Thesis (MCIS - Computer and Information Sciences) -- AUT University, 2007. / Includes bibliographical references. Also held in print (x, 102 leaves : ill. ; 30 cm.) in City Campus Theses Collection (T 332.7 OET)

Thesis (Ph. D.)--Open University. BLDSC no. DX184766.

A Research Report Submitted to the Faculty of Engineering and the Built Environment in partial fulfilment of the Requirements for the degree of Master of Science in Engineering / The research centred on improving the current software systems development life cycle (SDLC) of the credit scoring process at a financial institution based on systems engineering principles. The research sought ways to improve the current software SDLC in terms of cost, schedule and performance. This paper proposes an improved software SDLC that conforms to the principles of systems engineering. As decisioning has been automated in financial institutions, various processes are developed according to a software SDLC in order to ensure accuracy and validity thereof. This research can be applied to various processes within financial institutions where software development is conducted, verified and tested. A comparative analysis between the current software SDLC and a recommended SDLC was performed. Areas within the current SDLC that did not comply with systems engineering principles were identified. These inefficiencies were found during unit testing, functional testing and regression testing. An SDLC is proposed that conforms to systems engineering principles and is expected to reduce the current SDLC schedule by 20 per cent. Proposed changes include the sequence of processes within the SDLC, increasing test coverage by extracting data from the production environment, filtering and sampling data from the production environment, automating functional testing using mathematical algorithms, and creating a test pack for regression testing which adequately covers the software change. / MT2016

Thesis (M.M. (Research))--University of the Witwatersrand, Faculty of Commerce, Law and Management, School of Governance, 2016. / Most economies today are calling upon their or rather are starting to rely on their Small and Medium business Enterprises to stimulate the economy and also help address issues of unemployment. However it is also believed that even though this maybe the case, most economies still don’t give SMEs enough funding. The underlying public assumption is that all that is needed for SMEs to thrive is access to funding, as such this study sought to investigate the role of financial access in the success of SMEs. The study had intended to use financial ratios as proxies for success, however, the record keeping of the SMEs or lack thereof impeded this intention, so the study measured the success of the enterprise as perceived by the owner. The study sampled SMEs from all for regions of Swaziland, and besides a descriptive analysis that were carried out to examine the utilization of credit by the SMEs. This study also used a statistical model known as the Logit model, to determine the effect that credit access had on the success of the SME and also assess the challenges/barriers that the SMEs faced when trying to access funding. The results of this study deviated from the underlying public assumption, as they showed that an SME owner that had access to funding had reduced odds of success, if anything the results showed that the success of an SME did not entirely depend on the availability of funding, and there were other potent factors that posed as barriers to financial access. / DM2016

Despite being governed by several laws aimed at preventing racial inequality in access to housing and credit resources, the mortgage lending market remains a contributor to racial and place-based disparities in homeownership rates, wealth, and access to high-quality community resources. Scholarship has identified persistent disparities in mortgage loan approval rates and subprime lending between white borrowers and those from other racial and ethnic groups, and between white neighborhoods and neighborhoods with high levels of non-white residents. Against this backdrop, the mortgage lending industry is undergoing rapid, technology-driven changes in risk assessment and application processing. Traditional borrower risk-assessment methods including face-to-face discussions between lenders and applicants and the prominent use of FICO credit scores have been replaced or supplemented by automated decision-making tools at a new generation of institutions known as fintech lenders. Little is known about the relationship between lenders using these new tools and the racial and spatial disparities that have long defined the wider mortgage market. Given the well-documented history of discrimination in lending along with findings of technology-driven racial inequality in other economic sectors, fintech lending’s potential for racial discrimination warrants increased scrutiny. This dissertation compares the lending outcomes of traditional and fintech mortgage lenders in the United States depending on applicant and neighborhood racial characteristics. Using data from the Home Mortgage Disclosure Act, an original dataset classifying lenders as fintech or traditional, and an array of complimentary administrative data sources, it provides an assessment of the salience of race and place in the rates at which mortgage loans from each lender type are approved and assigned subprime terms. Results from a series of regression-based quantitative analyses suggest fintech mortgage lenders, like traditional mortgage lenders, approve and deny loans and distribute subprime credit at disparate rates to white borrowers and neighborhoods relative to nonwhite borrowers and neighborhoods. Findings suggest that policymakers and regulators must increase their oversight of fintech lenders, ensuring that further advances in lending technology do not concretize longstanding racial and spatial disparities.

Zugl.: Hannover, Univ., Diss., 2006

The Bayesian approach to logistic regression modelling for credit scoring is useful when there are data quantity issues. Data quantity issues might occur when a bank is opening in a new location or there is change in the scoring procedure. Making use of prior information (available from the coefficients estimated on other data sets, or expert knowledge about the coefficients) a Bayesian approach is proposed to improve the credit scoring models. To achieve this, a data set is split into two sets, “old” data and “new” data. Priors are obtained from a model fitted on the “old” data. This model is assumed to be a scoring model used by a financial institution in the current location. The financial institution is then assumed to expand into a new economic location where there is limited data. The priors from the model on the “old” data are then combined in a Bayesian model with the “new” data to obtain a model which represents all the available information. The predictive performance of this Bayesian model is compared to a model which does not make use of any prior information. It is found that the use of relevant prior information improves the predictive performance when the size of the “new” data is small. As the size of the “new” data increases, the importance of including prior information decreases

Thesis submitted in fulfillment of the requirements for the degree of Master of Management in Finance & Investment In the Faculty of Commerce and Law Management Wits Business School at the University of the Witwatersrand, 2015 / Risk based pricing has been a topic of discussion since the 2008 financial crisis as a result of the on-selling of packaged sub-prime assets. This paper will highlight the importance of correctly assessing risk within the framework of consumer credit provision. We will begin with a brief overview of the South African unsecured lending market, look into the definition of risk based pricing and the impact it has had in the market and conclude the paper by using a model by Robert Phillips to calculate the interest rate to be offered to a customer. / AC2016

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.

PEC-PG. CNPq / As cooperativas de crédito são regidas pelos mesmos princípios cooperativistas, mas agregam funções financeiras como os bancos tradicionais. A solidariedade na área financeira permite que as cooperativas de crédito levem aos seus cooperados os fundos poupados ou repassando os de desenvolvimento governamental das políticas públicas em forma de crédito. É evidente, no entanto, que nem sempre os “apoios” são devolvidos da mesma maneira como foram recebidos, neste mundo de muita perfeição e de alta competitividade. Assim, integra o elemento estranho no meio onde se imagina seu difícil acesso, a falta de confiança no cumprimento do contrato de crédito contraído pelos credores (cooperados). É conhecido como Risco de Crédito ou de um eventual não pagamento das dívidas contraídas pelos cooperados, o principal fator para processo de Gestão de Risco de Crédito nas instituições cooperativas do mundo. Desse modo, se insere o problema da pesquisa, sendo nova a gestão de risco nas cooperativas de crédito e num mercado assombrado pelas crises financeiras, e com isso se questiona: em que medida ou em que ponto o cumprimento das normas da gestão de risco de crédito nessas instituições vem sendo atendido? Com base nessa preocupação, traçaram-se os objetivos, que apontam em avaliar as práticas de gestão de risco em cooperativas de crédito do Sudoeste do Paraná (PR) de acordo com as resoluções do Conselho Monetário Nacional (CMN). Para isso, tem-se como objetivos específicos: listar as práticas de gestão de risco necessárias para a concessão de crédito; identificar de que forma estão sendo abordadas as práticas de gestão de risco de crédito, considerando-se normas de CMN; verificar qual é o impacto da gestão de risco percebido pelos gestores nas cooperativas de crédito; levantar em termos quantitativos quanto essas cooperativas perdem anualmente em inadimplência (default); comparar as práticas das cooperativas pesquisadas entre si e com as resoluções do CMN. O trabalho se justifica pela importância do processo de gestão de risco para as instituições cooperativas, para a academia e pela contribuição no reforço àquilo que o CMN vem recomendado nas suas resoluções. Para se atingir os resultados pretendidos, foi aplicado um estudo de caso múltiplo nas cooperativas CRESOL, SICOOB e SICREDI/PR, com abordagem qualitativa e quantitativa, em parte com dados secundários e primários. Os dados secundários foram levantados por meio da revisão da literatura referente às áreas de cooperativismo em geral e de crédito, a gestão de risco de crédito e normas e as resoluções do CMN sobre o tema, além de informações nos Relatórios Financeiros das três cooperativas. Os dados primários foram levantados por meio de aplicação de questionário nessas instituições, sendo entrevistados os Gerentes de Crédito, o Assessor Sênior da Controladoria e o Assessor e Supervisor de Crédito. Os dados levantados foram comparados entre as informações dos entrevistados da mesma instituição e depois com as outras, sendo que, na análise dos dados, os nomes das mesmas (instituições) deixaram de ser citadas e foi atribuído o nome de CASO (CASO1, CASO2, e 3 ). Foi identificada uma preocupação com a gestão de risco nessas instituições. Também se percebeu que o crédito só é liberado quando passa por análise de, no mínimo, três pessoas. Existem procedimentos de análise de crédito que seguem todas as alçadas necessárias para que a proposta seja deferida e também são avaliados de acordo com a renda do proponente e as cooperativas singulares são classificadas de acordo com seus patrimônios de Referências (PR) e Patrimônios de Referências exigidas (PRE), para receberem crédito das suas centrais e até para liberarem crédito aos seus cooperados Pessoa Jurídica, caso existam. Mesmo assim, foram localizadas as perdas (prejuízos), algumas mais acentuadas do que outras. Percebe-se que ainda existem reduzidos estudos sobre gestão de risco nas cooperativas de crédito, dada à situação em que se encontravam as mesmas, mas atualmente vale reforçar as pesquisas para conhecer como essas instituições lidam com a gestão de risco de crédito e outros riscos. / Credit unions are governed by the same cooperative principles but add financial functions as traditional banks. Solidarity in the financial area allows credit unions to take to their members or transferring funds spared government development of public policy in the form of credit. But it is not always clear that the "support" are returned the same way they were received, in this world of too much perfection and high competitiveness. Integrates the foreign element in the middle where you think its difficult access, lack of confidence in the fulfillment of the credit agreement contracted by creditors (cooperative). Known as credit risk or a possible non-payment of debts contracted by the cooperatives the main factor for Credit Risk Management process in cooperative institutions in the world. Thus falls the research problem, and new risk management in credit unions and a market haunted by financial crises, and if it asks: To what extent or at what point the compliance of the management of credit risk these institutions has been met? Based on this concern were traced objectives, which aim to assess the practices of risk management in credit unions Southwest of Paraná (PR) according to the resolutions of the National Monetary Council (CMN). For this, one has the following specific objectives: List the risk management practices needed to grant credit; Identify how they are being addressed management practices of credit risk considering CMN standard; Ascertain the impact of the management of risk perceived by managers in credit unions; Rise in quantitative terms as these cooperatives lost annually in default; Compare practices of cooperatives surveyed each other and with the resolutions of the CMN. The work is justified by the importance of the risk management process for cooperative institutions, academia and the contribution to the reinforcement to what the CMN has been recommended in its resolutions. And to achieve the desired results a study of multiple case was applied in cooperative CRESOL, SICOOB and SICREDI / PR, with qualitative and quantitative approach in part with secondary and primary data. The secondary data were collected by reviewing the literature pertaining to the areas of cooperative movement in general and credit risk management and credit standards and CMN resolutions on the topic, also collected in the Financial Reports of the three Credit unions. Primary data were collected through a questionnaire in these institutions, being interviewed Managers of Credit, Senior Advisor of the Comptroller, Assessor and Supervisor of Credit. And the data obtained were compared to the information of the respondents from the same institution and then with the other, in the data analysis of the same names (institutions) are no longer quoted and was assigned the name of CASE (case1 case2 and 3). A concern with risk management in these institutions was identified. Also noticed that credit is only been released when passing by analysis of at least three people. There are procedures for credit analysis that follows all the necessary limits for the proposal to be granted and are evaluated according to the income of the applicant and the individual cooperatives are classified according to their Wealth of References (PR in Portuguese) and Heritage References Required (PRE in Portuguese), to receive credit of their plants and up to release credit to their members Corporations if any. Yet losses were located some steeper others do not. Realize that there are still smaller studies on risk management in credit unions, given the situation they were in the same, but is currently worth strengthen research to know how these institutions deal with the management of credit risk and other risks. / 5000