Scopus Indexed Publications

Paper Details


Title
Predicting Satisfaction of Online Banking System in Bangladesh by Machine Learning
Author
Syeda Farjana Shetu, Israt Jahan, Mohammad Monirul Islam, Nazmun Nessa Moon, Refath Ara Hossain,
Email
shetu4247@daffodilvarsity.edu.bd
Abstract
Online banking refers to using your smartphone, tablet, or another internet-connected computer to browse and access your bank account. It is quick and free, and it usually allows you to perform a variety of activities, such as paying bills and exchanging currency, without having to visit or call your branch. As a developing nation, Bangladesh is seeing an increase in online banking. People are still reliant on online banking because it makes a man's life much easier. During the Corona incident, the use of online banking increased at an unprecedented pace. Online banking services such as Rocket, bKash, and Nagad are now available in the region. While online banking makes life easier, third-party money laundering incidents do occur from time to time. As a result, some people are unhappy with online banking. However, some people say that they are happy with their online banking experience. This work tries to address this critique and give the right advice to the customer. Customer satisfaction and frustration with online banking have been predicted using Machine Learning techniques in this study. Seven traditional machine learning classification algorithms Logistic Regression, Random Forest, Naïve Bayes, support vector machine, Neural network, Decision tree, K nearest neighbor algorithms to complete this research work and find the concluded delimiter.

Keywords
Banking System , Machine Learning and Prediction
Journal or Conference Name
2021 International Conference on Artificial Intelligence and Computer Science Technology (ICAICST)
Publication Year
2021
Indexing
scopus