Sentiment Analysis of Customer Feedback on Services Provided on Selected Banks’ Mobile Banking Applications in Nigeria
Uzodinma C. Onwuchekwa *
Babcock University, Nigeria.
Emmanuel C. Ogu
Department of Computer Science, School of Computing, Babcock University, Ilishan-Remo, Ogun State, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
This study examines customer feedback on mobile banking applications for Access Bank, UBA Bank, and First Bank in Nigeria using sentiment analysis. By analyzing user reviews from the Google Play Store, the research identifies key themes and sentiments, positive, neutral, and negative, using Support Vector Machine (SVM) classifiers. Results show Access Bank had the highest positive sentiment (74.1%), followed by UBA Bank (66.5%) and First Bank (48.3%). Negative feedback was highest for First Bank (45.4%), pointing to significant usability issues. Common positive themes included ease of use, reliability, and security, while negative comments highlighted technical glitches, poor customer support, and transaction failures. The findings suggest improvements in technical performance, authentication processes, and customer service could enhance user satisfaction. Regular sentiment monitoring is crucial for maintaining user trust and competitiveness in Nigeria’s mobile banking sector.
Keywords: Sentiment Analysis, mobile banking, customer feedback, machine learning, user satisfaction