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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Modelo de risco de cr?dito e a rela??o com vari?veis macroecon?micas

Nunes, Christiny Kelly Ferreira 04 August 2017 (has links)
Submitted by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-10-17T10:47:45Z No. of bitstreams: 1 DIS_CHRISTINY_KELLY_FERREIRA_NUNES_COMPLETO.pdf: 954134 bytes, checksum: 9b5f9a8ef9fc5629594411e21fc14351 (MD5) / Approved for entry into archive by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-10-17T10:47:57Z (GMT) No. of bitstreams: 1 DIS_CHRISTINY_KELLY_FERREIRA_NUNES_COMPLETO.pdf: 954134 bytes, checksum: 9b5f9a8ef9fc5629594411e21fc14351 (MD5) / Made available in DSpace on 2017-10-17T10:48:05Z (GMT). No. of bitstreams: 1 DIS_CHRISTINY_KELLY_FERREIRA_NUNES_COMPLETO.pdf: 954134 bytes, checksum: 9b5f9a8ef9fc5629594411e21fc14351 (MD5) Previous issue date: 2017-08-04 / This paper seeks to determine the relationship between the default rate of companies and macroeconomic indicators. Analyzing the two base lines of credit from a Financial Institution in the period from 2012 to 2015. For this was parameterized a statistical model in which it contemplates idiosyncratic and macroeconomic variables, using logistic regression statistical technique. The objective of this paper is to capture the sensitivity of the probability of default of companies considering the analysis horizon of twelve months. The results show that the default is sensitivy to insertion of macroeconomic indicators, mainly in relation to PIB and PIB next year projection, named throughout the paper as PIB next. Despite the positive signs the results not shown so expressive like other papers in the area. It may have been impacted by a smaller base, if compared to the others. We consider the objective of this paper was achieved showing the viability, applicability of the model and their impacts. As well as that it can be used not only for data analysis, but also as an input into a portfolio credit risk model. / Esse trabalho buscou averiguar a rela??o entre a taxa de inadimpl?ncia de empresas e indicadores macroecon?micos, analisando a base de duas linhas de cr?dito de uma Institui??o Financeira no per?odo de 2012 a 2015. Para isso foi parametrizado um modelo estat?stico que contempla vari?veis idiossincr?ticas e vari?veis macroecon?micas, com t?cnica estat?stica de regress?o log?stica. A ideia foi capturar a sensibilidade da probabilidade de default das empresas considerando o horizonte de doze meses a partir da concess?o da linha de cr?dito. Os resultados mostraram que a inadimpl?ncia das linhas ? sens?vel ? inser??o de indicadores macroecon?micos, principalmente em rela??o ao PIB do ano e ao PIB projetado, denominado ao longo do trabalho como PIB pr?ximo. Apesar da sinaliza??o positiva, tais resultados, de forma geral, n?o se mostraram t?o expressivos quanto outros trabalhos da ?rea, podendo ter sido impactados por uma base menor, se comparados aos demais. A an?lise e dados e revis?o bibliogr?fica apontaram para a viabilidade e aplicabilidade do modelo e de seus impactos. Evidenciaram ainda que o modelo possa ser utilizado n?o somente para a an?lise de dados, mas tamb?m como insumo num modelo de risco de cr?dito de portf?lio.
2

Proposta de um modelo de Credit Scoring para uma carteira de cr??dito consignado visando a????es de Cross-Sell.

OLIVEIRA, Marcos Santos 28 September 2016 (has links)
Submitted by Elba Lopes (elba.lopes@fecap.br) on 2016-12-12T17:27:40Z No. of bitstreams: 2 Marcos Santos Oliveira.pdf: 970582 bytes, checksum: 6d45d32bff529faa3e4f900f0ff06309 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2016-12-12T17:27:40Z (GMT). No. of bitstreams: 2 Marcos Santos Oliveira.pdf: 970582 bytes, checksum: 6d45d32bff529faa3e4f900f0ff06309 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-09-28 / This work has the objective to analyze the efficiency of the credit scoring model in cross-selling action to provide greater profitability aligned with the risk of new product. This study differs from others by using a database of clients who Payroll-linked loan from the conventional modeling of a Credit Scoring offer another product, the credit card that requires a better profile for meeting payments. The study resulted in 3 of profitability and performance scenarios. In Scenario 1 without use of shoring showed profitability of R$ 0.5 million and delinquencies of 16.1%. In the others scenarios with the use of the yields scores exceeded R$ 2.3 million and delinquencies below 9%. Scenarios 2 and 3 with just score Bureau companies. Scenario 4 includes Credit scoring model developed in this work, we showed the best discrimination between good and bad customers and the highest rate of approval, 75% against 64% of the best Bureau. For this, we used data provided by a financial institution. Using SPSS and statistical techniques, the risk analysis Relative, construction of dummies and Spearman correlation analysis, generated the model Logistic Regression Binary, validated with the Kolmogorov-Smirnov test, the ROC curve and others. The model developed credit scoring showed good results as to their power of customer classification. The effectiveness of Logistic Regression as credit performance prediction tool enables the application of the use of credit scoring model by the financial institution provider of data to improve profitability and default of the customer portfolio by credit card coming from the customer base of payroll loan. / Este trabalho tem o objetivo de analisar a efici??ncia do modelo de credit scoring na a????o de cross-selling para proporcionar uma maior rentabilidade alinhada ao risco do novo produto. A realiza????o deste estudo se diferencia dos demais por utilizar uma base de dados com clientes que realizaram empr??stimo Consignado, a partir da modelagem convencional de um Credit Scoring ofertar outro produto, o Cart??o de Cr??dito que exige um melhor perfil para cumprimento dos pagamentos. O estudo resultou em 3 cen??rios de rentabilidade e desempenho. No Cen??rio 1 sem uso do escoramento apresentou rentabilidade de R$ 0,5 milh??es e inadimpl??ncia de 16,1%. Nos demais cen??rios com uso de escores as rentabilidades ultrapassaram R$ 2,3 milh??es e inadimpl??ncias abaixo de 9%. Os Cen??rios 2 e 3 apenas com escore de empresas Bureau. O Cen??rio 4 inclui o modelo Cr??dit Scoring desenvolvido neste trabalho, apresentou a melhor discrimina????o entre clientes bons e maus e a maior taxa de aprova????o, sendo 75% contra 64% do melhor Bureau. Para isso, utilizou-se de dados fornecido por uma institui????o financeira. Utilizando o SPSS e t??cnicas estat??sticas, a an??lise de Risco Relativo, constru????o de dummies e a an??lise de correla????o de Spearman, foi gerado o modelo de Regress??o Log??stica Bin??ria, validado com o teste Kolmogorov-Smirnov, a Curva ROC e outros. O modelo de Credit Scoring desenvolvido apresentou resultados satisfat??rios quanto a seu poder de classifica????o dos clientes. A efic??cia da Regress??o Log??stica, como ferramenta de predi????o de performance de cr??dito, habilita a aplica????o da utiliza????o do modelo Credit Scoring pela institui????o financeira provedora dos dados para melhorar a rentabilidade e a inadimpl??ncia da carteira de clientes com Cart??o de Cr??dito oriundo da carteira de clientes do empr??stimo Consignado.
3

Determinantes do cr??dito banc??rio e os impactos do risco de cr??dito sobre a economia brasileira

Almeida, Fernanda Dantas 01 June 2016 (has links)
Submitted by Sara Ribeiro (sara.ribeiro@ucb.br) on 2017-04-17T14:20:44Z No. of bitstreams: 1 FernandaDantasAlmeidaTese2016.pdf: 2319400 bytes, checksum: f6fb411112df029c4bb77d8f3bb375bf (MD5) / Approved for entry into archive by Sara Ribeiro (sara.ribeiro@ucb.br) on 2017-04-17T14:20:57Z (GMT) No. of bitstreams: 1 FernandaDantasAlmeidaTese2016.pdf: 2319400 bytes, checksum: f6fb411112df029c4bb77d8f3bb375bf (MD5) / Made available in DSpace on 2017-04-17T14:20:57Z (GMT). No. of bitstreams: 1 FernandaDantasAlmeidaTese2016.pdf: 2319400 bytes, checksum: f6fb411112df029c4bb77d8f3bb375bf (MD5) Previous issue date: 2016-06-01 / Banking credit plays a key role for the economic development and, therefore, it is important to understand its dynamics and its actuation for the transmission of the monetary policy. Thus, this thesis consists of two studies that aim to understand the micro and macroeconomic behavior of bank credit, investigating the main determinants of bank credit as well as the interaction of the banking sector with other sectors of the economy. The microeconomic analysis aims to identify the major determinants of banking credit in the Brazilian economy, considering the influence of specific characteristics of the financial institutions and monetary policy in the period 2001 to 2012. This paper contributes with the literature by showing that there was no relevant impact from the macroeconomic environment on the credit supply in the analyzed period. The government has adopted a countercyclical credit policy mismatched from prevailing macroeconomic conditions. In turn, the macroeconomic analysis investigates the effects of credit risk for the financial intermediation and how this risk is transmitted to other agents in the economy. The DSGE model with financial frictions of Gertler and Karadi (2011) was modified to incorporate the risk of default given by the probability of non-payment of loans granted by the bank. This study contributes to the literature by deriving the probability of default of firms endogenously in the model, unlike most of the studies that assume it as exogenous. Moreover, as the model assumes two different interest rates for the two kinds of borrowers ("good" and "bad" payers), it allows the analysis of the impacts of the borrowers??? quality on the overall interest rate on loans. As a result, we identified a countercyclical default rate, which compensates the bank for the lost with ???bad??? payers. / O cr??dito banc??rio possui um papel fundamental para o desenvolvimento econ??mico de um pa??s e, por isso, ?? muito importante compreender sua din??mica e sua atua????o na transmiss??o da pol??tica monet??ria. Por essa raz??o, esta tese ?? formada por dois estudos que visam entender o comportamento do cr??dito banc??rio de forma micro e macroecon??mica, investigando os principais aspectos que o determinam, bem como a intera????o do setor banc??rio com os demais setores da economia. A an??lise microecon??mica buscou identificar empiricamente os determinantes do cr??dito banc??rio no Brasil, sob a ??tica da oferta, de modo a averiguar o efeito das estrat??gias dos bancos e evidenciar o impacto da pol??tica monet??ria sobre a oferta de cr??dito no per??odo de 2001 a 2012. Esse estudo constatou que n??o houve impacto do ambiente econ??mico sobre a oferta de cr??dito no per??odo analisado, dado que o governo adotou uma pol??tica credit??cia antic??clica descasada das condi????es macroecon??micas vigentes. Por outro lado, a an??lise macroecon??mica buscou investigar os efeitos do risco de cr??dito na intermedia????o financeira e como esses efeitos s??o repassados aos demais agentes da economia. Para tanto, utilizou-se o modelo DSGE com fric????es financeiras de Gertler e Karadi (2011), que foi modificado de modo a incorporar o risco de default dado pela probabilidade de n??o pagamento dos empr??stimos concedidos pelo banco. Esse estudo contribui com a literatura ao derivar a probabilidade de default das firmas endogenamente ao modelo, diferente de grande parte dos artigos que a tratam como uma medida ex??gena. Ademais, ao trazer duas taxas de juros distintas para diferentes tomadores de cr??dito, os ???bons??? e os ???maus??? pagadores, o modelo permite a an??lise de como a qualidade dos mutu??rios impacta na taxa de juros global dos empr??stimos. Como resultado, encontra-se uma taxa de default antic??clica, que funciona como uma compensa????o para o banco pelas perdas com os ???maus??? pagadores.

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