As a result of the change of financial environment, the competition of domestic banking industry has become more intense, and its management has also met the challenge. In order to grow the operating activities, the bank of Taiwan become less dependent on traditional deposit and loan activities and then turns to develop the non-traditional activities. Therefore the non-interest income increases year by year and the development of operating activities diversification has become the main business model to promote the profit. Based on the above reason, the study use the market and account data of listed banks from 1991 to 2009 to investigate the impact of operating activities diversification on the risk and performance of banks. The result of the empirical analysis by the accounting data shows that the higher degree of operating activities diversification can reduce the bank risk, but the performance is not actually good. When the bank develops the operating activities diversification by increasing the non-interest income, the risk will be getting higher but the performance will be getting better. Therefore, the banking industry can¡¦t put too much stress on the non-interest income. It should make the adequate decision between the risk and the performance. On the other hand, the result of the empirical analysis by the market data shows that the higher degree of operating activities diversification can increase the fluctuation of the stock price and when the non-interest income increases, Tobin's Q value gets higher. It demonstrated that the investors of the stock market anticipated the bank can improve the performance by increasing the non-interest income activities and gives recognition.

This paper investigates the influence of the shares of non-interest income and the diversification, which result from off-balance sheet activities, on the performance of banking in Taiwan. I also use ARCH-M model in this study. The sample period is from January 2000 to December 2011. I find that all sample banks and private banks do not benefit from off-balance sheet activities, but government banks benefit from off-balance sheet activities. In this paper, I also use CUSUM test to find the structural breakpoint and discuss the situation in accordance with it. The result shows that the structural breakpoint is at July 2002, which closes to the founded time of lots of financial holding companies. After the structural breakpoint, the positive impact of shares of non-interest income and diversification on the performance disappear.

Banking is topic, practice, business or profession almost as old as the very existence of man, but literarily it can be rooted deep back the days of the Renaissance (by the Florentine Bankers). It has sprouted from the very primitive Stone-age banking, through the Victorian-age to the technology-driven Google-age banking, encompassing automatic teller machines (ATMs), credit and debit cards, correspondent and internet banking. Credit risk has always been a vicinity of concern not only to bankers but to all in the business world because the risks of a trading partner not fulfilling his obligations in full on due date can seriously jeopardize the affaires of the other partner. The axle of this study is to have a clearer picture of how banks manage their credit risk. In this light, the study in its first section gives a background to the study and the second part is a detailed literature review on banking and credit risk management tools and assessment models. The third part of this study is on hypothesis testing and use is made of a simple regression model. This leads us to conclude in the last section that banks with good credit risk management policies have a lower loan default rate and relatively higher interest income.

<p>Banking is topic, practice, business or profession almost as old as the very existence of man, but literarily it can be rooted deep back the days of the Renaissance (by the Florentine Bankers). It has sprouted from the very primitive Stone-age banking, through the Victorian-age to the technology-driven Google-age banking, encompassing automatic teller machines (ATMs), credit and debit cards, correspondent and internet banking. Credit risk has always been a vicinity of concern not only to bankers but to all in the business world because the risks of a trading partner not fulfilling his obligations in full on due date can seriously jeopardize the affaires of the other partner.</p><p>The axle of this study is to have a clearer picture of how banks manage their credit risk. In this light, the study in its first section gives a background to the study and the second part is a detailed literature review on banking and credit risk management tools and assessment models. The third part of this study is on hypothesis testing and use is made of a simple regression model. This leads us to conclude in the last section that banks with good credit risk management policies have a lower loan default rate and relatively higher interest income.</p>

The dissertation thesis analyzes reasons for the consolidation of the banking sector in the Czech Republic, the shape of the consolidation and impact of the consolidation institution's activities on the performance of the Czech banking sector. The first part of the research deals with the reasons for consolidation, i.e. specificities of the banking sector in the Czechoslovakia before 1989 and the transformation of the banking sector during the 1990s. The factors analyzed significantly influenced the processes of disintermediation, universalization and diversification in commercial banking. The analysis of banking profitability measures, which is the second part of my dissertation thesis, employs those aspects mentioned above. The thesis concludes there was an objective necessity to consolidate the banking sector after 1990. However, the consolidation process had been influenced by both a deficient institutional environment and inflation of goals set for consolidation institutions. This generated inefficiencies related to the activities of consolidation institutions (e.g. the management of receivables and rent-seeking) and also influenced the income and profit performance measures of the banking sector in the Czech Republic.

Denna studie undersöker hur intäktsdiversifiering i europeiska bankverksamheter påverkar aktiemarknadens värdering och variationen i aktiepriserna. Europeiska bankverksamheter har sedan mitten på 1980-talet expanderat mot tjänster som genererar provisionsintäkter eftersom den historiska uppfattningen har varit att intäktsdiversifiering kan minska variationen i vinsterna och potentiellt öka marknadsvärderingen. Effekten av intäktsdiversifiering studeras utifrån OLS-regressioner på paneldata som består av 103 bankverksamheter från 24 länder i Europa för perioden 2005 till 2012. Aktiemarknadens värdering och variationen i aktiepriserna beräknas utifrån data över aktiepriser och från bankverksamheternas finansiella rapporter. Denna studie undersöker även resultatens ekonomiska signifikans för att utvärdera implikationerna av intäktsdiversifiering. Resultaten visar att en högre intäktsdiversifiering har en positiv effekt på aktiemarknadens värdering. Mer specifikt förväntar sig aktiemarknaden att ‘fee income’ har en positiv effekt på framtida vinster. Däremot innebär en högre intäktsdiversifiering även en högre variation i aktiepriserna. Den ekonomiska signifikansen visar att en högre intäktsdiversifiering främst har en betydande effekt på aktiemarknadens värdering och aktiens systematiska risk. Avslutningsvis framstår effekterna även ha varierat under tidsperioden och var större under den senaste finanskrisen. / This study examines how revenue diversification in European banks affects the market valuation and the total, systematic and idiosyncratic risk. Since the mid-1980s, European banks have expanded towards non-interest income generating activities. The historical perception has been that revenue diversification can reduce overall earnings volatility, potentially contributing to an increased market valuation. The effects of revenue diversification are examined by using OLS regressions on panel data containing 103 banks from 24 European countries over the period of 2005 to 2012. Stock market data and the data from banks’ financial statements are used to calculate market valuations and total, systematic and idiosyncratic risk. Additionally, this study examines the economic significance of the results in order to evaluate the implications of revenue diversification. The study finds a positive effect of revenue diversification on a bank’s market value. Specifically, the findings suggest that the stock market anticipates that ‘fee income’ can improve future profits. However, a higher degree of revenue diversification increases all types of risks. The economic significance reveals that revenue diversification has a considerable effect on the market valuation and the systematic risk. At last, the effects of revenue diversification appear to have varied over time and were greater during the recent financial crisis.

A credit card as a banking product has a dual nature both as a convenient loan and a payment tool. Credit card profitability prediction is a complex problem because of the variety of the card holders' behaviour patterns, a fluctuating balance, and different sources of interest and transactional income. The state of a credit card account depends on the type of card usage and payments delinquency, and can be defined as inactive, transactor, revolver, delinquent, and default. The proposed credit cards profit prediction model consists of four stages: i) utilisation rate and interest rate income prediction, ii) non-interest rate income prediction, iii) account state prediction with conditional transition probabilities, and iv) the aggregation of the partial models into total income estimation. This thesis describes an approach to credit card account-level profitability prediction based on multistate and multistage conditional probabilities models with different types of income and compares methods for the most accurate predictions. We use application, behavioural, card state, and macroeconomic characteristics as predictors. This thesis contains nine chapters: Introduction, Literature Review, six chapters giving descriptions of the data, methodologies and discussions of the results of the empirical investigation, and Conclusion. Introduction gives the key points and main aims of the current research and describes the general schema of the total income prediction model. Literature Review proposes a systematic analysis of academic work on loan profit modelling and highlights the gaps in the application of profit scoring to credit cards income prediction. Chapter 3 describes the data sample and gives the overview of characteristics. Chapter 4 is dedicated to the prediction of the credit limit utilisation and contains the comparative analysis of the predictive accuracy of different regression models. We apply five methods such as i) linear regression, ii) fractional regression, iii) beta-regression, iv) beta-transformation, and v) weighted logistic regression with data binary transformation for utilisation rate prediction for one- and two-stage models. Chapters 5 and 6 are dedicated to modelling the transition probabilities between credit card states. Chapter 5 describes the general model setups, model building methodology such as transition probability prediction with conditional binary logistic, ordinal, and multinomial regressions, the data sample description, the univariate analysis of predictors. Chapter 6 discusses regression estimation results for all types of regression and a comparative analysis of the models. Chapter 7 describes an approach to the non-interest rate income prediction and contains a comparative analysis of panel data regression techniques such as pooled and four random effect methods. We consider two sources of non-interest income generation: i) interchange fees and foreign exchange fees from transactions via pointof- sales (POS) and ii) ATM fees from cash withdrawals. We compare the predictive accuracy of a one-stage approach, which means the usage of a single linear model for the income amount estimation, and a two-stage approach, which means that the income amount conditional on the probability of POS and ATM transaction. Chapter 8 aggregates the results from the partial models into a single model for total income estimation. We assume that a credit card account does not have a single particular state and a single behavioural type in the future, but has a chance to move to any of possible states. The income prediction model is selected according to these states, and the transition probabilities are used as weights for the particular interest rate and non-interest rate income prediction models. Conclusion highlights the contributions of this research. We propose an innovative methodological approach for credit card income prediction as a system of models, which considers the estimation of the income from different sources and then aggregates the income estimations weighted by the states transition probabilities. The results of comparative analysis of regression methods for: i) utilization rate of credit limit and ii) non-interest income prediction, iii) the use of panel data with pooled and random effect for profit scoring, and iv) account level non-binary target transition probabilities estimation for credit cards can be used as benchmarks for further research and fill the gaps of empirical investigations in the literature. The estimation of the transition probability between states at the account level helps to avoid the memorylessness property of the Markov Chains approach. We have investigated the significance of predictors for models of this type. The proposed modelling approach can be applied for the development of business strategies such as credit limit management, customer segmentation by the profitability and behavioural type.

This correlation research study was used to investigate the impact of the Dodd-Frank legislation on the U.S. bank industry. The economic crisis of 2007-2009 had a global and significant financial impact, some of which still reverberates. In the United States, the reaction was The Dodd-Frank Wall Street Reform and Consumer Protection Act, which took effect July 21, 2010. This act has recently been the subject of academic research and remains debated in congress, with discussion focused on its repeal. The publicly available, secondary data set from banks' quarterly filed regulatory reporting provided the data used in this study. Every FDIC insured bank in the United States was included in the study. The research question for the study examined the unintended consequences of Dodd-Frank legislation as posited by the theories of Bexley (2014) and Barth, Prabha, and Swagel (2012) that Dodd-Frank was a regulatory overreaction and could have a long-term impact on a substantial number of financial institutions. From 2007 through 2013, the number of banks declined by over 1,753 institutions; a 19.82% decline. The structure of the research presumed that banks that relied heavily on consumer fees for depository services would be negatively impacted by rule changes and regulation regarding such fees. There were two research questions. The first focused on the role of the new rules in the decline of the number of banks. The second explored the role of the legislation in the financial performance of banks. Regression results resulted in not being able to reject the null hypotheses. The implication of the study for social change is that policy makers who understand these relationships may construct better regulation to mitigate unfair and deceptive consumer fees for banking services.

The significant change of the banking business models is easily observable in the current banking industry. Banks are forced to find additional source of income besides the one from traditional activities and thus the non-interest income is growing in importance. One of the reasons behind is that the banks need to recover from severe impacts of financial crisis in 2008-2010 and they want to adapt to the environment of low interest rates which has been occurring in the market since 2011. In this thesis, we analyze the presence of direct effect of non-interest income (proxied by fee income) on banks' performance using data of 220 commercial and investment banks from U.S. and EU-28 countries over the period of 2007-2014. Using System Generalized Methods of Moment, the direct effect was not detected. However, we conclude that economy with low inflation rate and growing gross domestic product improves the banks' profitability, as well as high capitalization and operating and credit quality efficiency. Furthermore, we found out that the volatility of the non-interest income has increased earlier than the crisis in 2008-2010 and it has been achieving almost continuous level till 2011 when it started decreasing again. Thus the hypothesis about relationship between volatility and financial crisis was rejected.

The diploma thesis deals mostly with interest rate risk issue. It describes the basic methods of interest rate risk measurement with use of analyses executing by Asset Liability Management department in banks. Such analyses as repricing GAP, net interest income analysis, market value of equity and sensitivity analyses to interest rate movements. There is an analysis of Czech crown yield curve as well, in order to deeper insight of its probability behaviour. Results of this analysis are used for advanced techniques in ALM. Especially knowledge of volatilities of particular yield points and theirs relations is used in these methods. There was also a multi equation model for predictions of yield curve development created. One of the variables in the model there is the 2-week repo rate of Czech National Bank included.