Text Mining for Customer Experience Mobile Banking Analysis

Helmi Adiningtyas, Aishananda Shavira Auliani

2023

Abstract

Improvements in information and communication technology have resulted in several innovative changes to reach consumers. The use of online financial transactions is increasing due to the convenience and security provided. The changed habit of customer transaction from traditional payment into digital or online payment creating a new need of customers and company new ways to fulfilled new mission of succession, to fulfill it company needs to providing good service that been customize to their customer’s needs. In this study, we examined the mobile banking customer experience through customer perception on Google Play Store, and we used BCA Mobile, one of Indonesia’s mobile banking services, as our case study. Sentiment analysis methods to assess customer satisfaction and topic modeling methods to extract key customer issues within each sentiment class. This research aims to provide an evaluation and valuable insight into customer experience in mobile banking. As a result of this research, BCA Mobile customers are dissatisfied with the app service. Consumers consider transactions with the most recent version of BCA mobile to be risky because it does not use pins or onetime passwords (OTP). This discovery may help BCA Mobile pay more attention to other app features to better understand the needs of their customers

Paper Citation

in Harvard Style

Adiningtyas H. and Shavira Auliani A. (2023). Text Mining for Customer Experience Mobile Banking Analysis. In Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD; ISBN 978-989-758-678-1, SciTePress, pages 162-165. DOI: 10.5220/0012445800003848

in Bibtex Style

@conference{icaisd23,
author={Helmi Adiningtyas and Aishananda Shavira Auliani},
title={Text Mining for Customer Experience Mobile Banking Analysis},
booktitle={Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD},
year={2023},
pages={162-165},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012445800003848},
isbn={978-989-758-678-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD
TI - Text Mining for Customer Experience Mobile Banking Analysis
SN - 978-989-758-678-1
AU - Adiningtyas H.
AU - Shavira Auliani A.
PY - 2023
SP - 162
EP - 165
DO - 10.5220/0012445800003848
PB - SciTePress