Decrease in Corp. Bond/Agent Bond & Increase in Government Bond/MSB (See Figure )

Concentration Index by Industries

-

500.0

1,000.0

1,500.0

2,000.0

2,500.0

3,000.0

01- 0101- 0702- 0102- 0703- 0103- 0704- 0104- 0705- 0105- 07

제조업 금융업 기타산업ManufactureManufacture

FinanceFinance

Other industriesOther industries

The increasing trend of concentration since 2001

- Financial sector’s share has been increasing sharply

- Corporate bonds on manufacture has been decreasing

Advantages of using Concentration Index

By analyzing the concentration index of bond markets

and its historical trend, it is possible to know in what

sort of bond markets money is concentrated or in what

industries bonds are focused.

Useful data to perceive bond market features or possible direction

Data by bond types and of industrial potion can be a

referential material, when investing bonds

Used as benchmark indicator when deciding the portion of Investment by industries

Possibility to prevent possible risk caused by excessive

concentration of money in specific bond types or

industries.

Useful materials for managing industrial risks

Manufacture of Automobiles and Trailers

II. Credit Spread Index

ObjectiveTo provide trustworthy indexes for bond market participants by measuring credit risks in the market, by grading credit and industries, based upon credit spread

Spread by credit levels can predict credit risk recognized in the market. Credit spread by industries shows the changes of credit risks in each industry .

Trend of Trend of Yield Yield

by Industriesby Industries

Trend of Trend of Spread Spread

by Industriesby Industries

Trend of Trend of Inter-Inter-

IndustryIndustrySpreadSpread

Graph

Period Standard

Table

……

Trendsof Yields and Spreadsof Each Industry

Trend of Spread Index by industries

Telecommunication

ConstructionChemical Ind.

Calculation Procedure

Calculation Method

Selection of Issues by index purposes: non-guarantee, senior, public offered or

normal bonds

(confined to only over BBB credit rate bonds)

Sector division by risks: by bond groups / credit rates / industries

Establishment of the event-rule: Rule-making in Corporation Restructuring Inducement

Law and when

restoring exceptional corporations

Selection of Issues by index purposes: non-guarantee, senior, public offered or

normal bonds

(confined to only over BBB credit rate bonds)

Sector division by risks: by bond groups / credit rates / industries

Establishment of the event-rule: Rule-making in Corporation Restructuring Inducement

Law and when

restoring exceptional corporations

NICENICEKBPKBP

KISKIS• Calculation of spreadindex by group/gradeand industries

• Use of graph and tables

KSDA (Korea Securities Dealers Association)

Rate of Returns by Industries

Monthly Summary Report

Homepage NoticeRate of returns by

group/grade

Rate of returns by

group/grade Market participan

ts

Market participan

ts

Calculation of Credit Spread Index Calculation of Credit Spread Index

< Bond Pricing Agencies > < Bond Pricing Agencies >

III. BMSI ( Bond Market Sentiment Index )

BMSI Objective

To provide bond market warning signals

To uplift the security of financial system by letting the overall market atmosphere recognized

To enquiry of over research institutes, funds, banks, and asset management companies about the

market sentiment.

Benefits of BMSI

Role as an indicator, when capital management institutions establish operational strategy

Utilization as an referential indicator of financial market decision-makings

Example : Bond Market Sentiment IndexExample : Bond Market Sentiment Index

Bond market sentiment survey ( Example )

What do you think interest rates will be in one month?1) increase 2) current level 3) decrease

Bond market sentiment survey ( Example )

What do you think interest rates will be in one month?1) increase 2) current level 3) decrease

Interest Rate Expectation

105.0110.0

120.0115.0

105.0 102.0

88.0

101.0

84.080.0

90.0

116.6

40.0

60.0

80.0

100.0

120.0

140.0

160.0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

3.5

3.7

3.9

4.1

4.3

4.5

4.7

4.9

5.1

5.3

Interest Rate (National Treasury Index) Interest Rate (National Treasury 3 yrs.)

BMSI Interpretation

BMSI Level

0: Cap

100:Base

200: Floor

“ BMSI 30 indicates that market psychology is tightened. ”

“ If BMSI is higher than 100, it is expected that interest rate will overall decrease, showing the expectation of market participants.”

“ BMSI 170 Indicates that market psychology is overheated.”

BMSI = (Good-Bad) / (Good+Bad) ] x 100 + 100Good = Number of respondents who expect that bond markets will be getting stronger (decrease of interest rate)Bad = Number of respondents who expect bond markets will be getting weaker (increase of interest rate)

BMSI = (Good-Bad) / (Good+Bad) ] x 100 + 100Good = Number of respondents who expect that bond markets will be getting stronger (decrease of interest rate)Bad = Number of respondents who expect bond markets will be getting weaker (increase of interest rate)

1. Benchmark Bond rate in one month? 1) higher than now 2) current level 3) lower than now

2. Term spread between 1yr MSB and 10yr K TB in one month? 1) wider than now 2) current level 3) narrower than now

3. Target rate(overnight rate) by BOK in one month ? 1) likely to be raised 2) to be unchanged 3) likely to be cut

4. What do you want about Target rate(overnight rate) by BOK in one month ? 1) want to be raised 2) to be unchanged 3) want to be cut

5. Target rate(overnight rate) by FOMC next time ? 1) likely to be raised 2) to be unchanged 3) likely to be cut

6. Net Bond issue amount in one month? 1) increase 2) current level 3) decrease

7. CP I in one month? 1) higher than now 2) current level 3) lower than now

8. Value of K orean Won in one month? 1) decrease 2) current level 3) increase

9. Investment clock for the Industry as 4 seasons in one month? (Oct 6.8%, Nov 8.6%) 1) Spring 2) Summer 3)Fall 4) Winter※ Ind Prod YoY 's likely to be under 5% from under 0%=>spring, over 5% => summer, from over 5% into the under 5% => fall, can be under 0% => winter

10. Consumption clock for the customer as 4 seasons in one month? (Oct 7.6%, Nov 6.5%) 1) Spring 2) Summer 3)Fall 4) Winter※ Consumer Expectation Index YoY 's likely to be under 5% from under 0%=>spring, over 5% => summer, from over 5% into the under 5% => fall, can be under 0% => winter

11. Trade Surplus in one month? 1) increase 2) current level 3) decrease

12. I 'm working for 1) the domestic company 2) the foreign company

13. I 'm working as 1) Fund manager, Trader 2) Analyst, Economist 3) something else

Thank you for your subscription in advance.

Bond Market Survey

Example : Bond Market Sentiment Index

BMSI Graphs

Call Rate BMSI

70.0

50.0

75.0

90.082.0

71.0

105.0110.0

85.0

95.0

80.0

110.5

40.0

60.0

80.0

100.0

120.0

140.0

160.0


3.00

3.10

3.20

3.30

3.40

3.50

3.60

3.70

3.80

Call Rate Expectation Call Rate

Interest Rate Expectation

105.0110.0

120.0115.0

105.0 102.0

88.0

101.0

84.080.0

90.0

116.6

40.0

60.0

80.0

100.0

120.0

140.0

160.0


3.5

3.7

3.9

4.1

4.3

4.5

4.7

4.9

5.1

5.3

Interest Rate (National Treasury Index) Interest Rate (National Treasury 3 yrs.)

Long-Short Spread BMSI

110.0102.0 105.0

111.0 110.0

85.090.0

105.0110.0

150.0

120.0125.2

40.0

60.0

80.0

100.0

120.0

140.0

160.0


3.00

3.50

4.00

4.50

5.00

5.50

6.00

long-short spread MSB Govt 10yr

Size of Bond Issurance BMSI

70.0

50.0

75.0

90.0

82.0

71.0

105.0110.0

85.0

95.0

80.0

110.53

18

13

76

12

1

-1

8

1

10

40.0

60.0

80.0

100.0

120.0

140.0

160.0


-5

0

5

10

15

20

Size of Bond Issuance Monthly Net Increase of Bond Issuance

Risk Management: The Cases of KoreaRisk Management: The Cases of KoreaII

: : Early Warning Systems for Individual Credit RisksEarly Warning Systems for Individual Credit Risks: : Early Warning Systems for Individual Credit RisksEarly Warning Systems for Individual Credit Risks

Early Warning Systems for Individual Credit Risk

1000.0

1001.0

1002.0

1003.0

1004.0

1005.0

1006.0

1007.0

1008.0

1009.0

1010.0

Time

Index

After serious credit risk of the year 2003 in Korea, the need to develop a new index to show how the credibility

of individual people changes has increased, with credit default rates being soared

NeutralZone

NeutralZone

GoodZone

GoodZone

Individual Credit Risk Index in Korea Individual Credit Risk Index in Korea

Background of Individual Credit Risk Index Background of Individual Credit Risk Index

Simple average of CB Risk Score over the entire population to calculate various indexes from Credit Panel Data

Simple average of CB Risk Score over the entire population to calculate various indexes from Credit Panel Data

Reporting the Credit Risk Index quarterly

STEP 4

STEP 3

STEP 2

STEP 1

Calculating Individual Credit Points

Object: 33,679,786 people aged from 20 to 89, dealings on credit Object: 33,679,786 people aged from 20 to 89, dealings on credit

Summation of Individual Credit Points

Averaging the summation and Indexing(Setting Index at the standard point of time, June 2004, as 1000.0)

Computation and Operation of Individual Credit Risk Index Computation and Operation of Individual Credit Risk Index

• Banks• Credit Card Co.• Capital Co.• Insurance Co.• Federation of savings banks• Federation of community credit corporatives• Credit union• Department stores

Financial CB Consortium

Financial CB Consortium

Consumer finance

KCFA CB ConsortiumKCFA CB Consortium

Information communication

CommunicationCB ConsortiumCommunicationCB Consortium

Finance & non-finance credit rating corporations

General member Companies

General member Companies

Korea Federation of Banks

Korea Federation of Banks

Financial organizations Public organization(ie. National Tax Service)

NICE Credit Bureau

NICE Credit Bureau

Credit InformationDatabase

= Gathering & Enquiry Info.

CB Service• Credit report• Credit grade • Early warning• Prevention of deception

InformationGathering

Service Providing Exchange of Info.

I. Credit Bureau Data ChannelI. Credit Bureau Data Channel

Credit Risk Score aims to provide credit score (average) and grade (10 levels), measuring

credit risks within the given period over the entire population relating to credit activities

Goal Goal Credit risk estimation of the overall populationCredit risk estimation of the overall population

Object Object Population relating credit activitiesPopulation relating credit activities

Content Content Forecast of non-performance of debts within 6 months ( over 90 days in arrears)Forecast of non-performance of debts within 6 months ( over 90 days in arrears)

Activities ActivitiesUtilized in screening loans and cards issuance, and estimating credit degree of the overall customers monthly and quarterly

Utilized in screening loans and cards issuance, and estimating credit degree of the overall customers monthly and quarterly

Features FeaturesRegarded as the typical model with improved accuracy reflecting the recent CB information (esp. arrears information) in contrast to the existing risk score

Regarded as the typical model with improved accuracy reflecting the recent CB information (esp. arrears information) in contrast to the existing risk score

Service typeService type Online search & deployment searchOnline search & deployment search

CB RiskScore

CB RiskScore

II. CB Risk ScoreII. CB Risk Score

III. Consumer Credit Panel Data

Credit Panel Data –Credit panel data over the public

Credit Panel Data by credit grades on a quarterly basis

Grade

Total

The entire individual on whom NCB has credit information; about 33 million people

CB Risk Score on each individual and aggregated grade on monthly basis

Information has been accumulated since Jun. 2003 The expectation that various information monitoring will gather more

contents.



Information has been accumulated since Jun. 2003 The expectation that various information monitoring will gather more

contents.

0bject individuals

Aggregated InformationAggregated Information

The Overall Public Delinquent Rate

Grade

01

2

3

4

5

6

7

8

9

10

Grade

01

2

3

4

5

6

7

8

9

10

Compared companies

Compared companies



Information has been accumulated since Jun. 2003

The expectation that various information monitoring will gather more contents.



Information has been accumulated since Jun. 2003

The expectation that various information monitoring will gather more contents.

0bject individuals0bject individuals

Aggregated Information

-Simple average of CB Risk Score over the entire population

-Possibility of calculating various indexes by analysis purposes from Credit Panel Data

(ex. Trend of customers below the7 grade )

Credit Panel Data

Average

Credit Panel Data-Trend of Credit Index

IV. Credit Index illustrated by Credit Panel DataIV. Credit Index illustrated by Credit Panel Data

Credit Bureau Business in Korea

History of Credit Bureau in Korea

Beginning of Credit Information Service

Establishment of CB ConsortiumCB reporting service

1987 2002 2003 2004 2005

CB Score ServiceCB Early Warning System

Revolution of CB Market

Simple service of reporting negative credit information on credit risk

Diversified Service providing positive credit informatione.g.) credit evaluation

Korea’s Credit Bureau MarketKorea’s Credit Bureau Market

NICE

Business & ServiceKIS Info

KCB

(Korea Credit Bureau)

Capital stock

(billion Won)33.5 23.8 50.0

Staff Number 283 187

CB member companies

2,599 949 20

Year of Establishmen

tSep. 1986 May. 1985 2005

Services

Credit Reporting

CB Risk Score

CB Recovery Score

CB Collection Score

Credit Reporting

Risk ScoreCredit Reporting

NICE CB Score uses the estimation items which can precisely predict short-term and long-

term insolvency rates, to keep the forecasting capability

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

90.00%

100.00%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00%

우량고객

불량고객

*. Analysis sample: 2.5 million customers

estimated in 1st quarter, 2004

Possibility of being registered as delinquent customers within

6 months

Possibility of being registered as delinquent customers within 12

months

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

90.00%

100.00%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00%

우량고객

불량

고객 K-S = 67.1%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

90.00%

100.00%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00%

우량고객

불량

고객

K-S = 66.3%

6 Month Forecast

6 Month Forecast

GoodGood

GoodGood

badbad

badbad

1) Short-term and Long-term Credit Forecast1) Short-term and Long-term Credit Forecast

2) Bench Mark Index illustrated by Credit Panel Data

Comparison of default rate of the overall public by CB grades with default rate over the companies’ portfolio by grades Possibility to appreciate the soundness of companies’ portfolio relative to the entire population

The overall public’s delinquent rateThe overall public’s delinquent rate

The companies’ delinquent rate by gradesThe companies’ delinquent rate by grades

The entire publicThe entire public

The companiesThe companies

Risk Management : The Cases of KoreaRisk Management : The Cases of KoreaIII

SME Credit RisksSME Credit RisksSME Credit RisksSME Credit Risks

Number of Companies

Number of Employees

Exports

SME 99% LE 1%

SME 86% LE 14%

SME 43% LE 57%

Insufficient collateral

High transaction cost

Low credit risk assessment ability

of financial institutions

: Limited access to formal

financing

SMEs in the Korean Economy

Importance Difficulties

SME Credit Database in KoreaSME Credit Database in Korea

Capital Head Office

Services

$ 72 million $ 72 million 5 Divisions,

2 Departments, 19 Teams/ Seoul

8 Branches nationwide

5 Divisions, 2 Departments, 19 Teams/ Seoul

8 Branches nationwide

Shareholders Shareholders

KCGF(47.8%),

KOTEC

KDB

IBK

KFB

SBC

KCGF(47.8%),

KOTEC

KDB

IBK

KFB

SBC

8 Types of

credit information

services to

domestic and

overseas clients

8 Types of

credit information

services to

domestic and

overseas clients

Established Korea Enterprise Data in Feb. 2005 as a spin-off company of KCGF’s credit information services

Credit bureau specializes in credit information of SMEs

Established Korea Enterprise Data in Feb. 2005 as a spin-off company of KCGF’s credit information services

Credit bureau specializes in credit information of SMEs

Corporate Credit Rating System (CCRS) by KED

Combined Rating beforeFiltering & AdjustmentNR

(Not Rated)

Yes

Quantitative Rating

Evaluated automatically

No

Financial Rating

Window DressingCheck

Qualitative Rating

Judged by Analyst

Biz Information Report

Financial RatioFactors

Non-financialQuantitative

Factors

Non-financialQualitative

Factors

Filtering Adjustment

Credit RatingCredit Rating

Industry Rating Industry Rating FAPs (Financial Filtering)FAPs (Financial Filtering)

CCRS - Estimated and Actual Default Ratio

Credit Rating Credit Rating No. of No. of Financial Financial

Statements Statements

No. of No. of Default Default

Estimated Default Estimated Default ProbabilityProbability

Average Average Actual Rate of Actual Rate of Default Default

AAA 2 0.03% – 0.17% 0.01% 0.00%

AA 26 1 0.17%-0.96% 0.56% 3.85%

A+ 57 0.96%-1.25% 1.10% 0.00%

A 69 1.25%-1.54% 1.39% 0.00%

A- 81 1.54%-1.83% 1.68% 0.00%

BBB+ 238 4 1.83%-2.17% 2.00% 1.68%

BBB 272 4 2.17%-2.52% 2.34% 1.47%

BBB- 358 14 2.52%-2.86% 2.69% 3.91%

BB+ 1,244 32 2.86%-3.42% 3.14% 2.57%

BB 1,574 57 3.42%-3.97% 3.69% 3.62%

BB- 1,813 74 3.97%-4.53% 4.25% 4.08%

B+ 4,001 177 4.53%-5.42% 4.97% 4.42%

B 3,478 204 5.42%-6.30% 5.86% 5.87%

B- 2,814 218 6.30%-7.19% 6.74% 7.75%

CCC+ 1,744 178 7.19%-8.94% 8.06% 10.21%

CCC 796 82 8.94%-10.70% 9.82% 10.30%

CCC- 389 39 10.70%-12.45% 11.57% 10.03%

CC 152 33 12.45%-22.94% 17.69% 21.71%

C 16 4 22.94%-100% 61.47% 25.00%

Total 19,124 1,121 5.86%

Risk Sharing:

Case Study of SME Securitization

2

IVIV

The main problems are that SMEs in Korea have high default risk

Credit Risks involved in P-CBO program at SBC

(by Korea Ratings, Periods : 1998~2004, unit : %)(by Korea Ratings, Periods : 1998~2004, unit : %) Cumulative Default Rate

Cumulative Default Rate

Rating 1 year 2year 3year 4year 5year 6year

AAA 0.00 0.00 0.00 0.00 0.00 0.00

AA 0.00 0.00 0.00 0.00 0.00 0.00

A 0.00 0.00 0.00 0.00 0.00 0.00

BBB 0.32 0.68 1.11 1.93 3.20 3.20

BB 3.94 6.77 9.12 10.18 11.29 12.48

B 13.73 17.10 19.44 19.44 19.44 19.44

Below B 0.16 0.36 0.60 1.09 1.82 1.82

Speculative 6.50 9.47 11.81 12.59 13.37 1.42

Average 2.22 3.41 4.47 5.07 5.82 6.13

SME Securitization Program by SBC: CBO Program in 1999

Primary in the sense the program helps SMEs issue bonds

23 SMEs23 SMEs

Small Business CorporationSmall Business Corporation

SPCSPC

Senior bonds (2yr 8.5billion, 3yr 36billion)

Senior bonds (2yr 8.5billion, 3yr 36billion)

Junior bonds(27.5 billion)

Junior bonds(27.5 billion)

Corporate bonds (72billion won)

Asset sales

Investor Repurchased by Small Business Corporation

Credit Enhancementby Korea Housing Bank

(10billion)

Credit Enhancementby Korea Housing Bank

(10billion)

Market Failure (Credit Quality Gap) Problems

SMEs have high default risk (WAR B+) but need alternative funding source

- Investors want good quality bonds

- Securitization helps reallocate risk

- Problems: How to sell junior bond?

The Role of SBC (Public Sector): Agent for Change

SBC securitization program illustrates dynamic evolutionary paths

- assumes junior bonds

- finds appropriate structures

- create mezzanine bond markets

- create junior bond markets

SBC securitization program illustrates dynamic evolutionary paths

- assumes junior bonds

- finds appropriate structures

- create mezzanine bond markets

- create junior bond markets

Catch 22 Problem

No one knows what structure is appropriate

No one knows the risk-return profile of the structure

No one invests in mezzanine bonds

Catch 22 Problem

No one knows what structure is appropriate

No one knows the risk-return profile of the structure

No one invests in mezzanine bonds

Title of SPCDate of Issue

Amount

(billion)No. of firms

Credit Grade

(WAR)

1st 1st SME Securitization 1999.12.30 72.0 Won 23 BB

2nd 2nd SME Securitization

2001.01.31 160 Won 52 BB-

3rd KOROmas Fund 2001.12.11 0.34 USD 59 BB-

4th 3rd SME Securitization 2002.09.06 81.5 Won 42 B

5th COROvoltin Fund 2002.11.14 0.35 USD 131 B

6th

4th SME Securitization 2003.05.09 98 Won 41 B

7th

5th SME Securitization 2004.2.27 94.4 Won 38 B+

8th

Yen CBO securitization

(6th SME Securitization)

2004.12.13 0.1 Yen 46 B+

9th 7th SME Securitization 2004.10.8 93.5 Won 43 B+

10th Piraruku Fund Ltd 2004.12.14 0.15 USD 74 B+

11th 8th SME Securitization 2005.6.30 84.7 Won 48 B+

Total 1,834.7 Won 598

P-CBO Programs for SMEs by SBC

Target WAR: BB - B+

Total Amount:1,834.7 billion KRW

# of firms: 598

Average funding per firm: 3 billion KRW

Special attention to

2nd: together with KCGF

8th : ABMI related Pan-Asian Bond

Title of SPC TypeReceivable

BackedMaturity

Currency Denomination

1st 1st SME SecuritizationSB(Straigh

t Bond)No 3 Local

2nd 2nd SME Securitization

SB No 1,2 Local

3rd KOROmas FundBW (Bond/

Warrant)No 3 USD

4th 3rd SME Securitization Loan Yes 3 Local

5th COROvoltin Fund BW No 5,7,10 USD

6th

4th SME Securitization Loan Yes 3 Local

7th

5th SME Securitization BW Yes 3 Local

8th



BW/SB No 3 JPY

9th 7th SME Securitization BW/SB/

LoanPartial(SB) 3 Local

10th Piraruku Fund BW No 5 USD

11th 8th SME Securitization BW No 3 Local

P-CBO Programs: Underlying Assets

Currency: local/G3

Maturity

: 3 years for local

5year for G3

Why 3 years benchmark

corporate bonds has 3

year tenor extending to 5

years is not economically

viable

Structure: three stages

introduction: SB(2nd with

KCGF) variation: Loan

backed by receivables

mature :BW

Currency: local/G3

Maturity

: 3 years for local

5year for G3

Why 3 years benchmark

corporate bonds has 3

year tenor extending to 5

years is not economically

viable

Structure: three stages

introduction: SB(2nd with

KCGF) variation: Loan

backed by receivables

mature :BW

Example of BW Structure: COROvoltin (5th)

Mezzanine bonds sold to domestic

investors

Warrants sold overseas

Participating

Companies

venture companies listed on KOSDAQ or IT companies which are expected to be listed soon

Companies’Needs

minimize interest rates (at the expense of issuing warrants) raise funds in USD ( in anticipation of won appreciation)

Warrant Investors’ Needs

Rationale for BW structure (Example: COROVoltin, 5th)Rationale for BW structure (Example: COROVoltin, 5th)

participate in the growth potentials of the companies offset the default loss with gain from exercising warrants

participate in the growth potentials of the companies offset the default loss with gain from exercising warrants

Title of SPC IssuerParticipating

InstitutionSenior Market SPC

3rd KOROmas Fund * o

5th COROvoltin Fund o

7th 5th SME Securitization

o o

8th



o o


o o

10th Piraruku Fund o o o o


o o o

Warrant Holders

SPC: buffer which offsets t

he default loss with either g

ain from exercising warrant

s or cash reserve from warr

ant sale

Market: speculators

(various methods including p

ublic auctions)

Issuer:

Corporate Control

interest alignment

Participant: Sweetener to m

ezzanine tranche

Senior :Sweetener

(*: linked to residuals after juni

or is paid off)

Warrants are detachable

Warrant Coverage:100%

Title of SPC Senior Junior Mezzanine

MezzanineInvestor

1st 1st SME Securitization 61.81% 38.19% - -

2nd 2nd SME Securitization 81% 19% - -

3rd KOROmas Fund 82.8% 17.2% - -

4th 3rd SME Securitization 84.6% 15.4% - -

5th COROvoltin Fund 76% 16.9% 7.1% Participant

6th

4th SME Securitization 81.63% 18.37% - -

7th

5th SME Securitization 85% 15% - -

8thYen CBO securitization(6th SME Securitization)

77% 20% 3% Participant

9th 7th SME Securitization 80.21% 17.65% 2.14% Issuer

10th Piraruku Fund 72.89% 17.11% 10% Issuer

11th 8th SME Securitization 70.01% 18% 9.9%/2%

Participant/issuer

Win-Win SME Securitization (tentative)

63.33% 18% 16.67%/2%

Mezzanine fund/issuer

Mezzanine Investors and Risk Sharing Structure

Senior: market

Junior: SBC

Mezzanine

Participating Institutions (underwriters,custodian banks), as they understand the risk better

Issuer: Moral Hazard

Market : Mezzanine Fund

Pool

WAR (B+)

38 firms

External Credit

Enhancement

:Bank C/L

Internal

;warrants 2%,

receivables:15%

Junior/SBC

Senior70.01%(AAA)

Junior18%

Mezzanine11.99%

Credit Enhancement Structure

Senior85%

(AAA)

Junior15%

43%

15%

25%

17%

Pool

WAR (B+)

48 firms

External:

Bank C/L

Warrants

46.49%

18%

16.53%

11.99%

Junior/SBC

Mezzanine

7%

Total 94.4 billion KRW

11th BW-Mezzanine 7th BW-receivable backed

Total 84.7 billion KRW

Variation: Piraruku Fund(10th)

Seller

(Hannuri)

Piraruku Fund

Limited

(SPV Issuer)

SBC

Junior Note (C & X Notes) SBC

BW Issuer

Investors

BW Issuer

Investors

Investors

BW Issuer

BW Issuer

BW Issuer

Hannuri

E70 Note

E69 Note

E3 Note

E2 Note

E1 Note

- par value of 10% of Reference Bonds reducing to

nil on Reference BW Event of Default

- [contractual option to exchange into 25% of

Reference Warrants any time after 2007]

US$25 million A1 Senior Floating Rate Notes due

2007 (semi-annual coupon and bullet redemption)

US$25 million A2 Senior Floating Rate Notes due


US$71 million A3Senior Floating Rate Notes due


Note Trustee

Portfolio Mana

ger

Advisor (Hann

uri)

Portfolio

Manager

(offshore)

Hannuri

Variation: Structure of Piraruku Fund(10th)

Foreign Exchange RiskManagement Program

run by SBC

SMEsBank

InvestorsSPC

Proceeds (\) Proceeds ($)Principal &Interest ($)

Principal &Interest ($)

Forward Contract

BW Issue

Principal &Interest (\)

Issuing companies can use Exchange Rate Risk Management Program to enter into custom-tailored forward contracts with banks at smaller costs

Issuing companies can use Exchange Rate Risk Management Program to enter into custom-tailored forward contracts with banks at smaller costs

SBC’s Foreign Exchange Risk Management Program

- Since the end of 1997, currency has fluctuated greatly

- SMEs, 42.2% of whose annual revenue comes from exports, suffered high exchange

rate risks

- SMEs incurred high transaction costs (due to small scale or poor credit) when they tried to

hedge their foreign exchange risk

SBC initiates an exchange-rate risk-management program for SMEs in 2004

- SBC selects SMEs to form pools

- SBC selects sponsoring banks

- SBC sets transaction costs associated with hedging activities

-loss sharing rule for default on forward contract:collateral money, 40% of fee

revenues to SBC, SBC

SBC initiates an exchange-rate risk-management program for SMEs in 2004

- SBC selects SMEs to form pools

- SBC selects sponsoring banks

- SBC sets transaction costs associated with hedging activities

-loss sharing rule for default on forward contract:collateral money, 40% of fee

revenues to SBC, SBC

Background of Exchange Rate management Program Background of Exchange Rate management Program

Reduce transaction fee

Exchange Risk Management Program - Continued

Before After Rate of Cost Reduction

Spot Rate Transaction Fee 1 won / $ 0.5 won / $ ▽ 50%

Forward Rate Transaction Fee 3 won / $ 1 won / $ ▽ 67%

Collateral (3 months) 10% of contract amount

1.5% of contract amount

▽ 85%

SMEs pay 0.5 – 0.75% in advance, and SBC matches the same amount

Duration of ContractCollateral rate

SME SBC

Forward Exchange

Within 7 days None None

Within a month Contract Amount x 0.5% Contract Amount x 0.5%

Within 3 months Contract Amount x 1.5% Contract Amount x 1.5%

Within 6 months Contract Amount x 3.0% Contract Amount x 3.0%

Within a year Contract Amount x 5.0% Contract Amount x 5.0%

Within 2 years Contract Amount x 7.5% Contract Amount x 7.5%

Future of P-CBO Program at SBC

P-CBO program will remain operative in the future

The maturity of bonds (issued by SMEs in the P-CBO programs) will be extended

from 3 years to 5 years

Mezzanine tranche is sold to the investors (since 8th transaction)

Junior tranche can be sold to other investors

CBO program can evolve to a platform program like “PROMISE” in Germany

P-CBO program will remain operative in the future

The maturity of bonds (issued by SMEs in the P-CBO programs) will be extended

from 3 years to 5 years

Mezzanine tranche is sold to the investors (since 8th transaction)

Junior tranche can be sold to other investors

CBO program can evolve to a platform program like “PROMISE” in Germany

V Implications to the Asian Bond Market

Initiative (ABMI)

2

Pan Asia Bond: Yen-denominated P-CBO

• Transaction date: December 13, 2004

• The issuance of Japanese yen-denominated P-CBO

between Korea and Japan is an important tangible

outcome for the endorsement of the Asian bond

market and also provides new sources for SMEs of

other countries in this region.

• The purpose of the issuance of yen-denominated P-

CBO is to create momentum for the development of

the Asian bond market and enhance economic

cooperation between Korea and Japan

• The securitization of a portfolio of yen-denominated

corporate bonds (Portfolio Securities) of 46 Korean

small and medium enterprises (Portfolio Obligors)

• Further credit-enhanced by the Industrial Bank of

Korea (IBK) and JBIC.

• The P-CBO interest rate is 20 to 30 basis points

lower than that for Korean won-denominated P-CBO,

even after taking the cost of hedging for foreign

exchange risks into account.

• Singapore instituted SME securitization program in

2005

Korean Proposal for ABMI: Structure of the Scheme

Country I

SME Loans/Bonds

SPCin

Country A

Senior

Junior

Senior

Junior

Senior

Junior

Country II

SME Loan/Bonds

Country III

SME Loan/Bonds

Senior

Junior

Regional Guarantee Mechanism

Credit guarantee

Issued in Country A’s currencyIssued in Local Currency

European Benchmark:EIF and SME securitization

Documents

Korea Fixed Income Research Institute Chung Ang University Risk Management and Sharing Case of South Korea Gyutaeg, Oh AFDC Workshop on Developing Asian