Results 31 to 40 of about 32,796 (305)
A hybrid feature selection method for credit scoring
EAI Endorsed Transactions on Context-aware Systems and Applications, 2017 Reliable credit scoring models played a very important role of retail banks to evaluate credit applications and it has been widely studied. The main objective of this paper is to build a hybrid credit scoring model using feature selection approach.
Sang Ha Van +2 more
doaj +1 more source
Credit Card Fraud Detection Using LSTM Algorithm
Wasit Journal of Computer and Mathematics Science, 2022 With the rapid growth of consumer credit and the huge amount of financial data developing effective credit scoring models is very crucial. Researchers have developed complex credit scoring models using statistical and artificial intelligence (AI ...
Yanash Azwin Mohmad
doaj +1 more source
Equipping entrepreneurs: consuming credit and credit scores [PDF]
Consumption Markets & Culture, 2013 On-line products that make an individual's credit score an object of consumption and equip credit consumers with the capacity to improve their score are shown to exemplify two sets of dynamic tendencies to change in mass market consumer credit. First, as credit consumers are differentiated, sorted and targeted by lenders according to credit scores ...
openaire +2 more sources
About psychological variables in application scoring models [PDF]
RAE: Revista de Administração de Empresas, 2015 The purpose of this study is to investigate the contribution of psychological variables and scales suggested by Economic Psychology in predicting individuals’ default.
Pablo Rogers +2 more
doaj +1 more source
Credit scoring in banks and financial institutions via data mining techniques: A literature review [PDF]
Journal of Artificial Intelligence and Data Mining, 2013 This paper presents a comprehensive review of the works done, during the 2000–2012, in the application of data mining techniques in Credit scoring. Yet there isn’t any literature in the field of data mining applications in credit scoring.
Seyed Mahdi sadatrasoul +3 more
doaj +1 more source
Credit scoring models: Evolution from standard statistical methods to machine learning techniques [PDF]
, 2023 openThis thesis investigates how credit scoring models have evolved over time from standard statistic techniques to advanced machine learning models and what advancements and challenges the evolution of these models has led to.This thesis investigates ...
DONGHI, FRANCESCO
core
Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani +10 more
wiley +1 more source
Which Curve Fits Best: Fitting ROC Curve Models to Empirical Credit-Scoring Data
Risks, 2022 In the practice of credit-risk management, the models for receiver operating characteristic (ROC) curves are helpful in describing the shape of an ROC curve, estimating the discriminatory power of a scorecard, and generating ROC curves without underlying
Błażej Kochański
doaj +1 more source
Credit Rating Score Analysis [PDF]
, 2017 We analyse a sample of funds and other securities each assigned a total rating score by an unknown expert entity. The scores are based on a number of risk and complexity factors, each assigned a category (factor score) of Low, Medium, or High by the expert entity.
Härdle, Wolfgang Karl +2 more
openaire +2 more sources
Does segmentation always improve model performance in credit scoring?
, 2012 Credit scoring allows for the credit risk assessment of bank customers. A single scoring model (scorecard) can be developed for the entire customer population, e.g. using logistic regression. However, it is often expected that segmentation, i.e. dividing
Lyn C. Thomas +3 more
core +1 more source