Measuring Securitization in the Flow of Funds Accounts in Japan Yoshiko Sato Financial Statistics Section Research and Statistics Department Bank of Japan Working Party on Financial Statistics, OECD Paris, 2-4 November /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 3/16

1.Statistical treatment – sector, instruments What sector captures securitization activity? How does the sector work? SPC and Trust sector A 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. 80.8% 4/16

Case 1 Originator (Banks) Case 2 Investors OriginatorInvestorsTrust Monetary claim trust (MCT) Case 3 Loan sales (not securitization) Trust MCT OriginatorInvestorsTrust MCT SPC Trust ABS Trust SPC and Trust 1.Statistical treatment – compilation method Typical Securitization Scheme in Japan 5/16

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 data aggregate 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. 6/16 Book 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. 7/16

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 Japans securitization. Private placement and non-resident SPC are partly covered. Primary data source of private placement of ABS/MBS is almost absent. Non-resident SPCs private placement is inseparable from the primary data source of BP and IIP statistics. 8/16

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 The volume has been expanding during the first half of 2000s. 3. What can we learn from FFA data? (1) Turning point 9/16

Proportion of Underlying Assets Housing loans includes JHFA s MBS. Housing loans excludes JHFAs MBS. 3. What can we learn from FFA data? (1) Turning point 10/16

SPC and Trust sector classified by type of underlying assets Housing loans Loans to companies and governments Trade credits and foreign trade creditsInstallment credit (i.e. lease) 3. What can we learn from FFA data? (1) Turning point 11/16

Balance of Payment Statistics Direct investmentPortfolio 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 What can we learn from FFA data? (2) Cross-border securitization 12/16

Expected transactions to be captured Transactions really happened Banks RecapitalizationSecuritization Borderline Sells assets Tokyo branch of the non-resident SPC Issues MBS Borderline Banks Domestic Investors Subordinated loans Originator 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 13/16 Types of SPC related transaction

Total30.5 Financial institutions23.0 Depository corporations12.0 Insurance8.6 Pension funds0.9 Other financial institutions1.5 Non-financial corporations6.7 General government0.0 Rest of the world0.8 (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 14/16

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. 15/16

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 End of presentation - 16/16