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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.

Quality assurance forms an integral part of education and training programme delivery. The purpose of this research was to determine whether the quality management systems (QMS) used by nursing education institutions in Gauteng are aligned to the SAQA criteria and guidelines for education and training providers. A quantitative, descriptive and exploratory design was followed using a self-administered questionnaire as data gathering instrument. A total of 32 respondents from three selected nursing education institutions completed the questionnaire. The data were analysed by using the Statistical Package for Social Sciences (SPSS) program. The findings revealed that the nursing education institutions only partially comply with SAQA’s core criteria for quality management systems. Recommendations to improve the current QMS were made. / Health Studies / M.A. (Health Studies)

Quality assurance forms an integral part of education and training programme delivery. The purpose of this research was to determine whether the quality management systems (QMS) used by nursing education institutions in Gauteng are aligned to the SAQA criteria and guidelines for education and training providers. A quantitative, descriptive and exploratory design was followed using a self-administered questionnaire as data gathering instrument. A total of 32 respondents from three selected nursing education institutions completed the questionnaire. The data were analysed by using the Statistical Package for Social Sciences (SPSS) program. The findings revealed that the nursing education institutions only partially comply with SAQA’s core criteria for quality management systems. Recommendations to improve the current QMS were made. / Health Studies / M.A. (Health Studies)