Analysing user trust in electronic banking using data mining methods
作者：
Highlights：
• This paper reviews different methods and techniques to determine which variables could be the most important to financial institutions in order to predict the likely levels of trust among electronic banking users including socio-demographic, economic, financial and behavioural strategic variables that entities have in their database.
• In order to validate the results, five experts in the subject with experience in different national and international companies were consulted.
• The best method to perform variable selection using the expert’s criterion is the MGA using Mutual Information computed with the k-NN algorithm.
摘要
•This paper reviews different methods and techniques to determine which variables could be the most important to financial institutions in order to predict the likely levels of trust among electronic banking users including socio-demographic, economic, financial and behavioural strategic variables that entities have in their database.•In order to validate the results, five experts in the subject with experience in different national and international companies were consulted.•The best method to perform variable selection using the expert’s criterion is the MGA using Mutual Information computed with the k-NN algorithm.
论文关键词：Financial sector,Electronic banking,Trust,Variable selection,Multi-objective optimisation,MOEAs,NSGA-II,MOGA,Genetic algorithms
论文评审过程：Available online 14 March 2013.
论文官网地址：https://doi.org/10.1016/j.eswa.2013.03.010
