Thesis (MTech (Cost and Management Accounting))--Cape Peninsula University of Technology, 2019 / The risk that borrowers may not fulfil borrowing obligation presents credit owners (lenders) with a default risk management opportunity to maximize risk-adjusted rate of return and maintain minimum exposure to default associated cost. This study investigated respondents' perception of the cost of credit default and examines requirements for default risk management (ORM) in the vehicle finance industry in South Africa. It is noted that with increased level of consumer indebtedness, an unstable economy, and high unemployment, vehicle financing faces a higher probability of default from borrowers. This descriptive investigation utilised both the quantitative and qualitative approaches using the survey method to collect data from 381 purposive, randomly selected respondents who are vehicle finance customers in South Africa; Cape Town specifically. Data collection took place in the Western Cape over a nine months period, utilising personal interview, and emails to administer open-ended questionnaires for credit managers and close-ended questionnaires, for the vehicle finances' customers, as data collection instrument. Responses received were codified and quantitative data was analysed using the Statistical Packages for Social Sciences (SPSS version 25) while qualitative data was analysed using the content analysis of percentage of word similarities. The study found mixed and variable respondents' perception of the cost of credit default. In conclusion, it is perceived that in South Africa the cost of credit would become more costly with credit default. It can be recommended that a default risk management intervention could be applied to mitigate the risk of credit default within the context of unified credit assessment policy of South Africa.

En Latinoamérica, se ha desarrollado, la inclusión financiera, de manera muy rápida en los últimos tiempos, sin embargo, este proceso todavía no consigue que la fuerza laboral esté integrada totalmente. El acceso al crédito en América Latina solo representa el 51% y, en el Perú, esta cifra desciende al 29% (CEPES,2016). En el rubro económico, los requerimientos para poder acceder a un crédito son muy rigurosos, donde prevalece el sector formal. Más de las dos terceras partes del poder laboral en el Perú (69%) no son formales, según la Organización Mundial del Trabajo. Asimismo, en el sector informal el otorgamiento de crédito carece de historial financiero y los montos son mínimos esto conlleva a que las entidades financieras eleven el riesgo y los costos asociados con los créditos en este sector. Esto nos muestra que las realidades de los créditos difieren demasiado con el proceso de evaluación de clientes generando una deficiente y mala representación de lo que ocurre en la vida real. Este proyecto permite está basado en que la gran cantidad de financieras solamente entregan créditos a su clientela que cuenta con un historial crediticio, en consecuencia, el fin de este proyecto, muy diferente a lo convencional, es poder otorgar créditos a personas naturales y/o empresas que se encuentran en el proceso de la formalidad. Contamos con referencias de otras partes del mundo, un claro ejemplo es en el país oriental de la China la cual cuenta con una realidad cultural muy diferente a la nuestra, sin embargo, cuenta con conocimientos que se pueden adaptar al proyecto nuestro. Con todo lo descrito, planteamos el desarrollo de un Modelo de Data Science que ayude a analizar a los clientes potenciales mediante el cálculo de su capacidad de pago y en base a eso predecir y ofrecer el producto que mejor se acople a los parámetros antes detallados (Cáceres & Paucar, 2019). Este proyecto desarrolla el Modelo de Data Science y se prueba en una Página Web en la misma caja rural (instalaciones) y en el sector campo mediante la ayuda de sus móviles, para demostrar los resultados logrados y las mejores comparativas de nuestro modelo con el método tradicional. Palabras claves: Data Science, Modelo de evaluación, Capacidad de pago, Data Analysis, Historial Crediticio, Caja Rural. / In Latin America, financial inclusion has increased considerably in recent years, but it still does not cover the entire workforce. According to World Bank studies, access to credit in Latin America represents only 51% and in Peru this figure drops to 29%. In the financial sector, the requirements for applying for credit are very rigid, giving priority to the formal sector. According to the International Labor Organization, 69% of the labor force in Peru is informal. Furthermore, in this sector the loans granted are small amounts and lack credit history, making the costs and risk associated with such loans high for the entities. That is why the analysis in the evaluation of the client without credit history is deficient with the reality that they present. The development of this project responds to the fact that the great majority of financial entities grant credits to clients who already have some credit history, therefore, what we want to show, unlike the rest, is that a credit can also be granted to people or micro entrepreneurs who are not yet totally formalized or do not present proof of income (ballots or receipt for fees). There are precedents of this type of cases at international level, particularly in China that have another reality to ours, but some concepts can be transferred to our project. Based on the above, we propose the development of a Data Science model that will allow us to evaluate potential clients and, in turn, evaluate their ability to pay and offer them an associated product for each client. To this end, the model was tested on a web page within the entity on their computers and outside through the use of mobile devices, in order to show results obtained by the model indicating improvements in the percentage of credit granted to clients by officials. Keywords: data science, evaluation model, payment capacity, data analysis, credit history, rural saving bank. / Tesis

El propósito de la presente investigación ha sido identificar aquellos factores que afectan el acceso al financiamiento de las pymes, esto debido a que a la fecha existen muchas limitantes que funcionan como barrera en el desarrollo de dichas empresas. Es preciso indicar que en el mercado en donde se desarrollan existen diversas formas de financiamiento; sin embargo, estas normalmente benefician o aportan un mayor apoyo y valor a las grandes empresas o a las que tienen un historial crediticio previo. Por ello, es que en este trabajo de investigación nos enfocamos en analizar específicamente el apoyo o facilidades de financiamiento que reciben las pymes para su desarrollo. Los tipos de financiamiento que existen para las pymes son con capital propio y/o con capital de terceros: el primero consiste en el inicio y financiamiento de las operaciones con los fondos propios de los inversionistas, y el segundo consiste en el otorgamiento de financiamiento mediante el capital semilla, préstamos informales, proveedores, subsidios del Estado, entidades bancarias-financieras y la emisión de bonos-acciones. Es importante mencionar que existen diversos factores que dificultan o facilitan el acceso al financiamiento de las pymes, los cuales se hacen referencia en esta investigación: la asimetría de la información, el riesgo crediticio, la calidad de los proyectos de negocios pymes y la experiencia previa del cliente. / The purpose of this research has been to identify those factors that affect access to financing for SMEs, due to the fact that to date there are many limitations that function as a barrier in the development of these companies. It is necessary to indicate that in the market where they are developed there are various forms of financing; however, these typically benefit or provide greater support and value to large companies or those with a prior credit history. Therefore, in this research work we focus on specifically analyzing the support or financing facilities that SMEs receive for their development. The types of financing that exist for SMEs are with own capital and / or with third-party capital: the first consists of starting and financing operations with investors' own funds, and the second consists of granting financing through seed capital, informal loans, suppliers, State subsidies, banking-financial entities and the issuance of bond-shares. It is important to mention that there are various factors that hinder or facilitate access to financing for SMEs, which are referenced in this research: the asymmetry of information, credit risk, the quality of SME business projects and previous experience. the client's. / Trabajo de Suficiencia Profesional