The aim of this study is to evaluate the risk-return efficiency of credit policies for managing portfolio credit risk of banking institutions. The focus of the empirical analysis is on the impact of risk pricing and problem loan restructuring on bank risk and returns using a simulation model that represents an operating environment of lenders servicing the Australian farm sector. Insurance theory principles and agency relationships between a borrower and a lender are integrated into the portfolio theory framework. The portfolio theory framework is then couched in terms of the capital budgeting approach to generate a portfolio return distribution function for a particular credit policy regime. Borrowers are segmented by region, industry, loan maturity and credit risk class. Each credit risk class defines risk constraints on which a stochastic simulation model may be developed for credit scoring an average borrower in a portfolio segment. The stochastic simulation method is then used to generate loan security returns for a particular credit policy regime through time with loan return outcomes weighted by the number of borrowers in a segment to give measures of portfolio performance. Stochastic dominance efficiency criteria are used to choose between distributions of NPV of bank returns measured for a number of credit policy alternatives. The findings suggest that banks servicing the Australian farm sector will earn more profit without additional portfolio risk if the maximum limit to which pricing accounts for default risk in loan reviews is positively linked to volatility of gross incomes of farm business borrowers. Importantly, credit-underwriting standards must also be formulated so as to procure farm business borrowers of above average productivity with loans that are fully secured using fixed assets. The results of simulations also suggest that restructuring loans in event of borrower default provide for large benefits compared to a �no restructuring� option.

This thesis is composed of three chapters. The first two chapters provides novel approaches for modeling and estimating the dependence structure for a large portfolio of assets using rating data. In both chapters a natural form of organizing a portfolio in terms of the levels of exposure to economic sectors and geographical regions, plays a key role in setting up the dependence structure. The last chapter investigates weather financial strategies that exploit sector or geographical heterogeneity in the asset space are relevant in terms of portfolio optimization. This is also done in a context of a large portfolio but with data on stock returns.

This thesis deals with credit risk modeling and related mathematical issues. In particular we study first-passage models for credit risk, where obligors default upon first passage of a ``credit quality" process to zero. The first passage problem for correlated Brownian motion is a mathematical structure which arises quite naturally in such models, in particular the seminal multivariate Black-Cox model. In general this problem is analytically intractable, however in two dimensions analytic results are available. In addition to correcting mistakes in several published formulae, we derive an exact simulation scheme for sampling the passage times. Our algorithm exploits several interesting properties of planar Brownian motion and conformal local martingales. The main contribution of this thesis is the development of a novel multivariate framework for credit risk. We allow for both stochastic trend and volatility in credit qualities, with dependence introduced by letting these quantities be driven by systematic factors common to all obligors. Exploiting a conditional independence structure we are able to express the proportion of defaults in an asymptotically large portfolio as a path functional of the systematic factors. The functional in question returns crossing probabilities of time-changed Brownian motion to continuous barriers, and is typically not available in closed form. As such the distribution of portfolio losses is in general analytically intractable. As such we devise a scheme for simulating approximate losses and demonstrate almost sure convergence of this approximation. We show that the model calibrates well, across both tranches and maturities, to market quotes for CDX index tranches. In particular we are able to calibrate to data from 2006, as well as more recent ``distressed" data from 2008.

This thesis deals with credit risk modeling and related mathematical issues. In particular we study first-passage models for credit risk, where obligors default upon first passage of a ``credit quality" process to zero. The first passage problem for correlated Brownian motion is a mathematical structure which arises quite naturally in such models, in particular the seminal multivariate Black-Cox model. In general this problem is analytically intractable, however in two dimensions analytic results are available. In addition to correcting mistakes in several published formulae, we derive an exact simulation scheme for sampling the passage times. Our algorithm exploits several interesting properties of planar Brownian motion and conformal local martingales. The main contribution of this thesis is the development of a novel multivariate framework for credit risk. We allow for both stochastic trend and volatility in credit qualities, with dependence introduced by letting these quantities be driven by systematic factors common to all obligors. Exploiting a conditional independence structure we are able to express the proportion of defaults in an asymptotically large portfolio as a path functional of the systematic factors. The functional in question returns crossing probabilities of time-changed Brownian motion to continuous barriers, and is typically not available in closed form. As such the distribution of portfolio losses is in general analytically intractable. As such we devise a scheme for simulating approximate losses and demonstrate almost sure convergence of this approximation. We show that the model calibrates well, across both tranches and maturities, to market quotes for CDX index tranches. In particular we are able to calibrate to data from 2006, as well as more recent ``distressed" data from 2008.

The aim of this research is to produce a model allowing me to estimate the credit risks in the aggregate and the sectors levels of the Swedish economy in response to the evaluation of key macroeconomic variables. In order to estimate the credit risk models for the Swedish economy, one-factor models were used and the employed data were covering the period from 2003 to 2011. One factor models’ estimations for the sectors facilitate a comparison of default rates’ determiners between different sectors. The analyze part of the thesis starts with the estimation of the credit risk model at the aggregate economy level and it follows by the estimation of the models for different sectors. Ten different sectors are analyzed and for all sectors, the default rate models are produced. Furthermore, the paper presents some examples of applying the estimated models to macro stress testing. The findings demonstrate that in the transport and in the sector others, the most significant macroeconomic indicators were GDP, interest rates and repo rates. But, in all other sectors: GDP, interest rates and inflation rates showed the highest significant results. All coefficients were significant at the 5 % confidence level either in aggregate level or in sectors level. The interest rates showed positive relations with the default rates while the GDP and the inflation rates showed opposite relations. Reciprocal analyzes of the sectors indicated that compared to other sectors, the default rates in the financial sector strongly depended on the GDP and in the construction sector it weakly depended on inflation rates. In addition, the credit risks were varying between the sectors. At the education and the sector others, default rates were low, fluctuated between 0 and 0.05%. In contrast, at the manufacturing, the wholesale, the transportation, and the finance sectors the default rates were very high. It fluctuated between 0.03% and 0.16%. Finally, estimated models were used for the sensitive analyze of default rates by creating shocks over the independent variables. So, these calculations provided that, the default rates in financial activities sector were the most sensible sector during the shock at the GDP and the default rates in the construction sector were the most insensible ones during the shock at the interest rates and the inflation rates. To conclude, the results of this thesis can help understand the relationship between credit risk and macroeconomic indicators. This research provides important findings on how the macroeconomic indicators influence the default rates of Swedish economy either at the aggregate or at the sectors level. The calculated models can be used for the default rates’ prediction or stress testing.

Background: Small businesses are considered as a valuable source for the society and the economic growth and bank loan is the main source of finance for them. Small businesses are commonly seen as riskier than larger businesses it is thus noteworthy to examine banks’ credit assessment for small businesses. The implementation of the Basel III Accord will start in 2013 with the aim to generate further protection of financial stability and promote sustainable economic growth, and the main idea underlying Basel III is to increase the capital basis of banks. Purpose: The purpose of this study is to describe how larger and smaller banks in Sweden are managing credit assessment of small businesses, and if this process differs according to the size of the bank. The authors further want to investigate how expectations of new capital regulations, in form of Basel III, affect the credit assessment and if it is affecting the ability of small businesses to receive loans. Method: In order to meet the purpose of the thesis a mixed model approach is used. The authors conducted semi-structured interviews with representatives from three smaller and three larger banks. Additional, statistics were computed in order to examine the economic state of the Swedish market, where also an archival research with 10 allocated banks operating with corporate services was executed. Conclusions: The banks have a well-developed credit process where building a mutual trust relationship with the customer is crucial. If the lender has a good relationship with the customer, it will ease the collection of credible information and thus enhance the process of making right decision. The research examined minor differences between smaller and larger banks in their credit assessment. Currently, the banks do not see any problems with adjusting to the new regulation and thus do not see specific effects for small businesses and their ability to receive loans. The effects that can be identified by the expectations of Basel III are the banks’ concern of charging the right price for the right risk and the demand of holding more capital when lending to businesses. The banks have come a long way on the adjustment to Basel III, which has pros and cons, thus it implies that banks are already charging customers for the effect of the regulations that will not be 100 percent implemented until 2019. The difference that was identified between larger and smaller banks is that larger banks seem to have more established strategies when working on the implementation of Basel III.

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Issuing cash cards brings banks a large amount of money from interest and fees. Because of the reason, many banks that refused to join the competition in the beginning changed their minds and offer the similar product to compete with each other. In such intensified competition environment, in order to earn customers¡¦ attention and grab the market shares, banks simply loosen the approved criteria, increase the approved speed, and lower the interest rates. However, if banks take these actions without thinking carefully or planning cautiously, it is very easy to have problems in the risk management. This research try to from the organization staffs¡¦ point of view to discuss what kinds of policies will affect their risk management perception and if there is any relationship between perception and achievement. Besides, this research also tries to understand where risk management should put great emphasis and what kinds of risks banks should pay attention when operating the business of cash cards This research assumes different card approved time, interest rates, credit limit update time, and credit evaluation systems will affect cash cards risk management perception. And the results find that higher interest rates and credit evaluation systems designed by foreign have significant effect for cash cards risk management perception. Besides, procedures planning and customers choosing will also affect the perception. All in all, banks with better risk management perception have better performance in the market shares. As for the risk sources, the main risks come from customers choosing. Therefore, banks should have developed credit risk measure systems, or in the future banks will suffer because of these problems.

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