Browsing by Subject "Credit scoring"
Now showing items 1-8 of 8
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Autobin: a predictive approach towards automatic binning using data splitting
(SASA, 2018)The concept of binning is known by many names: discretisation, classing, grouping and quantisation. It entails the mapping of continuous or categorical data into discrete bins. Binning is an important pre-processing step ... -
Automated construction of generalized additive neural networks for predictive data mining
(North-West University, 2006)In this thesis Generalized Additive Neural Networks (GANNs) are studied in the context of predictive Data Mining. A GANN is a novel neural network implementation of a Generalized Additive Model. Originally GANNs were ... -
Credit application scoring for consumers without credit history
(North-West University (South Africa). Vanderbijlpark Campus, 2019)Credit scoring is a tool that is used to either qualify or disqualify credit applicants by quantifying the risk factors relevant to classify them to high risk or low risk. Due to a demand in credit inclusion, financial ... -
Developing credit scorecards using logistic regression and classification and regression trees
(North-West University (South Africa), 2020)Financial institutes receive thousands of credit applications daily; thus, consumer credit has become increasingly important in the economy. Credit scoring is the evaluation of the risk associated with granting credit to ... -
The effect of the financial crisis on credit scoring in the retail credit market in South Africa
(North-West University, 2011)This study follows a three–pronged approach to investigate the effects of the global financial crisis on the South African retail credit market (using Woolworths as subject). These three prongs, or areas, include a literature ... -
Investigation of factorisation machines and its extensions to predictive models in a statistical context
(North-West University (South Africa), 2023)Factorisation machines originated from the field of machine learning and have gained popularity because of the high accuracy obtained in several prediction problems, particularly in the field of recommender systems. As ... -
An optimised credit scorecard to enhance cut-off score determination
(AOSIS, 2018)Background: Credit scoring is a statistical tool allowing banks to distinguish between good and bad clients. However, literature in the world of credit scoring is limited. In this article parametric and non-parametric ... -
Two statistical problems related to credit scoring
(North-West University, 2007)This thesis focuses on two statistical problems related to credit scoring. In credit scoring of individuals, two classes are distinguished, namely low and high risk individuals (the so-called "good" and "bad" risk classes). ...