Muitos economistas apontam que as condições macroeconômicas afetam o risco de crédito das instituições financeiras. Assim, há uma necessidade de avaliar a sensibilidade do risco de crédito das instituições financeiras à mudanças na economia a fim de evitar instabilidade no mercado de crédito. Este trabalho contribuiu para análise de risco de crédito pois apresentou modelos de previsão para a inadimplência do sistema financeiro no Brasil utilizando um conjunto abrangente de variáveis macroeconômicas no modelo. A análise também incorpora a composição da carteiras de crédito das instituições financeiras. A revisão bibliográfica utilizou, como constructo, estudos empíricos na área de risco de crédito soberano; testes de stress; credit scoring com variáveis macroeconômicas; estudos que relacionam inadimplência e variáveis econômicas e estudos que relacionam risco de crédito e composição da carteira de crédito. A base de dados mensais foi extraída do banco de dados do Banco Central e do IPEA. A variável resposta do modelo, a inadimplência, é definida como a relação entre o saldo em atraso superior a noventa dias dos contratos de crédito sobre o saldo de todos os contratos na data base. Foram extraídas 313 variáveis explicativas com base na revisão bibliográfica. Foram construídos modelos estatísticos de séries temporais (ARIMA) e séries temporais com variáveis explicativas exógenas (ARMAX) para prever a inadimplência. Os modelos foram construídos com uma base de dados de modelagem no período de Março de 2007 a Dezembro de 2011. O período de Janeiro de 2012 a Dezembro de 2012 foi utilizado para mensurar a performance dos modelos fora do tempo (amostra de validação). Variáveis explicativas indicadoras do saldo por região da carteira de crédito, dívida pública interna e juros se mostraram estatisticamente significativas para explicar a inadimplência do sistema financeiro no Brasil, sendo que (1) quanto maior o crescimento anual do saldo das operações de crédito do sistema financeiro nacional na região Centro-Oeste, menor a inadimplência; (2) quanto maior a média dos juros aplicados pelo Banco Central nos últimos três meses, menor a inadimplência e (3) quanto maior o crescimento da dívida interna do setor público, menor a inadimplência. Na comparação dos modelos obtidos, o modelo ARIMA apresentou melhor ajuste para o ano de 2012, porém o modelo ARMAX também se apresentou adequado por obter baixos valores dos resíduos. / Economists show that macroeconomic conditions affect credit risk of financial institutions. Thus, there is a need to evaluate the sensitivity of credit risk of financial institutions to changes in the economy in order to avoid instability in the credit market. This work contributed to the analysis of credit risk by presenting a prediction model for non-performing loans of Brazilian financial system using a comprehensive set of macroeconomic variables in the analysis. The model also incorporates the composition of the loan portfolios of financial institutions. The literature review used, as a construct, empirical studies in sovereign credit risk area, stress testing, credit scoring with macroeconomic variables, studies that relate non- performing loans and economic variables and studies relating to credit risk and composition of the loan portfolio. The monthly data base was extracted from Central Bank and IPEA data. The response variable of the model, the non-performing loans rate is defined as the ratio between the outstanding balance more than ninety days of credit agreements and the balance of all contracts in the data base. 313 explanatory variables were extracted based on the literature review. Statistical models of time series (ARIMA) and time series with exogenous explanatory variables (ARMAX) were built to predict non-performing loans. The modeling database used the period between March 2007 to December 2011. The period from January 2012 to December 2012 was used to measure the performance of the models out of time (validation sample). Explanatory variables by region of the loan portfolio, the internal public debt and the interest rate were statistically significant in explaining the default of the financial system in Brazil , where (1) the higher the annual growth of loans in Centro-Oeste, the lower the non-performing loans, (2) the higher average interest rates applied by the Central Bank in the last three months, the lower the non-performing loans and (3) the higher annual growth of domestic debt of the public sector, lower non-performing loans. Comparing the obtained models, ARIMA model showed better fit for the year 2012, but ARMAX model also performed properly with low residual values.

This study aims to estimate the ratio of non-performing loans to total loans (NPL ratio), its determinants and its response to different macroeconomic shocks. As the last financial crises had negative impact on the economy of many countries of the world, we have to strive for preventive measures that would help us to fully or at least partly avoid future crises. It should be achieved by sound risk management practices of all financial institutions. Important part of these risk management practices shall be - among others - stress tests that would test the health of the institution under severe conditions and negative shocks. For this study the vector autoregression model (VAR methodology) is used to see the response of credit risk (in terms of NPL ratio) to macroeconomic shocks in the Czech Republic. The variables used for this study are quarterly time series data of the period from 2002 to 2011 (GDP, inflation rate, unemployment rate, koruna exchange rate (CZK/USD), and interest rate). For each of these variables the impulse response function was created, to show the impact of macroeconomic shocks and the speed of adjustment of NPL ratio to these shocks. Keywords: Financial Crises, Credit Risk Management, Non-performing loans, Macroeconomic Shocks, Czech Republic, VARs

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.

For the evaluation of banks¡¦ performance, non-performing loans ratio and capital adequacy ratio are the two major indicators other than earnings performance. Among the various tools for earnings manipulation, loan loss provisions may be the only one that could affect bank¡¦s earning numbers, non-performing loans ratio and capital adequacy ratio simultaneously. In order to satisfy the need to increase earnings and capital adequacy ratio and to decrease non-performing loans ratio, banks may have motivation to conduct earnings management. The purpose of the study is thus to investigate whether there is a relationship between the earnings management by using the discretionary loan loss provisions and the earnings before loan loss provisions, non-performing loans ratio, capital adequacy ratio, asset size, loan growth rate, and loans uncollected. In addition, the study divides the sample banks into the following categories: (1) commercial banks versus others, (2) new banks versus old banks (based on the time the bank was founded), and (3) state-run versus non-state-run (based on whether the president of the bank is appointed by the government). The study also intends to examine whether earnings management conducted by the bank¡¦s management is different between the various categories. Based on the empirical results from the Taiwan Economics Journal (TEJ) database, the study found: (1) the three variables of earnings before loan loss provisions, asset size, and loans uncollected are significantly related to the earnings management by using discretionary loan loss provisions, and the higher the three variables, the higher the degree of earnings management; (2) non-performing loans ratio, capital adequacy ratio, and loan growth rate are not found to be significantly related to the earnings management by using discretionary loan loss provisions; (3) state-run banks have conducted more earnings management than non-state-run banks; and (4) there is no significant result found in other analyses for other categories.

<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>

Muitos economistas apontam que as condições macroeconômicas afetam o risco de crédito das instituições financeiras. Assim, há uma necessidade de avaliar a sensibilidade do risco de crédito das instituições financeiras à mudanças na economia a fim de evitar instabilidade no mercado de crédito. Este trabalho contribuiu para análise de risco de crédito pois apresentou modelos de previsão para a inadimplência do sistema financeiro no Brasil utilizando um conjunto abrangente de variáveis macroeconômicas no modelo. A análise também incorpora a composição da carteiras de crédito das instituições financeiras. A revisão bibliográfica utilizou, como constructo, estudos empíricos na área de risco de crédito soberano; testes de stress; credit scoring com variáveis macroeconômicas; estudos que relacionam inadimplência e variáveis econômicas e estudos que relacionam risco de crédito e composição da carteira de crédito. A base de dados mensais foi extraída do banco de dados do Banco Central e do IPEA. A variável resposta do modelo, a inadimplência, é definida como a relação entre o saldo em atraso superior a noventa dias dos contratos de crédito sobre o saldo de todos os contratos na data base. Foram extraídas 313 variáveis explicativas com base na revisão bibliográfica. Foram construídos modelos estatísticos de séries temporais (ARIMA) e séries temporais com variáveis explicativas exógenas (ARMAX) para prever a inadimplência. Os modelos foram construídos com uma base de dados de modelagem no período de Março de 2007 a Dezembro de 2011. O período de Janeiro de 2012 a Dezembro de 2012 foi utilizado para mensurar a performance dos modelos fora do tempo (amostra de validação). Variáveis explicativas indicadoras do saldo por região da carteira de crédito, dívida pública interna e juros se mostraram estatisticamente significativas para explicar a inadimplência do sistema financeiro no Brasil, sendo que (1) quanto maior o crescimento anual do saldo das operações de crédito do sistema financeiro nacional na região Centro-Oeste, menor a inadimplência; (2) quanto maior a média dos juros aplicados pelo Banco Central nos últimos três meses, menor a inadimplência e (3) quanto maior o crescimento da dívida interna do setor público, menor a inadimplência. Na comparação dos modelos obtidos, o modelo ARIMA apresentou melhor ajuste para o ano de 2012, porém o modelo ARMAX também se apresentou adequado por obter baixos valores dos resíduos. / Economists show that macroeconomic conditions affect credit risk of financial institutions. Thus, there is a need to evaluate the sensitivity of credit risk of financial institutions to changes in the economy in order to avoid instability in the credit market. This work contributed to the analysis of credit risk by presenting a prediction model for non-performing loans of Brazilian financial system using a comprehensive set of macroeconomic variables in the analysis. The model also incorporates the composition of the loan portfolios of financial institutions. The literature review used, as a construct, empirical studies in sovereign credit risk area, stress testing, credit scoring with macroeconomic variables, studies that relate non- performing loans and economic variables and studies relating to credit risk and composition of the loan portfolio. The monthly data base was extracted from Central Bank and IPEA data. The response variable of the model, the non-performing loans rate is defined as the ratio between the outstanding balance more than ninety days of credit agreements and the balance of all contracts in the data base. 313 explanatory variables were extracted based on the literature review. Statistical models of time series (ARIMA) and time series with exogenous explanatory variables (ARMAX) were built to predict non-performing loans. The modeling database used the period between March 2007 to December 2011. The period from January 2012 to December 2012 was used to measure the performance of the models out of time (validation sample). Explanatory variables by region of the loan portfolio, the internal public debt and the interest rate were statistically significant in explaining the default of the financial system in Brazil , where (1) the higher the annual growth of loans in Centro-Oeste, the lower the non-performing loans, (2) the higher average interest rates applied by the Central Bank in the last three months, the lower the non-performing loans and (3) the higher annual growth of domestic debt of the public sector, lower non-performing loans. Comparing the obtained models, ARIMA model showed better fit for the year 2012, but ARMAX model also performed properly with low residual values.

Die europäische Union hat Programme installiert (EFSF, EFSM, ESM) oder ist dabei dies zu tun (Europäische Einlagensicherung EDIS), die darauf hinauslaufen, dass Kapital von weniger korrupten Ländern in Länder mit höherem Korruptionsgrad transferiert wird. Die Literatur deckt einen deutlichen Zusammenhang zwischen Kreditgeschäft und Korruption auf. In korrupteren Regionen verzeichnen Banken mehr Kreditausfälle und verbuchen mehr Non-Performing-Loans. Korruption im Kreditgeschäft ist sowohl auf der Schuldnerseite (i), wie auch auf der (ii) Gläubigerseite wie auch auf der (iii) Seite der Regierung bzw. Regulatorik anzutreffen. Korrupte Länder zeichnen sich durch schwache Rechtssysteme aus, die es Gläubigern erschweren, ihre Rechte durchzusetzen. In Griechenland spricht man von „strategischen“ Kreditnehmern, die es von vornherein darauf anlegen, Kredite nicht ordnungsgemäß zu bedienen. Außer privaten Schuldnern zeigen auch öffentliche Schuldner in korrupteren Ländern eine höhere Ausfallquote ihrer Kredite („Moratorium“). Im Ergebnis bedeutet dies, dass es für Kapitalgeber ein großes Risiko darstellt, finanzielle Hilfen an korrupte Länder zu leisten. In Zukunft sollten bei allen europäischen Projekten, die mit rückzahlbaren Geldtransfers in Länder mit hohem Korruptionsgrad verbunden sind oder sein können, eine Korruptionsauswirkungsanalyse („corruption impact assessment“) angefertigt werden, welche die voraussichtlichen Folgen der Korruption für das Projekt darlegt. Außerdem sollten Banken in korrupteren Ländern mehr Eigenkapital halten. Die Europäische Einlagensicherung sollte aufgeschoben werden. / The European Union installed financial programs that enable the transfer of money from less corrupt countries into countries with higher corruption grades (EFSF, EFSM, ESM, European deposit insurance EDIS). This is a risk for lenders in less corrupt countries. The scientific literature proofs that there is a significant correlation between the corruption grade of a country and the Non-Performing-Loan-quota (i) and loan losses (ii). Corruption can be traced back to actions of debtors, of lenders and of regulators. The latter refuse to install strong legal systems that would enable it lenders to enforce their rights. In corrupt countries a collaboration of many parties at the expense of outsiders and especially foreigners can be observed. In Greece the term “strategic borrower” has been established to describe the phenomenon that borrowers systematically try to evade the redemption of their loans with the help of the weak legal system. Taken altogether it is risky for European lenders to transfer money into corrupt jurisdictions. It seems to be necessary to complement European financial projects with detailed impact assessments of the corruption-problem. Banks in corrupt countries should hold higher equity ratios. The European deposit insurance should be suspended.

The thesis deals with the development of China's financial system, with a particular focus on the banking sector. At the beginning of the work is briefly summarized the current development of China's economy, since the behaviors and positions of banks in the PRC are closely linked with the state of the economy and the state as such. Presents the basic elements of the Chinese banking system, constitutes the basic legislation and some banking institutions. It also discusses the banking system as a whole and finally discusses its greatest specifics, non performing loans and shadow banking.

Central and Eastern Europe(CEE) is the region where the ownership of banks has been through the most fundamental and massive changes during the past two decades. This paper analyses the role of state-ownership in commercial banks, whether and why state ownership imposes negative effects on commercial banks in CEE transition countries, through both theoretical arguments and empirical testings. The thesis summarizes previous literature and analyses the role of banking ownership and performance, particularly though a dynamic view of the banking privatisation process. It investigates the reasons why state-owned banks are harmful in CEE countries from a corporate governance point of view. Followed by empirical tests on this topic, including banking production efficiency measurement using Stochastic Frontier Analysis and second-stage regression analysis about the effects of ownership on banking efficiency and asset quality. This paper finds out that the state ownership of banks imposes negative effects on bank performance and hinders successful privatisation of enterprises. Banking production efficiency has been improving greatly in late 1990s and stayed at a constant high level in 2000s. Through panel data regressions, we find the negative effects of state-ownership on banking production efficiency and asset...

The thesis examines the relation of the low-interest rate environment to the banks' selected credit risk measures with a panel dataset on banks in Eurozone, Denmark, Japan, Sweden, and Switzerland covering the period 2011-2017. It employs a system GMM framework and a combination of bank-related and macroeconomic variables. This study builds on recent literature on effects of low-interest rates on banks' profitability and estimates the following three hypotheses: The potential effects of the low-interest rate on non-performing loans (NPL) ratio, risk-weighted assets (RWA) to total assets ratio, and changes in Tier 1 capital ratio. There are three main results: Firstly, the results suggest that a prolonged period of negative monetary interest rate can affect the NPL ratio and reveal a possible relationship between the 3M-interbank interest rate and NPL ratio. Thus, the thesis does not reject the first hypotheses. However, it rejects these hypotheses in case of the other two ratios. Secondly, the study finds a bank heterogeneity to be a significant determinant of the credit risk. Finally, using recent data, this thesis contributes to the literature focusing on the drivers of the NPL ratio, RWA to total assets ratio and Tier 1 capital ratio, where in case of the latter two the existing research is...