Classification Algorithms in Financial Application: Credit Risk Analysis on Legal Entities

This research aims at analyzing bank credit of legal entity (in non-default, default and temporarily default), for the purpose of assisting the decision made by the analyst of this area. For that, we used Artificial Neural Networks (ANNs), more specifically, the Multilayer Perceptron (MLP) and the Radial Basis Functions (RBF) and, also, the statistical model of Logistic Regression (LR). For the implementation of the ANNs and LR, the softwares MATLAB and SPSS were used, respectively. For the simulations developed 5.432 data with 15 attributes were collected by the experts of the institution bank (called “XYZ”). The results show that the default clients are easily identifiable, but for the nondelinquent clients and for the temporarily defaulters, the techniques had greater difficulty in the discrimination, suggesting that they are no so discriminants. The main contributions of this work are: the analysis of three classes of clients (non-default, default and temporarily default), rather than just two (non-default and default) as is usually done; the coding of variables (attributes) of the company XYZ aiming to maximize the accuracy of the techniques and the use of the one-against all method, little used by the researchers of this research area. This work presents new insights towards research over Credit Risk Assessment showing other possibilities of client classification and codification, allowing different types of studies to take place

Modelo borroso para la evaluación del riesgo en el otorgamiento de créditos de corto plazo a SME´s

Las pequeñas y medianas empresas (PyMEs) en Colombia, son las responsables de un crecimiento dinámico de la industria y el comercio, y han sido consideradas la columna vertebral de las economías en los últimos años; sin embargo, han tenido fuertes restricciones para acceder al mercado de créditos para su sostenibilidad y cubrir sus necesidades a corto y mediano plazo, debido principalmente a la poca información que se tiene de estas en el sector financiero. Lo anterior ha llevado a que muchos de los estudios de crédito se basen en información cualitativa y subjetiva la cual no es fácil de identificar o modelar por parte de un analista, lo que genera a las entidades financieras gran incertidumbre en la colocación de sus recursos. Para abordar este problema, se desarrolló un modelo basado en los principios de la lógica borrosa y la integración de las características más relevantes de los métodos para la toma de decisiones, ELECTRE y AHP. El modelo permitió evaluar un crédito de corto plazo mediante la caracterización de una PyME en términos de subcriterios que constituyen la información cuantitativa y cualitativa de esta. El modelo arrojó una buena sensibilidad al momento de modificar la importancia de cada una de las características de la PyME y permitió mejorar el proceso de asignación de dineros en una organización.Abstract: Small and mediumsized enterprises (SMEs) in Colombia are responsible for a dynamic growth of industry and commerce, and have been considered the backbone of economies in recent years; However, they have had strong restrictions on accessing the credit market for their sustainability and covering their needs in the short and medium term, mainly due to the lack of information available in the financial sector. This has led many of the credit studies to be based on qualitative and subjective information which is not easy to identify or model on the part of an analyst, which generates financial institutions great uncertainty in the placement of their resources. To address this problem, a model was developed based on the principles of fuzzy logic and the integration of the most relevant characteristics of the methods for decision making, ELECTRE and AHP. The model allowed to evaluate a short-term credit by characterizing a SME in terms of subcriteria that constitute the quantitative and qualitative information of this. The model showed a good sensitivity when changing the importance of each of the characteristics of the SME and allowed to improve the process of allocating money in an organization.Maestrí