Made available in DSpace on 2016-03-15T19:32:41Z (GMT). No. of bitstreams: 1 Luis Fernando Salles Moraes.pdf: 926577 bytes, checksum: 167e10d14baae4f409fdf302c7e5eefe (MD5) Previous issue date: 2012-08-15 / The current economic scenery, with high competition level among market players, easy access to economic and financial information and increasing number of companies that went bankrupt in recent years, changed the investors behavior and the decisive factors of investment targets. Nowadays, to mitigate these risks, shareholders became more concerned to long-term analysis and in this context arise the new concept of socially responsible companies, those that are sustainable and profitable to shareholders, even though this idea is also shared by BM&FBovespa it is not supported by current researches. This research aims to compare the probability of insolvency of corporations that make up the Corporate Sustainability Index (ISE) and others traded on BM&FBovespa. The research was done in two different moments: model creation and model application to a controlled group. The model used the insolvent and solvent companies from 2006 up to 2011 and established annual equations to calculate the probability of insolvency. Applying the model it was possible to identify the corporations probability of insolvency that belong to the ISE. The results of this study allowed to confirm based on the average probability of insolvency that ISE´s companies have less default chances if compared with sector correspondents traded in the stock market. / A conjuntura econômica atual, com alto nível de competição entre os agentes mercadológicos, a facilidade ao acesso às informações econômico-financeiro e o aumento do número de casos de falência empresarial, alteraram o comportamento dos investidores e o critério de seleção de empresas para investimento. Atualmente, visando mitigar os riscos de suas aplicações, os acionistas tornaram-se mais críticos e conscientes na análise de longo prazo e neste contexto, surge o conceito de empresas socialmente responsáveis. Estas empresas são caracterizadas por possuírem um negócio sustentável e rentável para os acionistas, porém este discurso, também adotado pela BM&FBovespa, não está comprovado pelas pesquisas atuais. Esta dissertação objetivou comparar a probabilidade de insolvência entre as empresas que compõem o Índice de Sustentabilidade Empresarial (ISE) e as demais transacionadas na BM&FBovespa. Foram realizadas duas etapas na pesquisa: construção do modelo e aplicação no grupo de controle. O modelo utilizou as empresas insolventes e solventes no período de 2006 a 2011 e estabeleceu equações anuais para o cálculo da probabilidade de insolvência. A aplicação do modelo identificou a probabilidade de insolvência entre as empresas pertencentes ao Índice de Sustentabilidade Empresarial (ISE) da BM&FBovespa e nas demais transacionadas. Os resultados obtidos permitiram confirmar através das médias da probabilidade de insolvência que as empresas pertencentes ao Índice de Sustentabilidade Empresarial possuem menor probabilidade ao default se comparadas com suas correspondentes setoriais comercializadas na bolsa.

Made available in DSpace on 2016-03-15T19:32:57Z (GMT). No. of bitstreams: 1 Tiago de Vasconcelos.pdf: 1565209 bytes, checksum: 5ee65e18e2c89dd6a31a10ea5fd7dccd (MD5) Previous issue date: 2015-08-12 / This project was done under a Professional Masters in Accounting and reflects the study that was developed to try to solve a real problem. In many companies in the construction sector, there is a wide divergence between the corporate accounting and tax accounting, this because the revenue recognition occurs at different times, generating different reports. In this situation, it is possible that while the corporate accounting shows profit, tax books shows losses, this because it was recognized less revenue than the costs incurred in the period. This issue becomes a problem when the company needs to obtain credit from financial institutions, and these, when considering the disparity between the tax and corporate results, adopt a conservative prudential position and, considering the unfavorable tax result, deny the credit. The developed research was exploratory and qualitative method. Eight interviews were conducted in depth with credit managers of large financial corporations, chosen by for convenience because of the difficulty of access to these professionals. The technique used for the treatment of the data was content analysis, conducted with the support of NVivo software. After the material analysis from the interviews that reflected the views of credit managers, it was observed the need to improve credit analysis model for companies classified in the Middle Market segment. The main contribution of this research, to improve the general model of credit analysis, was the introduction in the financial analysis phase of a Bridge Report, report that aims to demonstrate the composition and equalization of differences between the corporate and tax accounting, thus allowing the Credit Manager make an conscious decision without the first bias. / Este projeto foi realizado no âmbito de um Mestrado Profissional em Controladoria e reflete o estudo que foi desenvolvido para tentar solucionar um problema real. Em muitas empresas do setor de construção, há uma grande divergência entre a contabilidade societária e a contabilidade fiscal, isto porque o reconhecimento das receitas ocorre em momentos diferentes, gerando relatórios distintos. Nesta situação, é possível que, enquanto a contabilidade societária apresente lucro, a fiscal apresente prejuízo, por reconhecer uma receita menor que os custos incorridos no período. Esta situação se torna um problema quando a companhia precisa obter crédito nas instituições financeiras, e estas, ao verificarem a disparidade entre a o resultado fiscal e societário, adotam uma posição prudential conservadora e, considerando o resultado fiscal desfavorável, negam o crédito. A pesquisa desenvolvida foi exploratória e o método qualitativo. Foram realizadas oito entrevistas em profundidade com gestores de crédito de grandes corporações financeiras, escolhidas por conveniência, devido à dificuldade de acesso a esses profissionais. A técnica adotada para o tratamento dos dados foi a análise de conteúdo, realizada com o apoio do software NVIVO. Após a análise do material das entrevistas, que refletiu a opinião dos gestores de crédito, foi observada a necessidade de aperfeiçoamento do modelo de análise de crédito para as empresas classificadas no segmento Middle Market. A principal contribuição desta pesquisa, para melhoria do modelo geral de análise de crédito, foi a introdução, na fase de análise financeira, de um Bridge Report, relatório que tem a finalidade de demonstrar a composição e equalização das diferenças entre a contabilidade societária e a fiscal, permitindo, assim, ao Gestor de Crédito tomar uma decisão consciente sem o viés inicial.

The aim of this thesis is to evaluate the bank client´s creditworthiness for the purpose of loan financing and to formulate some proposals for its improvement. Some methods of financial and non-financial company analysis applied in banking practice are shown there. The proposals to ensure debt service are formulated on the basis of the results of analyzes.

Der Trend zur Auswertung aller nur möglichen Datenbestände für kommerzielle Zwecke ist eine nicht mehr aufzuhaltende Entwicklung. Auch für die Kreditwürdigkeitsprüfung wird überlegt, Daten aus Sozialen Netzwerken einzusetzen. Die Forschungsfrage entsteht, wie die Nutzer dieser Netzwerke reagieren, wenn Banken ihre privaten Profile durchsuchen. Mit Hilfe einer Befragung von 271 Probanden wurde dieses Problem erforscht. Die Ergebnisse sind wie folgt: Die betroffenen Bürger sehen die Entwicklung mit Sorge. Sie begreifen ganz rational die neuen Geschäftsmodelle und ihre Logik und erkennen die Vorteile. Sie stehen dem Big-Data-Ansatz nicht vollkommen ablehnend gegenüber. Abgelehnt wird es aber, wenn sich Daten aus sozialen Medien negativ für eine Person auswirken. Wenn man schon sein Facebook-Profil einer Bank öffnet, dann will man einen Vorteil davon haben, keinen Nachteil. Ein Teil der Gesellschaft lehnt das Schnüffeln in privaten Daten strikt ab. Insgesamt sind die Antworten deutlich linksschief verteilt mit einem sehr dicken Ende im ablehnenden Bereich. Das Schnüffeln in privaten Daten wird als unethisch und unfair empfunden. Die Menschen fühlen sich im Gegenzug berechtigt, ihre Facebook-Daten zu manipulieren. Eine wie-Du-mir-so-ich-Dir-Mentalität ist festzustellen. Wer kommerziell ausgeschnüffelt wird, der antwortet kommerziell mit Manipulationen seiner Daten. Insgesamt ist Banken zu raten, nicht Vorreiter der Entwicklung zu sein, sondern abzuwarten, welche Erfahrungen Fintechs machen. Banken haben zu hohe Opportunitätskosten in Form des Verlustes von Kundenvertrauen. / The trend to analyze all conceivable data sets for commercial purposes is unstoppable. Banks and fintechs try to use social media data to assess the creditworthiness of potential customers. The research question is how social media users react when they realize that their bank evaluates personal social media profiles. An inquiry among 271 test persons has been performed to analyze this problem. The results are as follows: The persons are able to rationally reflect the reasons for the development and the logic behind big data analyses. They realize the advantages, but also see risks. Opening social media profiles to banks should not lead to individual disadvantages. Instead, people expect an advantage from opening their profiles voluntarily. This is a moral attitude. An important minority of 20 to 30 % argues strictly against the commercial use of social media data. When people realize that they cannot prevent the commercial use of private data, they start to manipulate them. Manipulation becomes more extensive when test persons learn about critical details of big data analyses. Those who realize that their private data are used commercially think it would be fair to answer in the same style. So the whole society moves into a commercial direction. To sum up, banks should be reluctant and careful in analyzing private client big data. Instead, banks should give the lead to fintechs as they have fewer opportunity costs, because they do not depend on good customer relations for related products.

Выпускная квалификационная работа (магистерская диссертация) посвящена кредитному брокериджу. Кредитные брокеры возникли, когда задавленному агрессивной рекламой россиянину стало сложно ориентироваться в потоке информации и вникать в нюансы кредитных процентов, страховок и штрафов. Функции кредитных брокеров – это умение сориентироваться в требованиях десятков банков и подобрать кредит по оптимальным для заемщика условиям. И с каждым периодом развития кредитования хозяйствующих субъектов, особенно в секторе малого и среднего бизнеса, повышается спрос на услуги кредитного брокера. / Final qualification work (master thesis) devoted to credit brokerage. Mortgage brokers originated when crushed aggressive is the Russian became difficult to navigate in the information flow and to understand the nuances of the mortgage interest, insurances and fines. The functions of loan brokers is the ability to understand the requirements of dozens of banks and to choose the optimal loan for the borrower conditions. And with each period of development of crediting of economic entities, especially in the sector of small and medium business, the demand for the services of a mortgage broker.

This thesis deals with methodics of credit process of a particular credit union present on the Czech market. Because of confidentiality, the name of the credit union is not mentioned. The thesis is divided into four parts. The first part deals with characteristics of credit unions, their specifications and differences from banks. You can find in this part comparison of development of particular values of the analyzed credit union with the whole sector of Czech credit unions and bank sector as well. The second part is focused on importance of credit process, specifics of the balance of credit institutions, description of risks connected to credit process and principle of state regulation of this process. The third part describes in more details credit process of the analyzed credit union with further focus on acquisition period, credit analysis and decision making process. The last part explains questions of guarantee with all the types of guarantee of the analyzed credit union mentioned. Hence in the whole thesis the theory and practice is mixed together. In the concluding part I evaluate quality of credit process of the analyzed credit union, including the differences from credit process of bank institutions.

Made available in DSpace on 2015-12-03T18:33:13Z (GMT). No. of bitstreams: 1 Eudes_Martins_de_Araujo.pdf: 471826 bytes, checksum: 3fa94e3e0d87a5b29960d321fc0f5277 (MD5) Previous issue date: 2015-03-31 / The objective of this work is to verify if the credit rating model proposed by Brito and Assaf Neto (2008) designed for publicly held companies may also be applied to privately held companies in Brazil. In this work, 60 companies were used, being 30 of them in bankruptcy or insolvency processes in the period from 1994 to 2004, herein referred to as insolvent companies, and 30 of them with normal economic and financial situation referred here as solvent companies. In the present study, 60 companies were used; 30 of them presenting financial restrictions during the year of 2013 and 30 having a normal economic and financial situation. The model proposed by Brito and Assaf Neto (2008) used a logistic regression with 25 economic and financial indicators to see if they were able to separate solvent companies from non-solvent companies. Out of the 25 indicators used for this study, only 4 of them were statistically significant, namely: (I) retained profits on assets, (ii) financial debt, (III) net working capital and (IV) cash balance on sales. This four-variable model obtained a 90% accuracy in the correct classification of solvent and insolvent companies. However, the logistic regression model estimated based on the data from private companies showed different results from the one estimated by Brito and Assaf Neto (2008).In this case, only two variables showed to be statistically significant: (I) equity on assets and (II) cash balance on sales. This adjusted model reached a 57% accuracy in correctly classifying the companies. In short, the results presented here showed that it was not possible to estimate the adjusted credit-scoring model with a good accuracy for privately held companies in Brazil this based on extracted data from their financial statements. / O objetivo neste trabalho ?? verificar se o modelo de classifica????o de risco de cr??dito proposto por Brito e Assaf Neto (2008) desenvolvido para companhias de capital aberto tamb??m pode ser aplicado as companhias de capital fechado no Brasil. Nele foram utilizadas 60 companhias, sendo 30 com processos de concordata ou fal??ncia no per??odo de 1994 a 2004 denominadas insolventes e 30 com situa????o econ??mico-financeira normal denominadas solventes. No estudo aqui desenvolvido, tamb??m foram utilizadas 60 companhias; 30 apresentando restritivos financeiros durante o ano de 2013 e 30 com situa????o econ??mico-financeira normal. O modelo proposto por Brito e Assaf Neto (2008) utilizou uma regress??o log??stica com 25 indicadores econ??mico-financeiros para verificar se eles eram capazes de separar companhias solventes de companhias insolventes. Dos 25 indicadores utilizados, apenas 4 deles apresentaram signific??ncia estat??stica, sendo eles: (I) lucros retidos sobre ativo, (II) endividamento financeiro, (III) capital de giro l??quido e (IV) saldo de tesouraria sobre vendas. Esse modelo com quatro vari??veis obteve uma acur??cia de 90% nas classifica????es corretas das companhias abertas solventes e insolventes. No entanto, o modelo de regress??o log??stica estimado com base nos dados das companhias de capital fechado mostrou resultados distintos daquele estimado por Brito e Assaf Neto (2008). Nesse caso, apenas duas vari??veis se mostraram estatisticamente significantes: (I) patrim??nio l??quido sobre ativo e (II) saldo de tesouraria sobre vendas. Esse modelo ajustado obteve uma acur??cia de apenas 57% nas classifica????es corretas das companhias. Em suma os resultados aqui relatados mostraram que n??o foi poss??vel estimar um modelo ajustado de credit scoring com boa acur??cia para companhias de capital fechado no Brasil com base em dados extra??dos de suas demonstra????es financeiras.

The earlier theories considered trade credit as a substitute for bank credit. Recent theories suggest that bank credit and trade credit can also be considered as two complementary sources of financing. By using South African panel data from 2007 to 2015, the study examines if the problem of financial inclusion in South Africa can be mitigated by utilising trade credit data. The empirical findings using trade credit at current period are consistent with the earlier theories of trade credit that trade credit and bank credit are substitutes, but the model was not robust to estimation techniques. The study also used the lagged trade credit as a variable of interest and found that it is positively related to bank credit. This means that the trade credit data from the previous period can facilitate access to bank credit. Therefore, the information from trade credit can serve as a signal about firms’ quality and thus facilitates access to bank finance. / Economics / M. Com (Economics)

Made available in DSpace on 2016-06-02T19:53:33Z (GMT). No. of bitstreams: 1 FATTIBENE_Marcos_2015.pdf: 1035875 bytes, checksum: 9f4308478818fe20ad4a239e96c1bb67 (MD5) Previous issue date: 2015-01-27 / The credit analysis for individuals has traditionally relied on three pillars: documentary proof of income and residence; refers to negative credit bureaus as SERASA and SCPC and the use of forecasting models based on the hypothesis that similar profiles in the future will reproduce the same credit behavior of the past, such as the "credit scores" (HAND; HENLEY, 2007) . This approach has been adequate, while being susceptible to moments of economic crisis or to fast profile changing of the target market, as occurred in the U.S. subprime in 2008. This study aims to point out ways to use Social Networks informational content, where individuals express and record their opinions, preferences, and especially get evident their network of relationships, in the credit analysis context. It was made evident the feasibility to investigate the assumption that an individual's proximity to other appropriate profile payers, or vice versa, influences the repayment rate. To illustrate such a conclusion, a real social network, enriched with credit data obtained by statistical simulation, was used. Three models of data weighting and three other based on multiple linear regression models were developed. In general the results were not statistically significant, by need to use a non-brazilian social network, as well synthetic data bureau score, since real information was not available in this country. It was shown a way to investigate the hypothesis that the informational content of a social network may generate greater efficiency into credit analysis when added to decision-making, operational and control systems of this segment. / A análise de crédito para pessoas físicas tem tradicionalmente se apoiado em três pilares: comprovação documental de renda e de residência; consulta a birôs negativos de crédito, como SERASA Experian e SCPC e a utilização de modelos de projeção baseados na hipótese que perfis semelhantes reproduzirão no futuro o comportamento de crédito do passado, como por exemplo, os credit scores (HAND ; HENLEY, 2007). Tal abordagem tem se mostrado adequada, sendo, entretanto suscetível a momentos de crise econômica ou mudança rápida do perfil do mercado alvo, a exemplo do ocorrido no mercado imobiliário dos EUA no ano de 2008. O presente trabalho propõe-se indicar alternativas para a utilização do teor informacional presente nas Redes Sociais, onde os indivíduos registram suas opiniões, preferências e especialmente evidenciam sua rede de relacionamentos, no contexto da análise de risco de crédito. Evidenciaram-se formas de averiguação da premissa que proximidade de um indivíduo a outros com perfil de bons pagadores, ou vice-versa, influencia a taxa de adimplência. Para se ilustrar tais sugestões, foi utilizada uma rede social real, enriquecida com dados de crédito obtidos por simulação estatística. Foram elaborados três modelos de ponderação de dados e três modelos baseados em regressão linear múltipla. Em geral os resultados não foram estatisticamente significantes, dada a necessidade de uso de rede social estrangeira como também da geração de dados sintéticos de score de birô de crédito, dada a indisponibilidade de informações reais no País. Porém, ficou evidenciada a viabilidade da averiguação da hipótese de que o conteúdo informacional contido em redes sociais pode ampliar a eficiência do sistema de análise de crédito, se incorporado aos sistemas decisórios, operativos e de controle.

Made available in DSpace on 2016-03-15T19:32:50Z (GMT). No. of bitstreams: 1 Cy-dy Augusto Alves Filho.pdf: 1241998 bytes, checksum: 66cb09913a17b5fa16a6a396fd35a871 (MD5) Previous issue date: 2014-08-29 / The literature on analytical methods of accounting and corporate financial analysis models and cr edit indicators is large , and among the methods of credit risk classification is the classification model ratings, through which institutions classifie s customers according to their risk. However, the classical models of modeling credit risk using statisti cal techniques widely disseminated, as is the case of simple linear regression, the least squares method, among others. The quantile regression, evaluated in disseminated by Koenker and Basset (1978) has it as a main characteristic , analyzing the sample by the median and allow the analysis of subpopulations through the quantiles of the sample, which allows more specific inferences in according to the needs of the study. In recent years the concern with social and environmental issues have become increasing present in both the practical means and academia and in society in general, which brings up the idea of including the analysis of social indicators in environmental analysis credit, as already proposed in previous studies. However, the combined use of ec onomic, financial, social and environmental indicators, together with quantile regression, is an innovative proposal, and the subject of this academic study. This work is an exploratory and descriptive study , objective verify the possible contribution of t he inclusion of social and environmental variables, combined with the use of quantile regression for ratings classification and hence prediction of default. To fulfill this goal, we devel oped a database on panel, with the total of 561 observations, consist ing of data from publicly traded, its ratings, economic indicators, financial, social and environmental, the years 2007 to 2012 companies. With use of quantile regression was possible to infer that the social environmental variables are relevant for classi fication ratings and, consequently, to predict default. / A literatura a respeito de métodos de análise de indicadores co ntábeis e financeiros empresariais e modelos de análise de crédito é vasta, e dentre os métodos de classificação de risco de crédito, encontra - se o modelo de classificação de ratings , através do qual as instituições classificam seus clientes em função de s eu risco. Entretanto, os modelos clássicos de modelagem de risco de crédito se utilizam de técnicas estatísticas amplamente difundidas, como é o caso da regressão linear simples, método dos mínimos quadrados, entre outras. A regressão quantílica, estudada em difundida por Koenker e Basset (1978) tem como principal característica analisar a amostra através da mediana, e permitir a análise de subpopulações através dos quantis da amostra, o que permite realizar inferências mais específicas, de acordo com as ne cessidades do estudo. Nos últimos anos a preocupação com questões sociais e ambientais tem se tornado cada vez mais presente, tanto no meio prático quanto no meio acadêmico e na sociedade de maneira geral, o que traz à tona a ideia de incluir a análise de indicadores sócio ambientais na análise de crédito, como já foi proposto em estudos anteriores. No entanto, a utilização, de forma combinada, de indicadores econômicos, financeiros, sociais e ambientais, aliada à regressão quantílica, é uma proposta inovad ora, e o mote deste estudo acadêmico . Este trabalho exploratório, de natureza descritiva, objetiva verificar a possível contribuição da inclusão de variáveis sócio ambientais, aliada à utilização da regressão quantílica, para classificação de ratings e, consequentemente, previsão de default . Para cumprir tal objetivo foi desenvolvido um banco de dados em painel, com um total de 561 observações, formado por dados de empresas de capital aberto, seus ratings , indicadores econômicos, financeiros, sociais e ambi entais, dos anos de 2007 a 2012. Com a utilização da regressão quantílica foi possível inferir que as variáveis sócio ambientais são relevantes para a classificação de ratings e, consequentemente, para a previsão de default.