En el Perú tenemos diversas maneras de analizar y controlar el otorgamiento del crédito, cada tipo de crédito presenta una regulación distinta. En el presente proyecto de investigación nos enfocaremos en buscar el mejor método que permita controlar la cartera vencida de una empresa comercial. En la actualidad existen diversos parámetros como en la que brinda la Superintendencia de Banca Seguros y AFP, cálculo de la Pérdida Esperada según la normativa de Basilea II y una tercera propuesta que es el cómo se decide en un comité autónomo de Créditos. Para los tres parámetros se analiza el proceso de Provisiones, las provisiones son recursos que usan las empresas como prevención para proteger sus activos, esta estrategia ayuda a la empresa en el control de su cartera crediticia y mitigar el riesgo crediticio para la toma de decisiones e implantar nuevas políticas de control y seguimiento de la misma. Por último, revisaremos el impacto en su Estado de Resultado a fin de analizar el mejor método que una empresa Comercial podría adoptar afectando en el menos posible su Utilidad Neta. Para esto analizaremos una empresa comercial que vende productos de consumo a nivel nacional y se usará una data de cinco años (2014-2018). / In Peru we have different ways of analyzing and controlling the granting of credit, each type of credit has a different regulation. In this research project we will focus on finding the best method to control the overdue portfolio of a commercial company. At present there are several parameters such as the one provided by the Superintendence of Insurance Banking and AFP, calculation of the Expected Loss according to Basel II regulations and a third proposal which is how to decide in an autonomous Credit Committee. For the three parameters, the Provisions process is analyzed, the provisions are resources that companies use as prevention to protect their assets, this strategy helps the company to control its credit portfolio and mitigate credit risk for decision making and implement new policies to control and monitor it. Finally, we will review the impact on its Income Statement in order to analyze the best method that a Commercial company could adopt affecting as little as possible its Net Profit. For this purpose, we will analyze a commercial company that sells consumer products nationwide and will use a five-year (2014-2018) data. / Tesis

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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.

Thesis (Ph. D.)--State University of New York at Binghamton, Department of Economics, 2005. / Includes bibliographical references (leaves 280-289).

<p>This study aims to investigate the relationship between systematic risk and credit ratings. The systematic risk, frequently measured by beta, is an important consideration for both investors and corporations. Therefore it is interesting to examine if indications about the systematic risk could be gained by looking at credit ratings, especially on the Nordic market, where credit ratings are seemingly growing in importance. Consequently, the following research hypothesis is posed;<em> We intend to establish a relationship between market risk (Beta) and credit ratings for firms in the Nordic countries.</em></p><p><em> </em></p><p>In order to confirm or deny the research hypothesis, theories from peer reviewed databases were collected. These were divided into three sections; background theories, hypotheses about credit ratings and a literature review. The background theories consisted of two classical financial theories, the Capital Asset Pricing Model and the Efficient Market Hypothesis, which are the foundation upon which the research field have progressed. The hypotheses is specifically designed to explain the relationship between credit ratings and either systematic risk or stock price. The literature review contains information about studies which did not contribute to theory building, but produced results interesting in the research area.</p><p> </p><p>The actual sample in the thesis consisted of the 58 credit rated companies on the Nordic stock market. These companies were rated by Moody’s and/or Standard & Poor’s, the two largest credit rating agencies in the world. As a measure of the systematic risk, betas for each of the companies were calculated. To investigate the relationship between these variables a regression analysis was performed, as well as one sample T-test using the software SPSS.</p><p> </p><p>The result revealed a moderate relationship between beta and credit risk, a relationship which was not statistically significant on the five percent level. Our results suggest that credit ratings contain some information about companies’ systematic risk, a finding that might be useful for market participants.</p><p> </p>

This study was directed toward improving the balance and consistency of student participation by thinning, randomizing, and delaying credit for student participation. Each of three sections of a large college course (n = 55) employed a different contingency for choosing the days in which participation credit was awarded: (1) credit units identified ahead of time, (2) credit units announced at the end of the course, and (3) credit units randomly selected by students at the end of the course. For all contingencies, random selection of 2 out of 4 discussion days in each credit unit occurred at the conclusion of the course. The study compared the effects of the different credit contingencies on the percentage of students participating at selected levels across days and units. Students recorded their individual comments during class discussion. External raters recorded the number of timely and repetitious comments per student, the number of comprehension and factual questions posed by instructors, and the amount of positive and negative feedback provided to each student. Results showed that when students knew which units would provide participation credit (Section A), the percentage of non-participants and dominant participants decreased, while the percentage of credit-level participants increased. These results are consistent with previous research (e.g., Krohn et al, 2010) reporting balanced participation when students know in advance the specific units when credit is available for participation. Conversely, when students did not know until the end of the semester which units would provide credit (Sections B and C), participation patterns remained relatively similar across units. The percentage of participants at different levels in Sections B and C fell between the percentages for credit and non-credit levels in Section A. A 50-item survey also was given at the beginning of the course to assess student beliefs concerning class participation. The total survey scores significantly predicted student placement into low- or high-participation groups throughout the course. Logistic regression analyses showed that the primary factor, Personal History and Preference regarding Class Participation, better predicted membership in the low-participant group in non-credit units and membership in the high-participant group in credit units in Section A.

This study aims to investigate the relationship between systematic risk and credit ratings. The systematic risk, frequently measured by beta, is an important consideration for both investors and corporations. Therefore it is interesting to examine if indications about the systematic risk could be gained by looking at credit ratings, especially on the Nordic market, where credit ratings are seemingly growing in importance. Consequently, the following research hypothesis is posed; We intend to establish a relationship between market risk (Beta) and credit ratings for firms in the Nordic countries. In order to confirm or deny the research hypothesis, theories from peer reviewed databases were collected. These were divided into three sections; background theories, hypotheses about credit ratings and a literature review. The background theories consisted of two classical financial theories, the Capital Asset Pricing Model and the Efficient Market Hypothesis, which are the foundation upon which the research field have progressed. The hypotheses is specifically designed to explain the relationship between credit ratings and either systematic risk or stock price. The literature review contains information about studies which did not contribute to theory building, but produced results interesting in the research area.   The actual sample in the thesis consisted of the 58 credit rated companies on the Nordic stock market. These companies were rated by Moody’s and/or Standard &amp; Poor’s, the two largest credit rating agencies in the world. As a measure of the systematic risk, betas for each of the companies were calculated. To investigate the relationship between these variables a regression analysis was performed, as well as one sample T-test using the software SPSS.   The result revealed a moderate relationship between beta and credit risk, a relationship which was not statistically significant on the five percent level. Our results suggest that credit ratings contain some information about companies’ systematic risk, a finding that might be useful for market participants.

In this thesis, I imply a forward-looking systematic factor from CDO market spreads; I show that this factor is a measure of CDO market's expectation of future default correlation, and I empirically show that it is positively related to bond credit spreads. From this, I infer that corporate bond credit spreads are positively related to expected default correlation. The forward-looking factor stems from a CDO valuation model that I propose. The model assumes default can be characterized as a random event that occurs with an uncertain hazard rate that is mixture-Weibull distributed. Calibrating the model to CDO market spreads implies the model parameters. Using two and three mixing densities and data spanning January 2004 to February 2008, I show that the model calibrates to both the North American and European investment grade CDOs with negligible error. The factor I imply from the CDO market quotes is the standard deviation of the implied hazard rate density. I then show that the standard deviation of the implied hazard rate density increases as default correlation increases. This is done by characterizing firms' defaults with stochastic hazard rates that are defined by jump-diffusion processes that are correlated only through the Weiner processes, only through systematic jumps, or both. I use the models to generate CDO model spreads that are used to imply mixture-Weibull hazard rate densities. In addition, I provide evidence that the implied hazard rate density standard deviation has time variation that is independent to that of other common systematic factors. Lastly, I show that bond credit spreads are positively correlated with the standard deviation of the implied hazard rate density, and I conclude that credit spreads are positively related to expected default correlation. I provide evidence that firms' credit spreads are decreasing in firm diversity; that credit spread sensitivity to default correlation is decreasing in firm equity option implied volatility and decreasing in firm diversity; and that the variation in high credit quality bond spreads is predominantly explained by systematic factors whereas the variation in low credit quality bond spreads is explained by systematic and idiosyncratic factors.

In this thesis, I imply a forward-looking systematic factor from CDO market spreads; I show that this factor is a measure of CDO market's expectation of future default correlation, and I empirically show that it is positively related to bond credit spreads. From this, I infer that corporate bond credit spreads are positively related to expected default correlation. The forward-looking factor stems from a CDO valuation model that I propose. The model assumes default can be characterized as a random event that occurs with an uncertain hazard rate that is mixture-Weibull distributed. Calibrating the model to CDO market spreads implies the model parameters. Using two and three mixing densities and data spanning January 2004 to February 2008, I show that the model calibrates to both the North American and European investment grade CDOs with negligible error. The factor I imply from the CDO market quotes is the standard deviation of the implied hazard rate density. I then show that the standard deviation of the implied hazard rate density increases as default correlation increases. This is done by characterizing firms' defaults with stochastic hazard rates that are defined by jump-diffusion processes that are correlated only through the Weiner processes, only through systematic jumps, or both. I use the models to generate CDO model spreads that are used to imply mixture-Weibull hazard rate densities. In addition, I provide evidence that the implied hazard rate density standard deviation has time variation that is independent to that of other common systematic factors. Lastly, I show that bond credit spreads are positively correlated with the standard deviation of the implied hazard rate density, and I conclude that credit spreads are positively related to expected default correlation. I provide evidence that firms' credit spreads are decreasing in firm diversity; that credit spread sensitivity to default correlation is decreasing in firm equity option implied volatility and decreasing in firm diversity; and that the variation in high credit quality bond spreads is predominantly explained by systematic factors whereas the variation in low credit quality bond spreads is explained by systematic and idiosyncratic factors.

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.