Measuring Securitization in the Flow of Funds Accounts in Japan

Yoshiko SatoFinancial Statistics SectionResearch and Statistics DepartmentBank of Japan

Working Party on Financial Statistics, OECD Paris, 2-4 November 20091/16

Motivation

Recent financial turmoil has led an increasing number of people to look into Flow of Funds Accounts (FFA) statistics.

The statistics is primarily designed to describe a country’s financial structure in rather a long-term perspective. But recent financial events set it to another task of providing information to narrow “data gaps” or to capture “shadow banking system” (as highlighted in G20).

In this sense, the paper intends to assess to what extent FFA captures the securitization under the current statistical treatment.

– How do we compile securitization figures? – What is the coverage of securitization? – What can we learn from the FFA data? – What should we do to improve the statistics? 2/16

Outline

1. Statistical treatment

2. Assessment of coverage

3. What can we learn from FFA data?

4. Possible future approach

5. Conclusion

- Definition of the sector and instruments.

- Compilation method (Sources/Scope/Valuation/ Holding sector)

- Treatment of securitization through JHFA

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1.Statistical treatment – sector, instruments What sector captures securitization activity?

How does the sector work?

“SPC and Trust” sectorA sub-sector of non-banks in other financial institution

It issues ABS, ABCP, and MCT backed by loans, installment credit (i.e. lease), bonds, and trade credits.

Loans Structured-financing instrumentsHousing loans ・ABSConsumer credits ・ABCPLoans to companies and Government ・MCT (Monetary claim trusts)

Installment creditCorpotate bondsTrade credits and foreign trade credits

SPC and Trust

80.8%

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Case 1Originator

(Banks) (Banks)

Case 2

Investors

Originator InvestorsTrust

Monetary claim trust (MCT)

Case 3

Loan sales (not securitization)

Trust

MCT

Originator InvestorsTrust

MCT

MCT

SPC

TrustABS

Trust

SPC and Trust

1.Statistical treatment – compilation method

Typical Securitization Scheme in Japan

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1.Statistical treatment – compilation method Sources

Scope of the “SPC and Trust” sector

Valuation

4 major trust banks 11 trust subsidiaries 5 trust companies

MCT Direct reporting from 20 institutions

ABS Publicly available dataaggregate data from JSDA (Japan Security Dealers Association) classified by each type of underlying asset.

ABCP Estimation is conducted by assuming that it is proportionate to MCT.

Private or public issues ABS includes privately placed issues but since there is no primary data we

conduct estimation.Residency Domestic bonds issued by non-resident SPC are within the scope of “SPC and Trust” sector but available data are limited to the publicly placed issues. 6/16Book value basis

Treatment of securitization through JHFA

1.Statistical treatment – compilation method

Information of holding sector

Most difficult part to know.

Holding amounts of banks, insurance companies, finance companies, and social security funds are based on the financial statement.Those of non-residents are estimated. The residual with no specific holding entity goes to private non-financial institutions.

JHFA (Japan Housing Finance Agency) is the largest issuer of MBS. The outstanding amount of MBS reaches 8.9 trillion yen.

JHFA’ securitization is “On-balance sheet” securitization. So it is excluded from the SPC and Trust sector but included in the “Government financial institution” sector.

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2. Assessment of coverage

FFA has a good coverage in that

However, the coverage is incomplete in that

All major financial institutions are contributing to reporting MCT which are quite often used in Japan’s securitization.

Private placement and non-resident SPC are partly covered.

Primary data source of private placement of ABS/MBS is almost absent.

Non-resident SPC’s private placement is inseparable from the primary data source of BP and IIP statistics.

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0

5

10

15

20

25

30

35

40

1997

.04

1998

.02

1998

.04

1999

.02

1999

.04

2000

.02

2000

.04

2001

.02

2001

.04

2002

.02

2002

.04

2003

.02

2003

.04

2004

.02

2004

.04

2005

.02

2005

.04

2006

.02

2006

.04

2007

.02

2007

.04

2008

.02

2008

.04

2009

.02

Total Assets

(trillion yen)

Total assets of the SPC and Trusts sector

There is outstanding of 30 trillion yen in Structured-financing instruments.

The data correctly traces the turning point of the sector in mid 2007.

The volume has been expanding during the first half of 2000s.

3. What can we learn from FFA data?　　 (1) Turning point

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40.5%

25.8%

19.0%

9.7%

4.5% 0.6%

Housing loans

Loans to companies and governments

Trade credits and foreign trade credits

Installment credit (i.e. lease)

Consumer credits

Corporate Bonds

22.7%

33.5%

24.6%

12.6%

5.8%0.7%

Housing loans

Loans to companies and governments

Trade credits and foreign trade credits

Installment credit (i.e. lease)

Consumer credits

Corporate Bonds

Proportion of Underlying Assets

“Housing loans” includes JHFA’s MBS.

“Housing loans” excludes JHFA’s MBS.

3. What can we learn from FFA data?　　 (1) Turning point

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SPC and Trust sector classified by type of underlying assets

Housing loans

0

1

2

3

4

5

6

7

8

9

1997

.04

1998

.02

1998

.04

1999

.02

1999

.04

2000

.02

2000

.04

2001

.02

2001

.04

2002

.02

2002

.04

2003

.02

2003

.04

2004

.02

2004

.04

2005

.02

2005

.04

2006

.02

2006

.04

2007

.02

2007

.04

2008

.02

2008

.04

2009

.02

(trillion yen)

0

2

4

6

8

10

12

14(trillion yen)

Loans to companies and governments

0

1

2

3

4

5

6

7

8

9

10(trillion yen)

Trade credits and foreign trade credits

0

1

2

3

4

5

6

1997

.04

1998

.02

1998

.04

1999

.02

1999

.04

2000

.02

2000

.04

2001

.02

2001

.04

2002

.02

2002

.04

2003

.02

2003

.04

2004

.02

2004

.04

2005

.02

2005

.04

2006

.02

2006

.04

2007

.02

2007

.04

2008

.02

2008

.04

2009

.02

(trillion yen)

Installment credit (i.e. lease)

3. What can we learn from FFA data?　　 (1) Turning point

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Balance of Payment Statistics

-1

0

1

2

3

4

5

6

1997

.04

1998

.02

1998

.04

1999

.02

1999

.04

2000

.02

2000

.04

2001

.02

2001

.04

2002

.02

2002

.04

2003

.02

2003

.04

2004

.02

2004

.04

2005

.02

2005

.04

2006

.02

2006

.04

2007

.02

2007

.04

2008

.02

2008

.04

2009

.02

(trillion yen)

Direct investment

-20

-15

-10

-5

0

5

10

15

20

1997

.04

1998

.02

1998

.04

1999

.02

1999

.04

2000

.02

2000

.04

2001

.02

2001

.04

2002

.02

2002

.04

2003

.02

2003

.04

2004

.02

2004

.04

2005

.02

2005

.04

2006

.02

2006

.04

2007

.02

2007

.04

2008

.02

2008

.04

2009

.02

(trillion yen)

Portfolio investment in securities

Both increase toward the 4Q 2008 and decrease shortly after then.

If we assume that a part of such increase should attribute to any private placements of non-residents SPC, the figure would have behaved differently; it might have continued to increase until the end 2008.

3. What can we learn from FFA data?　　 (2) Cross-border securitization

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Expected transactions to be captured

Transactions really happened Banks’ Recapitalization

Securitization

Borderline Sells assetsTokyo branch of the non-resident SPC

Issues MBS

Borderline

Banks

Domestic Investors

Subordinated loans

OriginatorNon-resident

SPC

Non-resident SPC

Domestic Investors

Buy MBS

Portfolio investment in securities (outward)

Preferred stocks

Direct investment or portfolio investment in securities (outward)

3. What can we learn from FFA data?　　 (2) Cross-border securitization

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Types of SPC related transaction

Total 30.5

Financial institutions 23.0

Depository corporations 12.0

Insurance 8.6

Pension funds 0.9

Other financial institutions 1.5

Non-financial corporations 6.7

General government 0.0

Rest of the world 0.8

(trillion yen)

Sources: Bank of Japan, “Flow of Funds Accounts”

3. What can we learn from FFA data?　　 (3) Holding sector of “Structured-financial instruments”

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4. Possible Future Approach

Use of electronically registered data for statistical purpose instead of using survey data

International co-operation in data collection

Using existing data source is efficient without additional reporting burden if the data is permitted to use for social statistical purpose.

Electronically registered book-entry transfer system (i.e. JASDEC) has already been in operation. Such database is expected to contain security-by-security information.

Co-operation between the related bodies (industry association, depository center, other statistical authorities) should be prerequisite.

Statistics may not improve solely by compilers’ domestic efforts. International co-operation in data collection is helpful for identifying cross-border secutitization.

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5. Conclusion

Enriching primary data source is needed.

Data gap is a problem where no primary data exists.

Usefulness of FFA can be more enhanced by precise primary data.

FFA serves to capture securitization activity.It correctly traces the turning point in mid 2007.

- End of presentation -

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