Abstract Small and medium-size enterprises (SMEs) are the engine of economic deve- lopment, but market imperfections such as those caused by underdeveloped fi- nancial and legal systems impede their growth. Although SMEs form a large part of private sector in many countries, they face larger growth constraints and are less likely to have access to formal sources of external finance than large firms. SMEs have the characteristics of informational opacity, weak finance, imperfect management and small size. These characteristics bring about moral hazard and adverse election, implying high credit risk of SMEs. Lending technologies can help facilitate SMEs¡¦ access to finance. The credit supplementation institutions have significant effects on SMEs credit availa- bility, so it becomes an important issue to policy makers around the globe setting up relevant legal systems and supporting financial assistance to SMEs. Since The New Basel Capital Accord had released the criteria and credit risk models of regulatory capital requirements for banks to follow, how to choose an appropriate model to measure the credit risk of SMEs and reasonably price the loan assets on a risk-return basis have become a common task of banks and the credit supplementation institutions. This paper uses the model developed by Kuo (2003) - ¡§How to Gauge the Default Probability: An Empirical Investigation of the Market-Based Approach to Bank¡¦s Loan Asset ¡¨ to gauge the probability of default to bank¡¦s loan asset for SMEs which guaranteed by Taiwan SMEG. Using market-based risk neutral approach, the probability of default for each SMEs¡¦ loan will be endogenously determined. This paper also uses the actuarial valuation principles to simulate the reasonable guarantee fee which should be received by SMEG through the breakeven analysis. The empirical results show that: 1.The tradeoff between recovery rate and the probability of default has joint effects. The probability of default increases rapidly while the recovery rate is over 70% and decreases smoothly while the recovery rate is below 60%. 2.The guaranteed loans over 70% coverage under the Authorized Approach have higher probability of default, as banks usually depend on the credit supp- lementation institutions for the larger portion of subrogation payment. 3.The guaranteed loans below 60% coverage under the Normal Approach have lower probability of default, as banks won¡¦t endure high probability of default and will turn to be conservative while lending to SMEs. Banks must also forward the relevant documents to the Taiwan SMEG for scrutiny and consideration, and it has reduced the default risk. 4.The guaranteed loans of 100% coverage under the Package Credit Guarantee have the highest probability of default if banks fully depend on the whole guaranteed coverage. However the bank loans lose given default will rely on bank¡¦s lending strategy, as the subrogation rate is set to be fixed on a maximum limit of guaranteed loans. 5.Using the actuarial valuation principles, with the estimations of pro- bability of default the reasonable rate of guarantee fee can be simulated through the breakeven analysis. The contribution of this paper is to submit the practical value for bank¡¦s loan pricing strategy, lending policy decision and credit risk management, also submit a subsidiary referential implication for SMEG to set the rate of guarantee fee, using the reduced form model to estimate default probability of bank¡¦s loan assets for SMEs which guaranteed by Taiwan SMEG, and using the actuarial va- luation principles to simulate the guarantee fee through the breakeven analysis.

L'elemento che distingue un'operazione di cartolarizzazione consiste, secondo la definizione espressa nell'accordo di Basilea2, nell'identificazione di almeno due differenti posizioni di rischio (tranche), stratificate e subordinate, emesse a fronte di uno specifico portafoglio di attività. Nonostante il ricorso al tranching sia ampiamente diffuso e standardizzato le determinanti che giustificano il ricorso all'emissione multi-tranche sono ad oggi poco approfondite. Inoltre, i titoli emessi a fronte di operazioni di cartolarizzazione (CDO) possiedono profili di esposizione al rischio di credito differenziati, in termini di incidenza delle perdite attese ed inattese, ed in termini di correlazione con altri fattori di rischio: la valutazione del profilo di rischio è condizione necessaria per l'attribuzione di un giudizio di rating e per la definizione di un appropriato premio al rischio (pricing). Si rivela necessaria tanto la stima della distribuzione delle perdite del portafoglio (credit risk modelling) quanto l'analisi strutturale dei flussi di cassa generati e l'allocazione degli stessi alle tranche (cash flow modelling). Sulla base della letteratura di security design la tesi intende valutare l'efficienza del processo di intermediazione basato sulla cartolarizzazione multi-tranche rispetto all'intermediazione bancaria tradizionale e a forme di asset-backed security con unica tranche e focalizza l'analisi attraverso una verifica empirica delle teorie economiche a supporto del tranching, con particolare riferimento alla cartolarizzazione dei prestiti concessi ad imprese di piccola e media dimensione, oggetto di analisi specifica condotta nell'ambito di un'esperienza di stage presso il Fondo europeo degli investimenti. Quindi, grazie alla realizzazione di un modello computazionale sviluppato con un software di pianificazione finanziaria multidimensionale (Quantrix), la tesi presenta un approfondimento delle technicalities, mediante una modellizzazione dei flussi e della loro allocazione (Waterfall Payment Order), allo scopo di apprezzare il valore aggiunto di queste strutture di intermediazione. Aspetto, questo, non sviluppato nella letteratura accademica. L'analisi si rivolge alle operazioni realizzate nell'ambito dei due principali programmi di cartolarizzazione dei prestiti alle PMI attuati in Europa (Ftpyme e Promise). / Securitisation is a structured finance instrument which involves pooling of financial assets (such as loans and bonds) and creating multiple tranched liabilities, collateralized debt obligation (CDO), of a single issuer with different risk-return characteristics, which are sold as separate securities. According to the New Basel Capital Accord, tranching is the key feature that distinguishes securitisation transactions; although commonly applied, the factors that determine the extent and the nature of tranching remain largely unknown. Moreover, because tranching allows the risk characteristics of the collateral pool to be transformed, it contributes to transaction complexity in assessing the risk properties of such structured instruments: the risk profile that can be generated through tranched exposure, in terms both of expected/unexpected incidence losses and correlated default of pool assets, can lead to substantial differences among tranches, depending on the level of subordination below a certain tranche. Key to the reliability of structured finance pricing and ratings is the accuracy in assessing the credit risk in the underlying portfolio (credit risk modelling), as well as the accurate modelling of the distribution of cash flows to different classes of CDO (cash flow modelling). By analyzing the finance literature relating to security design and securitization this thesis provides an analysis of the efficiency of financial intermediation model based on securitisation and an empirical test of theories supporting the economic added value of tranching, with regard to SMEs loan securitisation, which topic was specifically investigated during a stage at the European Investment Fund. By realization of a computational model, performed using a multidimensional modelling software (Quantrix), the thesis closely examines securitisation transaction's technicalities, by modelling both portfolio cash flows and funds allocation (Waterfall Payment Order), in order to asses the ability of the structure to withstand various stressed scenarios. This analysis offers an analytical and micro-approach to securitisation transactions, which has not deeply investigated in academic literature yet. The model applies to SMEs loan securitisation transactions, concluded within specific securitisation European Programme (Ftpyme in Spain and Promise in Germany).