Credit Risk Transfer and Systemic Risk. Study Case on Romania

1. Credit Risk Transfer and Systemic Risk. Study Case on Romania Coordonator: PhD.Professor Moisa ALTAR Student: Irina LUPA

2. Introduction • Remarks by Chairman Alan Greenspan (1998)“In the context of bank capital adequacy, supervisors increasingly must be able to assess sophisticated internal credit risk measurement systems, as well as gauge the impact of the continued development in securitization and credit derivative markets. It is critical that supervisors incorporate, where practical, the risk analysis tools being developed and used on a daily basis within the banking industry itself. If we do not use the best analytical tools available, and place these tools in the hands of highly trained and motivated supervisory personnel, then we cannot hope to supervise under our basic principle -- supervision as if there were no safety net.” (1999) “Heavier supervision and regulation designed to reduce systemic risk would likely lead to the virtual abdication of risk evaluation by creditors of such entities, who could--in such an environment--rely almost totally on the authorities to discipline and protect the bank. The resultant reduction in market discipline would, in turn, increase the risks in the banking system, quite the opposite of what is intended. Such a heavier hand would also blunt the ability of U.S. banks to respond to crisis events. Increased government regulation is inconsistent with a banking system that can respond to the kinds of changes that have characterized recent years, changes that are expected to accelerate in the years ahead.”

3. Literature Review • D. Baur and E. Joossens (2005) • M. Davis and V. Lo (2001) • Upper and Worms (2004) • C. H. Furfine (2003) • O. De Bandt and P. Hartmann (2000) • F. Allen and D. Gale (2000)

4. Defaults Exposures portfolio SPV Investor holdings scenarios LOSS Investors state of default Inter-bank linkages matrix Default of credit institutions by contagion effect The measurement of the aggregatedimpact The conceptual model of the impact a securitization might have on financial stability

5. Data • Logit Model: • Credit Register – the status of default of companies in debt (Dec. 2004 and Dec. 2005) • Ministry of Finance – financial statements of companies (Dec. 2004) • Securitization: • Credit Register – value of loan exposures to companies (Dec. 2004) • Contagion: • the matrix of inter-bank exposures (Dec. 2005) • the level of own funds for each bank (Dec. 2005) • the value of assets for each bank (Dec. 2005) • the value of the risk-weighted assets for each bank (Dec. 2005)

6. Originator’s Loan Portfolio Loan portfolio structure of the originator Loan portfolio of the originator

7. Originator’s Loan Portfolio The securitization will only include a fraction of the institution’s company loans portfolio. The securitized exposure amounts will affect the institution’s total risk-weighted assets (RWA). In order to determine the appropriate weighted exposure amount we develop a logit model that evaluates debtor’s probability of default (PD). The RWA will be calculated according to the provisions of Basel II. Risk-weighted assets (RWA) = K x 12.5 x EAD Capital requirement (K) =[LGD×N[(1 – R)^-0.5×G(PD)+(R/(1 – R))^0.5×G(0.999)]–PDxLGD]x(1–1.5 x b)^-1×(1+(M– 2.5)×b) Correlation (R) = 0.12 × (1 –EXP(-50 ×PD)) /(1 –EXP(-50)) + 0.24 ×[1 –(1 –EXP(-50 × PD))/(1 –EXP(-50))] Maturity adjustment (b) = (0.11852 – 0.05478 × ln(PD))^2 • LGD – loss given value has been considered to be 45% • M – the maturity is considered 2.5 yrs.

8. Logit Model • The variables, that have the highest discriminatory power, and are included in the model are: • the term of recovery of receivables (trc); • the rate of repaying short-termed debt (tmps); • net cash-flow rate (tn12at).

9. Logit Model Statistics Roc curve of the model AUROC value after 1000 bootstrap iterations

10. Rating Scale Estimated Default Probabilities Distribution among debtors

11. The Holding of Securitizations • senior securitizations • junior securitizations

12. The Value of Securitizations after Inflicted Loss The initial shock in the system is generated by a random number of defaults in the securitized portfolio. The value of the absolute loss is generated by adding up exposures, in a descending default probability manner, until the total defaulted number is equal to that of the random number. The effect of the absolute loss on the value of the securitizations is: Where a’i and x’i represent the value of the junior and senior securitizations after the loss, V is the portfolio value, L is the level of loss, s and j are those discussed above.

13. Inter-bank Linkages The matrix of inter-bank exposures highlights the inter-bank assets of each credit institution to the other (n-1) banks in the system (left picture). The weight of inter-bank exposures compared to own funds show there are only a few banks that could default due to the loss of all their inter-bank exposures (right picture). • Inter-bank linkages determine an incomplete structure (according to Allen&Gale (2000)) • only 4 banks are exposed to insolvency if they lost all of their inter-bank exposures

14. Inter-bank Linkages If the inter-bank matrix is: , where xij is the gross exposure of bank “i” to bank „j”. Then, the propagation of loss takes place the following way: , where xij has the same meaning as above and pjrepresents inter-bank liabilities of bank “j”. Insolvency occurs whenever the insolvency indicator (IS) drops under 2%. When a bank defaults, it is removed from the matrix and analyses are continued the next round. Then IS is calculated for the remaining non-defaulted banks in the system.

15. Results Average number of investor-banks that default in the first round (s1) Average number of banks that default by contagion in the following rounds (m1) Average share of the system assets that default by contagion in the following rounds (sever1) Average share of the system assets that default in the first round (atd)

16. Results • Inter-bank exposures are multipliedby 2 Average number of banks that default by contagion in the following rounds (m1) Average share of the system assets that default by contagion in the following rounds (sever1) Only in some cases does the amount of inter-bank exposures exceed the credit institution’s level of own funds. The labeled values mark these institutions at risk.

17. Results • Inter-bank exposures aremultipliedby3 Average number of banks that default by contagion in the following rounds (m1) Average share of the system assets that default by contagion in the following rounds (sever1) There are more situations where the amount of interbank exposures exceed the credit institution’s level of own funds in this case. The labeled values mark these institutions at risk.

18. Results We assume that three credit institutions default simultaneously. This would mean that automatically all their loans on the inter-bank market will be considered losses to other banks. This is the maximum effect that can take place on the inter-bank market. • Inter-bank exposures arenot multiplied • Inter-bank exposures aremultiplied by 2 • Inter-bank exposures aremultiplied by 3

19. Conclusions • credit risk transfer does not have major implications on the financial stability, given that the credit institutions are capitalized. • the inter-bank market is characterized by both a low degree of connectivity (10.43%) and a low level of exposure amounts, issues that will significantly reduce contagion risk, given that investors will default as the result of very poor quality of the purchased securitizations. Generally, the banks that are affected by contagion are the small ones and even so the average number of banks that default is 0.005. The average defaulted assets due to contagion is around 0.026% and the maximum number of contagion rounds is 2.

20. Bibliography

21. Thank you for your attention!